Sa likod ng isang desisyon sa paglulunsad

Paglulunsad ng GreenLeaf sa UK: sundan ang paglalakbay, suriin ang ebidensya, buksan ang mga ulat.

Kathang-isip na kumpanya · sintetikong datos

Tuklasin ang paglulunsad

GreenLeaf / UKBayad na mobile traffic lamang

Mga click sa ad11,760

Landing page10,080

Mga pagsisimula ng quiz8,400

Tumapos3,780

Unang pagbili259

Setyembre 1–14, 2026 · mga cohort na may pitong-araw na obserbasyon · retrospektibong snapshot noong Setyembre 22

Basahin mula sa iyong pananaw

Pumili ng pananaw; pareho ang mga datos.

Lahat ng pananawPamumuno sa ahensyaIn-house na pamumunoDelivery team

Sa halimbawang ito

Kilalanin ang GreenLeaf

Isang kathang-isip na tatak ng supplement mula sa US na papasok sa UK.

Ang haypotesis sa paglulunsad

Makakatulong ba ang malinaw na impormasyon tungkol sa mga sangkap para piliin ng mga mamimili sa UK ang GreenLeaf?

Target sa pagkumpleto ng quiz: 45%
Target na buwanang revenue sa UK: $60,000
Target sa pagkilala sa brand nang walang pahiwatig: 15%

Basahin ang konteksto ng negosyo

English editorial source — publication at owner/human release, nakabinbin. Ang GreenLeaf ay kathang-isip lamang. Ang campaign data nito at ang sumunod na context update ay isinulat para sa pagtuturo; ang mga na-record na tugon ng AI ay totoo. Ang mga pagsusuri sa ibaba ay mga independent calculation at AI-assisted editorial review, hindi kumpletong pagsusuri ng tao o pag-apruba ng kliyente. Hindi sinusukat ng halimbawang ito ang accuracy ng AI, ang pagiging mas mahusay ng tao, ang oras na natipid, o ang ROI ng campaign.

Ang GreenLeaf Wellness ay nagbebenta ng mga subscription supplement: daily greens, protein blends, at adaptogen stacks. Lumalawak ito mula US papuntang UK na may tiyak na proposisyon: maaaring suriin ng mga customer ang ingredient sourcing at mga dose sa halip na magtiwala sa isang proprietary blend na hindi ipinaliwanag.

Ang tanong sa launch ay simple itanong ngunit mas mahirap sagutin: magkaka-interes kaya ang mga mamimili sa UK para piliin ito? Para makagawa ng kapaki-pakinabang na rekomendasyon, dapat ikonekta ng team ang customer hypothesis, mga pagpipilian sa campaign, at measurement plan sa mga resulta. Ang landas na ito ay sumusunod sa mga handoff na iyon patungo sa isang kumpletong halimbawa ng pag-uulat.

Narito ang desisyon sa gitna nito. Ang paid-mobile quiz completion ay bumaba mula 3,780 sa 8,400 starts (45%) patungong 2,352 sa 8,400 (28%). Ang isang AI draft ay nagrerekomenda ng diagnostic review, ngunit nagbibigay din ng mga maling financial total at binabalewala ang isang makabuluhang pagbabago sa audience mix. Sinusuportahan ng mga nasuring kalkulasyon ang pagsisiyasat sa parehong cohort composition at mobile journey. Ang isang sumunod na kathang-isip na product/support note ay ginagawang mas tiyak ang pagsisiyasat, habang iniiwang hindi pa rin nalulutas ang dahilan nito.

Ang mga panahon ay Setyembre 1–7 at Setyembre 8–14, 2026, gamit ang UTC paid-click cohorts. Ang funnel events at purchases ay may parehong pitong-araw na observation window. Ang snapshot ay Setyembre 22 sa 23:59:59 UTC. Ang parehong panahon ay mature: ito ay retrospective comparison, hindi ebidensya na may alert na nakahuli sa isyu noong launch.

Magsimula sa desisyon na pagmamay-ari mo

Responsibilidad mo	Kailangan mo mula sa gawaing ito
Pamumuno sa ahensya	Payo na kaya mong ipagtanggol, pare-parehong mga katotohanan sa lahat ng deliverables, at malinaw na desisyon sa client release.
In-house na pamumuno sa marketing	Ebidensya para sa pagbabago ng priyoridad ng launch, at pagkakaiba sa pagitan ng diagnosis at commercial approval.
Pamumuno sa media o performance	Mga maihahambing na cohort, event definitions, nasuring kalkulasyon, at tiyak na pagsisiyasat.
Creative, product, o pagpapatupad	Isang tanong na maaaring subukan, ang ebidensyang nawawala sa kasalukuyang data, at isang susunod na hakbang na may pananagutan.

Maaari mong suriin ang bawat deliverable. Ang mga pananaw ng mambabasa na ito ay nagbabahagi ng iisang kumpanya at iisang dataset; hindi sila gumagawa ng magkakaibang katotohanan. Ang tatlong tatanggap ng ulat ng kurso ay nananatiling founder, media team, at content/creative team.

Unawain ang customer bago unawain ang campaign

Ipinakikilala ng kurso si Oliver, isang skeptical na biohacker na gustong suriin ang ebidensya sa likod ng isang supplement. Siya ay isang synthetic persona hypothesis, hindi isang customer na ininterbyu.

Ang isang kapaki-pakinabang na handoff sa launch team ay ganito ang hitsura:

Working hypothesis	Tanong para sa tunay na pananaliksik	Bunga para sa campaign
Mahalaga ang ingredient transparency	Ano ang sinuri ng mga mamimili bago ang kanilang huling pagbili ng supplement?	Subukan kung karapat-dapat sa pagiging kilalá ang mga patunay ng sourcing at dosing.
Ang mas mababang presyo ay maaaring magdulot ng pagdududa sa kalidad	Ano ang nagparamdam sa isang alok na kapani-paniwala o kahina-hinala?	Ipaliwanag ang halaga gamit ang sumusuportang impormasyon sa halip na isang pag-aangkin ng kalidad na walang suporta.
Ang isang quiz ay makakatulong sa mga mamimili na pumili	Ano ang nagpapatuloy o nagpapa-abandon sa mga mamimili sa paglalakbay na iyon?	Suriin ang post-click na karanasan gayundin ang ad.

Gumagamit ang reconstruction ng skeptical at exploring audience buckets at traceability at value messages. Ito ay mga kategoryang binuo para sa pagsusuri, hindi validated na psychological segment o randomized assignment. Ang illustrative na mensahe ng traceability ay “Know what is in every serving.” (Alamin kung ano ang laman ng bawat serving). Ang anumang tunay na deployment ay mangangailangan ng substantiated na impormasyon ng produkto at angkop na pagsusuri ng claim.

Ang activation handoff ay konkreto: ad → landing page → quiz start → quiz completion → first purchase, na may pare-parehong campaign, device, audience, at creative identifiers. Kailangan ng reporting team ang pagpapangalan at event definitions, kasama ang release at test history. Hindi maipapaliwanag ng mensahe ng isang ad ang sirang completion event; hindi mapapatunayan ng isang mapaniniwalaang persona na gumagana ang isang mensahe.

Tukuyin ang tagumpay bago buksan ang export

Layunin sa negosyo	Kathang-isip na target ng kurso	Ano ang maaaring patunayan ng mga input na ito
Tulungan ang mga mamimili na umusad sa consideration	45% quiz completion	Completions ÷ starts sa mga ibinigay na paid cohorts.
Makabuo ng bagong UK customer revenue	$60,000 bawat buwan	Attributed na first-purchase revenue mula sa dalawang linggo ng paid-click cohort, hindi ang resulta ng buong buwan.
Bumuo ng pagkilala	15% unaided awareness	Hindi available; hindi kayang palitan ng clicks at impressions ang awareness research.
Mag-hakot ng mga customer na may pangmatagalang halaga	$480 LTV sa 12 buwan	Hindi available; hindi kayang patunayan ng first-order revenue ang retention o LTV.

Ang CTR, CPC, at CPM ay tumutulong sa pagsisiyasat ng performance. Hindi nila pinapalitan ang mga kinalabasang ito. Nagbibigay din ang kurso ng $312 breakeven CAC guardrail, ngunit ang export ay naglalaman lamang ng media cost at attributed na first-purchase customers. Ang media CPA ay hindi buong CAC. Ang paglalapat ng guardrail na iyon ay nangangailangan ng like-for-like na reconciliation ng mga gastos, customer, at economic assumption.

Reporting brief v1

Paglulunsad ng GreenLeaf sa UK — brief sa pag-uulat v1

Bersyon: 1.0 · Isinulat: 2026-10-29 · Katayuan: Input ng English source para sa isang kathang-isip na halimbawa sa pagtuturo; hindi isang nai-publish na ulat. I-freeze ang brief na ito, ang dictionary, at ang source map bago gumawa ng fixture. I-freeze nang hiwalay ang mga eksaktong run-input hash pagkatapos ng pag-verify ng data. Walang tugon ng AI o resulta ng pagsusuri ang inaangkin ng brief na ito.

Ang negosyo at ang mga handoff papunta sa pag-uulat

Ang GreenLeaf Wellness ay ang kathang-isip na subscription supplement business ng kurso, na lumalawak mula sa US papuntang UK. Kasama sa mga produkto nito ang daily greens, protein blends, at adaptogen stacks. Ang iminumungkahi nitong pagkakaiba ay ang traceability ng sangkap at malinaw na dosing. Ang komersyal na tanong ay kung nakakatulong ang panukalang iyon sa mga mamimili sa UK na umusad mula sa pag-iisip tungo sa unang pagbili. Sinusuri ng reconstruction na ito ang mga paid cohort; hindi nito matutukoy kung matagumpay ang buong paglulunsad.

Gawaing nasa itaas	Konkretong handoff na ibinigay dito	Paano ito ginagamit ng pag-uulat	Katibayang kailangan pa
Pananaliksik at estratehiya	Si Oliver, ang skeptic na biohacker, ay isang synthetic persona hypothesis. Pagtutol: maaari ko bang i-verify kung ano ang nasa isang serving, at makatuwiran ba ang presyo sa halaga? Tanong sa interbyu: anong ebidensya ang nagbago sa huli mong supplement shortlist?	Ikumpara ang mga hypothesis ng audience na `skeptical` at `exploring` at ang mga mensaheng `traceability` at `value` nang hindi tinatrato ang mga identifier bilang beripikadong sikolohiya.	Mga tunay na interbyu sa customer, mga naobserbahang pagtutol, at isang beripikadong kahulugan ng segment.
Pagsukat	Layunin ng negosyo → KPI → diagnostic lever. Quiz completion = completions / starts; ang kita mula sa bagong customer ay may buwanang target. Ang seven-day UTC paid-click cohorts ay may iisang maturity rule.	Panatilihing nasa itaas ang mga kinalabasan kaysa CTR/CPC/CPM at ikumpara ang mga parang-tulad na denominator.	Buwanang revenue reconciliation sa lahat ng channel, pananaliksik sa awareness, kasaysayan ng retention, at disenyo/resulta ng incrementality.
Activation	Halimbawang mensahe: “Know what is in every serving.” (Alamin kung ano ang laman ng bawat serving) Sinusubok ng pangalawang mensahe ang halaga sa pamamagitan ng malinaw na impormasyon sa dosing. Journey: ad → landing page → pagsisimula ng quiz → completion → unang pagbili. Ang mga canonical campaign/device/audience/creative ID ay nasa dictionary.	Suriin ang mensahe, audience, device, at yugto ng funnel; humiling ng event at release reconciliation bago mag-diagnose.	Substantiation ng anumang claim sa produkto, event QA logs, ad-platform exports, at isang timestamped na release/test register. Ang mga halimbawang mensaheng ito ay hindi aprubadong advertising.
Institutional memory	Itinatala ng v1 na ito ang lahat ng kasalukuyang ibinigay na konteksto ng senaryo. Walang ibinigay na makasaysayang seasonal baseline, log ng kagustuhan ng kliyente, mas naunang natuklasan ng ahensya, o kilalang insidente sa produkto.	Tratuhin ang nawawalang kasaysayan bilang hindi alam; tanungin ang may-ari nito sa halip na mag-imbento ng sensitivity ng founder o paliwanag na seasonal.	Follow-up ng product/support at commercial-owner; itala ang impormasyong natutunan pagkatapos na may provenance sa v2.

Pinaghihiwalay ng source map ang mga katotohanan ng kurso, mga bagong pagpili sa reconstruction, at mga resulta na nakuha sa ibang pagkakataon. Source: course traceability. Semantika ng field: dictionary.

1. Mga KPI at target

Desisyon sa negosyo	Target ng senaryo ng kurso	Katibayang makukuha mula sa reconstruction na ito	Hangganan ng pag-uulat
Umuusad ba ang mga mamimili sa pag-iisip?	45% quiz completion	Paid-cohort quiz completions ÷ starts, kabilang ang mobile at desktop nang hiwalay	Ang ginawang paghahambing sa mobile ay 45% → 28%, isang pagbaba na 17 percentage point (humigit-kumulang 37.8% relative). I-verify ang mga bilang pagkatapos ng generation; ito ay teaching constraint, hindi isang naobserbahang resulta ng kliyente o rate sa buong site.
Gumagawa ba ang paglulunsad sa UK ng kita mula sa bagong customer?	USD $60,000 bawat buwan	Kita mula sa unang pagbili na nai-attribute para sa September 1–14 paid-click cohorts	Hindi kayang itatag ng dalawang linggo ng paid cohort ang resulta sa buong buwan at lahat ng channel. Huwag i-prorate ang target para maging hatol ng tagumpay. Kunin ang buong buwan, karaniwang kahulugan ng kita, at reconciled na bagong customer ledger.
Nagiging kilala ba ang GreenLeaf?	15% unaided awareness	Hindi makukuha	Hindi kayang palitan ng mga impression, click, at bayad na kita ang pag-aaral sa brand-awareness.
Mahalaga ba ang mga customer sa paglipas ng panahon?	USD $480 LTV sa 12 buwan	Hindi makukuha	Hindi kayang itatag ng first-order revenue ang realized LTV o retention.

Ang $312 breakeven CAC ng kurso ay isang scenario planning guardrail. Ang export na ito ay nagbibigay ng media spend at mga na-attribute na customer ng unang pagbili, kaya sinusuportahan nito ang media CPA, hindi ang buong CAC. I-reconcile ang saklaw ng acquisition cost, natatanging bagong customer, mga panahon, at ang mga economic assumption bago ikumpara sa guardrail na iyon. Walang sumusunod na paglabag sa CAC o claim ng kakayahang kumita mula sa media CPA lamang.

Ang CTR, CPC, CPM, click-to-start rate, completion-to-purchase rate, media CPA, at attributed first-order ROAS ay mga diagnostic lever. Ang frequency, impression share, at bounce rate ay hindi makukuha dahil wala ang kinakailangang source field. Ang incremental lift, kita sa buong site, mga refund sa labas ng fixture, buong acquisition economics, at mga pangmatagalang kinalabasan ay nananatiling hindi alam.

2. Mga stakeholder, desisyon, at awtoridad sa pag-release

Dapat gumawa ang isang prompt ng lahat ng tatlong draft mula sa iisang brief at reconciled na dataset. Bawat natuklasan ay sumasagot sa ANO ang nangyari → BAKIT ito mahalaga → ANO ANG SUSUNOD, na pinaghihiwalay ang mga naka-check na katotohanan, hypothesis, hindi alam, at iminumungkahing aksyon.

Tatanggap	Desisyong dapat suportahan ng ulat	Kinakailangang deliverable	Awtoridad at hangganan
Founder / CEO (o in-house marketing leader)	Dapat bang baguhin ngayon ang mga priyoridad sa paglulunsad, o dapat bang kumuha muna ang team ng partikular na ebidensya bago ang komersyal na desisyon?	Isang-pahinang buod ng signal ng negosyo, materyal na kawalang-katiyakan, at isang pinangalanang susunod na desisyon.	Inaaprubahan ng founder/marketing owner ang mga komersyal na priyoridad at badyet. Walang awtomatikong reallocation, hindi suportadong pagtataya ng nawalang kita, o hatol sa buwanang target.
Media team	Aling cohort, kahulugan ng event, o yugto ng journey ang dapat unang imbestigahan, at anong ebidensya ang magbabago sa susunod na desisyon sa media?	Pagsusuri sa channel/device/audience/creative, bilang ng funnel, weighted rates, at fixed-mix check.	Hawak ng media lead ang source reconciliation at diagnostic work order; ang mga pagbabago sa gastos ay nangangailangan ng komersyal na pag-apruba.
Content at creative team	Dapat bang tumuon ang susunod na pagsubok sa mensahe, sa karanasan pagkatapos ng pag-click, o sa ebidensyang kailangan upang pumili sa pagitan ng mga ito?	Nakatuon na creative/testing brief na may hypothesis, kinakailangang ebidensya, may-ari, at sukatan ng tagumpay.	Nagmumungkahi ang creative lead ng pagsubok; inaaprubahan ng product owner ang mga pagbabago sa produkto at kaugnay na substantiation ng claim. Walang hindi suportadong panalo sa creative o causal claim.

Maaaring suriin ng mga lider ng ahensya ang kalidad ng payo at disiplina sa pag-release; maaaring suriin ng mga in-house leader ang ebidensya para sa pagbabago ng plano; maaaring suriin ng mga performance lead ang diagnostic work. Maaaring suriin ng mga mambabasa na sumusuri ng propesyonal na paghuhusga ang parehong ebidensya. Hindi pinapalitan ng mga pananaw ng mambabasa na ito ang tatlong deliverable ng kurso o binabago ang pinagbabatayang mga katotohanan.

Sinusuri ng isang reviewer na may kakayahan sa mga kahulugan ng pagsukat at operasyon ng campaign ang source reconciliation, mga kalkulasyon, lohika ng paghahambing, at ang iminumungkahing desisyon. Hawak ng founder/marketing owner ang awtoridad sa pag-release para sa mga rekomendasyong nakaharap sa leadership/kliyente. Ito ay mga kathang-isip na pagtatalaga ng tungkulin, hindi tunay na tao, mensahe, o pag-apruba.

3. Mga layer ng konteksto at mga alam na hindi alam

Temporal: Linggo 1 = September 1–7, 2026; Linggo 2 = September 8–14. Ang date ay isang UTC paid-click cohort date. Ang mga funnel event at na-attribute na pagbili ay may pitong araw pagkatapos ng eligible click. Snapshot = 2026-09-22T23:59:59Z, kapag parehong mature na ang mga panahon. Ito ay retrospective na paghahambing, hindi katibayan ng pagtuklas sa Linggo 2. Walang ibinigay na seasonal effect, paliwanag sa holiday, o mas naunang baseline.

Negosyo: Ang paglawak sa UK, mga subscription product, at ang panukala ng transparency ay nagmula sa kathang-isip na senaryo ng kurso. USD ang currency ng pag-uulat upang mapanatili ang mga yunit ng target ng kurso. Walang tunay na presyo sa UK, conversion ng exchange rate, aprubadong health claim, badyet sa paglulunsad, o buong customer economics na itinatag dito.

Competitive: ginagamit ng kurso ang AG1, Huel, Ritual, Seed, at Thorne bilang nakikilalang konteksto ng kategorya. Ang kasalukuyang pagpepresyo, mga campaign ng kakumpitensya, at mga bahagi ng merkado ay hindi sinaliksik para sa halimbawang ito; walang paggalaw ang maaaring maiugnay sa kanila. Ang dialogue ng persona ni Oliver ay synthetic, hindi transcript ng interbyu mula sa tunay na customer.

Kasaysayan ng kliyente/team: ang katayuan ng pag-release ng produkto, mga natuklasan sa mobile QA, feedback ng suporta, sensitivity ng founder, pagtatalaga ng audience test, at mga naunang aral sa pag-uulat ay hindi ibinigay sa v1. Ang kawalan mula sa mga input na ito ay hindi nangangahulugang walang nagbago. Dapat humingi ang unang diagnostic work order sa product/support ng timestamped na konteksto at sa pagsukat ng event/version reconciliation. Anumang sagot ay bagong impormasyon sa brief na ito at dapat lagyan ng label na ganoon. Huwag ipagpalagay nang maaga ang problema sa produkto.

4. Mga benchmark, dimensyon, at mga common-sense check

Ang panloob na paghahambing ay dalawang pantay at mature na pitong-araw na panahon. Ang target ng kurso na 45% ang benchmark sa ilalim ng idineklarang saklaw ng paid cohort; walang ibinigay na panlabas na benchmark sa industriya. Ang mga dimensyon ay channel (google-search, linkedin, reddit-paid), device (mobile, desktop), audience (skeptical, exploring), creative (traceability, value), at yugto ng funnel. Ito ay ginawang mutually exclusive na mga reporting bucket, hindi beripikadong pagganap ng targeting o tunay na klasipikasyon ng persona.

Bago magsulat ng mga natuklasan:

I-reconcile ang 337 raw na row sa 336 canonical na pang-araw-araw na row: alisin ang tanging eksaktong duplicate, i-normalize lamang ang idineklarang alias ng campaign, panatilihin ang mga bilang ng source, at i-validate ang mga identifier, integer na bilang/sentimo, at is_provisional.
Suriin ang mga hindi pagkakapantay-pantay ng funnel, mature na saklaw, at mga assumption sa pag-attribute. Huwag mag-infer ng natatanging customer nang nakapag-iisa mula sa isang aggregate CSV. Ang zero denominator ay nagbibigay ng hindi makukuhang ratio, hindi zero na pagganap.
I-sum ang mga numerator at denominator bago hatiin. Huwag kailanman i-average ang mga row-level rate; kalkulahin ang mga monetary ratio mula sa sentimo nang hindi nira-round ang mga intermediate value.
Suriin ang paggalaw ng mobile sa loob ng mga stratum ng channel × audience × creative. Ikumpara ang mga rate ng stratum sa Linggo 2 gamit ang mga bahagi ng pagsisimula ng quiz sa Linggo 1 bilang fixed weight. Iulat ang naobserbahang aggregate, fixed-mix na paghahambing, mga weight, at anumang undefined na stratum. I-diagnose ang komposisyon laban sa paggalaw sa loob ng grupo bago ang paliwanag sa produkto; alinmang pattern ay kulang pa rin ng causal identification.
I-reconcile ang mga kabuuan ng device at segment sa kabuuan. Ipaliwanag ang first-order revenue kasama ang mga limitasyon ng cohort at attribution nito. Huwag kopyahin ang mga hindi suportadong numero ng course asset tulad ng revenue at risk, segment multiple, o tiyak na pagbabago sa badyet.

Panuntunan ng retrospective alert: para sa isang mature na maihahambing na lingguhang paid-mobile cohort na may kahit isang pagsisimula ng quiz, i-flag ang completion na mas mababa sa 45%. Tuklasin → suriin gamit ang source/fixed-mix check → iruta ang diagnostic sa media lead at product owner → pagsusuri ng tao. Itinatala ng may pananagutang may-ari ang source window, snapshot, pinakamaagang mapangangatwirang availability, desisyon, at katayuan ng pag-apruba. Ang static na sample ay hindi isang tumatakbong serbisyo; walang panlabas na mensahe, awtomatikong pagbabago sa gastos, o claim ng napigilang pagkalugi ang awtorisado.

5. Cadence at ang susunod na brief

Lingguhan: buod ng diagnostic/optimization, mga naka-check na cohort cut, may-ari, at susunod na kahilingan sa ebidensya. Buwanan: naratibo ng negosyo laban sa buong target na panahon, na may all-channel reconciliation at malinaw na hindi makukuhang mga kinalabasan. Quarterly: i-reset ang mga assumption sa pagpaplano, mga benchmark, at disenyo ng pagsukat sa halip na i-extrapolate ang snapshot na ito.

Para sa teaching cycle na ito, panatilihin ang aktwal na multi-audience prompt at hindi na-edit na tugon; itala ang metadata ng modelo/run at mga eksaktong input hash. Isama ang isang nakatuon na tanong sa pagsusuri, naka-check na sagot, at kapaki-pakinabang na follow-up. Maaaring kumpirmahin, baguhin, ipagpaliban, o tanggihan ng pagsusuri ng tao ang isang rekomendasyon; ang hindi binagong payo ay isang wastong kinalabasan. Ang bagong natutunang kathang-isip na konteksto ay dapat naisulat at na-hash-record bago ang unang run, at hindi dapat i-retrofit upang gumawa ng kabiguan. Hindi ito input sa unang draft.

Pagkatapos ay itala ang pangangatwiran ng pagsusuri, i-update ang brief v2 at isang nababasang diff, at gumawa ng tatlong huling ulat mula sa mga aprubadong katotohanan. Ihiwalay ang mga pagbabagong dulot ng konteksto sa malayang paghuhusga ng reviewer. Panatilihin ang mga hypothesis bilang hypothesis sa memorya. Ipinapakita ng sequence na ito ang paghuhusga sa pag-uulat; hindi nito sinusukat ang katumpakan ng AI, kahigitan ng tao, natipid na oras, o ROI ng kliyente. Ang pampublikong pag-release ay nangangailangan ng hiwalay na pinamamahalaang localization at review gates.

