2026年9月1–14日 · 每个点击队列观察七天 · 采用9月22日快照回顾比较
本示例包含
认识 GreenLeaf
一个进入英国市场的虚构美国营养补充剂品牌。
市场拓展假设
成分透明能帮助英国买家选择GreenLeaf吗?
- 测验完成率目标
- 45%
- 英国月收入目标
- US$60,000
- 无提示品牌认知度目标
- 15%
阅读业务背景
英文编辑来源——发布与所有者/人工放行仍待完成。 GreenLeaf 为虚构公司。其营销活动数据及后续背景更新系教学用途编写;所记录的人工智能回复为真实内容。下列检查为独立计算与人工智能辅助编辑审阅,并非已完成的人工审阅或客户批准。本示例不衡量人工智能准确性、人工优越性、节省的时间或营销活动投资回报率。
GreenLeaf Wellness 销售订阅型补剂:每日绿粉、蛋白粉混合品和适应原组合。该公司正从美国拓展至英国,并提出一项具体主张:客户可以查看原料来源与剂量,而不必相信一句无法解释的专有配方。
发布的问题问起来简单,回答起来更难:英国买家会不会足够在意,从而选择它? 要给出有用的建议,团队必须把客户假设、营销活动选择与衡量计划同结果联系起来。本条路径会跟随这些交接,形成一份完整的报告示例。
其核心决策如下。付费移动端测验完成率从 3,780 / 8,400 次开始(45%) 降至 2,352 / 8,400(28%)。一份人工智能草稿建议进行诊断性复核,但同时给出了错误的财务总额,还否定了受众构成中的一项有意义变化。经过核对的各项计算支持同时调查队列构成和移动端旅程。之后一份虚构的产品/支持说明让调查更具体,但原因仍未查明。
两个时段分别为 9 月 1–7 和 9 月 8–14,2026,采用 UTC 付费点击队列。漏斗事件与购买采用相同的七天观察窗口。快照时间为 9 月 22 23:59:59 UTC。两个时段均已成熟:这是一次回顾性比较,并不证明发布期间曾有警报发现问题。
从你拥有的决策开始
| 你的职责 | 你从这项工作中需要什么 |
|---|---|
| 代理机构领导层 | 你可以捍卫的建议、各交付成果之间一致的事实,以及明确的客户放行决策。 |
| 内部营销领导层 | 改变发布优先级的证据,以及诊断与商业批准之间的区分。 |
| 媒介或绩效领导层 | 可比较的队列、事件定义、经过核对的计算和一项具体调查。 |
| 创意、产品或实施工作 | 一个可检验的问题、当前数据缺失的证据,以及一个可问责的下一步。 |
你可以检查每项交付成果。这些读者视角共享同一家公司和同一份数据集;它们不会编造不同的事实。该课程的三个报告接收方仍然是创始人、媒介团队和内容/创意团队。
先理解客户,再解读营销活动
课程介绍了 Oliver,一个持怀疑态度的生物黑客,他想审核一款补剂背后的证据。他是一个合成人物假设,并非接受过访谈的客户。
向发布团队提供一次有用的交接应当像这样:
| 工作假设 | 留给真实研究的问题 | 对营销活动的后果 |
|---|---|---|
| 原料透明很重要 | 买家在上一次购买补剂前核实了什么? | 测试来源和剂量证明是否值得放在显要位置。 |
| 更低的价格可能引发对品质的怀疑 | 是什么让一项优惠显得可信或可疑? | 用支持性信息解释价值,而不是用一句毫无依据的品质断言。 |
| 测验可以帮助买家选择 | 是什么让买家信任或放弃那段旅程? | 同时检查点击后体验和广告。 |
本次重建使用了 skeptical 和 exploring 两个受众分桶,以及 traceability 和 value 两条信息。这些是用于分析的构造类别,并非经过验证的心理细分或随机分配。说明性的可溯源信息是 “Know what is in every serving.”(了解每份产品含有哪些成分)。任何真实部署都需要有据可查的产品信息和适当的声明审核。
激活交接是具体的:广告 → 落地页 → 测验开始 → 测验完成 → 首次购买,并带有一致的营销活动、设备、受众和创意标识符。报告团队需要命名规范和事件定义,还需要发布与测试历史。一条广告的信息无法解释一次损坏的完成事件;一个看似可信的人物也无法证明一条信息有效。
在打开导出表之前定义成功
