# 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](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.