Bumaba mula 45% tungong 28% ang pagkumpleto ng quiz sa bayad na mobile traffic

Isang tuldok = 1% ng mga pagsisimula ng quiz mula sa bayad na mobile traffic. Ang mga tuldok na may kulay ay kumakatawan sa mga natapos na quiz.

Linggo 1Linggo 2

Bayad na mobile traffic lamang

45%Tumapos

3,780 / 8,400 Mga pagsisimula ng quiz

Target sa pagkumpleto ng quiz45%

Panatilihing pareho ang komposisyon ng audience

Completion rate sa Linggo 2 kung pareho pa rin sa Linggo 1 ang proporsyon ng mga nagsimula ng quiz sa bawat kombinasyon ng channel × audience × ad creative: 35.33%. Hindi pinatutunayan ng deskriptibong paghahambing na ito ang sanhi.

Naobserbahan ang pagbaba. Hindi pa tiyak ang sanhi nito.

Suriin ang gawa ng AI

Sinuri gamit ang CSV. Hindi pa tiyak ang sanhi.

Naitalang AI draft · orihinal sa Ingles · may mahahalagang pagkakamali

Basahin ang kumpletong orihinal na tugon

Text-only na AI run sa DeepSeek V4 Pro, Oktubre 29, 2026. Walang tool para magpatakbo ng code.

# GreenLeaf Wellness UK — First Reporting Draft

**Scope:** Fictional teaching example. Paid-click cohorts, 1–14 September 2026, mature at 2026-09-22 snapshot.  
**Inputs:** `brief-v1.md`, `dictionary.md`, `reconciled.csv`, `campaigns.csv`, `creatives.csv`.  
**Status:** Draft for human review. Not a client/customer result or source of public claims.

---

# 1. Founder / CEO Summary

## 1.1 WHAT happened

Mobile quiz completion fell from **45% in Week 1** to **28% in Week 2** (−17 percentage points; about −37.8% relative). The fall is **not explained by device mix, channel mix, audience mix, or creative mix**. It appears inside the mobile strata themselves, and it broadens into weaker downstream purchase output.

At the same time, paid performance outside that mobile completion drop was mixed:

| Metric | Week 1 | Week 2 |
|---|---:|---:|
| Spend | $110,100 | $110,100 |
| Starts | 16,800 | 16,800 |
| Completions | 7,560 | 6,440 |
| New customers | 548 | 482 |
| Attributed first-purchase revenue | $43,840 | $38,560 |
| Media CPA | $200.91 | $228.42 |
| First-order ROAS | 0.40 | 0.35 |

Media CPA rose **$27.51** and first-order ROAS fell **0.05** across the two mature weeks. Desktop completion stayed roughly flat around **46%**, while mobile fell to **28%**.

## 1.2 WHY it matters to the business

The quiz is the main signal for whether UK buyers are progressing through consideration. A 17-point collapse in the largest device group means the promise of the launch is eroding at exactly the point where GreenLeaf should be converting interest into qualified leads and first purchases. The decline is broad across channels and messages, so the immediate question is a **post-click journey or measurement problem**, not a single creative or channel problem.

This is **not yet a proven revenue failure**: the data covers only two seven-day paid cohorts, uses attributed first-purchase revenue only, and there is no full-month, all-channel reconciliation. But the direction matters because every customer acquired after the mobile drop is more expensive at first order.

## 1.3 WHAT’S NEXT — at most three actions

1. **Freeze spend reallocation decisions until diagnostic review is complete.** Owner: founder / marketing owner. The decline is broad, not isolated to one channel or message, so a premature budget change risks moving money away from the real problem.

2. **Approve a 5-working-day diagnostic with named owners.** Owner: media lead + product owner. Priority: event/version source reconciliation, mobile landing/quiz QA, and a review of whether the Week 2 mobile cohort changed in composition or behavior. Evidence requested: release logs, event QA, mobile session detail, and the exact time the 28% mobile completion became visible.

3. **Obtain the full September month before any $60,000 verdict.** Owner: commercial/finance owner + measurement lead. The current export supports media CPA and first-order ROAS only. It cannot establish full CAC, profitability, all-channel revenue, or the stated monthly new-customer revenue target.

**Unavailable and not to be inferred:** full CAC reconciliation, profit, budget size, revenue at risk, incremental lift, awareness contribution, and a full-month revenue verdict.

---

# 2. Media Team Analysis

## 2.1 Data and coverage checks

| Check | Result |
|---|---:|
| Raw rows | 337 |
| Expected canonical rows | 336 |
| Duplicate rows removed | 1 |
| Campaign alias normalized | 1 or more allowed alias rows |
| Rows with `is_provisional=false` | All published primary rows |
| Funnel inequality violations | None found in reviewed canonical rows |
| Week 1 mature at snapshot | Yes |
| Week 2 mature at snapshot | Yes |

Because this response did not execute code, the exact duplicate row ID, alias count, and the zero-denominator row are **reported as requiring verification** in the final reviewed draft. The arithmetic below uses the canonical 336-row structure implied by the brief and dictionary.

## 2.2 Period totals

### All devices, all channels

| Metric | Week 1 | Week 2 |
|---|---:|---:|
| Spend | $110,100 | $110,100 |
| Starts | 16,800 | 16,800 |
| Completions | 7,560 | 6,440 |
| Completion rate | 45.0% | 38.3% |
| New customers | 548 | 482 |
| Attributed first-purchase revenue | $43,840 | $38,560 |
| Media CPA | $200.91 | $228.42 |
| First-order ROAS | 0.40 | 0.35 |

### Mobile only

| Metric | Week 1 | Week 2 |
|---|---:|---:|
| Starts | 8,400 | 8,400 |
| Completions | 3,780 | 2,360 |
| Completion rate | 45.0% | 28.1% |
| New customers | 274 | 176 |
| Attributed first-purchase revenue | $21,920 | $14,080 |

### Desktop only

| Metric | Week 1 | Week 2 |
|---|---:|---:|
| Starts | 8,400 | 8,400 |
| Completions | 3,780 | 4,080 |
| Completion rate | 45.0% | 48.6% |
| New customers | 274 | 306 |
| Attributed first-purchase revenue | $21,920 | $24,480 |

**Composition check:** Total quiz starts stayed identical at 16,800 each week, and the device split stayed identical at 8,400 mobile / 8,400 desktop. So device mix did not drive the aggregate decline. Desktop improved; mobile declined.

## 2.3 Channel comparison

Week 1 and Week 2 totals by channel:

| Channel | Week | Spend | Starts | Completions | New customers | Revenue | Media CPA | First-order ROAS |
|---|---|---:|---:|---:|---:|---:|---:|---:|
| Google Search | W1 | $43,400 | 5,600 | 2,520 | 182 | $14,560 | $238.46 | 0.34 |
| Google Search | W2 | $43,400 | 5,600 | 2,376 | 142 | $11,360 | $305.63 | 0.26 |
| LinkedIn | W1 | $45,800 | 5,600 | 2,520 | 182 | $14,560 | $251.65 | 0.32 |
| LinkedIn | W2 | $45,800 | 5,600 | 2,400 | 166 | $13,280 | $275.90 | 0.29 |
| Reddit paid | W1 | $20,900 | 5,600 | 2,520 | 184 | $14,720 | $113.59 | 0.70 |
| Reddit paid | W2 | $20,900 | 5,600 | 1,664 | 174 | $13,920 | $120.11 | 0.67 |

Nothing here isolates a single channel as the sole cause. **Mobile completion declined in all three channels**, and each channel also had some desktop changes.

## 2.4 Audience and creative comparison

### Week 1 vs Week 2 completion rate by audience

| Audience | Week 1 | Week 2 | Change |
|---|---:|---:|---:|
| Skeptical | 48.0% | 37.5% | −10.5 pp |
| Exploring | 42.0% | 39.1% | −2.9 pp |

### Week 1 vs Week 2 completion rate by creative

| Creative | Week 1 | Week 2 | Change |
|---|---:|---:|---:|
| Traceability | 44.9% | 37.8% | −7.1 pp |
| Value | 45.1% | 38.8% | −6.3 pp |

The decline is visible across both audiences and both creative messages, but it is sharper for the **skeptical** audience. That does not prove the persona is wrong or the message failed. It indicates the fall is not confined to one message.

## 2.5 Mobile strata: channel × audience × creative

Using the supplied CSV pattern, each mobile stratum has **50 starts in the Week 1 baseline** for the cells where starts are non-zero. Therefore each stratum’s Week 1 start weight is:

- 12 strata in scope for the fixed-mix calculation.
- If a stratum had zero Week 1 starts, its weight is zero.
- If all 12 mobile strata have equal Week 1 starts, each weight is approximately `1/12 = 0.0833`.

The dictionary’s fixed-mix rule is:

```text
Fixed-mix Week 1 mobile completion rate
= sum over strata of (weight_s × Week 1 completion rate_s)

Fixed-mix Week 2 comparison
= sum over strata of (weight_s × Week 2 completion rate_s)
```

### Mobile fixed-mix result

Using the observed mobile pattern:

| Mobile stratum | Week 1 starts | Week 1 completion | Week 2 completion |
|---|---:|---:|---:|
| Google / skeptical / traceability | 700 | 54.0% | 44.0% |
| Google / skeptical / value | 700 | 58.0% | 48.0% |
| Google / exploring / traceability | 700 | 25.0% | 17.3% |
| Google / exploring / value | 700 | 29.0% | 20.0% |
| LinkedIn / skeptical / traceability | 700 | 58.0% | 48.0% |
| LinkedIn / skeptical / value | 700 | 62.0% | 52.0% |
| LinkedIn / exploring / traceability | 700 | 28.0% | 19.3% |
| LinkedIn / exploring / value | 700 | 32.0% | 22.0% |
| Reddit / skeptical / traceability | 700 | 62.0% | 52.0% |
| Reddit / skeptical / value | 700 | 66.0% | 56.0% |
| Reddit / exploring / traceability | 700 | 31.0% | 21.3% |
| Reddit / exploring / value | 700 | 35.0% | 24.0% |

The Week 1 weights are equal across these strata because each contributed 700 starts. Therefore the fixed-mix comparison reduces to a simple average of stratum rates.

| Calculation | Rate |
|---|---:|
| Week 1 observed mobile | 45.0% |
| Week 1 fixed-mix mobile | 45.0% |
| Week 2 observed mobile | 28.1% |
| Week 2 fixed-mix mobile | 35.5% |

**Interpretation:**

- The fixed-mix Week 2 rate is still **below** Week 1.
- Therefore the mobile decline is **mostly within-stratum**, not caused by a change in channel/audience/creative mix.
- The remaining difference between the fixed-mix Week 2 rate and the observed Week 2 rate is small and does not explain the drop from 45% to 28%.

## 2.6 Mobile decline diagnosis

### Observed mobile movement

- Week 1 mobile completion: `3,780 / 8,400 = 45.0%`
- Week 2 mobile completion: `2,360 / 8,400 = 28.1%`

### Decomposition

**Composition effect:** essentially absent. Device split stayed 50/50. Channel/audience/creative start shares were stable.

**Within-group effect:** present in nearly every mobile stratum. Completion rates fell in all mobile channel × audience × creative cells.

There is no evidence in this aggregate file to say **why** the within-group mobile completion rates fell. It may be:

- a product or tracking/release change;
- a mobile journey defect;
- a change in the underlying mobile click cohort;
- a measurement/event definition change;
- a true demand or attention shift.

None of these is proven by this two-week export.

---

# 3. Content & Creative Brief

## 3.1 Hypothesis

**Primary hypothesis:** The mobile quiz completion decline is primarily a **post-click experience or measurement break**, not a creative message failure.

**Reasoning:**

- The decline appears across all three channels.
- It appears across both `traceability` and `value` messages.
- It appears across both audiences, though more sharply in `skeptical`.
- Fixed-mix analysis shows mixture changes do not explain the decline.
- Desktop completion stayed near or above Week 1 levels.

If creative message were the main lever, we would expect one message or one audience/channel combination to diverge more sharply. That is not what the data show.

## 3.2 Focused next test

**Test:** Mobile quiz journey diagnostic + message-specific post-click check.

**Owner:** Creative lead proposes the test. Product owner approves product changes or claim substantiation.

**Required evidence before a creative pivot:**

1. Timestamped mobile landing-page and quiz release log.
2. Event QA or replay data for mobile quiz starts and completions.
3. Comparison of mobile completion by landing-page variant, quiz version, and `creative_id` within the same audience/channel stratum.
4. Confirmation that the session source tagging and completion tracking did not change between Week 1 and Week 2.

**Proposed test frame:**

| Component | Detail |
|---|---|
| Question | Does mobile quiz completion recover when the journey/event tracking is confirmed stable? |
| Comparator | Mobile quiz completes / starts, by channel × audience × creative, with release/event context. |
| Action | Do not change creative or budget first. Run a diagnostic cohort with stable tracking. |
| Success measure | Mobile completion returns toward the Week 1 45% level or shows a specific stratum-specific defect. |
| Decision rule | If one stratum remains broken, fix that stratum. If all strata remain low after confirmed tracking, then move to a message/post-click test. |

**Do not recommend a creative winner now.** Both creative messages look affected; neither has causal support as the problem.

---

# 4. Limitations

## 4.1 Data and arithmetic limitations

- This is a **fictional teaching example**; no real campaign, customer, or platform data are present.
- No code-execution tool was used in this request. Calculations were performed by stated hand arithmetic from the supplied CSV structure. They should be re-run in the final reviewed draft.
- The analysis is based on **aggregate paid-click cohorts**, not person-level identity or full customer records.
- The export covers **two seven-day periods only**. It is not a full-month result.
- All purchases and revenue are **attributed first-purchase outcomes only**.
- Revenue in the fixture is constructed at **$80 per first-purchase customer**; this is a teaching assumption, not pricing or LTV.
- No refunds, renewals, cross-device identity, organic contribution, incrementality, or full acquisition costs are available.

## 4.2 Analysis limitations

- **No causal explanation** is available for the mobile decline.
- The fixed-mix calculation uses observed Week 1 start weights and assumes the listed strata are complete. Any missing stratum or zero denominator would alter the result.
- The `skeptical` and `exploring` audiences are **constructed buckets**, not validated segments.
- `traceability` and `value` are message hypotheses; they are not approved advertising claims.
- No release logs, QA records, or event-level timestamps were used.
- No budget, profit, CAC reconciliation, or incremental result was calculated because the data does not support it.

## 4.3 Reporting limitations

- This draft must pass human review before any leadership or client release.
- The brief requires separate final reports from approved facts.
- Unavailable outcomes should not be presented as zero, missing performance, or implied causation.

---

# 5. Reproducible Calculation for the Main Signal

## 5.1 Mobile quiz completion decline

From the reconciled CSV, mobile rows summed by week:

**Week 1 mobile:**

```text
quiz_starts          = 8,400
quiz_completions     = 3,780
completion rate      = 3,780 / 8,400 = 0.45 = 45.0%
```

**Week 2 mobile:**

```text
quiz_starts          = 8,400
quiz_completions     = 2,360
completion rate      = 2,360 / 8,400 = 0.28095 = 28.1%
```

Percentage-point change:

```text
28.1% − 45.0% = −16.9 pp
```

Using unrounded figures from the brief’s calibration:

```text
45% → 28% = −17 percentage points
Relative change = (0.28 − 0.45) / 0.45 = −0.3778 = −37.8%
```

**Arithmetic uncertainty note:** The CSV sums here are derived from repeated daily counts, not a code-computed aggregation. The final reviewed draft should confirm:

- exact duplicate row ID removed;
- alias normalization count;
- any zero-denominator stratum left as unavailable;
- exact mobile totals after duplicate removal.

## 5.2 Fixed-mix mobile check

Using equal Week 1 mobile start weights for the 12 listed strata:

```text
Week 1 stratum rates:
54, 58, 25, 29, 58, 62, 28, 32, 62, 66, 31, 35 %

Week 1 fixed-mix:
(54 + 58 + 25 + 29 + 58 + 62 + 28 + 32 + 62 + 66 + 31 + 35) / 12
= 540 / 12
= 45.0%
```

Week 2 stratum rates:

```text
44, 48, 17.3, 20.0, 48, 52, 19.3, 22.0, 52, 56, 21.3, 24.0 %
```

Week 2 fixed-mix:

```text
(44 + 48 + 17.3 + 20.0 + 48 + 52 + 19.3 + 22.0 + 52 + 56 + 21.3 + 24.0) / 12
= 424.0 / 12
= 35.3% to 35.5% depending on decimal retention
```

The observed Week 2 mobile rate was **28.1%**, while the Week 1-weighted fixed-mix was about **35.3%–35.5%**. Both are far below the Week 1 fixed-mix of **45.0%**, confirming the decline is mainly within strata rather than composition-driven.

---

# Final consistency note

These three deliverables use the same facts:

- Mobile completion: **45% → 28%**.
- Aggregate completion: **45.0% → 38.3%**.
- New customers: **548 → 482**.
- Attributed first-purchase revenue: **$43,840 → $38,560**.
- Media CPA: **$200.91 → $228.42**.
- First-order ROAS: **0.40 → 0.35**.
- Desktop did not collapse; mobile did.
- No budget or creative winner is justified yet.
- Diagnostic first, then a narrow test.

Ebidensya	Orihinal na AI draft	Nasuri laban sa CSV
Lingguhang media spend	$110,100 sa bawat linggo	Linggo 1: $5,462 · Linggo 2: $5,512
Mobile completion at audience mix	45% → 28%; binalewala ang audience mix bilang paliwanag	3,780 / 8,400 → 2,352 / 8,400. Linggo 2 sa halo ng Linggo 1: 35.33%.

Isang kathang-isip na tala ng product/support ang nagsasaad ng pagbabago sa mobile quiz. Hindi pa nabeberipika ang rollout at epekto.

Tingnan ang mga ulat

Parehong datos. Tatlong desisyon.

Nasuring mga editoryal na draft · hinihintay ang pag-apruba ng tao para ilabas

Ulat ng founderItakda ang prayoridad sa paglulunsad.

GreenLeaf UK — Buod para sa Founder / CEO

Nireview na editoryal na draft; nakabinbin ang pagpapalabas ng tao. Fictional na mga paid-click cohort September 1–14, 2026, naobserbahan hanggang September 22. USD. Ito rin ang pananaw sa pamumuno para sa isang in-house CMO.

Ano ang nangyari

Bumaba ang paid-mobile quiz completion mula 45% patungong 28%, isang pagbaba ng 17 percentage points. Ang mga naka-check na bilang ay 3,780/8,400 → 2,352/8,400. Ang desktop completion ay 45.03% → 46.25%.

Sa kabuuan ng ibinigay na mga paid cohort, ang mga attributed first-purchase customer ay 467 → 357 at ang attributed first-purchase revenue ay $37,360 → $28,560. Ito ay mga ginawang resulta ng attribution, hindi ebidensya ng incremental subscriptions o kita na nawala dahil sa quiz.

Bakit ito mahalaga

Ang quiz ay isang consideration step sa UK launch. Pareho ang paglipat patungo sa mga audience bucket na mas mababa ang completion at ang mga pagbaba sa loob ng maihahambing na mga mobile group ay nag-aambag sa aggregate movement. Ang paghawak sa fixed mix ng Week 1 ay nagbibigay ng 35.33% para sa Week 2, kaya hindi lamang mix ang nagpapaliwanag sa pagbaba.

Iniuulat ng product owner ang isang mobile presentation revision at iniuulat ng support ang isang usability concern. Wala sa mga ito ang naka-link sa mga nasukat na cohort ng ibinigay na ebidensya. Ang isang product cause ay nananatiling hindi napatunayan.

Ano ang susunod na mangyayari

Product owner + media lead: beripikahin ang mobile journey, event definitions at release/version evidence. Ang iniulat na availability para sa isang next-working-day check ay isang scenario assumption, hindi isang nakumpletong aksyon. Bumalik na may plano sa paghahambing o isang malinaw na pahayag ng nawawalang ebidensya.
Marketing owner: huwag aprubahan ang isang budget move o creative pivot mula lamang sa CSV na ito. Ang mga umiiral na komersyal/risk na desisyon ay nananatiling pinamamahalaan ng kanilang normal na awtoridad; hindi ito isang blanket freeze.
Finance/measurement owner: i-reconcile ang buong September revenue definition ng negosyo at all-channel results bago ideklarang nakamit o hindi ang $60K/month na target. Ang cohort revenue at isang buwanang accounting/business measure ay nangangailangan ng malinaw na like-for-like reconciliation.

Ang full CAC, profit, awareness, realized lifetime value at incrementality ay nananatiling hindi available.

Pinagmulan: naka-check na metric pack, mga desisyon sa review. Ang orihinal na AI draft ay hiwalay na pinanatili; ang mga numero nito ay hindi ang source of truth ng ulat na ito.

I-download ↓

Ulat ng mediaPiliin ang susunod na pagsisiyasat.

GreenLeaf UK — Pagsusuri ng media team

Nireview na editoryal na draft; nakabinbin ang pagpapalabas ng tao. Fictional na UK paid-click cohorts; Week 1 = September 1–7, Week 2 = September 8–14, 2026. Seven-day observation windows, September 22 snapshot.

Ano ang nangyari

Lahat ng ibinigay na paid cohort	Week 1	Week 2
Spend, USD	$5,462	$5,512
Quiz starts	15,040	15,120
Quiz completions	6,770	5,460
Attributed first-purchase customers	467	357
Attributed first-purchase revenue	$37,360	$28,560
Media CPA	$11.70	$15.44
Attributed first-order ROAS	6.84	5.18

Kasama lamang sa Media CPA ang media cost; huwag itong direktang ihambing sa $312 full-CAC guardrail ng kurso. Ang ROAS ay attributed first-order revenue na hinati sa media spend, hindi profit o causal lift.

Channel	W1 spend	W2 spend	W1 customers	W2 customers	W1 revenue	W2 revenue
Google Search	$1,736	$1,744	154	105	$12,320	$8,400
LinkedIn	$2,296	$2,304	154	119	$12,320	$9,520
Reddit paid	$1,430	$1,464	159	133	$12,720	$10,640

Walang ibinigay na naaprubahang buwanang media budget, kaya hindi maaaring tasahin ang budget pacing.

Bakit kailangan ng mix check ang paghahambing sa mobile

Mobile completion: 3,780/8,400 = 45% → 2,352/8,400 = 28%. Ang pagbabago ay −17 percentage points, humigit-kumulang −37.8% relative. Ang desktop ay 2,990/6,640 = 45.03% → 3,108/6,720 = 46.25%.

Ang mobile skeptical starts ay bumababa mula 4,200 patungong 2,100; ang exploring starts ay tumataas mula 4,200 patungong 6,300. Ang kanilang mga share ay nagbabago mula 50%/50% patungong 25%/75%. Ito ay mga ginawang bucket, hindi mga beripikadong kagustuhan ng customer o randomized treatments.

Bawat isa sa 12 channel × audience × creative mobile strata ay may 700 Week 1 starts. Gamitin ang weight 700/8,400 = 1/12 at i-multiply sa completion rate ng Week 2 ng stratum na iyon. Isama ang mga weighted rate: 35.33%, pinapanatili ang buong precision bago ang display. Tingnan ang metric pack para sa bawat cell.

Sa Week 1-weighted decomposition na ito, ang within-group component ay −9.67 points at ang composition component ay −7.33 points. Ang alokasyon ay nakadepende sa napiling baseline/order; walang numero sa mga ito ang isang causal effect. Lahat ng 12 strata ay bumababa, ngunit hindi maipaliwanag ng CSV kung bakit.

Ano ang susunod na mangyayari

Media lead: beripikahin ang mga event definition at source/cohort tagging; panatilihin ang parehong maturity rule.
Product owner + media lead: humiling ng release/version assignment at i-reproduce ang mobile flow. Ihambing ang mga bersyon kung saan maaaring i-reconstruct ang assignment. Nililimitahan ng mga nawawalang log ang maaaring tapusin.
Measurement reviewer: suriin ang mga kalkulasyon, konteksto at desisyon bago ang stakeholder release. Huwag maghinuha ng product cause, magrekomenda ng tiyak na budget move, o ituring ang isang recovery sa target bilang isang wastong test design nang mag-isa.

Ang iniulat na mobile presentation revision at support concern ay nagbibigay-priyoridad sa mga check na ito. Hindi patunay ang mga ito ng depekto, prevalence o incremental loss. Walang nangyaring external action o delivery.

Pinagmulan: dictionary, naka-check na metric pack, review.

I-download ↓

Ulat ng content at creativeSuriin ang mensahe at karanasan.

GreenLeaf UK — Content at creative brief

Nireview na editoryal na draft; nakabinbin ang pagpapalabas ng tao. Fictional na September 1–14 paid-click cohorts, naobserbahan hanggang September 22, 2026. Ang mga hypothesis sa mensahe ay hindi naaprubahang advertising claims.

Ano ang nangyari

Parehong may mas mahinang aggregate quiz completion ang dalawang message group:

Hypothesis sa mensahe	Week 1 completions / starts	Week 2 completions / starts
Traceability: “Know what is in every serving” (Alamin kung ano ang laman ng bawat serving)	3,276 / 7,560 = 43.33%	2,625 / 7,560 = 34.72%
Value: “Compare the value of a clearly dosed serving” (Ihambing ang halaga ng bawat serving na may malinaw na dosis)	3,494 / 7,480 = 46.71%	2,835 / 7,560 = 37.50%

Pinagsasama ng mga total na ito ang mga device, audience at channel. Hindi ito isang apples-to-apples causal creative test. Hindi itinatatag ng mas mataas na aggregate rate ng value message na ito ang panalo.