| 业务目标 | 虚构课程目标 | 这些输入能够确立什么 |
|---|---|---|
| 帮助买家在考虑阶段推进 | 45% 测验完成率 | 所提供付费队列中的完成次数 ÷ 开始次数。 |
| 产生新的英国客户收入 | 每月 $60,000 | 两个付费点击队列周产生的归因首次购买收入,并非整月结果。 |
| 建立认知度 | 15% 无提示知名度 | 不可用;点击和展示无法替代知名度研究。 |
| 获取具有持久价值的客户 | 12 个月的 LTV 为 $480 | 不可用;首单收入无法确立留存或 LTV。 |
CTR、CPC 和 CPM 有助于调查绩效。它们不能替代这些结果。课程还给出 $312 的盈亏平衡 CAC 护栏,但导出表只包含媒介成本和归因的首次购买客户。媒介 CPA 并非完整的 CAC。 应用该护栏需要对成本、客户和经济假设进行同口径的核对。
报告简报 v1
GreenLeaf 英国发布——报告简报 v1
**版本:**1.0 · **撰写:**2026-10-29 · 状态: 虚构教学示例的英文源输入;并非已发布报告。在生成合成示例数据之前冻结本简报、词典和来源映射。数据验证后另行冻结确切的运行输入哈希。本简报不主张任何 AI 响应或分析结果。
业务与报告交接
GreenLeaf Wellness 是本课程的虚构订阅制补充剂业务,正从美国扩展至英国。其产品包括每日绿粉、蛋白混合粉和适应原组合。其拟议的差异化在于成分可追溯性和透明剂量。商业问题是:这一主张能否帮助英国买家从考虑推进到首次购买。本次重建仅考察付费队列;无法判定整个发布活动的成败。
| 上游工作 | 此处提供的具体交接 | 报告如何使用 | 仍需要的证据 |
|---|---|---|---|
| 研究与策略 | Oliver,持怀疑态度的生物黑客,是一个合成人物假设。异议:我能否核实每份含量,价格是否体现价值?采访问题:什么证据改变了你上一次补充剂候选名单? | 比较skeptical和exploring受众假设以及traceability和value信息,而不将标识符当作经过验证的心理学结论。 | 真实客户访谈、观察到的异议和经过验证的细分定义。 |
| 测量 | 业务目标 → KPI → 诊断杠杆。测验完成率 = 完成数 / 开始数;新客户收入有月度目标。七天 UTC 付费点击队列采用共同的成熟度规则。 | 将结果置于 CTR/CPC/CPM 之上,并比较同类分母。 | 全渠道月度收入对账、认知度研究、留存历史和增量设计/结果。 |
| 激活 | 示例信息:“Know what is in every serving.”(了解每份产品含有哪些成分)。第二条信息通过清晰的剂量信息检验价值。旅程:广告 → 落地页 → 测验开始 → 完成 → 首次购买。规范的活动/设备/受众/创意 ID 见词典。 | 检查信息、受众、设备和漏斗阶段;诊断前先请求事件与发布对账。 | 任何产品主张的证实、事件 QA 日志、广告平台导出以及带时间戳的发布/测试登记。这些示例信息并非获批广告。 |
| 机构记忆 | 本 v1 记录当前提供的所有场景背景。未提供历史季节性基线、客户偏好日志、早期机构发现或已知产品事件。 | 将缺失的历史视为未知;询问其所有者,而不是凭空编造创始人敏感性或季节性解释。 | 产品/支持和商业所有者的跟进;将随后得知的信息连同出处记录在 v2 中。 |
来源映射区分课程事实、新的重建选择和之后得出的结果。来源:课程可追溯性。字段语义:词典。
1. KPI 与目标
| 业务决策 | 课程场景目标 | 本次重建可获得的证据 | 报告边界 |
|---|---|---|---|
| 买家是否在推进考虑? | 45% 测验完成率 | 付费队列测验完成数 ÷ 开始数,分别包括移动端和桌面端 | 所撰写的移动端对比为 45% → 28%,下降 17 个百分点(相对降幅约 37.8%)。生成后需核实计数;这是教学约束,而非观察到的客户结果或全站比率。 |
| 英国发布是否产生新客户收入? | 每月 USD $60,000 | 九月 1–14 付费点击队列的归属首次购买收入 | 两周付费队列不能确立整月、全渠道结果。不得将目标按比例折算为成功判定。需获取整月数据、统一收入定义和对账后的新客户账本。 |
| GreenLeaf 的知名度是否提升? | 15% 无提示认知度 | 不可获得 | 展示量、点击量和付费收入不能替代品牌认知度研究。 |
| 客户是否随时间产生价值? | 12 个月 LTV USD $480 | 不可获得 | 首单收入无法确立已实现的 LTV 或留存。 |
课程的 $312 盈亏平衡 CAC 是场景规划的护栏。本导出提供媒体支出和归属首次购买客户,因此支持的是媒体 CPA,而非完整 CAC。在与该护栏比较之前,需对账获客成本范围、独立新客户、期间和经济假设。仅凭媒体 CPA 不能得出任何 CAC 超标或盈利性结论。
CTR、CPC、CPM、点击到开始率、完成到购买率、媒体 CPA 和归属首单 ROAS 是诊断杠杆。频次、展示份额和跳出率不可获得,因为所需源字段缺失。增量提升、全站收入、合成示例数据之外的退款、完整获客经济性和长期结果仍然未知。
2. 利益相关者、决策与发布权限
一次提示必须基于同一简报和对账后的数据集产出全部三份草稿。每项发现都应回答发生了什么 → 为什么重要 → 下一步是什么,将经核查的事实、假设、未知项和建议行动区分开来。
| 接收方 | 报告必须支持的决策 | 必需交付物 | 权限与边界 |
|---|---|---|---|
| 创始人/CEO(或内部营销负责人) | 发布优先级现在是否应调整,还是团队应先获取具体证据再作商业决策? | 一页摘要:商业信号、实质性不确定性和明确的下一步决策。 | 创始人/营销所有者批准商业优先级和预算。不得自动重新分配资源、提出无依据的收入损失估计或月度目标判定。 |
| 媒体团队 | 应首先调查哪个队列、事件定义或旅程阶段?什么证据会改变下一次媒体决策? | 渠道/设备/受众/创意分析、漏斗计数、加权比率和固定组合检验。 | 媒体负责人拥有来源对账和诊断工作单的决定权;支出变更需商业批准。 |
| 内容与创意团队 | 下一次测试应聚焦信息、点击后体验,还是聚焦选择二者所需的证据? | 聚焦的创意/测试简报:假设、所需证据、负责人和成功衡量标准。 | 创意负责人提出测试;产品所有者批准产品变更和相关的声明证实。不得提出无依据的创意胜出或因果结论。 |
机构负责人可以检查建议质量和发布纪律;内部负责人可以检查改变计划的证据;绩效负责人可以检查诊断工作。评估专业判断的读者可以检查同样的证据。这些读者视角不能替代三份课程交付物,也不能改变基本事实。
熟悉测量定义和活动运营的审查者检查来源对账、计算、比较逻辑和建议的决策。创始人/营销所有者保留面向领导层/客户建议的发布权限。这些都是虚构的角色分配,不是真人、真实信息或真实批准。
3. 背景层与已知未知
时间: 第 1 周 = 九月 1–7,2026;第 2 周 = 九月 8–14。date 是 UTC 付费点击队列日期。漏斗事件和归属购买共享合格点击后的七天。快照 = 2026-09-22T23:59:59Z,此时两个期间均已成熟。这是回顾性对比,并非第 2 周期间检测到的证据。未提供任何季节性影响、假日解释或更早基线。
业务: 英国扩展、订阅产品和透明度主张来自虚构的课程场景。报告货币为 USD,以保持课程目标单位。此处未确立任何真实英国价格、汇率换算、获批健康声明、发布预算或完整客户经济性。
竞争: 课程将 AG1、Huel、Ritual、Seed 和 Thorne 作为可识别的品类背景。本示例未研究当前定价、竞品活动和市场份额;不能将任何变动归因于它们。Oliver 的人物对话是合成的,不是真实客户的访谈记录。
客户/团队历史: 产品发布状态、移动端 QA 发现、支持反馈、创始人敏感性、受众测试分配和此前的报告经验均未在 v1 中提供。这些输入中未出现,并不意味着没有变化。第一份诊断工作单必须向产品/支持索取带时间戳的背景,并向测量索取事件/版本对账。任何答案对本简报而言都是新信息,必须如此标注。不得预先假定产品问题。
4. 基准、维度与常识检查