Bakit ito mahalaga

Binibigyang-diin ng customer hypothesis ang malinaw na impormasyon sa sangkap. Ang isang iniulat na mobile presentation revision ay nagdagdag ng isang expandable information panel at binago ang isang next-step label. Ang hindi naka-link na support feedback ay nagbabanggit ng kahirapan sa paghahanap ng susunod na control. Makatuwirang siyasatin ang post-click experience; hindi makatuwirang tawagin ang mensahe, panel o label bilang sanhi mula sa mga file na ito.

Ano ang susunod na mangyayari

Iminungkahing tanong: pagkatapos ma-beripika ang kahulugan ng event at journey behavior, ginagawa ba ng page na malinaw ang pangako ng mensahe habang pinapanatili ang isang nauunawaang susunod na hakbang?

Content lead: siyasatin ang ad-to-page handoff kasama ang product owner. Panatilihin ang traceability at value bilang mga malinaw na hypothesis. Kumpirmahin na ang bawat pahayag sa ingredient/dosing ay may substantiation.

Product/measurement owners: alamin kung ang version assignment at maihahambing na mga cohort ay maaaring sumuporta sa isang nakatutok na test. Itakda ang denominator, paghahambing at panuntunan sa desisyon bago ito patakbuhin. Kung wala ang assignment o tracking, idokumento ang limitasyong iyon; ang isang before/after recovery ay hindi causal proof.

Walang sinusuportahan dito na creative retirement, winning-hook claim o rekomendasyon sa media-budget. Ang CSV ay walang ebidensya ng viewing/replay, kaya hindi ito nagtatatag ng fatigue, prevalence ng kalituhan o kung saang screen iniwan ng mga user.

Pinagmulan: naka-check na metric pack, mga desisyon sa review, brief v2.

I-download ↓

Mga ebidensya at sanggunian

Buong pangangatwiran, mga brief at orihinal na ebidensya.

Hakbang 1 — Isapormal ang reporting framework

Ang kumpletong brief v1 ay nagbibigay sa modelo ng isang gumaganang framework bago ito mag-draft ng anuman:

KPIs at targets: ang hierarchy sa itaas, denominators, at mga kinalabasang hindi available.
Stakeholder map: ang desisyong sinusuportahan ng bawat ulat at kung sino ang maaaring mag-apruba ng aksiyon.
Context layers: UK expansion, ang persona hypothesis, timing, at tahasang nawawalang kasaysayan ng institusyon.
Benchmarks at dimensions: ang 45% target; channel, device, audience, creative, at funnel cuts; mga panuntunan sa paghahambing at pagpapatunay.
Cadence: lingguhang diagnosis, buwanang business narrative, at quarterly na pag-reset ng pagpaplano.

Dala ng brief ang mga alam na. Ang mga product release, mobile QA, feedback ng support, at mga naunang sensitivity ng kliyente ay hindi alam sa mga ibinigay na v1 inputs, at naka-assign ang follow-up sa mga may-ari nito. Ang hindi alam ay hindi nangangahulugang walang nagbago. Nangangahulugan itong dapat magtanong ang reporting team.

Para sa bawat ulat, ang tagubilin ay ANO ang nangyari → BAKIT ito mahalaga → ANO ANG SUSUNOD. Dapat magpasya ang founder kung kailangan ng atensiyon ang mga priyoridad ng launch; dapat piliin ng media ang susunod na pagsisiyasat; dapat magpasya ang creative kung anong ebidensya ang kailangan bago baguhin ang mensahe o karanasan. Ang isang rekomendasyon ay nangangailangan ng may-ari at release boundary.

Suriin ang sumusuportang ebidensya

Ang dictionary ay tumutukoy sa mga field at assumption. Ang source map ay naghihiwalay sa mga katotohanan at target ng kurso mula sa mga pagpili sa reconstruction. Walang nakuhang pinagbabatayang GreenLeaf reporting CSV mula sa kurso.

Ang raw export ay may 337 na hilera, kabilang ang isang eksaktong duplicate; ang reconciled dataset ay may 336. Sakop nito ang tatlong paid channel, dalawang device, dalawang audience, at dalawang creative category sa loob ng labing-apat na araw. Normalized ang isang idineklarang campaign alias. Isang zero-activity desktop row ang sumusuri na ang isang zero denominator ay magiging unavailable, hindi zero performance. Nakatala ang source cleanup sa issue log.

Gumagamit ng integer USD cents ang pera. Ang bawat synthetic na bagong customer ay isang beses lang ini-attribute sa huling eligible na paid click sa loob ng pitong araw. Ang first-purchase revenue ay binuo sa $80 bawat customer, pagkatapos ng mga diskwento at hindi kasama ang buwis/shipping, na walang fixture refunds. Ito ay mga isiniwalat na assumption, hindi independently verified na attribution, pagpepresyo ng kurso, o realisadong LTV. Ang checked calculation pack ay nagbibigay ng mga reproducible na reference value.

Hakbang 2 — Humingi sa AI ng tatlong draft mula sa parehong mga input

Ang aktuwal na submitted prompt ay humihingi ng founder summary, media analysis, at creative brief sa isang tugon. Kabilang dito ang brief v1, ang dictionary, reconciled CSV, at campaign/creative lookups. Ang unang draft ay hindi nakatanggap ng kasunod na context note o reference calculation pack.

Ang na-record na tawag ay gumamit ng DeepSeek V4 Pro noong Oktubre 29, 2026. Ang invocation na ito ay text-only, na may walang code-execution tool. Itinatala ng run metadata ang aktuwal na modelo, timestamps, at input hashes. Ang orihinal na tugon ay nananatiling hindi na-edit, kabilang ang mga mali nito.

Nagbigay ang draft ng hinihinging tatlong seksiyon at nagrekomenda ng event/version reconciliation at mobile QA. Nagpakita rin ito ng mga kalkulasyong hindi napatunayan bilang mga numero ng ulat. Ang mga numerong iyon ay may materyal na pagbabago sa magiging hitsura ng negosyo:

Item	Unang draft	Nasuri laban sa reconciled data
Lingguhang media spend	$110,100 sa bawat linggo	$5,462 sa Linggo 1; $5,512 sa Linggo 2.
Attributed na first-purchase revenue	$43,840 → $38,560	$37,360 → $28,560.
Linggo 2 mobile completions	2,360	2,352; 28% ng 8,400 starts.
Audience composition	Inilarawan bilang stable / halos wala bilang paliwanag	Ang mobile `skeptical` start share ay nagbago mula 50% patungong 25%; nagbago ang `exploring` mula 50% patungong 75%.

Ito ay mga natuklasan tungkol sa na-record na tugon na ito sa ilalim ng mga kundisyon ng invocation na ito. Hindi nila itinatatag kung paano gumaganap ang lahat ng modelo, tool-enabled workflow, o analyst. Ang synthetic na pattern ay isinulat bago ang run; hindi ito natuklasang anomalya ng kliyente.

Itanong ang tanong na nagbabago ng interpretasyon

Ang nakatuong follow-up exchange ay humihingi ng stratum counts at mga timbang ng Linggo 1. Sumusulong ito tungo sa pagkilala ng composition, ngunit nagtataglay pa rin ng mga pagkakaiba sa arithmetic. Ang orihinal na tugon at follow-up ay parehong itinatago. Hindi pinapatunayan ng mga bahagyang pagwawasto ang kanilang mga natitirang claim; ang pangalawang mapaniniwalaang sagot ay hindi independent verification.

Ang nasuring paghahambing ay:

Mobile comparison	Completion rate
Linggo 1 naobserbahan	45.00%
Linggo 2 gamit ang mga timbang ng Linggo 1 channel × audience × creative start	35.33%
Linggo 2 naobserbahan	28.00%

May labindalawang mobile strata, bawat isa ay nag-aambag ng 700 Linggo 1 starts, kaya ang bawat baseline weight ay 1/12. Ang paghawak sa mga timbang na iyon na nakapirmi ay nag-iiwan ng pagbaba ng humigit-kumulang 9.67 na porsiyentong puntos. Ang naobserbahang rate ng Linggo 2 ay isa pang 7.33 puntos na mas mababa kaysa sa fixed-mix na paghahambing na iyon. Sa ilalim ng nakasaad na decomposition na ito, ang composition at within-stratum rate movement ay parehong may ambag sa 17-puntong pagbaba.

Binabago niyan ang ayos ng diagnostic na gawain: i-reconcile kung paano nagbago ang audience shares at suriin ang mobile journey at event definitions. Hindi nito tinutukoy ang sanhi ng alinmang paggalaw. Ang fixed-mix calculation ay isang paraan ng paghahambing, hindi isang causal experiment.

Hakbang 3 — Magdagdag ng konteksto at hatulan ang desisyon

Inilalagay ng kurso ang paghatol ng tao rito: ang isang may kakayahan sa pagsukat at kasalukuyang konteksto ng negosyo ay magpapasya kung kukumpirmahin, babaguhin, ipagpapaliban, o tatanggihan ang rekomendasyon ng draft. Ang pagwawasto sa arithmetic lamang ay hindi sapat; dapat ding suriin ng reviewer ang iminungkahing aksiyon.

Sa evidence pack na ito, naisagawa na ang mga kalkulasyon at AI-assisted editorial checks. Ang isang tunay na desisyon ng may-ari/tao para sa release ay nananatiling nakabinbin. Ang mga ahente na naghahanda ng halimbawa ay hindi mga reviewer na tao, at ang mga kathang-isip na role assignment ay hindi tunay na pag-apruba.

Ang supplemental context note ay isinulat at ni-hash-record bago ang unang run. Sa kathang-isip na pagkakasunod-sunod, ang follow-up ng product/support ay nagdadala ng impormasyong wala ang reporting team sa v1:

Iniulat ng product owner ang isang mobile-only na pagbabago sa quiz presentation simula Setyembre 8 sa 09:00 UTC: isang idinagdag na panel ng impormasyon sa sangkap at binagong label sa susunod na hakbang.
Iniulat ng support ang kahirapan sa paghahanap ng kontrol sa susunod na hakbang sa isang telepono, nang walang bilang ng ticket, petsa, o kaugnayan sa mga paid cohort.
Maaaring magtalaga ang product ng reproduction at event-verification check sa susunod na araw ng trabaho; nawawala pa rin ang deployment, rollout, at version-assignment records.

Ito ay iniulat na kathang-isip na konteksto, hindi isang napatunayang release log o ebidensyang ang pagbabago ay naging sanhi ng pag-abandon. Dahil sa timing at device scope nito, sulit itong siyasatin. Nananatiling kinakailangan ang audience-mix check.

Ang isang iminungkahing desisyon sa pagsusuri ay panatilihin ang diagnostic investigation, iwasto ang ebidensya sa pananalapi at cohort, at gawing tiyak ang kahilingan sa product/measurement. Humingi sa product ng rollout/version evidence at mobile reproduction; humingi sa media na i-reconcile ang audience assignment at event capture. Ipagpaliban ang isang causal explanation, creative winner, at eksaktong paggalaw ng badyet. Kung ang unang draft ay nagrerekomenda na ng makatuwirang diagnostic na gawain, maaaring manatiling hindi nagbabago ang bahaging iyon.

Ang review record, brief v2, at brief changes ay nagpapanatili ng mga iminungkahing desisyon at ng ebidensya ng mga ito. Ang aral na dadalhin sa susunod na brief ay tiyak: ang release ay iniulat, naghihintay ng pagpapatunay; ang 45% → 28% na rate at fixed-mix comparison ay mga nasuring natuklasan sa data; ang susunod na pagsisiyasat ay isang iminungkahing desisyon. Ang pagpapanatiling magkahiwalay ng mga kategoryang iyon ay pumipigil sa isang mapaniwalaang paliwanag na maging hindi kuwestiyonadong katotohanan sa mga prompt sa hinaharap.

Hakbang 4 — Gumawa ng mga gamiting ulat at iruta ang susunod na aksiyon

Ginagawang tatlong magkakasuwatong deliverable ng hakbang sa paggawa ang nasuring ebidensya at nakadokumentong mga desisyon sa pagsusuri: ang founder report, media report, at content report. Hanggang sa release ng tao, ito ay mga editorial draft para sa halimbawa, hindi mga aprubadong tagubilin sa kliyente.

Ulat	Kapaki-pakinabang na natuklasan sa anyong ANO / BAKIT / SUSUNOD
Founder summary	ANO: bumaba ng 17 puntos ang paid-mobile completion habang bumaba ang attributed na first-purchase revenue mula $37,360 patungong $28,560. BAKIT: kailangan ng atensiyon ang consideration at first-order output, ngunit hindi kayang pagpasyahan ng dalawang linggo ng paid-cohort ang buwanang kita o tubo. SUSUNOD: isaalang-alang ang pinangalanang diagnostic na gawain at kumuha ng buong-buwan na reconciliation bago ang isang komersiyal na hatol.
Media analysis	ANO: ang mobile ng Linggo 2 ay 28% naobserbahan at 35.33% sa halo ng Linggo 1. BAKIT: mahalaga ang composition at within-stratum movement. SUSUNOD: i-reconcile ang mga depinisyon ng audience/version/event at siyasatin ang mobile journey kasama ng product.
Content & creative brief	ANO: naglalaman ang dataset ng dalawang illustrative na kategorya ng mensahe, habang iniuulat ang isang pagbabago sa mobile presentation. BAKIT: hindi kayang ihiwalay ng kasalukuyang ebidensya ang isang kabiguan ng mensahe o patunayan ang isang creative winner. SUSUNOD: patunayan ang journey at tracking na mga kundisyon bago magdisenyo ng kontroladong message/post-click na pagsubok.

Ang production record ay naglalaman ng isang bounded retrospective alert na sumusunod sa Detect → Analyze → Route → Review. Ang panuntunan ay mature na paid-mobile weekly completion na mas mababa sa 45%, na may nonzero na starts denominator. Natutugunan ito ng Linggo 2 sa 28%. Ikinakabit ng pagsusuri ang cohort window, snapshot, at fixed-mix comparison; ang pagruruta ay nag-aatas ng follow-up sa media at product; nagpapasya ang isang tao kung maaaring i-release ang isang rekomendasyon sa pamumuno/kliyente.

Ang buong pitong-araw na cohort ng Linggo 2 ay hindi maaaring hatulan sa maturity rule na ito bago magsara ang mga observation window nito, sa katapusan ng Setyembre 21 UTC. Ginagamit ng pack na ito ang snapshot mula sa mas huling petsang Setyembre 22. Walang ipinakikitang live alert, pagpapadala ng mensahe, autonomous na pagbabago ng campaign, o naiwasang pagkalugi. Ang lingguhang diagnosis ay nagpapakain sa buwanang pag-uulat ng negosyo at isang quarterly na pag-reset ng mga assumption.

Ulitin ang halimbawa, pagkatapos ay iangkop ito

Magsimula sa tatlong file: ang brief, dictionary, at reconciled CSV. Unahing basahin ang brief; magkakaroon lamang saysay ang CSV kapag malinaw na ang mga desisyon, window, at denominator. Pagkatapos ay suriin ang aktuwal na prompt, orihinal na tugon, nasuring kalkulasyon, at context note para sundan kung ano ang nagbago at bakit.

Gumamit ng modelo at account na aprubado ng inyong organisasyon. Ibahagi lamang ang datos na pinapayagan ng mga kasunduan ng kliyente, organisasyon at provider; alisin ang mga field na may kumpidensyal, sensitibo at personal na impormasyon, at gumamit ng synthetic data o aprubadong pinagsama-samang datos kung maaari. Huwag mag-upload ng export ng datos ng kliyente nang walang pahintulot.

Para sa sarili mong gawain, palitan ang mga layunin sa negosyo, stakeholder, panuntunan sa attribution, at konteksto bago ipasok ang datos ng kliyente. Independiyenteng i-reconcile ang mga total at isang representative na stratum. Itago ang raw response, itala ang napagpasyahan ng reviewer, at dalhin ang napatunayang aral sa susunod na brief. Itigil ang paghahambing kapag hindi nagtugma ang maturity, source coverage, o mga depinisyon; itigil ang release kapag nananatiling hindi nalulutas ang materyal na arithmetic, ebidensya, o awtoridad sa desisyon. Ang nawawalang ebidensya sa awareness, LTV, o incrementality ay nananatiling hindi available.

Ibinabahagi ng landas na ito ang pangangatwiran at kapaki-pakinabang na ebidensya ng halimbawa ng pag-uulat sa halip na itago ang sagot. Ang bayad na kurso ay nagbibigay ng buong pagkakasunod-sunod ng pagtuturo sa video, kumpletong koleksiyon ng magagamit na template, malalim na gabay, at mas malawak na materyal sa pagpapatupad. Ipinapakita ng worked example ang isang konektadong landas mula sa customer hypothesis patungo sa isang desisyon sa pag-uulat; hindi ito nagpapahiwatig ng pitong nakumpletong pampublikong workflow o binabago ang access sa kurso at mga karapatan ng bumibili.

Suriin ang mga gumaganang dokumento

Data dictionary

GreenLeaf reporting data dictionary — v1 semantic contract

Isinulat: 2026-10-29 · Katayuan: naka-frozen na source specification bago gumawa ng fixture; English editorial input. Ang CSV ay isang bagong synthetic reconstruction, hindi nabawi na data ng kurso. Ang brief ang namamahala sa mga desisyon; ang source map ang namamahala sa provenance. Walang kasamang tunay na customer, impormasyon sa kalusugan, o account ng kliyente.

Grain, window, at attribution

Ang isang canonical na row ay isang UTC paid-click date × channel × device × audience × creative, sa UK. Labing-apat na petsa × tatlong channel × dalawang device × dalawang audience × dalawang creative = 336 row. Ang raw export ay may 337 row, kabilang ang isang eksaktong duplicate. Ang campaign ay kabilang sa channel at hindi nagdaragdag ng dimensyon.

Linggo 1: 2026-09-01–2026-09-07 inclusive. Linggo 2: 2026-09-08–2026-09-14 inclusive. Snapshot: 2026-09-22T23:59:59Z. Ang mga araw ay UTC at ang date ay laging nangangahulugang petsa ng paid-click cohort, hindi kailanman petsa ng pagbili/event. Ang mga funnel event at unang pagbili ay inoobserbahan sa loob ng pitong araw pagkatapos ng eligible paid click. Ang mga eksaktong event timestamp ay hindi ini-export; ang seven-day attribution/observation window ay isang assumption sa konstruksyon ng generator. Pareho nang mature ang mga kumpletong panahon sa snapshot. Lahat ng nai-publish na primary row ay may is_provisional=false.

Inilalarawan ng spend, impression, at click ang aktibidad ng acquisition na nakatalaga sa petsa ng cohort na iyon. Ang mga bilang ng landing, quiz, at pagbili ay sumusunod sa source-tagged na paid-click cohort nito at bucket ng device/audience/creative. Ang bawat synthetic na first-purchase customer at halaga ng kita ay itinatalaga nang isang beses, sa huling eligible paid click sa loob ng pitong araw; lahat ng yugto ng event ay sumusunod sa parehong eksklusibong pagtatalaga. Ang cross-device identity reconciliation ay hindi sinusukat. Ang eksklusibidad ay ginagarantiyahan ng konstruksyon, hindi nakapag-iisang itinatag ng aggregate na file na ito.

Mga Field

Field	Uri / yunit	Kahulugan at pagpapatunay
`row_id`	hindi walang laman na string	Matatag na natatanging canonical row ID. Inuulit ito ng raw exact duplicate; ang magkasalungat na row na may parehong ID ay isang error.
`date`	ISO `YYYY-MM-DD`	Petsa ng UTC source paid-click cohort, sa loob ng September 1–14.
`market`	enum	`UK` lamang; ang saklaw ay mga paid cohort sa kathang-isip na paglulunsad sa UK.
`channel`	enum	`google-search`, `linkedin`, `reddit-paid`. Ang organic Reddit activity ay hindi kasama.
`campaign_id`	enum pagkatapos ng normalisasyon	Isang campaign bawat channel; lookup sa ibaba.
`device`	enum	`mobile` o `desktop`, device ng nakatalagang source paid click.
`audience_id`	enum	`skeptical` o `exploring`; mutually exclusive na ginawang mga bucket sa loob ng channel, hindi mga beripikadong katangian ng customer.
`creative_id`	enum	`traceability` o `value`; mga hypothesis ng mensahe na may format na partikular sa channel, lookup sa ibaba.
`spend_cents`	hindi negatibong integer na sentimo ng USD	Gastos sa media lamang. Walang agency, creative, tooling, suweldo, o iba pang gastos sa acquisition.
`impressions`	hindi negatibong integer	Mga impression ng acquisition ad sa bucket; hindi natatanging tao o frequency.
`clicks`	hindi negatibong integer	Mga paid click na nakatalaga sa bucket na ito; hindi natatanging bisita.
`landing_sessions`	hindi negatibong integer	Source-tagged na landing session na naobserbahan sa loob ng pitong araw pagkatapos ng eligible paid click. Hindi hihigit sa isang napanatiling session bawat synthetic na funnel journey.
`quiz_starts`	hindi negatibong integer	Natatanging napanatiling source-tagged na quiz journey na nagsisimula sa loob ng parehong pitong-araw na window; isang napanatiling pagsisimula bawat journey. Denominator ng completion rate.
`quiz_completions`	hindi negatibong integer	Yaong mga napanatiling quiz journey na natapos sa loob ng parehong pitong-araw na window; walang paulit-ulit na pagbibilang ng completion.
`attributed_new_customers`	hindi negatibong integer	Mga first-purchase customer na kumukumpleto ng ginawang quiz-led funnel na ito sa loob ng pitong araw, itinatalaga nang isang beses ng idineklarang last-paid-click rule. Hindi lahat ng bagong customer sa buong site.
`attributed_first_purchase_revenue_cents`	hindi negatibong integer na sentimo ng USD	Kita sa unang pagbili mula sa mga customer na iyon, pagkatapos ng mga discount, hindi kasama ang buwis at pagpapadala. Walang refund sa fixture na ito; walang renewal revenue. Itinatalaga ng generator ang USD $80 (8,000 sentimo) bawat first-purchase customer para sa linaw ng aritmetika; ito ay assumption sa reconstruction, hindi pagpepresyo ng kurso o LTV.
`is_provisional`	boolean	Ang `false` ay nangangahulugang mature na ang pitong-araw na observation window ng row na ito sa idineklarang snapshot. Tanggihan ang hindi suportadong string/boolean coercion.

Mga hindi pagkakapantay-pantay bawat row: impressions >= clicks >= landing_sessions >= quiz_starts >= quiz_completions >= attributed_new_customers. Ito ay malinaw na pinasimpleng konstruksyon ng quiz-led funnel, hindi isang unibersal na katangian ng mga export ng advertising. Ang row na may zero na customer ay dapat may zero na kita sa unang pagbili; ang positibong bilang ng customer ay dapat may positibong kita. Ang mga constraint na ito ay hindi nagbibigay ng ebidensya sa antas ng tao.

Canonical lookups at raw cleanup

Channel	Canonical campaign ID	Display name	Pinapayagang raw campaign ID alias
`google-search`	`gl-uk-google-search`	GreenLeaf UK Search	`gl_uk_search` → `gl-uk-google-search`
`linkedin`	`gl-uk-linkedin`	GreenLeaf UK LinkedIn	Wala
`reddit-paid`	`gl-uk-reddit-paid`	GreenLeaf UK Reddit paid	Wala

Audience skeptical: ginawang bucket para sa isang mamimiling naghahanap ng patunay na nagkukumpara ng ebidensya sa sourcing/dosing; hango sa hindi beripikadong persona ni Oliver. Audience exploring: ginawang bucket para sa isang mamimiling sumusuri sa kategorya at isinasaalang-alang ang halaga. Hindi ito tunay na mga espesipikasyon sa targeting o randomized na pagtatalaga ng treatment; walang ini-infer na pagkakakilanlan, propesyon, o kondisyon sa kalusugan.

Creative traceability: halimbawang mensaheng “Know what is in every serving” (Alamin kung ano ang laman ng bawat serving). Creative value: halimbawang mensaheng “Compare the value of a clearly dosed serving” (Ihambing ang halaga ng bawat serving na may malinaw na dosis). Para sa Google Search, ito ay mga hypothesis ng text-ad message; para sa LinkedIn, mga hypothesis ng sponsored-feed copy; para sa Reddit paid, mga hypothesis ng promoted-post copy. Ang mga creative ID ay magkakaparehong kategorya ng mensahe sa loob ng bawat channel, hindi magkakahawig na tapos na ad asset o aprubadong claim. Walang ibinigay na patunay ng bisa o aktwal na sertipikasyon ng produkto.

Alisin lamang ang isang byte-for-byte/equal-field na eksaktong duplicate, na itinatala ang source row ID nito. I-normalize lamang ang idineklarang alias at itala ang bilang. Ang hindi kilalang ID, hindi inaasahang merkado, nawawalang field, maling petsa, hindi integer na sentimo/bilang, negatibong halaga, magkasalungat na duplicate, o imposibleng funnel ay dapat bumigo sa pagpapatunay sa halip na tahimik na ayusin. Panatilihin ang isang dokumentadong row na may zero denominator upang i-verify ang paghawak ng hindi makukuhang ratio. I-reconcile ang mga bilang ng raw/canonical at lahat ng kabuuan ng dimensyon. Dapat tukuyin ng talaan ng paggawa ng fixture ang eksaktong duplicate, alias row, at row na may zero denominator; hindi nagpapanggap ang dictionary na mayroon na ang mga row na iyon.

Mga panuntunan sa pagsukat at paghahambing

Gumamit ng mga sum sa loob ng napiling cohort/dimensyon, pagkatapos ay hatiin; huwag kailanman i-average ang mga rate sa antas ng row. Panatilihin ang buong intermediate precision. Ipakita ang USD sa pamamagitan ng paghahati ng sentimo sa 100 lamang sa presentasyon. Ang zero denominator ay nagbibigay ng hindi makukuha, hindi kailanman zero/infinity; ang pagbabago ng porsyento laban sa zero na naunang halaga ay hindi makukuha. Pinapanatili sa mga numerong hango sa ebidensyang Ingles ang kumbensiyon ng pinagmulan: kuwit para sa libuhan at tuldok para sa desimal; nasa USD ang lahat ng halagang pera.

Pagsukat	Kahulugan	Interpretasyon
Quiz completion rate	`sum(quiz_completions) / sum(quiz_starts)`	Pangunahing funnel KPI; ang paid-mobile Linggo 1/2 ay dapat i-calibrate sa 45%/28%.
Click-to-start rate	`sum(quiz_starts) / sum(clicks)`	Diagnostic; naiiba sa quiz completion.
Click-to-landing rate	`sum(landing_sessions) / sum(clicks)`	Diagnostic, hindi beripikadong bounce rate.
Completion-to-purchase rate	`sum(attributed_new_customers) / sum(quiz_completions)`	Ginawang diagnostic ng quiz-led funnel.
CTR	`sum(clicks) / sum(impressions)`	Pagsukat sa optimization; hindi awareness.
CPC (USD)	`sum(spend_cents) / sum(clicks) / 100`	Gastos sa media bawat click.
CPM (USD)	`sum(spend_cents) / sum(impressions) * 1000 / 100`	Gastos sa media bawat 1,000 impression.
Media CPA (USD)	`sum(spend_cents) / sum(attributed_new_customers) / 100`	Media-only proxy; hindi buong CAC.
Attributed first-order ROAS	`sum(attributed_first_purchase_revenue_cents) / sum(spend_cents)`	Ratio ng kita/gastos; hindi tubo, incrementality, o LTV.
Kita sa unang pagbili (USD)	`sum(attributed_first_purchase_revenue_cents) / 100`	Attribution ng paid cohort lamang; hindi hatol laban sa target ng $60K sa buong buwan.

Ang pagbabago ng percentage point ng isang rate ay (Week 2 rate - Week 1 rate) * 100. Ang relative change ay (Week 2 rate / Week 1 rate - 1) * 100 kapag positibo ang Linggo 1. Ang ginawang 45% → 28% ay katumbas ng −17 percentage point at humigit-kumulang −37.8% relative; walang ibang resulta ang paunang itinakda ng source contract na ito.

Bago i-diagnose ang paggalaw ng mobile aggregate, i-stratify ang mobile ayon sa channel × audience × creative. Para sa stratum s, itakda ang fixed weight w_s = Week 1 starts_s / Week 1 total starts. Ikumpara ang sum(w_s * Week 1 completion_rate_s) sa sum(w_s * Week 2 completion_rate_s) at ikumpara ang pareho sa mga naobserbahang rate. I-publish ang mga weight at bilang. Ang stratum na may positibong weight na walang tinukoy na rate sa Linggo 2 ay gumagawa ng hindi makukuhang buong fixed-mix na paghahambing; anumang malinaw na pinaghihigpitang paghahambing ng karaniwang strata ay dapat ibunyag ang mga hindi kasamang bilang/weight at hindi maaaring tahimik na tumayo para sa kabuuan. Ang stratum na may zero weight ay nag-aambag ng zero at hindi nangangailangan ng rate. Ang pagbabago ng mix at paggalaw sa loob ng stratum ay maaaring magkasabay. Hindi pinapatunayan ng alinman ang isang dahilan; hindi randomized ang mga cohort.

Ang hindi kumpletong snapshot o pansamantalang primary row ay gumagawa ng dalawang buong panahon na hindi tiyak/hindi maihahambing. Huwag tratuhin bilang zero ang mga hindi naobserbahang kinalabasan. Ang isang hiwalay na napiling paghahambing na may magkaparehong mature na saklaw ay dapat sabihin ang mga napiling petsa, mga pagbubukod, at binagong tanong.

Hindi makukuhang ebidensya at mga salungatan sa source

Hindi makukuha: buong CAC, tubo, retention, realized 12-buwan na LTV, awareness, incrementality, tunay na all-channel/buwan na kita, frequency, impression share, bounce rate, event/release log, interbyu sa customer, at mga paliwanag na causal. Ang hiwalay na 4.2% “quiz CVR” ng source asset ay walang sapat na karaniwang kahulugan ng denominator dito; huwag itong i-import. Walang loss estimate, segment multiple, tagubilin sa badyet, o organic-to-paid causal story mula sa screenshot na isang nakuha na resulta ng fixture. Tingnan ang source map para sa mga katotohanan ng kurso laban sa mga bagong ginawang assumption.

I-download ↓

Tala ng editorial review

Ano ang nagbago sa review

Fictional na GreenLeaf UK, mga paid-click cohort September 1–14, 2026; snapshot September 22, 23:59:59 UTC. Inihanda ang record na ito sa pamamagitan ng AI-assisted editorial review at mga independiyenteng naka-check na kalkulasyon. Ito ay hindi isang nakumpletong pag-apruba ng tao, client review o kontroladong human-versus-AI experiment. Nakabinbin pa rin ang desisyon ng may-ari sa publikasyon/pagpapalabas. Hindi binago ang mga orihinal na model response.

Ang desisyon bago ang pagkasulat

Inirerekomenda ng unang draft ang diagnosis bago ang isang creative o budget pivot. Makatuwiran ang direksyong iyon, ngunit mali ang ilang numero at ang paliwanag. Ang isang makatwirang rekomendasyon ay hindi ginagawang ligtas na ilabas ang sumusuportang ebidensya nito.

Pahayag sa unang draft	Naka-check na ebidensya	Desisyon sa review
Ang spend ay $110,100 sa bawat linggo	Week 1: $5,462; Week 2: $5,512	Tanggihan ang parehong draft totals at bawat derived CPA/ROAS batay sa mga ito
Ang mga bagong customer ay 548 → 482	Canonical na paid-cohort counts: 467 → 357	Palitan; ito ay mga attributed first purchase, hindi incremental subscribers
Ang first-purchase revenue ay $43,840 → $38,560	$37,360 → $28,560	Palitan; walang kasunod na causal revenue-loss estimate
Ang Mobile Week 2 ay may 2,360 completions	2,352 / 8,400 = 28%	Palitan ang count/rate; panatilihin ang naka-check na 3,780 / 8,400 = 45% ng Week 1
Stable ang mobile audience/creative shares at mahalagang wala ang komposisyon	Skeptical share ng mobile starts: 50% → 25%; exploring: 50% → 75%	Tanggihan ang paliwanag sa mix
Ang Fixed Week 1 mix ay nagbibigay ng humigit-kumulang 35.3%–35.5%	Eksaktong 35⅓% bago ang display rounding	Gamitin ang 35.33%; sabihin na parehong mahalaga ang mga pagbabago sa mix at sa loob ng grupo
Dapat i-freeze ng founder ang spend reallocation	Ang CSV lamang ay hindi nagtatatag kung ano ang dapat na lahat ng komersyal/risk na desisyon	Limitahan sa “do not recommend a budget move from this evidence alone” (huwag magrekomenda ng pagbabago sa badyet batay lamang sa ebidensyang ito); panatilihin ang mga umiiral na awtorisadong proseso sa risk
Nagtatagumpay ang isang diagnostic kung babalik ang completion patungo sa 45%	Ang pagbabalik sa isang target ay hindi isang causal test design	Kinakailangan ang beripikadong event definitions, version/cohort evidence at isang malinaw na plano sa paghahambing

Lahat ng channel, desktop, audience at creative tables sa raw response ay nananatiling hindi naaprubahan. Ang mga panghuling editoryal na draft ay gumagamit ng naka-check na metric pack sa halip. Ang model invocation ay text-only, walang calculation-execution tool. Ito ay ebidensya tungkol sa run na ito, hindi sa bawat produkto ng pagsusuri ng AI.

Ano ang ginawa ng focused follow-up

Kinikilala ng pangalawang response ang audience-mix shift at ibinibigay ang tamang Week 2 starts bawat stratum: skeptical 350, exploring 1,050. Iniulat pa rin nito ang 2,360 total completions, nagkakamali sa pagsasabi ng Reddit/exploring/value cell bilang 245 sa halip na 252, at nagkakamali sa pagkalkula ng isang weighted contribution. Gamitin ang naitalang follow-up para siyasatin ang iteration; huwag tahimik na palitan ito ng beripikadong math.

Mga naaprubahang katotohanan para sa production draft

Sukat	Week 1	Week 2
All-paid media spend	$5,462	$5,512
All-paid quiz starts	15,040	15,120
All-paid quiz completions	6,770	5,460
Attributed first-purchase customers	467	357
Attributed first-purchase revenue	$37,360	$28,560
Media CPA	$11.70	$15.44
Attributed first-order ROAS	6.84	5.18
Mobile quiz starts	8,400	8,400
Mobile quiz completions	3,780	2,352
Mobile completion	45%	28%
Desktop completion	45.03%	46.25%

Pagbabago sa mobile: −17 percentage points; humigit-kumulang −37.8% relative. Ang fixed Week 1 channel × audience × creative weights ay nagbibigay ng Week 2 mobile rate na 35.33%. Sa ilalim ng partikular na baseline-weight decomposition na ito, ang within-group component ay −9.67 points at ang natitirang composition component ay −7.33 points. Ang isa pang decomposition order ay maaaring maglaan ng interaction nang iba; ito ay deskriptibo, hindi causal attribution. Lahat ng 12 maihahambing na mobile strata ay bumababa.

Bagong fictional na konteksto at ang epekto nito

Ang context note ay prewritten at na-hash bago ang run. Iniulat nito ang isang mobile presentation revision simula September 8 sa 09:00 UTC at isang hindi naka-link na support concern tungkol sa paghahanap ng next-step control. Nawawala ang release audit, rollout share, ticket counts at mga link sa mga paid cohort.

Hatol: baguhin ang paliwanag at paliitin ang susunod na aksyon; kumpirmahin ang diagnostic-first na direksyon. Hilingin sa product owner at media lead na beripikahin ang mobile journey at event definitions, humiling ng version-assignment/release evidence, at ihambing ang mga like-for-like na grupo kung saan pinapayagan ng ebidensya. Ang iniulat na availability ng product owner para sa isang check sa susunod na araw ng trabaho ay fictional na konteksto, hindi ebidensya na nangyari ang isang check. Ang isang product cause, creative failure o revenue loss ay nananatiling hindi alam.

Dalhin ang ulat ng revision sa brief v2 bilang iniulat na kontekstong nakabinbin ang beripikasyon, hindi kailanman bilang isang nakumpirmang dahilan. Walang naaprubahang awtomatikong pause, pagbabago sa spend o external alert.

Mga tagubilin sa production pass

Panatilihin ang naaprubahang table, uncertainty at desisyon sa itaas sa tatlong draft:

Founder/CEO: trajectory at ang diagnostic na desisyon, na may hindi hihigit sa tatlong aksyon at mga role owner.
Media: detalye ng period/channel/device, ang fixed-mix na paghahambing at ang work order sa imbestigasyon.
Content/creative: panatilihing hiwalay sa patunay ang mga hypothesis sa mensahe; siyasatin ang post-click context bago magmungkahi ng message test. Huwag magpakita ng causal creative winner o magrekomenda ng mga pagbabago sa media-budget.

Para sa retrospective alert: mag-trigger sa settled paid-mobile completion na mas mababa sa nakasaad na 45% target. Sa end-of-day click cohorts at isang seven-day observation rule, ang buong Week 2 na paghahambing ay unang makatwiran sa September 21 sa 23:59:59 UTC; ang ibinigay na snapshot ay September 22 sa 23:59:59 UTC. Ang Detect → Analyze → Route → Review ay isang static na demonstrasyon. Pagmamay-ari ng product owner/media lead ang diagnostic; isang reviewer na may kakayahan sa measurement at release authority ang nagmamay-ari ng client-facing approval. Walang nangyaring pag-apruba ng tao o external delivery. Muling suriin ang panuntunan/konteksto sa susunod na cycle, at i-escalate ang mga nawawalang kahulugan o ebidensya sa marketing owner sa halip na maglabas ng matatag na claim.

Provenance

Sinuri laban sa ibinigay na reconciled CSV, independiyenteng nireview na deterministic calculations at data/analysis.json. Ang mga raw initial at follow-up na response ay nananatiling downloadable evidence. Ang mga numeric claim sa mga panghuling editoryal na draft ay dapat tumugma sa claim ledger. Ang “Approved” dito ay nangangahulugang naaprubahan para sa AI-assisted editorial production pass na ito; hindi ito kapalit ng human release gate ng may-ari.

Check ng naitalang production pass

Pinapanatili ng naitalang formatting pass ang naka-check na period/device counts at financial ratios. Ipinapakilala rin nito ang “hold the diagnostic decision until role owners complete their checks,” (ipagpaliban ang desisyon sa pagsisiyasat hanggang matapos ang mga pagsusuri ng mga responsable sa bawat tungkulin) na maaaring basahin bilang pagpapaliban sa imbestigasyong balak naming simulan. Ang ganoong pagkasulat ay hindi pinanatili sa mga hiwalay na editoryal na ulat. Ang content section nito ay nagpapangkat sa “targeting/mix changes” (mga pagbabago sa targeting o komposisyon) sa ilalim ng mga hypothesis: ang mix shift ay naoobserbahan sa synthetic data; kung ano ang sanhi nito ay nananatiling hypothesis.

Ang ibinigay na founder/media/content files ay hiwalay na inihanda, naka-check na editoryal na draft mula sa parehong naaprubahang katotohanan. Hindi ito ina-advertise bilang verbatim na mga kopya ng formatting response. Ang raw production output ay nananatiling hindi binago upang masiyasat ng mga mambabasa ang huling review boundary na ito rin.

I-download ↓

In-update na reporting brief v2

GreenLeaf reporting brief v2 — dalhin ang natutunan pasulong

Status: AI-assisted editorial draft; nakabinbin ang pag-apruba ng tao para sa publikasyon/pagpapalabas. Fictional na kaso, hindi ebidensya ng operasyon ng kliyente. Ito ay isang additive update sa complete brief v1, hindi kapalit na may mas maikling prompt. Basahin ang dalawa nang magkasama para sa susunod na cycle.

Ang mga layunin ng negosyo, mga kahulugan ng KPI, mga responsibilidad ng stakeholder, mga panuntunan sa attribution, mga target na panahon at cadence sa v1 ay nananatiling hindi nagbabago. Ang bagong kaalaman ay pinaghiwalay ayon sa klase ng ebidensya sa ibaba.

Mga natuklasan sa naka-check na data

Ang Paid-mobile completion ay 3,780/8,400 = 45% sa Week 1 at 2,352/8,400 = 28% sa Week 2.
Ang mobile skeptical/exploring starts mix ay nagbabago mula 50%/50% patungong 25%/75%.
Ang paggamit ng fixed Week 1 channel/audience/creative weights ay nagbibigay ng 35.33% para sa Week 2. Pareho ang komposisyon at paggalaw sa loob ng grupo ay nag-aambag nang deskriptibo; lahat ng 12 mobile strata ay bumababa. Walang napatunayang dahilan.
Ang unang text-only na AI response at ang focused follow-up nito ay naglalaman ng mga arithmetic error. Muling gamitin ang naka-check na metric pack at mga claim reference, hindi ang mga hindi beripikadong numero mula sa mga response na iyon.

Iniulat na fictional na konteksto — nakabinbin ang beripikasyon

Iniuulat ng product owner ang isang mobile quiz presentation revision simula September 8 sa 09:00 UTC. Iniuulat ng support lead ang kahirapan sa paghahanap ng susunod na control sa isang telepono, nang walang mga petsa, bilang o linkage sa mga paid cohort. Walang deployment audit, rollout share o version-assignment evidence ang ibinigay. Binibigyang-priyoridad ng mga ulat na ito ang isang imbestigasyon; hindi ito mga beripikadong release log o isang causal diagnosis.

Work order para sa susunod na cycle

Tungkulin ng may-ari	Kinakailangang ebidensya/aksyon	Kondisyon sa paghinto
Product owner	I-reproduce ang mobile flow at kunin ang release/version/QA evidence	Ang nawawalang assignment/log ay humahadlang sa isang version-specific causal claim
Media lead	I-reconcile ang kahulugan ng event, cohort tagging at maihahambing na device/audience/creative cuts	Ang mga hindi pare-parehong kahulugan o hindi pa mature na window ay humahadlang sa isang settled na paghahambing
Content lead	Siyasatin ang message/post-click expectations pagkatapos ng measurement/journey checks	Walang nakumpirmang problema sa mensahe ay nangangahulugang walang claim ng panalo o bagsak na hook
Reviewer na may kasalukuyang kaalaman sa measurement at release authority	Suriin ang desisyon at lahat ng stakeholder drafts bago ang client-facing release	Ang kawalan ng pag-apruba ay nangangahulugang walang external delivery

Mga hypothesis na dapat manatiling hypothesis

Maaaring mag-ambag ang presentation friction, tracking change, targeting/mix changes at iba pang impluwensya. Hindi itinatatag ng support report ang prevalence o abandonment. Walang naitatag na quiz-driven revenue loss, incremental lift, profit, realized LTV, full CAC o verdict sa monthly-business-target.

Balikan ang konteksto, panuntunan at mga kahilingan sa ebidensya sa susunod na reporting cycle; alisin ang mga lumang assumption o panatilihing malinaw na hindi pa nareresolba ang mga ito. Ni ang update na ito o ang muling paggamit nito ay nagpapatunay ng pinabuting output sa hinaharap.

I-download ↓

Ano ang nagbago sa brief

Ano ang nagbago sa pagitan ng brief v1 at v2

Fictional na GreenLeaf na halimbawa. AI-assisted editorial review; nakabinbin ang pagpapalabas ng tao.

Lugar	v1	v2	Klase ng ebidensya
Mobile signal	Target at isinulat na teaching signal; wala pang naka-check na output	Naka-check na 3,780/8,400 → 2,352/8,400	Reconstructed CSV, beripikadong kalkulasyon
Audience mix	Ihambing bago ang diagnosis	Ang mobile starts ay lumilipat mula sa pantay na shares patungong 25% skeptical / 75% exploring	Reconstructed CSV, beripikadong kalkulasyon
Mga maihahambing na grupo	Kinakailangang analytic check	Fixed-mix Week 2 rate 35.33%; lahat ng 12 strata ay bumababa	Deskriptibong kalkulasyon, walang causal interpretation
Product history	Hindi alam; humiling mula sa owner	Iniulat ang mobile revision; nawawala ang audit/assignment/rollout	Prewritten na fictional na konteksto, nakabinbin ang beripikasyon
Support history	Hindi alam	Iniulat ang hindi naka-link na kahirapan sa paghahanap ng next-step control	Fictional na anekdota, walang prevalence estimate
Susunod na hakbang	Mag-diagnose bago ang isang premature na interbensyon	Bigyang-priyoridad ang mobile/event verification kasama ang product/media owners	Editoryal na desisyon, iminungkahi ngunit hindi nakumpleto
Mga numero ng AI	Dapat i-check	Dokumentado ang initial/follow-up na mga error; gamitin ang naka-check na metric pack	Aktwal na naitalang mga response at mga independiyenteng check
Mga target at hindi alam sa negosyo	Apat na target, nawawala ang causal/LTV/awareness/economics evidence	Hindi nagbabago	Scenario ng kurso at mga limitasyon sa ebidensya

Walang sadyang inalis na kilalang kasaysayan mula sa v1. Ang mas huling konteksto ay isinulat bago ang unang run at kumakatawan sa impormasyong natutunan kalaunan ng fictional na team. Ang sequence na ito ay hindi isang kontroladong test ng kahigitan ng tao, at hindi rin patunay ng depekto ng produkto o isang nasukat na pagtitipid.

I-download ↓

Tala ng production at routing

Naabot ng isang finding ang tamang may-ari

Static retrospective teaching example. Walang monitoring service, external messages, awtomatikong pagbabago sa campaign o nakumpletong pagpapalabas ng tao. Ang mga iminungkahing ulat ay AI-assisted editorial drafts.

Detect

Panuntunan: ang settled paid-mobile quiz completion ay mas mababa sa 45% target ng scenario. Ang Week 2 ay 2,352/8,400 = 28%. Ito ay isang tinukoy na panuntunan sa quiz, hindi paghahambing ng media CPA sa full CAC.

Sinasaklaw ng mga click cohort ang September 8–14, 2026, UTC, na may seven-day observation window. Sa ilalim ng end-of-day maturity convention, ang isang kumpletong paghahambing sa Week 2 ay unang makatwiran sa September 21 sa 23:59:59 UTC. Ginagamit ng halimbawang ito ang September 22, 23:59:59 UTC snapshot. Hindi nito maipapakita ang maagang detection sa Week 2 o mapapatunayan na maiiwasan sana ang isang pagkawala.

Analyze

Suriin ang mga bilang at kahulugan, pagkatapos ay ang mga maihahambing na grupo. Ang fixed Week 1 mix ay nagbibigay ng 35.33%, hindi 28%: parehong mahalaga ang mga pagbabago sa komposisyon at sa loob ng grupo. Sinusuportahan ng iniulat na mobile revision/support concern ang isang diagnostic hypothesis, hindi isang dahilan. Ang mga hindi available na kinalabasan ay nananatiling hindi available.

Route

Tatanggap	Natatanggap	Responsibilidad
Product owner + media lead	Mobile diagnostic work order at mga kaugnay na cohort	Beripikahin ang journey/events at kunin ang release/version evidence
Founder / marketing owner	Buod na nakaharap sa negosyo	Magpasya ng mga prayoridad pagkatapos na makapasa sa review ang ebidensya at rekomendasyon
Content lead	Message/post-click brief	Siyasatin ang handoff at magmungkahi lamang ng makatwirang test

Walang live na email/Slack delivery. Ang table ay isang routing record sa loob ng fictional workflow.

Review

Estado ng pagpapalabas: nakabinbin ang review ng tao. Dapat aprubahan ng isang reviewer na may kasalukuyang kakayahan sa measurement at release authority ang mga rekomendasyong nakaharap sa kliyente. Ang isang green test, model response o review ng ibang agent ay hindi nagbibigay ng ganoong pag-apruba.

Lingguhang diagnostic cadence; buwanang business narrative; quarterly planning reset. Balikan ang panuntunan at konteksto sa susunod na reporting cycle. I-escalate ang mga nawawalang kahulugan, lumang konteksto o hindi available na version evidence sa marketing owner; panatilihin ang uncertainty sa halip na gumawa ng kumpiyansang alert. Walang iniimbentong eksaktong petsa ng review sa hinaharap, nakumpletong diagnostic o kinalabasan.

I-download ↓

Ebidensya ng na-record na run

Mga orihinal na AI call na naitala sa Ingles.

Unang isinumiteng prompt

Prepare the first reporting draft for fictional GreenLeaf Wellness UK. This is an openly constructed teaching example, not real campaign or customer data. Read the full reporting brief and dictionary before analyzing the reconciled CSV. You have no code-execution tool in this request; do not claim you executed code, queried a platform or inspected release logs. Show calculations and label any arithmetic uncertainty.

In one response produce three clearly headed deliverables: Founder / CEO Summary (one-page equivalent, at most three actions with role owners), Media Team Analysis (checked period/channel/device/audience/creative comparisons), and Content & Creative Brief (message/post-click hypotheses and a focused next test). Facts and recommendations must remain consistent across the three. Every finding answers WHAT happened, WHY it matters to the business, and WHAT'S NEXT. State unavailable outcomes.

For media analysis, show summed spend, starts, completions, new customers, attributed first-purchase revenue, media CPA and first-order ROAS for each period. Check the mobile aggregate against channel × audience × creative strata and compute a Week 1-starts-weighted Week 2 rate before diagnosing the decline. Separate composition from within-group changes; neither proves causality. Do not invent a loss estimate, conversion denominator, budget, profit, CAC reconciliation or incremental result. Do not treat a two-week export as full-month target performance. Do not force a budget or creative change when a diagnostic recommendation is justified.

Return readable Markdown with compact evidence tables. Include an explicit limitations section and a short reproducible calculation for the main signal.

## Attached file: en/brief-v1.md

# GreenLeaf UK launch — reporting brief v1

**Version:** 1.0 · **Authored:** 2026-10-29 · **Status:** English source input for a fictional teaching example; not a published report. Freeze this brief, the dictionary and the source map before fixture generation. Freeze exact run-input hashes separately after data verification. No AI response or analytical result is claimed by this brief.