内部对比是两个相等且已成熟的七天期间。45% 课程目标是在已声明的付费队列范围下的基准;未提供任何外部行业基准。维度为渠道(google-search、linkedin、reddit-paid)、设备(mobile、desktop)、受众(skeptical、exploring)、创意(traceability、value)和漏斗阶段。这些是构建的互斥报告分组,并非经过验证的定向效果或真实人物分类。
在撰写发现之前:
- 将 337 条原始行对账到 336 条规范每日行:删除唯一一条完全重复行,仅规范化已声明的活动别名,保留源计数并验证标识符、整数计数/美分和
is_provisional。 - 检查漏斗不等式、成熟覆盖和归因假设。不得从聚合 CSV 独立推断独立客户数。零分母产生不可获得比率,而非零绩效。
- 先求分子与分母之和,再相除。永远不要对行级比率取平均;货币比率须用美分计算,且不得对中间值取整。
- 在渠道 × 受众 × 创意分层内检查移动端变动。用第 1 周测验开始份额作为固定权重,比较第 2 周分层比率。报告观察到的聚合值、固定组合比较、权重和任何未定义分层。先诊断构成变化与组内变动,再给出产品解释;两种模式都仍缺乏因果识别。
- 将设备和细分总计对账到整体。用队列和归因限制解释首单收入。不得复制无依据的课程资产数字,例如风险收入、细分倍数或精确预算调整。
回顾性预警规则: 对于成熟可比、且至少有一次测验开始的每周付费移动队列,若完成率低于 45%,则标记。检测 → 用来源/固定组合检查分析 → 将诊断转交媒体负责人和产品所有者 → 人工审查。负责的所有者记录来源窗口、快照、最早可辩护可用时间、决策和审批状态。静态样本并非运行中的服务;不授权任何外部消息、自动支出变更或预防损失声明。
5. 节奏与下一份简报
每周:诊断/优化摘要、经核查的队列切片、负责人和下一个证据请求。每月:对照完整目标期间的业务叙述,明确说明全渠道对账和不可获得的结果。每季:重置规划假设、基准和测量设计,而不是外推这份快照。
在本教学周期中,保留实际的多受众提示和未经编辑的响应;记录模型/运行元数据和确切输入哈希。包含一个聚焦的分析问题、经核查的答案和有用的后续行动。人工审查可以确认、修改、推迟或拒绝某项建议;不改变建议同样是有效结果。新了解的虚构背景必须在初次运行之前写好并记录哈希,不得为制造失败而事后补写。它不是第一份草稿的输入。
随后记录审查理由,更新简报 v2 和可读差异,并根据获批事实产出三份最终报告。区分由背景促成的变更与审查者独立判断。在记忆中把假设保留为假设。这一序列展示的是报告判断力;它不衡量 AI 准确性、人类优越性、节省时间或客户 ROI。公开发布需通过单独管理的本地化和审查关卡。
付费流量的移动端测验完成率从45%降至28%
每个点代表付费流量在移动端开始测验次数的1%;实心点表示已完成的测验。
3,780 / 8,400 测验开始次数
保持受众构成不变
将各渠道 × 受众 × 广告素材组合的测验开始次数占比固定为第1周水平,第2周的完成率为35.33%。这一描述性比较不能确定原因。
已观察到下降,原因尚未查明。
核验 AI 的工作
已对照CSV核验。原因尚未查明。
已记录的AI初稿 · 英文原文 · 含有重大错误
阅读完整的原始回复
2026年10月29日的DeepSeek V4 Pro纯文本调用,未使用代码执行工具。
# 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.| 证据 | 原始人工智能草稿 | 对照 CSV 核对 |
|---|---|---|
| 每周媒介支出 | 每周 $110,100 | 第 1 周:$5,462 · 第 2 周:$5,512 |
| 移动端完成率与受众构成 | 45% → 28%;否定了受众构成作为解释 | 3,780 / 8,400 → 2,352 / 8,400。第 2 周按第 1 周构成:35.33%。 |
一份虚构的产品/客服记录提到移动端测验有改动。上线情况和影响尚未核实。
查看工作成果
同一组事实,三个决策。
已核验的编辑稿 · 等待人工批准发布
创始人报告确定市场拓展的优先事项。
GreenLeaf UK — 创始人 / CEO 摘要
经审核的编辑草稿;等待人类发布。 虚构 9 月 1–14 日付费点击队列,2026,观察截至 9 月 22 日。以 USD 计。这也是面向内部 CMO 的领导层视角。