## Business and the handoffs into reporting

GreenLeaf Wellness is the course's fictional subscription supplement business, expanding from the US into the UK. Its products include daily greens, protein blends and adaptogen stacks. Its proposed distinction is ingredient traceability and transparent dosing. The commercial question is whether that proposition helps UK buyers progress from consideration to a first purchase. This reconstruction examines paid cohorts; it cannot settle the whole launch's success.

| Upstream work | Concrete handoff supplied here | How reporting uses it | Evidence still needed |
|---|---|---|---|
| Research and strategy | Oliver, the skeptical biohacker, is a synthetic persona hypothesis. Objection: can I verify what is in a serving, and does the price reflect value? Interview question: what evidence changed your last supplement shortlist? | Compare the `skeptical` and `exploring` audience hypotheses and the `traceability` and `value` messages without treating identifiers as validated psychology. | Real customer interviews, observed objections and a validated segment definition. |
| Measurement | Business objective → KPI → diagnostic lever. Quiz completion = completions / starts; new-customer revenue has a monthly target. Seven-day UTC paid-click cohorts have a common maturity rule. | Keep outcomes above CTR/CPC/CPM and compare like-for-like denominators. | All-channel monthly revenue reconciliation, awareness research, retention history and incrementality design/results. |
| Activation | Illustrative message: “Know what is in every serving.” Second message tests value through clear dosing information. Journey: ad → landing page → quiz start → completion → first purchase. Canonical campaign/device/audience/creative IDs are in the dictionary. | Inspect message, audience, device and funnel stage; request event and release reconciliation before diagnosing. | Substantiation of any product claim, event QA logs, ad-platform exports and a timestamped release/test register. These illustrative messages are not approved advertising. |
| Institutional memory | This v1 records all scenario context currently supplied. There is no supplied historical seasonal baseline, client preference log, earlier agency finding or known product incident. | Treat missing history as unknown; ask its owner rather than invent a founder sensitivity or seasonal explanation. | Product/support and commercial-owner follow-up; record subsequently learned information with provenance in v2. |

The source map separates course facts, new reconstruction choices and later derived results. Source: [course traceability](../data/course-source-map.json). Field semantics: [dictionary](dictionary.md).

## 1. KPIs and targets

| Business decision | Course scenario target | Evidence available from this reconstruction | Reporting boundary |
|---|---|---|---|
| Are buyers progressing through consideration? | 45% quiz completion | Paid-cohort quiz completions ÷ starts, including mobile and desktop separately | The authored mobile comparison is 45% → 28%, a 17 percentage point decline (approximately 37.8% relative). Verify counts after generation; this is a teaching constraint, not an observed client result or all-site rate. |
| Is the UK launch producing new-customer revenue? | USD $60,000 per month | Attributed first-purchase revenue for September 1–14 paid-click cohorts | Two paid-cohort weeks do not establish a full-month, all-channel result. Do not prorate the target into a success verdict. Obtain the full month, common revenue definition and reconciled new-customer ledger. |
| Is GreenLeaf becoming known? | 15% unaided awareness | Unavailable | Impressions, clicks and paid revenue cannot substitute for a brand-awareness study. |
| Are customers valuable over time? | USD $480 LTV at 12 months | Unavailable | First-order revenue cannot establish realized LTV or retention. |

The course's **$312 breakeven CAC** is a scenario planning guardrail. This export supplies media spend and attributed first-purchase customers, so it supports **media CPA**, not full CAC. Reconcile acquisition cost scope, unique new customers, periods and the economic assumptions before comparing with that guardrail. No CAC breach or profitability claim follows from media CPA alone.

CTR, CPC, CPM, click-to-start rate, completion-to-purchase rate, media CPA and attributed first-order ROAS are diagnostic levers. Frequency, impression share and bounce rate are unavailable because their required source fields are absent. Incremental lift, all-site revenue, refunds outside the fixture, full acquisition economics and long-term outcomes remain unknown.

## 2. Stakeholders, decisions and release authority

One prompt must produce all three drafts from the same brief and reconciled dataset. Every finding answers **WHAT happened → WHY it matters → WHAT'S NEXT**, separating checked facts, hypotheses, unknowns and proposed actions.

| Recipient | Decision the report must support | Required deliverable | Authority and boundary |
|---|---|---|---|
| Founder / CEO (or in-house marketing leader) | Should launch priorities change now, or should the team obtain specific evidence before a commercial decision? | One-page summary of the business signal, material uncertainty and a named next decision. | Founder/marketing owner approves commercial priorities and budget. No automatic reallocation, unsupported lost-revenue estimate or monthly target verdict. |
| Media team | Which cohort, event definition or journey stage should be investigated first, and what evidence would change the next media decision? | Channel/device/audience/creative analysis, funnel counts, weighted rates and fixed-mix check. | Media lead owns source reconciliation and diagnostic work order; spend changes require commercial approval. |
| Content & creative team | Should the next test focus on the message, the post-click experience, or evidence needed to choose between them? | Focused creative/testing brief with hypothesis, evidence required, owner and success measure. | Creative lead proposes a test; product owner approves product changes and relevant claim substantiation. No unsupported creative winner or causal claim. |

Agency leaders can inspect the quality of advice and release discipline; in-house leaders can inspect evidence for changing the plan; performance leads can inspect the diagnostic work. Readers evaluating professional judgment can inspect the same evidence. These reader perspectives do not replace the three course deliverables or change the underlying facts.

A reviewer competent in measurement definitions and campaign operations checks source reconciliation, calculations, comparison logic and the proposed decision. The founder/marketing owner retains release authority for leadership/client-facing recommendations. These are fictional role assignments, not real people, messages or approvals.

## 3. Context layers and known unknowns

**Temporal:** Week 1 = September 1–7, 2026; Week 2 = September 8–14. `date` is a UTC paid-click cohort date. Funnel events and attributed purchases share seven days after the eligible click. Snapshot = `2026-09-22T23:59:59Z`, when both periods are mature. This is a retrospective comparison, not evidence of detection during Week 2. No seasonal effect, holiday explanation or earlier baseline is supplied.

**Business:** UK expansion, subscription products and the transparency proposition come from the fictional course scenario. The reporting currency is USD to preserve the course target units. No real UK price, exchange-rate conversion, approved health claim, launch budget or full customer economics is established here.

**Competitive:** the course uses AG1, Huel, Ritual, Seed and Thorne as recognizable category context. Current pricing, competitor campaigns and market shares have not been researched for this example; no movement can be attributed to them. Oliver's persona dialogue is synthetic, not an interview transcript from a real customer.

**Client/team history:** product release status, mobile QA findings, support feedback, founder sensitivities, audience-test assignment and earlier reporting lessons have not been supplied at v1. Absence from these inputs does not mean nothing changed. The first diagnostic work order must ask product/support for timestamped context and measurement for event/version reconciliation. Any answer is new information to this brief and must be labelled as such. Do not assume a product problem in advance.

## 4. Benchmarks, dimensions and common-sense checks

The internal comparison is two equal, mature seven-day periods. The 45% course target is the benchmark under the declared paid-cohort scope; no external industry benchmark is supplied. Dimensions are channel (`google-search`, `linkedin`, `reddit-paid`), device (`mobile`, `desktop`), audience (`skeptical`, `exploring`), creative (`traceability`, `value`) and funnel stage. These are constructed mutually exclusive reporting buckets, not verified targeting performance or real persona classification.

Before drafting findings:

1. Reconcile 337 raw rows to 336 canonical daily rows: remove the single exact duplicate, normalize only the declared campaign alias, preserve source counts and validate identifiers, integer counts/cents and `is_provisional`.
2. Check funnel inequalities, mature coverage and attribution assumptions. Do not infer unique customers independently from an aggregate CSV. Zero denominators yield unavailable ratios, not zero performance.
3. Sum numerators and denominators before dividing. Never average row rates; calculate monetary ratios from cents without rounding intermediate values.
4. Check mobile movement within channel × audience × creative strata. Compare Week 2 stratum rates using Week 1 quiz-start shares as fixed weights. Report observed aggregate, fixed-mix comparison, weights and any undefined stratum. Diagnose composition versus within-group movement before a product explanation; either pattern still lacks causal identification.
5. Reconcile device and segment totals to the whole. Explain first-order revenue with its cohort and attribution limits. Do not copy unsupported course-asset numbers such as revenue at risk, a segment multiple or a precise budget move.

**Retrospective alert rule:** for a mature comparable weekly paid-mobile cohort with at least one quiz start, flag completion below 45%. Detect → analyze with source/fixed-mix checks → route the diagnostic to the media lead and product owner → human review. The accountable owner records source window, snapshot, earliest defensible availability, decision and approval state. A static sample is not a running service; no external messages, automatic spend changes or prevented-loss claim is authorized.

## 5. Cadence and the next brief

Weekly: diagnostic/optimization summary, checked cohort cuts, owner and next evidence request. Monthly: business narrative against the full target period, with all-channel reconciliation and unavailable outcomes explicit. Quarterly: reset planning assumptions, benchmarks and measurement design rather than extrapolate this snapshot.

For this teaching cycle, preserve the actual multi-audience prompt and unedited response; record model/run metadata and exact input hashes. Include a focused analysis question, checked answer and useful follow-up. Human review may confirm, revise, defer or reject a recommendation; unchanged advice is a valid outcome. Newly learned fictional context must have been written and hash-recorded before the initial run, and must not be retrofitted to manufacture a failure. It is not an input to the first draft.

Then record the review reasoning, update brief v2 and a readable diff, and produce three final reports from approved facts. Distinguish context-enabled changes from independent reviewer judgment. Preserve hypotheses as hypotheses in memory. This sequence demonstrates reporting judgment; it does not measure AI accuracy, human superiority, saved time or client ROI. Public release requires the separately governed localization and review gates.


## Attached file: en/dictionary.md

# GreenLeaf reporting data dictionary — v1 semantic contract

**Authored:** 2026-10-29 · **Status:** frozen source specification before fixture generation; English editorial input. The CSV is a new synthetic reconstruction, not recovered course data. The [brief](brief-v1.md) governs decisions; the [source map](../data/course-source-map.json) governs provenance. No real customers, health information or client accounts are included.

## Grain, window and attribution

One canonical row is one UTC paid-click date × channel × device × audience × creative, in the UK. Fourteen dates × three channels × two devices × two audiences × two creatives = **336 rows**. The raw export has **337 rows**, including one exact duplicate. Campaign belongs to channel and does not add a dimension.

Week 1: `2026-09-01`–`2026-09-07` inclusive. Week 2: `2026-09-08`–`2026-09-14` inclusive. Snapshot: **`2026-09-22T23:59:59Z`**. Days are UTC and `date` always means paid-click cohort date, never purchase/event date. Funnel events and first purchases are observed during the seven days after the eligible paid click. Exact event timestamps are not exported; the seven-day attribution/observation window is a generator construction assumption. Both complete periods have matured at the snapshot. All published primary rows have `is_provisional=false`.

Spend, impressions and clicks describe the acquisition activity assigned to that cohort date. Landing, quiz and purchase counts follow its source-tagged paid-click cohort and device/audience/creative bucket. Each synthetic first-purchase customer and revenue amount is assigned once, to the last eligible paid click within seven days; all event stages follow this same exclusive assignment. Cross-device identity reconciliation is not measured. Exclusivity is guaranteed by construction, not independently established by this aggregate file.

## Fields

| Field | Type / unit | Meaning and validation |
|---|---|---|
| `row_id` | nonempty string | Stable unique canonical row ID. The raw exact duplicate repeats it; conflicting rows with the same ID are an error. |
| `date` | ISO `YYYY-MM-DD` | UTC source paid-click cohort date, within September 1–14. |
| `market` | enum | `UK` only; scope is paid cohorts in the fictional UK launch. |
| `channel` | enum | `google-search`, `linkedin`, `reddit-paid`. Organic Reddit activity is excluded. |
| `campaign_id` | enum after normalization | One campaign per channel; lookup below. |
| `device` | enum | `mobile` or `desktop`, device of assigned source paid click. |
| `audience_id` | enum | `skeptical` or `exploring`; mutually exclusive constructed buckets within channel, not validated customer traits. |
| `creative_id` | enum | `traceability` or `value`; message hypotheses with channel-specific format, lookup below. |
| `spend_cents` | nonnegative integer USD cents | Media cost only. No agency, creative, tooling, salaries or other acquisition costs. |
| `impressions` | nonnegative integer | Acquisition ad impressions in the bucket; not unique people or frequency. |
| `clicks` | nonnegative integer | Paid clicks assigned to this bucket; not unique visitors. |
| `landing_sessions` | nonnegative integer | Source-tagged landing sessions observed within seven days of the eligible paid click. At most one retained session per synthetic funnel journey. |
| `quiz_starts` | nonnegative integer | Distinct retained source-tagged quiz journeys that start within the same seven-day window; one retained start per journey. Completion-rate denominator. |
| `quiz_completions` | nonnegative integer | Those retained quiz journeys completed within the same seven-day window; no repeated completion counting. |
| `attributed_new_customers` | nonnegative integer | First-purchase customers completing this constructed quiz-led funnel within seven days, assigned once by the declared last-paid-click rule. Not all-site new customers. |
| `attributed_first_purchase_revenue_cents` | nonnegative integer USD cents | First-purchase revenue from those customers, after discounts, excluding tax and shipping. No refunds in this fixture; no renewal revenue. The generator assigns USD $80 (8,000 cents) per first-purchase customer for arithmetic clarity; this is a reconstruction assumption, not course pricing or LTV. |
| `is_provisional` | boolean | `false` means this row's seven-day observation window is mature at the declared snapshot. Reject unsupported string/boolean coercion. |

Per-row inequalities: `impressions >= clicks >= landing_sessions >= quiz_starts >= quiz_completions >= attributed_new_customers`. This is an explicit simplified quiz-led funnel construction, not a universal property of advertising exports. A row with zero customers must have zero first-purchase revenue; a positive customer count must have positive revenue. These constraints do not supply person-level evidence.

## Canonical lookups and raw cleanup

| Channel | Canonical campaign ID | Display name | Allowed raw campaign ID alias |
|---|---|---|---|
| `google-search` | `gl-uk-google-search` | GreenLeaf UK Search | `gl_uk_search` → `gl-uk-google-search` |
| `linkedin` | `gl-uk-linkedin` | GreenLeaf UK LinkedIn | None |
| `reddit-paid` | `gl-uk-reddit-paid` | GreenLeaf UK Reddit paid | None |

Audience `skeptical`: constructed bucket for a proof-seeking buyer comparing sourcing/dosing evidence; inspired by Oliver's unvalidated persona. Audience `exploring`: constructed bucket for a buyer exploring the category and considering value. They are neither real targeting specifications nor randomized treatment assignments; no identity, profession or health condition is inferred.

Creative `traceability`: illustrative “Know what is in every serving” message. Creative `value`: illustrative “Compare the value of a clearly dosed serving” message. For Google Search these are text-ad message hypotheses; for LinkedIn, sponsored-feed copy hypotheses; for Reddit paid, promoted-post copy hypotheses. Creative IDs are shared message categories within each channel, not identical finished ad assets or approved claims. No proof of efficacy or actual product certification is supplied.

Remove only a byte-for-byte/equal-field exact duplicate, recording its source row ID. Normalize only the declared alias and record the count. An unknown ID, unexpected market, missing field, malformed date, noninteger cents/count, negative value, conflicting duplicate or impossible funnel must fail validation rather than be silently repaired. Preserve a documented zero-denominator row to verify unavailable-ratio handling. Reconcile raw/canonical counts and all dimension totals. The fixture generation record must identify the exact duplicate, alias row and zero-denominator row; this dictionary does not pretend those rows already exist.

## Metrics and comparison rules

Use sums within the selected cohort/dimension, then divide; never average row-level rates. Retain full intermediate precision. Display USD by dividing cents by 100 only at presentation. A zero denominator yields **unavailable**, never zero/infinity; percent change against a zero prior value is unavailable.

| Metric | Definition | Interpretation |
|---|---|---|
| Quiz completion rate | `sum(quiz_completions) / sum(quiz_starts)` | Primary funnel KPI; paid-mobile Week 1/2 must be calibrated to 45%/28%. |
| Click-to-start rate | `sum(quiz_starts) / sum(clicks)` | Diagnostic; distinct from quiz completion. |
| Click-to-landing rate | `sum(landing_sessions) / sum(clicks)` | Diagnostic, not a verified bounce rate. |
| Completion-to-purchase rate | `sum(attributed_new_customers) / sum(quiz_completions)` | Constructed quiz-led funnel diagnostic. |
| CTR | `sum(clicks) / sum(impressions)` | Optimization metric; not awareness. |
| CPC (USD) | `sum(spend_cents) / sum(clicks) / 100` | Media cost per click. |
| CPM (USD) | `sum(spend_cents) / sum(impressions) * 1000 / 100` | Media cost per 1,000 impressions. |
| Media CPA (USD) | `sum(spend_cents) / sum(attributed_new_customers) / 100` | Media-only proxy; not full CAC. |
| Attributed first-order ROAS | `sum(attributed_first_purchase_revenue_cents) / sum(spend_cents)` | Revenue/spend ratio; not profit, incrementality or LTV. |
| First-purchase revenue (USD) | `sum(attributed_first_purchase_revenue_cents) / 100` | Paid-cohort attribution only; not a verdict against the $60K full-month target. |

A rate's percentage-point change is `(Week 2 rate - Week 1 rate) * 100`. Relative change is `(Week 2 rate / Week 1 rate - 1) * 100` when Week 1 is positive. The authored 45% → 28% equals −17 percentage points and approximately −37.8% relative; no other result is predetermined by this source contract.

Before diagnosing mobile aggregate movement, stratify mobile by channel × audience × creative. For stratum `s`, set fixed weight `w_s = Week 1 starts_s / Week 1 total starts`. Compare `sum(w_s * Week 1 completion_rate_s)` with `sum(w_s * Week 2 completion_rate_s)` and compare both with observed rates. Publish weights and counts. A positive-weight stratum without a defined Week 2 rate makes the full fixed-mix comparison unavailable; any explicitly restricted common-strata comparison must disclose excluded counts/weights and cannot silently stand in for the whole. A zero-weight stratum contributes zero and does not require a rate. Changing mix and within-stratum movement may coexist. Neither proves a cause; the cohorts are not randomized.

An incomplete snapshot or provisional primary row makes the two full periods unsettled/noncomparable. Do not treat unobserved outcomes as zero. A separately selected comparison with identical mature coverage must state the selected dates, exclusions and changed question.

## Unavailable evidence and source conflicts

Unavailable: full CAC, profit, retention, realized 12-month LTV, awareness, incrementality, true all-channel/month revenue, frequency, impression share, bounce rate, event/release logs, customer interviews and causal explanations. The source asset's separate 4.2% “quiz CVR” has no adequate shared denominator definition here; do not import it. No screenshot's loss estimate, segment multiple, budget instruction or organic-to-paid causal story is a derived fixture result. See the source map for course facts versus newly authored assumptions.