发生了什么
付费移动端测验完成率从 45% 降到 28%,下降 17 个百分点。已核对的数量是 3,780/8,400 → 2,352/8,400。桌面端完成率为 45.03% → 46.25%。
在所提供付费队列中,归因首购客户为 467 → 357,归因首购收入为 $37,360 → $28,560。这些是构造出来的归因结果,不是增量订阅的证据,也不是因测验造成的收入损失证据。
为什么重要
测验是英国发布的考虑环节。向完成率较低的受众桶转变和可比移动组内部下降共同促成了总体变化。固定第 1 周组合,第 2 周完成率为 35.33%,因此仅用组合无法解释下降。
产品负责人报告了移动端呈现改版,支持部门报告了可用性问题。所提供的证据没有把两者与测量队列关联起来。产品原因仍未得到证实。
接下来发生什么
- 产品负责人 + 媒体负责人: 核实移动端旅程、事件定义以及发布/版本证据。所称可在下一个工作日进行检查是情景假设,不是已完成行动。返回比较计划或明确的缺失证据说明。
- 营销负责人: 不要仅凭这份 CSV 批准预算变动或创意转向。现有商业/风险决策仍按其正常权限管理;这不是全面冻结。
- 财务/测量负责人: 在宣布 $60K/月 目标达成或未达成前,核对业务的完整 9 月收入定义和全渠道结果。队列收入和月度会计/业务指标需要明确的同类核对。
完整 CAC、利润、认知度、已实现终身价值和增量性仍不可得。
媒介报告选择下一步调查。
GreenLeaf UK — 媒体团队分析
经审核的编辑草稿;等待人类发布。 虚构英国付费点击队列;第 1 周 = 9 月 1–7 日,第 2 周 = 9 月 8–14 日,2026。七天观察窗口,9 月 22 日快照。
发生了什么
| 所有已提供付费队列 | 第 1 周 | 第 2 周 |
|---|---|---|
| 支出,USD | $5,462 | $5,512 |
| 测验开始 | 15,040 | 15,120 |
| 测验完成 | 6,770 | 5,460 |
| 归因首购客户 | 467 | 357 |
| 归因首购收入 | $37,360 | $28,560 |
| 媒体 CPA | $11.70 | $15.44 |
| 归因首单 ROAS | 6.84 | 5.18 |
媒体 CPA 仅含媒体成本;请勿直接与课程的 $312 完整 CAC 护栏比较。ROAS 是归因首单收入除以媒体支出,不是利润或因果提升。
| 渠道 | 第 1 周支出 | 第 2 周支出 | 第 1 周客户 | 第 2 周客户 | 第 1 周收入 | 第 2 周收入 |
|---|---|---|---|---|---|---|
| Google Search | $1,736 | $1,744 | 154 | 105 | $12,320 | $8,400 |
| $2,296 | $2,304 | 154 | 119 | $12,320 | $9,520 | |
| Reddit paid | $1,430 | $1,464 | 159 | 133 | $12,720 | $10,640 |
未提供经批准的月度媒体预算,因此无法评估预算进度。
为什么移动端比较需要组合检查
移动端完成率:3,780/8,400 = 45% → 2,352/8,400 = 28%。变化为 −17 个百分点,约 −37.8% 相对变化。桌面端为 2,990/6,640 = 45.03% → 3,108/6,720 = 46.25%。
移动端怀疑型开始从 4,200 降到 2,100;探索型开始从 4,200 升到 6,300。其占比从 50%/50% 变为 25%/75%。这些是构造出来的桶,不是经验证的客户偏好,也不是随机化处理。
12 个渠道 × 受众 × 创意移动端分层中,每层在第 1 周均有 700 次开始。使用权重 700/8,400 = 1/12,乘以该层第 2 周的完成率。对加权比率求和:35.33%,在显示前保留完整精度。每个单元格见指标包。