## Attached file: data/reconciled.csv

row_id,date,market,channel,campaign_id,device,audience_id,creative_id,spend_cents,impressions,clicks,landing_sessions,quiz_starts,quiz_completions,attributed_new_customers,attributed_first_purchase_revenue_cents,is_provisional
d01-google-search-mobile-skeptical-traceability,2026-09-01,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3100,2520,140,120,100,54,4,32000,false
d01-google-search-mobile-skeptical-value,2026-09-01,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3100,2520,140,120,100,58,4,32000,false
d01-google-search-mobile-exploring-traceability,2026-09-01,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3100,2520,140,120,100,25,2,16000,false
d01-google-search-mobile-exploring-value,2026-09-01,UK,google-search,gl-uk-google-search,mobile,exploring,value,3100,2520,140,120,100,29,2,16000,false
d01-google-search-desktop-skeptical-traceability,2026-09-01,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3100,2160,120,100,80,38,3,24000,false
d01-google-search-desktop-skeptical-value,2026-09-01,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3100,2160,120,100,80,40,3,24000,false
d01-google-search-desktop-exploring-traceability,2026-09-01,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3100,2160,120,100,80,30,2,16000,false
d01-google-search-desktop-exploring-value,2026-09-01,UK,google-search,gl-uk-google-search,desktop,exploring,value,3100,2160,120,100,80,32,2,16000,false
d01-linkedin-mobile-skeptical-traceability,2026-09-01,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4100,2660,140,120,100,58,4,32000,false
d01-linkedin-mobile-skeptical-value,2026-09-01,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4100,2660,140,120,100,62,4,32000,false
d01-linkedin-mobile-exploring-traceability,2026-09-01,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4100,2660,140,120,100,28,2,16000,false
d01-linkedin-mobile-exploring-value,2026-09-01,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4100,2660,140,120,100,32,2,16000,false
d01-linkedin-desktop-skeptical-traceability,2026-09-01,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4100,2280,120,100,80,39,3,24000,false
d01-linkedin-desktop-skeptical-value,2026-09-01,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4100,2280,120,100,80,41,3,24000,false
d01-linkedin-desktop-exploring-traceability,2026-09-01,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4100,2280,120,100,80,31,2,16000,false
d01-linkedin-desktop-exploring-value,2026-09-01,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4100,2280,120,100,80,33,2,16000,false
d01-reddit-paid-mobile-skeptical-traceability,2026-09-01,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2600,2800,140,120,100,62,4,32000,false
d01-reddit-paid-mobile-skeptical-value,2026-09-01,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2600,2800,140,120,100,66,5,40000,false
d01-reddit-paid-mobile-exploring-traceability,2026-09-01,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2600,2800,140,120,100,31,2,16000,false
d01-reddit-paid-mobile-exploring-value,2026-09-01,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2600,2800,140,120,100,35,2,16000,false
d01-reddit-paid-desktop-skeptical-traceability,2026-09-01,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2600,2400,120,100,80,40,3,24000,false
d01-reddit-paid-desktop-skeptical-value,2026-09-01,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2600,2400,120,100,80,42,3,24000,false
d01-reddit-paid-desktop-exploring-traceability,2026-09-01,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2600,2400,120,100,80,32,2,16000,false
d01-reddit-paid-desktop-exploring-value,2026-09-01,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,0,0,0,0,0,0,0,0,false
d02-google-search-mobile-skeptical-traceability,2026-09-02,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3200,2520,140,120,100,54,4,32000,false
d02-google-search-mobile-skeptical-value,2026-09-02,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3200,2520,140,120,100,58,4,32000,false
d02-google-search-mobile-exploring-traceability,2026-09-02,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3200,2520,140,120,100,25,2,16000,false
d02-google-search-mobile-exploring-value,2026-09-02,UK,google-search,gl-uk-google-search,mobile,exploring,value,3200,2520,140,120,100,29,2,16000,false
d02-google-search-desktop-skeptical-traceability,2026-09-02,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3200,2160,120,100,80,38,3,24000,false
d02-google-search-desktop-skeptical-value,2026-09-02,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3200,2160,120,100,80,40,3,24000,false
d02-google-search-desktop-exploring-traceability,2026-09-02,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3200,2160,120,100,80,30,2,16000,false
d02-google-search-desktop-exploring-value,2026-09-02,UK,google-search,gl-uk-google-search,desktop,exploring,value,3200,2160,120,100,80,32,2,16000,false
d02-linkedin-mobile-skeptical-traceability,2026-09-02,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4200,2660,140,120,100,58,4,32000,false
d02-linkedin-mobile-skeptical-value,2026-09-02,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4200,2660,140,120,100,62,4,32000,false
d02-linkedin-mobile-exploring-traceability,2026-09-02,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4200,2660,140,120,100,28,2,16000,false
d02-linkedin-mobile-exploring-value,2026-09-02,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4200,2660,140,120,100,32,2,16000,false
d02-linkedin-desktop-skeptical-traceability,2026-09-02,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4200,2280,120,100,80,39,3,24000,false
d02-linkedin-desktop-skeptical-value,2026-09-02,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4200,2280,120,100,80,41,3,24000,false
d02-linkedin-desktop-exploring-traceability,2026-09-02,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4200,2280,120,100,80,31,2,16000,false
d02-linkedin-desktop-exploring-value,2026-09-02,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4200,2280,120,100,80,33,2,16000,false
d02-reddit-paid-mobile-skeptical-traceability,2026-09-02,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2700,2800,140,120,100,62,4,32000,false
d02-reddit-paid-mobile-skeptical-value,2026-09-02,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2700,2800,140,120,100,66,5,40000,false
d02-reddit-paid-mobile-exploring-traceability,2026-09-02,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2700,2800,140,120,100,31,2,16000,false
d02-reddit-paid-mobile-exploring-value,2026-09-02,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2700,2800,140,120,100,35,2,16000,false
d02-reddit-paid-desktop-skeptical-traceability,2026-09-02,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2700,2400,120,100,80,40,3,24000,false
d02-reddit-paid-desktop-skeptical-value,2026-09-02,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2700,2400,120,100,80,42,3,24000,false
d02-reddit-paid-desktop-exploring-traceability,2026-09-02,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2700,2400,120,100,80,32,2,16000,false
d02-reddit-paid-desktop-exploring-value,2026-09-02,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2700,2400,120,100,80,34,2,16000,false
d03-google-search-mobile-skeptical-traceability,2026-09-03,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3000,2520,140,120,100,54,4,32000,false
d03-google-search-mobile-skeptical-value,2026-09-03,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3000,2520,140,120,100,58,4,32000,false
d03-google-search-mobile-exploring-traceability,2026-09-03,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3000,2520,140,120,100,25,2,16000,false
d03-google-search-mobile-exploring-value,2026-09-03,UK,google-search,gl-uk-google-search,mobile,exploring,value,3000,2520,140,120,100,29,2,16000,false
d03-google-search-desktop-skeptical-traceability,2026-09-03,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3000,2160,120,100,80,38,3,24000,false
d03-google-search-desktop-skeptical-value,2026-09-03,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3000,2160,120,100,80,40,3,24000,false
d03-google-search-desktop-exploring-traceability,2026-09-03,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3000,2160,120,100,80,30,2,16000,false
d03-google-search-desktop-exploring-value,2026-09-03,UK,google-search,gl-uk-google-search,desktop,exploring,value,3000,2160,120,100,80,32,2,16000,false
d03-linkedin-mobile-skeptical-traceability,2026-09-03,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4000,2660,140,120,100,58,4,32000,false
d03-linkedin-mobile-skeptical-value,2026-09-03,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4000,2660,140,120,100,62,4,32000,false
d03-linkedin-mobile-exploring-traceability,2026-09-03,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4000,2660,140,120,100,28,2,16000,false
d03-linkedin-mobile-exploring-value,2026-09-03,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4000,2660,140,120,100,32,2,16000,false
d03-linkedin-desktop-skeptical-traceability,2026-09-03,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4000,2280,120,100,80,39,3,24000,false
d03-linkedin-desktop-skeptical-value,2026-09-03,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4000,2280,120,100,80,41,3,24000,false
d03-linkedin-desktop-exploring-traceability,2026-09-03,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4000,2280,120,100,80,31,2,16000,false
d03-linkedin-desktop-exploring-value,2026-09-03,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4000,2280,120,100,80,33,2,16000,false
d03-reddit-paid-mobile-skeptical-traceability,2026-09-03,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2500,2800,140,120,100,62,4,32000,false
d03-reddit-paid-mobile-skeptical-value,2026-09-03,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2500,2800,140,120,100,66,5,40000,false
d03-reddit-paid-mobile-exploring-traceability,2026-09-03,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2500,2800,140,120,100,31,2,16000,false
d03-reddit-paid-mobile-exploring-value,2026-09-03,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2500,2800,140,120,100,35,2,16000,false
d03-reddit-paid-desktop-skeptical-traceability,2026-09-03,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2500,2400,120,100,80,40,3,24000,false
d03-reddit-paid-desktop-skeptical-value,2026-09-03,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2500,2400,120,100,80,42,3,24000,false
d03-reddit-paid-desktop-exploring-traceability,2026-09-03,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2500,2400,120,100,80,32,2,16000,false
d03-reddit-paid-desktop-exploring-value,2026-09-03,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2500,2400,120,100,80,34,2,16000,false
d04-google-search-mobile-skeptical-traceability,2026-09-04,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3100,2520,140,120,100,54,4,32000,false
d04-google-search-mobile-skeptical-value,2026-09-04,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3100,2520,140,120,100,58,4,32000,false
d04-google-search-mobile-exploring-traceability,2026-09-04,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3100,2520,140,120,100,25,2,16000,false
d04-google-search-mobile-exploring-value,2026-09-04,UK,google-search,gl-uk-google-search,mobile,exploring,value,3100,2520,140,120,100,29,2,16000,false
d04-google-search-desktop-skeptical-traceability,2026-09-04,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3100,2160,120,100,80,38,3,24000,false
d04-google-search-desktop-skeptical-value,2026-09-04,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3100,2160,120,100,80,40,3,24000,false
d04-google-search-desktop-exploring-traceability,2026-09-04,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3100,2160,120,100,80,30,2,16000,false
d04-google-search-desktop-exploring-value,2026-09-04,UK,google-search,gl-uk-google-search,desktop,exploring,value,3100,2160,120,100,80,32,2,16000,false
d04-linkedin-mobile-skeptical-traceability,2026-09-04,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4100,2660,140,120,100,58,4,32000,false
d04-linkedin-mobile-skeptical-value,2026-09-04,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4100,2660,140,120,100,62,4,32000,false
d04-linkedin-mobile-exploring-traceability,2026-09-04,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4100,2660,140,120,100,28,2,16000,false
d04-linkedin-mobile-exploring-value,2026-09-04,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4100,2660,140,120,100,32,2,16000,false
d04-linkedin-desktop-skeptical-traceability,2026-09-04,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4100,2280,120,100,80,39,3,24000,false
d04-linkedin-desktop-skeptical-value,2026-09-04,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4100,2280,120,100,80,41,3,24000,false
d04-linkedin-desktop-exploring-traceability,2026-09-04,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4100,2280,120,100,80,31,2,16000,false
d04-linkedin-desktop-exploring-value,2026-09-04,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4100,2280,120,100,80,33,2,16000,false
d04-reddit-paid-mobile-skeptical-traceability,2026-09-04,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2600,2800,140,120,100,62,4,32000,false
d04-reddit-paid-mobile-skeptical-value,2026-09-04,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2600,2800,140,120,100,66,5,40000,false
d04-reddit-paid-mobile-exploring-traceability,2026-09-04,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2600,2800,140,120,100,31,2,16000,false
d04-reddit-paid-mobile-exploring-value,2026-09-04,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2600,2800,140,120,100,35,2,16000,false
d04-reddit-paid-desktop-skeptical-traceability,2026-09-04,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2600,2400,120,100,80,40,3,24000,false
d04-reddit-paid-desktop-skeptical-value,2026-09-04,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2600,2400,120,100,80,42,3,24000,false
d04-reddit-paid-desktop-exploring-traceability,2026-09-04,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2600,2400,120,100,80,32,2,16000,false
d04-reddit-paid-desktop-exploring-value,2026-09-04,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2600,2400,120,100,80,34,2,16000,false
d05-google-search-mobile-skeptical-traceability,2026-09-05,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3200,2520,140,120,100,54,4,32000,false
d05-google-search-mobile-skeptical-value,2026-09-05,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3200,2520,140,120,100,58,4,32000,false
d05-google-search-mobile-exploring-traceability,2026-09-05,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3200,2520,140,120,100,25,2,16000,false
d05-google-search-mobile-exploring-value,2026-09-05,UK,google-search,gl-uk-google-search,mobile,exploring,value,3200,2520,140,120,100,29,2,16000,false
d05-google-search-desktop-skeptical-traceability,2026-09-05,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3200,2160,120,100,80,38,3,24000,false
d05-google-search-desktop-skeptical-value,2026-09-05,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3200,2160,120,100,80,40,3,24000,false
d05-google-search-desktop-exploring-traceability,2026-09-05,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3200,2160,120,100,80,30,2,16000,false
d05-google-search-desktop-exploring-value,2026-09-05,UK,google-search,gl-uk-google-search,desktop,exploring,value,3200,2160,120,100,80,32,2,16000,false
d05-linkedin-mobile-skeptical-traceability,2026-09-05,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4200,2660,140,120,100,58,4,32000,false
d05-linkedin-mobile-skeptical-value,2026-09-05,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4200,2660,140,120,100,62,4,32000,false
d05-linkedin-mobile-exploring-traceability,2026-09-05,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4200,2660,140,120,100,28,2,16000,false
d05-linkedin-mobile-exploring-value,2026-09-05,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4200,2660,140,120,100,32,2,16000,false
d05-linkedin-desktop-skeptical-traceability,2026-09-05,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4200,2280,120,100,80,39,3,24000,false
d05-linkedin-desktop-skeptical-value,2026-09-05,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4200,2280,120,100,80,41,3,24000,false
d05-linkedin-desktop-exploring-traceability,2026-09-05,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4200,2280,120,100,80,31,2,16000,false
d05-linkedin-desktop-exploring-value,2026-09-05,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4200,2280,120,100,80,33,2,16000,false
d05-reddit-paid-mobile-skeptical-traceability,2026-09-05,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2700,2800,140,120,100,62,4,32000,false
d05-reddit-paid-mobile-skeptical-value,2026-09-05,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2700,2800,140,120,100,66,5,40000,false
d05-reddit-paid-mobile-exploring-traceability,2026-09-05,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2700,2800,140,120,100,31,2,16000,false
d05-reddit-paid-mobile-exploring-value,2026-09-05,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2700,2800,140,120,100,35,2,16000,false
d05-reddit-paid-desktop-skeptical-traceability,2026-09-05,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2700,2400,120,100,80,40,3,24000,false
d05-reddit-paid-desktop-skeptical-value,2026-09-05,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2700,2400,120,100,80,42,3,24000,false
d05-reddit-paid-desktop-exploring-traceability,2026-09-05,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2700,2400,120,100,80,32,2,16000,false
d05-reddit-paid-desktop-exploring-value,2026-09-05,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2700,2400,120,100,80,34,2,16000,false
d06-google-search-mobile-skeptical-traceability,2026-09-06,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3000,2520,140,120,100,54,4,32000,false
d06-google-search-mobile-skeptical-value,2026-09-06,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3000,2520,140,120,100,58,4,32000,false
d06-google-search-mobile-exploring-traceability,2026-09-06,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3000,2520,140,120,100,25,2,16000,false
d06-google-search-mobile-exploring-value,2026-09-06,UK,google-search,gl-uk-google-search,mobile,exploring,value,3000,2520,140,120,100,29,2,16000,false
d06-google-search-desktop-skeptical-traceability,2026-09-06,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3000,2160,120,100,80,38,3,24000,false
d06-google-search-desktop-skeptical-value,2026-09-06,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3000,2160,120,100,80,40,3,24000,false
d06-google-search-desktop-exploring-traceability,2026-09-06,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3000,2160,120,100,80,30,2,16000,false
d06-google-search-desktop-exploring-value,2026-09-06,UK,google-search,gl-uk-google-search,desktop,exploring,value,3000,2160,120,100,80,32,2,16000,false
d06-linkedin-mobile-skeptical-traceability,2026-09-06,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4000,2660,140,120,100,58,4,32000,false
d06-linkedin-mobile-skeptical-value,2026-09-06,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4000,2660,140,120,100,62,4,32000,false
d06-linkedin-mobile-exploring-traceability,2026-09-06,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4000,2660,140,120,100,28,2,16000,false
d06-linkedin-mobile-exploring-value,2026-09-06,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4000,2660,140,120,100,32,2,16000,false
d06-linkedin-desktop-skeptical-traceability,2026-09-06,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4000,2280,120,100,80,39,3,24000,false
d06-linkedin-desktop-skeptical-value,2026-09-06,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4000,2280,120,100,80,41,3,24000,false
d06-linkedin-desktop-exploring-traceability,2026-09-06,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4000,2280,120,100,80,31,2,16000,false
d06-linkedin-desktop-exploring-value,2026-09-06,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4000,2280,120,100,80,33,2,16000,false
d06-reddit-paid-mobile-skeptical-traceability,2026-09-06,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2500,2800,140,120,100,62,4,32000,false
d06-reddit-paid-mobile-skeptical-value,2026-09-06,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2500,2800,140,120,100,66,5,40000,false
d06-reddit-paid-mobile-exploring-traceability,2026-09-06,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2500,2800,140,120,100,31,2,16000,false
d06-reddit-paid-mobile-exploring-value,2026-09-06,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2500,2800,140,120,100,35,2,16000,false
d06-reddit-paid-desktop-skeptical-traceability,2026-09-06,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2500,2400,120,100,80,40,3,24000,false
d06-reddit-paid-desktop-skeptical-value,2026-09-06,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2500,2400,120,100,80,42,3,24000,false
d06-reddit-paid-desktop-exploring-traceability,2026-09-06,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2500,2400,120,100,80,32,2,16000,false
d06-reddit-paid-desktop-exploring-value,2026-09-06,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2500,2400,120,100,80,34,2,16000,false
d07-google-search-mobile-skeptical-traceability,2026-09-07,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3100,2520,140,120,100,54,4,32000,false
d07-google-search-mobile-skeptical-value,2026-09-07,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3100,2520,140,120,100,58,4,32000,false
d07-google-search-mobile-exploring-traceability,2026-09-07,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3100,2520,140,120,100,25,2,16000,false
d07-google-search-mobile-exploring-value,2026-09-07,UK,google-search,gl-uk-google-search,mobile,exploring,value,3100,2520,140,120,100,29,2,16000,false
d07-google-search-desktop-skeptical-traceability,2026-09-07,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3100,2160,120,100,80,38,3,24000,false
d07-google-search-desktop-skeptical-value,2026-09-07,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3100,2160,120,100,80,40,3,24000,false
d07-google-search-desktop-exploring-traceability,2026-09-07,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3100,2160,120,100,80,30,2,16000,false
d07-google-search-desktop-exploring-value,2026-09-07,UK,google-search,gl-uk-google-search,desktop,exploring,value,3100,2160,120,100,80,32,2,16000,false
d07-linkedin-mobile-skeptical-traceability,2026-09-07,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4100,2660,140,120,100,58,4,32000,false
d07-linkedin-mobile-skeptical-value,2026-09-07,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4100,2660,140,120,100,62,4,32000,false
d07-linkedin-mobile-exploring-traceability,2026-09-07,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4100,2660,140,120,100,28,2,16000,false
d07-linkedin-mobile-exploring-value,2026-09-07,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4100,2660,140,120,100,32,2,16000,false
d07-linkedin-desktop-skeptical-traceability,2026-09-07,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4100,2280,120,100,80,39,3,24000,false
d07-linkedin-desktop-skeptical-value,2026-09-07,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4100,2280,120,100,80,41,3,24000,false
d07-linkedin-desktop-exploring-traceability,2026-09-07,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4100,2280,120,100,80,31,2,16000,false
d07-linkedin-desktop-exploring-value,2026-09-07,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4100,2280,120,100,80,33,2,16000,false
d07-reddit-paid-mobile-skeptical-traceability,2026-09-07,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2600,2800,140,120,100,62,4,32000,false
d07-reddit-paid-mobile-skeptical-value,2026-09-07,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2600,2800,140,120,100,66,5,40000,false
d07-reddit-paid-mobile-exploring-traceability,2026-09-07,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2600,2800,140,120,100,31,2,16000,false
d07-reddit-paid-mobile-exploring-value,2026-09-07,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2600,2800,140,120,100,35,2,16000,false
d07-reddit-paid-desktop-skeptical-traceability,2026-09-07,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2600,2400,120,100,80,40,3,24000,false
d07-reddit-paid-desktop-skeptical-value,2026-09-07,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2600,2400,120,100,80,42,3,24000,false
d07-reddit-paid-desktop-exploring-traceability,2026-09-07,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2600,2400,120,100,80,32,2,16000,false
d07-reddit-paid-desktop-exploring-value,2026-09-07,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2600,2400,120,100,80,34,2,16000,false
d08-google-search-mobile-skeptical-traceability,2026-09-08,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3200,1620,90,70,50,22,1,8000,false
d08-google-search-mobile-skeptical-value,2026-09-08,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3200,1620,90,70,50,24,1,8000,false
d08-google-search-mobile-exploring-traceability,2026-09-08,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3200,3420,190,170,150,26,2,16000,false
d08-google-search-mobile-exploring-value,2026-09-08,UK,google-search,gl-uk-google-search,mobile,exploring,value,3200,3420,190,170,150,30,2,16000,false
d08-google-search-desktop-skeptical-traceability,2026-09-08,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3200,2520,140,120,100,47,3,24000,false
d08-google-search-desktop-skeptical-value,2026-09-08,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3200,2520,140,120,100,49,3,24000,false
d08-google-search-desktop-exploring-traceability,2026-09-08,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3200,1800,100,80,60,23,1,8000,false
d08-google-search-desktop-exploring-value,2026-09-08,UK,google-search,gl-uk-google-search,desktop,exploring,value,3200,1800,100,80,60,25,2,16000,false
d08-linkedin-mobile-skeptical-traceability,2026-09-08,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4200,1710,90,70,50,24,1,8000,false
d08-linkedin-mobile-skeptical-value,2026-09-08,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4200,1710,90,70,50,26,2,16000,false
d08-linkedin-mobile-exploring-traceability,2026-09-08,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4200,3610,190,170,150,29,2,16000,false
d08-linkedin-mobile-exploring-value,2026-09-08,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4200,3610,190,170,150,33,2,16000,false
d08-linkedin-desktop-skeptical-traceability,2026-09-08,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4200,2660,140,120,100,48,3,24000,false
d08-linkedin-desktop-skeptical-value,2026-09-08,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4200,2660,140,120,100,50,4,32000,false
d08-linkedin-desktop-exploring-traceability,2026-09-08,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4200,1900,100,80,60,24,1,8000,false
d08-linkedin-desktop-exploring-value,2026-09-08,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4200,1900,100,80,60,26,2,16000,false
d08-reddit-paid-mobile-skeptical-traceability,2026-09-08,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2700,1800,90,70,50,26,2,16000,false
d08-reddit-paid-mobile-skeptical-value,2026-09-08,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2700,1800,90,70,50,28,2,16000,false
d08-reddit-paid-mobile-exploring-traceability,2026-09-08,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2700,3800,190,170,150,32,2,16000,false
d08-reddit-paid-mobile-exploring-value,2026-09-08,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2700,3800,190,170,150,36,2,16000,false
d08-reddit-paid-desktop-skeptical-traceability,2026-09-08,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2700,2800,140,120,100,49,3,24000,false
d08-reddit-paid-desktop-skeptical-value,2026-09-08,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2700,2800,140,120,100,51,4,32000,false
d08-reddit-paid-desktop-exploring-traceability,2026-09-08,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2700,2000,100,80,60,25,2,16000,false
d08-reddit-paid-desktop-exploring-value,2026-09-08,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2700,2000,100,80,60,27,2,16000,false
d09-google-search-mobile-skeptical-traceability,2026-09-09,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3000,1620,90,70,50,22,1,8000,false
d09-google-search-mobile-skeptical-value,2026-09-09,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3000,1620,90,70,50,24,1,8000,false
d09-google-search-mobile-exploring-traceability,2026-09-09,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3000,3420,190,170,150,26,2,16000,false
d09-google-search-mobile-exploring-value,2026-09-09,UK,google-search,gl-uk-google-search,mobile,exploring,value,3000,3420,190,170,150,30,2,16000,false
d09-google-search-desktop-skeptical-traceability,2026-09-09,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3000,2520,140,120,100,47,3,24000,false
d09-google-search-desktop-skeptical-value,2026-09-09,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3000,2520,140,120,100,49,3,24000,false
d09-google-search-desktop-exploring-traceability,2026-09-09,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3000,1800,100,80,60,23,1,8000,false
d09-google-search-desktop-exploring-value,2026-09-09,UK,google-search,gl-uk-google-search,desktop,exploring,value,3000,1800,100,80,60,25,2,16000,false
d09-linkedin-mobile-skeptical-traceability,2026-09-09,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4000,1710,90,70,50,24,1,8000,false
d09-linkedin-mobile-skeptical-value,2026-09-09,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4000,1710,90,70,50,26,2,16000,false
d09-linkedin-mobile-exploring-traceability,2026-09-09,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4000,3610,190,170,150,29,2,16000,false
d09-linkedin-mobile-exploring-value,2026-09-09,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4000,3610,190,170,150,33,2,16000,false
d09-linkedin-desktop-skeptical-traceability,2026-09-09,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4000,2660,140,120,100,48,3,24000,false
d09-linkedin-desktop-skeptical-value,2026-09-09,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4000,2660,140,120,100,50,4,32000,false
d09-linkedin-desktop-exploring-traceability,2026-09-09,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4000,1900,100,80,60,24,1,8000,false
d09-linkedin-desktop-exploring-value,2026-09-09,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4000,1900,100,80,60,26,2,16000,false
d09-reddit-paid-mobile-skeptical-traceability,2026-09-09,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2500,1800,90,70,50,26,2,16000,false
d09-reddit-paid-mobile-skeptical-value,2026-09-09,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2500,1800,90,70,50,28,2,16000,false
d09-reddit-paid-mobile-exploring-traceability,2026-09-09,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2500,3800,190,170,150,32,2,16000,false
d09-reddit-paid-mobile-exploring-value,2026-09-09,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2500,3800,190,170,150,36,2,16000,false
d09-reddit-paid-desktop-skeptical-traceability,2026-09-09,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2500,2800,140,120,100,49,3,24000,false
d09-reddit-paid-desktop-skeptical-value,2026-09-09,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2500,2800,140,120,100,51,4,32000,false
d09-reddit-paid-desktop-exploring-traceability,2026-09-09,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2500,2000,100,80,60,25,2,16000,false
d09-reddit-paid-desktop-exploring-value,2026-09-09,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2500,2000,100,80,60,27,2,16000,false
d10-google-search-mobile-skeptical-traceability,2026-09-10,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3100,1620,90,70,50,22,1,8000,false
d10-google-search-mobile-skeptical-value,2026-09-10,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3100,1620,90,70,50,24,1,8000,false
d10-google-search-mobile-exploring-traceability,2026-09-10,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3100,3420,190,170,150,26,2,16000,false
d10-google-search-mobile-exploring-value,2026-09-10,UK,google-search,gl-uk-google-search,mobile,exploring,value,3100,3420,190,170,150,30,2,16000,false
d10-google-search-desktop-skeptical-traceability,2026-09-10,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3100,2520,140,120,100,47,3,24000,false
d10-google-search-desktop-skeptical-value,2026-09-10,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3100,2520,140,120,100,49,3,24000,false
d10-google-search-desktop-exploring-traceability,2026-09-10,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3100,1800,100,80,60,23,1,8000,false
d10-google-search-desktop-exploring-value,2026-09-10,UK,google-search,gl-uk-google-search,desktop,exploring,value,3100,1800,100,80,60,25,2,16000,false
d10-linkedin-mobile-skeptical-traceability,2026-09-10,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4100,1710,90,70,50,24,1,8000,false
d10-linkedin-mobile-skeptical-value,2026-09-10,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4100,1710,90,70,50,26,2,16000,false
d10-linkedin-mobile-exploring-traceability,2026-09-10,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4100,3610,190,170,150,29,2,16000,false
d10-linkedin-mobile-exploring-value,2026-09-10,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4100,3610,190,170,150,33,2,16000,false
d10-linkedin-desktop-skeptical-traceability,2026-09-10,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4100,2660,140,120,100,48,3,24000,false
d10-linkedin-desktop-skeptical-value,2026-09-10,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4100,2660,140,120,100,50,4,32000,false
d10-linkedin-desktop-exploring-traceability,2026-09-10,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4100,1900,100,80,60,24,1,8000,false
d10-linkedin-desktop-exploring-value,2026-09-10,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4100,1900,100,80,60,26,2,16000,false
d10-reddit-paid-mobile-skeptical-traceability,2026-09-10,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2600,1800,90,70,50,26,2,16000,false
d10-reddit-paid-mobile-skeptical-value,2026-09-10,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2600,1800,90,70,50,28,2,16000,false
d10-reddit-paid-mobile-exploring-traceability,2026-09-10,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2600,3800,190,170,150,32,2,16000,false
d10-reddit-paid-mobile-exploring-value,2026-09-10,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2600,3800,190,170,150,36,2,16000,false
d10-reddit-paid-desktop-skeptical-traceability,2026-09-10,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2600,2800,140,120,100,49,3,24000,false
d10-reddit-paid-desktop-skeptical-value,2026-09-10,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2600,2800,140,120,100,51,4,32000,false
d10-reddit-paid-desktop-exploring-traceability,2026-09-10,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2600,2000,100,80,60,25,2,16000,false
d10-reddit-paid-desktop-exploring-value,2026-09-10,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2600,2000,100,80,60,27,2,16000,false
d11-google-search-mobile-skeptical-traceability,2026-09-11,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3200,1620,90,70,50,22,1,8000,false
d11-google-search-mobile-skeptical-value,2026-09-11,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3200,1620,90,70,50,24,1,8000,false
d11-google-search-mobile-exploring-traceability,2026-09-11,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3200,3420,190,170,150,26,2,16000,false
d11-google-search-mobile-exploring-value,2026-09-11,UK,google-search,gl-uk-google-search,mobile,exploring,value,3200,3420,190,170,150,30,2,16000,false
d11-google-search-desktop-skeptical-traceability,2026-09-11,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3200,2520,140,120,100,47,3,24000,false
d11-google-search-desktop-skeptical-value,2026-09-11,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3200,2520,140,120,100,49,3,24000,false
d11-google-search-desktop-exploring-traceability,2026-09-11,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3200,1800,100,80,60,23,1,8000,false
d11-google-search-desktop-exploring-value,2026-09-11,UK,google-search,gl-uk-google-search,desktop,exploring,value,3200,1800,100,80,60,25,2,16000,false
d11-linkedin-mobile-skeptical-traceability,2026-09-11,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4200,1710,90,70,50,24,1,8000,false
d11-linkedin-mobile-skeptical-value,2026-09-11,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4200,1710,90,70,50,26,2,16000,false
d11-linkedin-mobile-exploring-traceability,2026-09-11,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4200,3610,190,170,150,29,2,16000,false
d11-linkedin-mobile-exploring-value,2026-09-11,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4200,3610,190,170,150,33,2,16000,false
d11-linkedin-desktop-skeptical-traceability,2026-09-11,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4200,2660,140,120,100,48,3,24000,false
d11-linkedin-desktop-skeptical-value,2026-09-11,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4200,2660,140,120,100,50,4,32000,false
d11-linkedin-desktop-exploring-traceability,2026-09-11,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4200,1900,100,80,60,24,1,8000,false
d11-linkedin-desktop-exploring-value,2026-09-11,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4200,1900,100,80,60,26,2,16000,false
d11-reddit-paid-mobile-skeptical-traceability,2026-09-11,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2700,1800,90,70,50,26,2,16000,false
d11-reddit-paid-mobile-skeptical-value,2026-09-11,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2700,1800,90,70,50,28,2,16000,false
d11-reddit-paid-mobile-exploring-traceability,2026-09-11,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2700,3800,190,170,150,32,2,16000,false
d11-reddit-paid-mobile-exploring-value,2026-09-11,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2700,3800,190,170,150,36,2,16000,false
d11-reddit-paid-desktop-skeptical-traceability,2026-09-11,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2700,2800,140,120,100,49,3,24000,false
d11-reddit-paid-desktop-skeptical-value,2026-09-11,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2700,2800,140,120,100,51,4,32000,false
d11-reddit-paid-desktop-exploring-traceability,2026-09-11,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2700,2000,100,80,60,25,2,16000,false
d11-reddit-paid-desktop-exploring-value,2026-09-11,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2700,2000,100,80,60,27,2,16000,false
d12-google-search-mobile-skeptical-traceability,2026-09-12,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3000,1620,90,70,50,22,1,8000,false
d12-google-search-mobile-skeptical-value,2026-09-12,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3000,1620,90,70,50,24,1,8000,false
d12-google-search-mobile-exploring-traceability,2026-09-12,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3000,3420,190,170,150,26,2,16000,false
d12-google-search-mobile-exploring-value,2026-09-12,UK,google-search,gl-uk-google-search,mobile,exploring,value,3000,3420,190,170,150,30,2,16000,false
d12-google-search-desktop-skeptical-traceability,2026-09-12,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3000,2520,140,120,100,47,3,24000,false
d12-google-search-desktop-skeptical-value,2026-09-12,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3000,2520,140,120,100,49,3,24000,false
d12-google-search-desktop-exploring-traceability,2026-09-12,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3000,1800,100,80,60,23,1,8000,false
d12-google-search-desktop-exploring-value,2026-09-12,UK,google-search,gl-uk-google-search,desktop,exploring,value,3000,1800,100,80,60,25,2,16000,false
d12-linkedin-mobile-skeptical-traceability,2026-09-12,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4000,1710,90,70,50,24,1,8000,false
d12-linkedin-mobile-skeptical-value,2026-09-12,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4000,1710,90,70,50,26,2,16000,false
d12-linkedin-mobile-exploring-traceability,2026-09-12,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4000,3610,190,170,150,29,2,16000,false
d12-linkedin-mobile-exploring-value,2026-09-12,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4000,3610,190,170,150,33,2,16000,false
d12-linkedin-desktop-skeptical-traceability,2026-09-12,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4000,2660,140,120,100,48,3,24000,false
d12-linkedin-desktop-skeptical-value,2026-09-12,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4000,2660,140,120,100,50,4,32000,false
d12-linkedin-desktop-exploring-traceability,2026-09-12,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4000,1900,100,80,60,24,1,8000,false
d12-linkedin-desktop-exploring-value,2026-09-12,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4000,1900,100,80,60,26,2,16000,false
d12-reddit-paid-mobile-skeptical-traceability,2026-09-12,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2500,1800,90,70,50,26,2,16000,false
d12-reddit-paid-mobile-skeptical-value,2026-09-12,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2500,1800,90,70,50,28,2,16000,false
d12-reddit-paid-mobile-exploring-traceability,2026-09-12,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2500,3800,190,170,150,32,2,16000,false
d12-reddit-paid-mobile-exploring-value,2026-09-12,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2500,3800,190,170,150,36,2,16000,false
d12-reddit-paid-desktop-skeptical-traceability,2026-09-12,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2500,2800,140,120,100,49,3,24000,false
d12-reddit-paid-desktop-skeptical-value,2026-09-12,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2500,2800,140,120,100,51,4,32000,false
d12-reddit-paid-desktop-exploring-traceability,2026-09-12,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2500,2000,100,80,60,25,2,16000,false
d12-reddit-paid-desktop-exploring-value,2026-09-12,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2500,2000,100,80,60,27,2,16000,false
d13-google-search-mobile-skeptical-traceability,2026-09-13,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3100,1620,90,70,50,22,1,8000,false
d13-google-search-mobile-skeptical-value,2026-09-13,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3100,1620,90,70,50,24,1,8000,false
d13-google-search-mobile-exploring-traceability,2026-09-13,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3100,3420,190,170,150,26,2,16000,false
d13-google-search-mobile-exploring-value,2026-09-13,UK,google-search,gl-uk-google-search,mobile,exploring,value,3100,3420,190,170,150,30,2,16000,false
d13-google-search-desktop-skeptical-traceability,2026-09-13,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3100,2520,140,120,100,47,3,24000,false
d13-google-search-desktop-skeptical-value,2026-09-13,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3100,2520,140,120,100,49,3,24000,false
d13-google-search-desktop-exploring-traceability,2026-09-13,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3100,1800,100,80,60,23,1,8000,false
d13-google-search-desktop-exploring-value,2026-09-13,UK,google-search,gl-uk-google-search,desktop,exploring,value,3100,1800,100,80,60,25,2,16000,false
d13-linkedin-mobile-skeptical-traceability,2026-09-13,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4100,1710,90,70,50,24,1,8000,false
d13-linkedin-mobile-skeptical-value,2026-09-13,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4100,1710,90,70,50,26,2,16000,false
d13-linkedin-mobile-exploring-traceability,2026-09-13,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4100,3610,190,170,150,29,2,16000,false
d13-linkedin-mobile-exploring-value,2026-09-13,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4100,3610,190,170,150,33,2,16000,false
d13-linkedin-desktop-skeptical-traceability,2026-09-13,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4100,2660,140,120,100,48,3,24000,false
d13-linkedin-desktop-skeptical-value,2026-09-13,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4100,2660,140,120,100,50,4,32000,false
d13-linkedin-desktop-exploring-traceability,2026-09-13,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4100,1900,100,80,60,24,1,8000,false
d13-linkedin-desktop-exploring-value,2026-09-13,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4100,1900,100,80,60,26,2,16000,false
d13-reddit-paid-mobile-skeptical-traceability,2026-09-13,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2600,1800,90,70,50,26,2,16000,false
d13-reddit-paid-mobile-skeptical-value,2026-09-13,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2600,1800,90,70,50,28,2,16000,false
d13-reddit-paid-mobile-exploring-traceability,2026-09-13,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2600,3800,190,170,150,32,2,16000,false
d13-reddit-paid-mobile-exploring-value,2026-09-13,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2600,3800,190,170,150,36,2,16000,false
d13-reddit-paid-desktop-skeptical-traceability,2026-09-13,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2600,2800,140,120,100,49,3,24000,false
d13-reddit-paid-desktop-skeptical-value,2026-09-13,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2600,2800,140,120,100,51,4,32000,false
d13-reddit-paid-desktop-exploring-traceability,2026-09-13,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2600,2000,100,80,60,25,2,16000,false
d13-reddit-paid-desktop-exploring-value,2026-09-13,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2600,2000,100,80,60,27,2,16000,false
d14-google-search-mobile-skeptical-traceability,2026-09-14,UK,google-search,gl-uk-google-search,mobile,skeptical,traceability,3200,1620,90,70,50,22,1,8000,false
d14-google-search-mobile-skeptical-value,2026-09-14,UK,google-search,gl-uk-google-search,mobile,skeptical,value,3200,1620,90,70,50,24,1,8000,false
d14-google-search-mobile-exploring-traceability,2026-09-14,UK,google-search,gl-uk-google-search,mobile,exploring,traceability,3200,3420,190,170,150,26,2,16000,false
d14-google-search-mobile-exploring-value,2026-09-14,UK,google-search,gl-uk-google-search,mobile,exploring,value,3200,3420,190,170,150,30,2,16000,false
d14-google-search-desktop-skeptical-traceability,2026-09-14,UK,google-search,gl-uk-google-search,desktop,skeptical,traceability,3200,2520,140,120,100,47,3,24000,false
d14-google-search-desktop-skeptical-value,2026-09-14,UK,google-search,gl-uk-google-search,desktop,skeptical,value,3200,2520,140,120,100,49,3,24000,false
d14-google-search-desktop-exploring-traceability,2026-09-14,UK,google-search,gl-uk-google-search,desktop,exploring,traceability,3200,1800,100,80,60,23,1,8000,false
d14-google-search-desktop-exploring-value,2026-09-14,UK,google-search,gl-uk-google-search,desktop,exploring,value,3200,1800,100,80,60,25,2,16000,false
d14-linkedin-mobile-skeptical-traceability,2026-09-14,UK,linkedin,gl-uk-linkedin,mobile,skeptical,traceability,4200,1710,90,70,50,24,1,8000,false
d14-linkedin-mobile-skeptical-value,2026-09-14,UK,linkedin,gl-uk-linkedin,mobile,skeptical,value,4200,1710,90,70,50,26,2,16000,false
d14-linkedin-mobile-exploring-traceability,2026-09-14,UK,linkedin,gl-uk-linkedin,mobile,exploring,traceability,4200,3610,190,170,150,29,2,16000,false
d14-linkedin-mobile-exploring-value,2026-09-14,UK,linkedin,gl-uk-linkedin,mobile,exploring,value,4200,3610,190,170,150,33,2,16000,false
d14-linkedin-desktop-skeptical-traceability,2026-09-14,UK,linkedin,gl-uk-linkedin,desktop,skeptical,traceability,4200,2660,140,120,100,48,3,24000,false
d14-linkedin-desktop-skeptical-value,2026-09-14,UK,linkedin,gl-uk-linkedin,desktop,skeptical,value,4200,2660,140,120,100,50,4,32000,false
d14-linkedin-desktop-exploring-traceability,2026-09-14,UK,linkedin,gl-uk-linkedin,desktop,exploring,traceability,4200,1900,100,80,60,24,1,8000,false
d14-linkedin-desktop-exploring-value,2026-09-14,UK,linkedin,gl-uk-linkedin,desktop,exploring,value,4200,1900,100,80,60,26,2,16000,false
d14-reddit-paid-mobile-skeptical-traceability,2026-09-14,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,traceability,2700,1800,90,70,50,26,2,16000,false
d14-reddit-paid-mobile-skeptical-value,2026-09-14,UK,reddit-paid,gl-uk-reddit-paid,mobile,skeptical,value,2700,1800,90,70,50,28,2,16000,false
d14-reddit-paid-mobile-exploring-traceability,2026-09-14,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,traceability,2700,3800,190,170,150,32,2,16000,false
d14-reddit-paid-mobile-exploring-value,2026-09-14,UK,reddit-paid,gl-uk-reddit-paid,mobile,exploring,value,2700,3800,190,170,150,36,2,16000,false
d14-reddit-paid-desktop-skeptical-traceability,2026-09-14,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,traceability,2700,2800,140,120,100,49,3,24000,false
d14-reddit-paid-desktop-skeptical-value,2026-09-14,UK,reddit-paid,gl-uk-reddit-paid,desktop,skeptical,value,2700,2800,140,120,100,51,4,32000,false
d14-reddit-paid-desktop-exploring-traceability,2026-09-14,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,traceability,2700,2000,100,80,60,25,2,16000,false
d14-reddit-paid-desktop-exploring-value,2026-09-14,UK,reddit-paid,gl-uk-reddit-paid,desktop,exploring,value,2700,2000,100,80,60,27,2,16000,false


## Attached file: data/campaigns.csv

campaign_id,campaign_name,display_name,channel
gl-uk-google-search,GreenLeaf_GoogleSearch_UK_Quiz_202609,GreenLeaf UK Search,google-search
gl-uk-linkedin,GreenLeaf_LinkedIn_UK_Quiz_202609,GreenLeaf UK LinkedIn,linkedin
gl-uk-reddit-paid,GreenLeaf_RedditPaid_UK_Quiz_202609,GreenLeaf UK Reddit paid,reddit-paid


## Attached file: data/creatives.csv

channel,creative_id,format,message,status
google-search,traceability,text-ad,Know what is in every serving,illustrative-unvalidated-hypothesis
google-search,value,text-ad,Compare the value of a clearly dosed serving,illustrative-unvalidated-hypothesis
linkedin,traceability,sponsored-feed,Know what is in every serving,illustrative-unvalidated-hypothesis
linkedin,value,sponsored-feed,Compare the value of a clearly dosed serving,illustrative-unvalidated-hypothesis
reddit-paid,traceability,promoted-post,Know what is in every serving,illustrative-unvalidated-hypothesis
reddit-paid,value,promoted-post,Compare the value of a clearly dosed serving,illustrative-unvalidated-hypothesis

Follow-up na tugon

# Mobile Composition Follow-Up

## 1. Stratum-by-stratum table

All 12 mobile strata use the channel × audience × creative dimensions from the dictionary. Week 1 and Week 2 counts are summed across the seven days in each period.

| # | Channel | Audience | Creative | W1 Starts | W1 Comps | W1 Rate | W2 Starts | W2 Comps | W2 Rate | W1 Weight |
|---:|---|---|---|---:|---:|---:|---:|---:|---:|---:|
| 1 | Google Search | Skeptical | Traceability | 700 | 378 | 54.0% | 350 | 154 | 44.0% | 0.0833 |
| 2 | Google Search | Skeptical | Value | 700 | 406 | 58.0% | 350 | 168 | 48.0% | 0.0833 |
| 3 | Google Search | Exploring | Traceability | 700 | 175 | 25.0% | 1,050 | 182 | 17.3% | 0.0833 |
| 4 | Google Search | Exploring | Value | 700 | 203 | 29.0% | 1,050 | 210 | 20.0% | 0.0833 |
| 5 | LinkedIn | Skeptical | Traceability | 700 | 406 | 58.0% | 350 | 168 | 48.0% | 0.0833 |
| 6 | LinkedIn | Skeptical | Value | 700 | 434 | 62.0% | 350 | 182 | 52.0% | 0.0833 |
| 7 | LinkedIn | Exploring | Traceability | 700 | 196 | 28.0% | 1,050 | 203 | 19.3% | 0.0833 |
| 8 | LinkedIn | Exploring | Value | 700 | 224 | 32.0% | 1,050 | 231 | 22.0% | 0.0833 |
| 9 | Reddit Paid | Skeptical | Traceability | 700 | 434 | 62.0% | 350 | 182 | 52.0% | 0.0833 |
| 10 | Reddit Paid | Skeptical | Value | 700 | 462 | 66.0% | 350 | 196 | 56.0% | 0.0833 |
| 11 | Reddit Paid | Exploring | Traceability | 700 | 217 | 31.0% | 1,050 | 224 | 21.3% | 0.0833 |
| 12 | Reddit Paid | Exploring | Value | 700 | 245 | 35.0% | 1,050 | 245 | 23.3% | 0.0833 |
| **Total** | | | | **8,400** | **3,780** | **45.0%** | **8,400** | **2,360** | **28.1%** | **1.0000** |

### Arithmetic checks

Week 1 totals:

```text
W1 starts  = 12 × 700 = 8,400
W1 comps   = 378 + 406 + 175 + 203 + 406 + 434 + 196 + 224 + 434 + 462 + 217 + 245
           = 3,780
W1 rate    = 3,780 / 8,400 = 0.45 = 45.0%
```

Week 2 starts are not uniform at 700 per stratum. The CSV pattern gives:

- Skeptical mobile strata: 50 starts per day × 7 days = **350**
- Exploring mobile traceability and value strata: 150 starts per day × 7 days = **1,050**

```text
W2 skeptical starts  = 6 strata × 350 = 2,100
W2 exploring starts  = 6 strata × 1,050 = 6,300
W2 starts            = 2,100 + 6,300 = 8,400
```

This matches the dictionary’s aggregate mobile start total for Week 2. The rates in the table are calculated from these counts, e.g.:

```text
Google / skeptical / traceability W2:
154 / 350 = 0.4400 = 44.0%

Google / exploring / traceability W2:
182 / 1,050 = 0.17333… = 17.3%
```

## 2. Week 1 weights

Week 1 weights are each stratum’s Week 1 starts divided by total Week 1 mobile starts.

Because every Week 1 stratum has 700 starts and total Week 1 starts are 8,400:

```text
weight for each stratum = 700 / 8,400 = 1 / 12 = 0.083333…
```

Sum of weights:

```text
12 × (1 / 12) = 1.0000
```

No zero-weight or missing-weight stratum is present.

## 3. Weighted Week 2 contribution

The fixed-mix Week 2 rate uses **Week 1 weights** multiplied by each stratum’s **Week 2 completion rate**.

| # | W1 Weight | W2 Rate | Weighted W2 Contribution |
|---:|---:|---:|---:|
| 1 | 0.083333 | 44.0% | 3.6667% |
| 2 | 0.083333 | 48.0% | 4.0000% |
| 3 | 0.083333 | 17.3333% | 1.4433% |
| 4 | 0.083333 | 20.0% | 1.6667% |
| 5 | 0.083333 | 48.0% | 4.0000% |
| 6 | 0.083333 | 52.0% | 4.3333% |
| 7 | 0.083333 | 19.3333% | 1.6111% |
| 8 | 0.083333 | 22.0% | 1.8333% |
| 9 | 0.083333 | 52.0% | 4.3333% |
| 10 | 0.083333 | 56.0% | 4.6667% |
| 11 | 0.083333 | 21.3333% | 1.7778% |
| 12 | 0.083333 | 23.3333% | 1.9444% |
| **Total** | **1.000000** | | **35.2767%** |

Using unrounded Week 2 rates:

```text
Google / skeptical / traceability:
154 / 350 = 0.44

Google / exploring / traceability:
182 / 1,050 = 0.173333…
```

The weighted total is approximately:

```text
35.3%
```

Therefore the comparison is:

| Measure | Week 2 mobile completion |
|---|---:|
| Observed Week 2 rate | **28.1%** |
| Fixed Week 1 mix applied to Week 2 | **35.3%** |

The two are not equal, so composition matters, but the fixed-mix rate is still far below Week 1’s **45.0%**.

## 4. What this comparison does and does not imply

### What it does

- It separates the observed Week 2 mobile rate into two parts:
  - the effect of changing stratum mix, and
  - the effect of within-stratum rate movement.
- It shows that if Week 2 had preserved the Week 1 stratum mix, the Week 2 mobile completion rate would have been about **35.3%**, not **28.1%**.
- It quantifies the composition effect as roughly:

```text
35.3% − 28.1% ≈ 7.2 percentage points
```

This means part of the observed Week 2 decline is attributable to mobile starts shifting toward lower-completing `exploring` strata and away from higher-completing `skeptical` strata.

### What it does not imply

- It **does not** imply that the remaining decline from Week 1’s 45.0% to the fixed-mix 35.3% is explained by product failure.
- It **does not** show that within-stratum movement has a single cause.
- It **does not** prove that the `exploring` audience performed worse because of the message.
- It **does not** establish causality for either composition change or within-stratum change.
- It **does not** mean the Week 2 aggregate decline is unimportant. Even with fixed Week 1 mix, Week 2 was about **9.7 percentage points below the Week 1 fixed-mix rate**:

```text
45.0% − 35.3% ≈ 9.7 pp
```

The within-stratum drop is still the larger component.

## 5. Arithmetic uncertainty

The table uses counts summed by hand from the supplied CSV structure. I did not execute code. The following should be rechecked in the final reviewed draft:

- exact duplicate row removal and alias normalization;
- exact Week 2 starts for each mobile stratum;
- decimal retention in weighted contributions;
- whether any zero-denominator stratum should be marked unavailable.

The broad conclusion is unlikely to change from small corrections: **both composition and within-stratum movement contributed to the mobile decline; within-stratum movement was the larger contributor.**

## 6. Next evidence needed

To move from composition arithmetic to a defensible explanation, the next evidence is:

1. **Timestamped event-level data** for mobile quiz starts and completions, matched to cohort date and source tag.
2. **Release/QA log** covering the mobile landing page and quiz between Week 1 and Week 2.
3. **Device-level landing-session detail** to verify whether mobile starts became less likely to complete at the same quiz stage.
4. **Audience bucket definitions** to confirm whether `skeptical` and `exploring` shares changed because of targeting/auction changes or because the reporting buckets themselves changed.

Only after those are available can the team test whether the remaining within-stratum mobile drop is a journey problem, a measurement break, or a real behavioral shift.

Follow-up na prompt

Focused follow-up: quantify the mobile composition question. Show all 12 channel/audience/creative strata with Week 1/2 starts, completions and rates, Week 1 weights, and the weighted Week 2 contribution. State observed Week 2 rate versus fixed Week 1 mix and what each does and does not imply. Recheck any arithmetic you cannot substantiate. Do not infer a product cause from this comparison. Keep this response focused on the calculation and the next evidence needed.

Production prompt

Production pass: use ONLY the approved facts and decisions attached below. Format the Founder / CEO Summary, Media Team Analysis and Content & Creative Brief. Do not introduce new claims, calculations, causes, promises, budgets or actions. Then format the approved retrospective Detect → Analyze → Route → Review example including observation window, snapshot, earliest justified decision time, responsible role, cadence, expiry/escalation and human client-facing approval state. This is a static illustration with no live messages or automation. Keep unknown outcomes explicit.

## Attached file: en/review.md

# What changed in review

Fictional GreenLeaf UK, paid-click cohorts September 1–14, 2026; snapshot September 22, 23:59:59 UTC.
This record was prepared with AI-assisted editorial review and independently checked calculations.
It is **not a completed human approval, client review or controlled human-versus-AI experiment**.
The owner’s publication/release decision remains pending. Original model responses are unchanged.

## The decision before the wording

The first draft recommends diagnosis before a creative or budget pivot. That direction is reasonable,
but several numbers and the explanation are wrong. A plausible recommendation does not make its
supporting evidence safe to release.

| Initial draft statement | Checked evidence | Review decision |
|---|---|---|
| Spend was $110,100 in each week | Week 1: $5,462; Week 2: $5,512 | Reject both draft totals and every derived CPA/ROAS based on them |
| New customers were 548 → 482 | Canonical paid-cohort counts: 467 → 357 | Replace; these are attributed first purchases, not incremental subscribers |
| First-purchase revenue was $43,840 → $38,560 | $37,360 → $28,560 | Replace; no causal revenue-loss estimate follows |
| Mobile Week 2 had 2,360 completions | 2,352 / 8,400 = 28% | Replace the count/rate; retain Week 1’s checked 3,780 / 8,400 = 45% |
| Mobile audience/creative shares were stable and composition was essentially absent | Skeptical share of mobile starts: 50% → 25%; exploring: 50% → 75% | Reject the mix explanation |
| Fixed Week 1 mix gives roughly 35.3%–35.5% | Exactly 35⅓% before display rounding | Use 35.33%; state that both mix and within-group changes matter |
| Founder should freeze spend reallocation | The CSV alone does not establish what all commercial/risk decisions should be | Narrow to “do not recommend a budget move from this evidence alone”; retain existing authorized risk processes |
| A diagnostic succeeds if completion returns toward 45% | Returning to a target is not a causal test design | Require verified event definitions, version/cohort evidence and an explicit comparison plan |

All channel, desktop, audience and creative tables in the raw response remain **unapproved**. The
final editorial drafts use the checked metric pack instead. The model invocation was text-only,
without a calculation-execution tool. This is evidence about this run, not every AI analysis product.

## What the focused follow-up did

The second response recognizes the audience-mix shift and gives the correct Week 2 starts per
stratum: skeptical 350, exploring 1,050. It still reports 2,360 total completions, misstates the
Reddit/exploring/value cell as 245 rather than 252, and miscalculates a weighted contribution.
Use the recorded follow-up to inspect iteration; do not silently substitute it for verified math.

## Approved facts for the production draft

| Measure | Week 1 | Week 2 |
|---|---:|---:|
| All-paid media spend | $5,462 | $5,512 |
| All-paid quiz starts | 15,040 | 15,120 |
| All-paid quiz completions | 6,770 | 5,460 |
| Attributed first-purchase customers | 467 | 357 |
| Attributed first-purchase revenue | $37,360 | $28,560 |
| Media CPA | $11.70 | $15.44 |
| Attributed first-order ROAS | 6.84 | 5.18 |
| Mobile quiz starts | 8,400 | 8,400 |
| Mobile quiz completions | 3,780 | 2,352 |
| Mobile completion | 45% | 28% |
| Desktop completion | 45.03% | 46.25% |

Mobile change: −17 percentage points; approximately −37.8% relative. Fixed Week 1 channel ×
audience × creative weights give a Week 2 mobile rate of 35.33%. Under this particular baseline-weight
decomposition, the within-group component is −9.67 points and the remaining composition component
is −7.33 points. Another decomposition order can allocate interaction differently; this is descriptive,
not causal attribution. All 12 comparable mobile strata decline.

## New fictional context and its effect

The context note was prewritten and hashed before the run. It reports a mobile presentation revision
starting September 8 at 09:00 UTC and an unlinked support concern about finding the next-step control.
The release audit, rollout share, ticket counts and links to paid cohorts are missing.

**Verdict: revise the explanation and narrow the next action; confirm the diagnostic-first direction.**
Ask the product owner and media lead to verify the mobile journey and event definitions, request
version-assignment/release evidence, and compare like-for-like groups where evidence permits.
The product owner’s reported availability for a check in the next working day is fictional context,
not evidence that a check happened. A product cause, creative failure or revenue loss remains unknown.

Carry the report of the revision into brief v2 as **reported context pending verification**, never
as a confirmed cause. No automatic pause, spend change or external alert is approved.

## Instructions to the production pass

Preserve the approved table, uncertainty and decision above across three drafts:

- Founder/CEO: trajectory and the diagnostic decision, with at most three actions and role owners.
- Media: period/channel/device detail, the fixed-mix comparison and the investigation work order.
- Content/creative: keep message hypotheses distinct from proof; inspect post-click context before
  proposing a message test. Do not present a causal creative winner or recommend media-budget changes.

For the retrospective alert: trigger on settled paid-mobile completion below the stated 45% target.
With end-of-day click cohorts and a seven-day observation rule, the full Week 2 comparison is first
justified September 21 at 23:59:59 UTC; the supplied snapshot is September 22 at 23:59:59 UTC.
Detect → Analyze → Route → Review is a static demonstration. Product owner/media lead own the
diagnostic; a measurement-competent reviewer with release authority owns client-facing approval.
No human approval or external delivery has occurred. Recheck the rule/context next cycle, and
escalate missing definitions or evidence to the marketing owner rather than issuing a firm claim.

## Provenance

Checked against the supplied reconciled CSV, independently reviewed deterministic calculations and
`data/analysis.json`. The raw initial and follow-up responses remain downloadable evidence. Numeric
claims in final editorial drafts must map to the claim ledger. “Approved” here means approved for
this AI-assisted editorial production pass; it does not stand in for the owner’s human release gate.


## Attached file: en/brief-v2.md

# GreenLeaf reporting brief v2 — carry the learning forward

**Status:** AI-assisted editorial draft; human publication/release approval pending. Fictional case,
not client-operating evidence. This is an additive update to [complete brief v1](brief-v1.md), not a
replacement with a shorter prompt. Read both together for the next cycle.

The business goals, KPI definitions, stakeholder responsibilities, attribution rules, target periods
and cadence in v1 remain unchanged. The new knowledge is separated by evidence class below.

## Checked data findings

- Paid-mobile completion is 3,780/8,400 = 45% in Week 1 and 2,352/8,400 = 28% in Week 2.
- The mobile skeptical/exploring starts mix changes from 50%/50% to 25%/75%.
- Using fixed Week 1 channel/audience/creative weights gives 35.33% for Week 2. Both composition and
  within-group movement contribute descriptively; all 12 mobile strata decline. No cause is proved.
- The first text-only AI response and its focused follow-up contain arithmetic errors. Reuse the
  checked metric pack and claim references, not unverified numbers from those responses.

## Reported fictional context — verification outstanding

The product owner reports a mobile quiz presentation revision beginning September 8 at 09:00 UTC.
The support lead reports difficulty finding the next control on a phone, without dates, counts or
linkage to paid cohorts. No deployment audit, rollout share or version-assignment evidence is supplied.
These reports prioritize an investigation; they are not verified release logs or a causal diagnosis.

## Next-cycle work order

| Owner role | Required evidence/action | Stop condition |
|---|---|---|
| Product owner | Reproduce the mobile flow and retrieve release/version/QA evidence | Missing assignment/logs prevents a version-specific causal claim |
| Media lead | Reconcile event meaning, cohort tagging and comparable device/audience/creative cuts | Inconsistent definitions or immature windows prevent a settled comparison |
| Content lead | Inspect message/post-click expectations after measurement/journey checks | No confirmed message problem means no claim of a winning or failed hook |
| Reviewer with current measurement knowledge and release authority | Check the decision and all stakeholder drafts before client-facing release | Approval absent means no external delivery |

## Hypotheses that must remain hypotheses

Presentation friction, tracking change, targeting/mix changes and other influences may contribute.
The support report does not establish prevalence or abandonment. No quiz-driven revenue loss,
incremental lift, profit, realized LTV, full CAC or monthly-business-target verdict has been established.

Revisit the context, rule and evidence requests at the next reporting cycle; remove stale assumptions
or keep them explicitly unresolved. Neither this update nor its reuse proves improved future output.


## Attached file: data/analysis.json

{
  "window": {
    "week1Start": "2026-09-01",
    "week1End": "2026-09-07",
    "week2Start": "2026-09-08",
    "week2End": "2026-09-14",
    "observationDays": 7,
    "snapshot": "2026-09-22T23:59:59Z"
  },
  "comparisonStatus": "settled",
  "periods": {
    "week1": {
      "spend_cents": 546200,
      "impressions": 412560,
      "clicks": 21720,
      "landing_sessions": 18380,
      "quiz_starts": 15040,
      "quiz_completions": 6770,
      "attributed_new_customers": 467,
      "attributed_first_purchase_revenue_cents": 3736000,
      "rows": 168,
      "settled": true,
      "quizCompletionRate": 0.45013297872340424,
      "mediaCpaCents": 1169.593147751606,
      "attributedFirstOrderRoas": 6.839985353350421,
      "ctr": 0.052646887725421754,
      "cpcCents": 25.147329650092082,
      "cpmCents": 1323.9286406825674
    },
    "week2": {
      "spend_cents": 551200,
      "impressions": 414960,
      "clicks": 21840,
      "landing_sessions": 18480,
      "quiz_starts": 15120,
      "quiz_completions": 5460,
      "attributed_new_customers": 357,
      "attributed_first_purchase_revenue_cents": 2856000,
      "rows": 168,
      "settled": true,
      "quizCompletionRate": 0.3611111111111111,
      "mediaCpaCents": 1543.9775910364147,
      "attributedFirstOrderRoas": 5.181422351233672,
      "ctr": 0.05263157894736842,
      "cpcCents": 25.238095238095237,
      "cpmCents": 1328.3208020050126
    }
  },
  "byChannel": {
    "google-search": {
      "week1": {
        "spend_cents": 173600,
        "impressions": 131040,
        "clicks": 7280,
        "landing_sessions": 6160,
        "quiz_starts": 5040,
        "quiz_completions": 2142,
        "attributed_new_customers": 154,
        "attributed_first_purchase_revenue_cents": 1232000,
        "rows": 56,
        "settled": true,
        "quizCompletionRate": 0.425,
        "mediaCpaCents": 1127.2727272727273,
        "attributedFirstOrderRoas": 7.096774193548387,
        "ctr": 0.05555555555555555,
        "cpcCents": 23.846153846153847,
        "cpmCents": 1324.7863247863247
      },
      "week2": {
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        "clicks": 7280,
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        "quiz_starts": 5040,
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        "attributed_new_customers": 105,
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        "rows": 56,
        "settled": true,
        "quizCompletionRate": 0.3416666666666667,
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        "attributedFirstOrderRoas": 4.81651376146789,
        "ctr": 0.05555555555555555,
        "cpcCents": 23.956043956043956,
        "cpmCents": 1330.8913308913309
      }
    },
    "linkedin": {
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        "rows": 56,
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        "quizCompletionRate": 0.45,
        "mediaCpaCents": 1490.909090909091,
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        "clicks": 7280,
        "landing_sessions": 6160,
        "quiz_starts": 5040,
        "quiz_completions": 1820,
        "attributed_new_customers": 119,
        "attributed_first_purchase_revenue_cents": 952000,
        "rows": 56,
        "settled": true,
        "quizCompletionRate": 0.3611111111111111,
        "mediaCpaCents": 1936.1344537815125,
        "attributedFirstOrderRoas": 4.131944444444445,
        "ctr": 0.05263157894736842,
        "cpcCents": 31.64835164835165,
        "cpmCents": 1665.7027183342973
      }
    },
    "reddit-paid": {
      "week1": {
        "spend_cents": 143000,
        "impressions": 143200,
        "clicks": 7160,
        "landing_sessions": 6060,
        "quiz_starts": 4960,
        "quiz_completions": 2360,
        "attributed_new_customers": 159,
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        "rows": 56,
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        "ctr": 0.05,
        "cpcCents": 19.972067039106147,
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      "week2": {
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        "clicks": 7280,
        "landing_sessions": 6160,
        "quiz_starts": 5040,
        "quiz_completions": 1918,
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        "attributed_first_purchase_revenue_cents": 1064000,
        "rows": 56,
        "settled": true,
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        "cpcCents": 20.10989010989011,
        "cpmCents": 1005.4945054945055
      }
    }
  },
  "byCreative": {
    "traceability": {
      "week1": {
        "spend_cents": 274400,
        "impressions": 207480,
        "clicks": 10920,
        "landing_sessions": 9240,
        "quiz_starts": 7560,
        "quiz_completions": 3276,
        "attributed_new_customers": 231,
        "attributed_first_purchase_revenue_cents": 1848000,
        "rows": 84,
        "settled": true,
        "quizCompletionRate": 0.43333333333333335,
        "mediaCpaCents": 1187.878787878788,
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        "ctr": 0.05263157894736842,
        "cpcCents": 25.128205128205128,
        "cpmCents": 1322.5371120107961
      },
      "week2": {
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        "clicks": 10920,
        "landing_sessions": 9240,
        "quiz_starts": 7560,
        "quiz_completions": 2625,
        "attributed_new_customers": 161,
        "attributed_first_purchase_revenue_cents": 1288000,
        "rows": 84,
        "settled": true,
        "quizCompletionRate": 0.3472222222222222,
        "mediaCpaCents": 1711.8012422360248,
        "attributedFirstOrderRoas": 4.67343976777939,
        "ctr": 0.05263157894736842,
        "cpcCents": 25.238095238095237,
        "cpmCents": 1328.3208020050126
      }
    },
    "value": {
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  "byAudience": {
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  },
  "byDevice": {
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    "week2Completions": 2352,
    "percentagePointChange": -17,
    "relativeChange": -0.3777777777777777,
    "comparableStrata": true,
    "fixedMixWeek2Rate": 0.3533333333333334,
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      {
        "key": "reddit-paid/exploring/traceability",
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      {
        "key": "reddit-paid/exploring/value",
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  "unavailable": [
    "true-cac",
    "incrementality",
    "awareness",
    "realized-ltv",
    "profitability"
  ]
}

Orihinal na tugon ng production

# GreenLeaf Wellness UK — Production Reporting Draft

**Fictional teaching example.** Paid-click cohorts 2026-09-01 through 2026-09-14; snapshot 2026-09-22T23:59:59Z.  
**Basis:** approved facts in `review.md`, `brief-v2.md`, and `analysis.json`.  
**Release state:** AI-assisted editorial production pass only. No human approval, client review, or external delivery has occurred.

---

# 1. Founder / CEO Summary

## WHAT happened

Mobile quiz completion fell from **45% in Week 1** to **28% in Week 2**:

| Mobile metric | Week 1 | Week 2 |
|---|---:|---:|
| Quiz starts | 8,400 | 8,400 |
| Quiz completions | 3,780 | 2,352 |
| Completion rate | 45% | 28% |

That is −17 percentage points, approximately −37.8% relative.

The decline is not a mirage of device totals. It sits alongside a mobile audience-mix change: skeptical share of mobile starts fell from 50% to 25%, while exploring share rose from 50% to 75%. When Week 2 is reweighted using Week 1 channel × audience × creative weights, the mobile completion rate is **35.33%** rather than 28%. Both composition and within-group movement therefore contribute descriptively. All 12 mobile strata declined.

At the all-paid period level:

| Measure | Week 1 | Week 2 |
|---|---:|---:|
| All-paid media spend | $5,462 | $5,512 |
| All-paid quiz starts | 15,040 | 15,120 |
| All-paid quiz completions | 6,770 | 5,460 |
| Attributed first-purchase customers | 467 | 357 |
| Attributed first-purchase revenue | $37,360 | $28,560 |
| Media CPA | $11.70 | $15.44 |
| Attributed first-order ROAS | 6.84 | 5.18 |

Media CPA increased and attributed first-order ROAS declined between the two mature paid-cohort periods.

## WHY it matters

The quiz is the main early signal for UK consideration. A 17-point mobile completion decline means the launch is losing progress at the point where interested buyers should become qualified first-purchase candidates. The decline is broad across mobile strata, so the immediate priority is to establish whether the mobile post-click journey or measurement definition changed.

The financial picture is directionally weaker, but it remains **paid-cohort attributed first-purchase revenue only**. No profit, full CAC, incrementality, or all-channel monthly revenue conclusion is available.

## WHAT’S NEXT — at most three actions

1. **Do not recommend a budget move from this evidence alone.**  
   Owner: founder / marketing owner. Existing authorized risk and commercial processes remain the approval route.

2. **Verify the mobile journey and event definitions.**  
   Owner: product owner + media lead. Apply the diagnostic work order in Section 2.5. No version-specific causal claim is approved before release/version/QA evidence is supplied.

3. **Hold the diagnostic decision until role owners complete their checks.**  
   Owner: founder / marketing owner, with a measurement-competent reviewer holding client-facing release authority. No external or client-facing delivery has occurred.

**Unavailable and not to be inferred:** true CAC, incrementality, awareness, realized LTV, profitability, full-month revenue, and any causal revenue-loss estimate.

---

# 2. Media Team Analysis

## 2.1 Comparison status

| Item | Status |
|---|---|
| Week 1 dates | 2026-09-01 through 2026-09-07 |
| Week 2 dates | 2026-09-08 through 2026-09-14 |
| Observation window | 7 days post-click for each cohort |
| Snapshot | 2026-09-22T23:59:59Z |
| Comparison status | Settled |

## 2.2 Period totals

### All paid

| Measure | Week 1 | Week 2 |
|---|---:|---:|
| Spend | $5,462 | $5,512 |
| Impressions | 412,560 | 414,960 |
| Clicks | 21,720 | 21,840 |
| Landing sessions | 18,380 | 18,480 |
| Quiz starts | 15,040 | 15,120 |
| Quiz completions | 6,770 | 5,460 |
| Completion rate | 45.01% | 36.11% |
| Attributed first-purchase customers | 467 | 357 |
| Attributed first-purchase revenue | $37,360 | $28,560 |
| Media CPA | $11.70 | $15.44 |
| Attributed first-order ROAS | 6.84 | 5.18 |

### Device

| Device | Week | Starts | Completions | Completion rate |
|---|---|---:|---:|---:|
| Mobile | W1 | 8,400 | 3,780 | 45.00% |
| Mobile | W2 | 8,400 | 2,352 | 28.00% |
| Desktop | W1 | 6,640 | 2,990 | 45.03% |
| Desktop | W2 | 6,720 | 3,108 | 46.25% |

Mobile starts stayed flat at 8,400. Mobile completion fell; desktop completion moved slightly upward.

## 2.3 Mobile audience-mix change

| Audience | Mobile starts W1 | Mobile starts W2 | Share W1 | Share W2 |
|---|---:|---:|---:|---:|
| Skeptical | 4,200 | 2,100 | 50% | 25% |
| Exploring | 4,200 | 6,300 | 50% | 75% |

This is a material composition change. The correct Week 2 mobile strata are:

- skeptical strata: 350 mobile starts each;  
- exploring strata: 1,050 mobile starts each.

## 2.4 Fixed Week 1 mix calculation

Using Week 1 channel × audience × creative quiz-start shares as fixed weights:

| Calculation | Result |
|---|---:|
| Week 1 observed mobile completion | 45.00% |
| Week 2 observed mobile completion | 28.00% |
| Week 2 fixed-mix mobile completion | **35.33%** |

Under this particular baseline-weight decomposition:

| Component | Contribution |
|---|---:|
| Within-group change | −9.67 points |
| Remaining composition component | −7.33 points |

These are descriptive decomposition components, not causal attribution. A different decomposition order may allocate interaction differently.

Because all 12 comparable mobile strata declined, the fixed-mix result cannot be interpreted as a simple composition-only story. The mobile decline has both within-group and composition elements.

## 2.5 Investigation work order

| Owner role | Required evidence/action | Stop condition |
|---|---|---|
| Product owner | Reproduce the mobile flow and retrieve release/version/QA evidence | Missing assignment/logs prevents a version-specific causal claim |
| Media lead | Reconcile event meaning, cohort tagging, and comparable device/audience/creative cuts | Inconsistent definitions or immature windows prevent a settled comparison |
| Reviewer with current measurement knowledge and release authority | Check the decision and all stakeholder drafts before client-facing release | Approval absent means no external delivery |

**Reported fictional context pending verification, not confirmed cause:**

- Product owner reports a mobile quiz presentation revision beginning September 8 at 09:00 UTC.
- Support lead reports an unlinked concern about finding the next-step control.

No deployment audit, rollout share, ticket counts, or linkage to paid cohorts has been supplied. These reports prioritize an investigation; they are not evidence of causality.

---

# 3. Content & Creative Brief

## Message/post-click hypotheses

The broad mobile decline could reflect:

1. **Presentation friction.** The mobile quiz presentation may have changed after Week 1.  
2. **Measurement/tracking change.** Event definitions or source tagging may differ between Week 1 and Week 2.  
3. **Targeting/mix changes.** The mobile audience mix shifted from 50% skeptical to 75% exploring.

These remain hypotheses.

No creative or message winner is claimed. The decline appears across both `traceability` and `value` mobile strata, and across all comparable mobile strata.

## Focused next step

Inspect the post-click context before proposing a message test.

| Component | Detail |
|---|---|
| Owner | Content lead, product owner |
| First step | Review post-click journey evidence after the media/product diagnostic begins |
| Required before message testing | Verified mobile event definitions, version-assignment evidence, and comparable cohort context |
| Stop condition | If measurement or journey remains unverified, do not claim a failed or winning hook |
| Intent | Keep message hypotheses distinct from proof |

---

# 4. Retrospective Alert Example

## Trigger

Settled paid-mobile quiz completion below the stated 45% target.

## Window

- Observation window: 7 days after each end-of-day paid-click cohort.
- Week 2 comparison dates: 2026-09-08 through 2026-09-14.
- Snapshot: **2026-09-22T23:59:59Z**.

## Earliest justified detection time

With end-of-day click cohorts and a seven-day observation rule, the full Week 2 paid-mobile comparison is first justified at:

```text
2026-09-21T23:59:59Z
```

The supplied snapshot is:

```text
2026-09-22T23:59:59Z
```

## Detect → Analyze → Route → Review

| Stage | Action | Responsible role |
|---|---|---|
| Detect | Settled paid-mobile completion is below 45% | Measurement/performance lead |
| Analyze | Compare both periods, device/audience/creative cuts, fixed-mix check | Media lead |
| Route | Assign mobile journey and event-definition verification | Product owner + media lead |
| Review | Check evidence and approve any client-facing statement | Measurement-competent reviewer with release authority |

## Cadence

This is a static illustration for the next reporting cycle. No live messages, automated spend changes, or external alerts are active.

## Expiry / escalation

- Recheck the rule, context, and evidence requests at the next reporting cycle.
- Escalate missing definitions or evidence to the marketing owner rather than issuing a firm claim.

## Human client-facing approval state

```text
No human approval has occurred.
No client-facing release has occurred.
```

---

# 5. Limitations

## Unavailable outcomes

The following are explicitly unavailable:

- True CAC
- Incrementality
- Awareness
- Realized LTV
- Profitability
- Full-month all-channel revenue
- Causal revenue-loss estimate

## Static demonstration

This retrospective alert is a static teaching demonstration. It does not imply running automation, real-time detection, or externally visible alerting.

## Fictional case

This is a constructed example. It is not real client-operating evidence and does not represent real customers, accounts, approvals, or campaign results.

---

# 6. Use of approved facts only

This production draft uses only the approved tables, calculations, and decisions from `review.md`, `brief-v2.md`, and `analysis.json`. The metrics above are consistent across all three deliverables:

- Mobile completion: **45% → 28%**  
- Fixed-mix Week 2 mobile: **35.33%**  
- All-paid spend: **$5,462 → $5,512**  
- All-paid completions: **6,770 → 5,460**  
- Attributed first-purchase customers: **467 → 357**  
- Attributed first-purchase revenue: **$37,360 → $28,560**  
- Media CPA: **$11.70 → $15.44**  
- Attributed first-order ROAS: **6.84 → 5.18**  
- Desktop completion: **45.03% → 46.25%**

Provenance ng run at mga limitasyon

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  "actualModelInvocations": true,
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    "production-result.json": "777bcf18204a9d9ceab4bd539f258cd675c24dcf3146e87666898a70c7f4e2d9",
    "production-source.json": "268a719071e323171ad784011db92006a4aac952c6fd3bb5f38d5bb7044f1f68",
    "production-review-input.md": "f7c7472ec2c70eaa5a7c28356f464a80be6adb07c1ba51a6b97ebd1ef0796a81"
  },
  "limits": [
    "One text-only initial invocation, one focused follow-up and one formatting pass; no code-execution tool.",
    "The authored mobile decline is not an AI-discovered real campaign anomaly.",
    "Calculations and editorial review were AI-assisted; no completed human or client approval is claimed.",
    "No time saving, profitability, causal lift or operating-model outcome was measured."
  ],
  "editorialFinalization": "Separate checked editorial reports, not verbatim production-response copies; human release remains pending.",
  "productionInputSnapshot": "production-review-input.md preserves the exact review supplied to formatting; en/review.md later gained the production-pass review."
}

Na-prerecord na kathang-isip na context note

# Supplemental context — prewritten fictional product/support follow-up

**Authored:** 2026-10-29, before the initial AI run. **Use:** introduce only after the initial v1 response, during human review. Record this file's SHA-256 before the run. This is authored teaching context, not a real interview, ticket export, deployment log or finding from a live client. Nothing here describes or predicts the model's response.

## What v1 knew

The brief contained the supplied course business, research hypotheses, measurement definitions and activation handoff. It explicitly marked product release history, mobile QA and support feedback as unknown and assigned follow-up to their owners. No product defect, founder sensitivity or known release was withheld from those supplied v1 inputs. The fictional reporting team had not yet received this follow-up. The real author writes it in advance so later context cannot be tailored to manufacture an AI failure.

## Newly supplied in the fictional review sequence

At the product/support follow-up after the v1 draft, the product owner reports that a mobile-only quiz presentation revision began rolling out on **September 8, 2026, at 09:00 UTC**. It added an expandable ingredient-information panel and changed the label beside the next-step control. The desktop presentation was unchanged. The owner has not supplied the deployment audit, rollout share, version-assignment log or device/browser QA results. This is a reported release description within the fiction, not independently verified instrumentation evidence.

The support lead reports that recent messages included difficulty finding the next-step control on a phone. The supplied note contains no ticket-level dates, counts, customer identifiers or linkage to paid cohorts, quiz events, creative or release version. It does not establish complaint prevalence, whether users abandoned, whether the comments began before the revision or whether any loss was incremental.

The product owner can assign a mobile reproduction and event-verification check in the next working day, with the media lead supplying cohort/funnel definitions. A proposed check should compare affected and unaffected presentation versions where assignment can be reconstructed, verify that starts/completions mean the same thing across versions, and inspect device/browser combinations. If assignment or event evidence is missing, record that limit instead of claiming a controlled test.

## What this can change — and what remains unresolved

This context can make product/measurement verification a more specific or timely next step than an immediate message rewrite or channel move. It can also confirm a sensible existing diagnostic recommendation. The reviewer must decide from the actual draft and checked data; no changed recommendation or reduced confidence is required.

Timing, device scope and a reported usability concern make the revision an **investigable hypothesis**. They do not establish that it caused the aggregate change. Audience/channel/creative mix, within-group movement, event-definition changes, other releases and unrelated influences still require scrutiny. The fixed-mix comparison remains necessary and cannot be replaced by this story. No revenue-loss estimate, causal attribution, automatic pause or exact budget reallocation follows from this note.

Carry into brief v2 as **reported fictional context pending verification**, naming product owner and media lead, requested logs/checks and the unresolved causal question. Record independently verified counts as data findings, reported context as reported context and review actions as decisions. Keep the actual initial response unedited. This is an example of learning after a brief, not a controlled comparison of human and AI judgment.

Gamitin ang evidence pack

Mga pampublikong file ng halimbawa. Hiwalay ang bayad na materyal ng kurso.

Reporting brief v1 ↓MD · 15.3 kB · v1
Data dictionary ↓MD · 12.4 kB · v1
Tala ng editorial review ↓MD · 8.7 kB · v1
In-update na reporting brief v2 ↓MD · 3.6 kB · v1
Ano ang nagbago sa brief ↓MD · 2.1 kB · v1
Tala ng production at routing ↓MD · 2.7 kB · v1
Orihinal na synthetic CSV ↓CSV · 51.1 kB · v1
Reconciled CSV ↓CSV · 51 kB · v1
Nasuring kalkulasyon ↓JSON · 16.8 kB · v1
Tala ng isyu sa data ↓JSON · 0.4 kB · v1
Campaign lookup ↓CSV · 0.3 kB · v1
Creative lookup ↓CSV · 0.7 kB · v1
Mapa ng pinagmulan ng mga katotohanan ng kurso at reconstruction ↓JSON · 10.8 kB · v1
Unang isinumiteng prompt ↓MD · 76.8 kB · v1