在这种第 1 周加权分解中,组内分量为 −9.67 个百分点,构成分量为 −7.33 个百分点。分配取决于所选基线/顺序;两个数字都不是因果效应。所有 12 个层均下降,但 CSV 无法解释原因。
接下来发生什么
- 媒体负责人: 核实事件定义和来源/队列标记;保持相同的成熟度规则。
- 产品负责人 + 媒体负责人: 调取发布/版本分配并复现移动端流程。在可重建分配的情况下比较版本。缺少日志会限制可得出结论的范围。
- 测量审核人: 在相关方发布前检查计算、背景和决策。不要推断产品原因、建议精确的预算变动,或把恢复到目标本身当作有效检验设计。
所报告的移动端呈现改版和支持问题用于优先安排这些检查。它们不能证明缺陷、普遍性或增量损失。未发生任何外部行动或交付。
内容与创意报告检查广告信息与用户体验。
GreenLeaf UK — 内容与创意简报
经审核的编辑草稿;等待人类发布。 虚构 9 月 1–14 日付费点击队列,观察截至 9 月 22 日,2026。消息假设不是经批准的广告声明。
发生了什么
两个消息组的总体测验完成率都较低:
| 消息假设 | 第 1 周完成 / 开始 | 第 2 周完成 / 开始 |
|---|---|---|
| 可溯源:“Know what is in every serving”(了解每份产品含有哪些成分) | 3,276 / 7,560 = 43.33% | 2,625 / 7,560 = 34.72% |
| 价值:“Compare the value of a clearly dosed serving”(比较成分剂量标示清楚的每份产品的价值) | 3,494 / 7,480 = 46.71% | 2,835 / 7,560 = 37.50% |
这些总数合并了设备、受众和渠道。它们不是同类可比的因果创意测试。价值消息更高的总体比率不能确立其为赢家。
为什么重要
客户假设强调清晰的成分信息。所报告的移动端呈现改版增加了一个可展开的信息面板,并更改了下一步标签。无法关联的支持反馈提到难以找到下一个控件。检查点击后体验是合理的;根据这些文件就认定消息、面板或标签是原因则不合理。
接下来发生什么
拟议问题: 在事件含义和旅程行为得到核实后,页面是否在保持下一步可理解的同时清晰传达了消息承诺?
内容负责人: 与产品负责人一起检查从广告到页面的交接。将可溯源和价值保留为明确假设。确认每项成分/剂量陈述都有依据。
产品/测量负责人: 确定版本分配和可比队列能否支持聚焦测试。在运行前设定分母、比较和决策规则。如果缺少分配或追踪,记录该限制;前后恢复不是因果证明。
这里不支持任何创意退役、获胜钩子声明或媒体预算建议。CSV 中没有观看/重放证据,因此不能确立疲劳、困惑普遍性或用户在哪个屏幕放弃。
证据资料库
完整推理、简报与原始证据。
步骤 1 —— 把报告框架写成规范
完整简报 v1 在模型起草任何内容之前,先为它提供了工作框架:
- KPI 与目标: 上述层级、分母和不可用的结果。
- 利益相关者地图: 每份报告所支持的决策,以及谁可以批准行动。
- 背景层次: 英国拓展、人物假设、时间和明确缺失的机构历史。
- 基准与维度: 45% 的目标;渠道、设备、受众、创意和漏斗切分;比较与验证规则。
- 节奏: 每周诊断、每月业务叙事和每季度规划重置。
简报承载了已经知道的东西。产品发布、移动端质量保证、支持反馈和早前的客户敏感事项在所提供的 v1 输入中均为未知,后续事项已分配给其所有者。未知并不意味着什么都没变。它意味着报告团队必须去问。
每份报告的指令都是 发生了什么 → 为什么重要 → 下一步是什么。创始人必须判断发布优先级是否需要关注;媒介必须选择下一步调查;创意必须决定在改变信息或体验之前需要什么证据。一项建议需要一名所有者,也需要一条放行边界。
检查支持证据
数据字典 定义了字段和假设。来源映射 把课程事实和目标同重建选择区分开。未从课程中恢复任何 GreenLeaf 报告的底层 CSV。
原始导出表有 337 行,其中包括一行完全重复;核对后的数据集为 336 行。它覆盖十四个天内的三个付费渠道、两种设备、两个受众和两个创意类别。一个已声明的营销活动别名被规范化。一行零活动桌面行用于检查:零分母应变为不可用,而不是零绩效。来源清理记录在问题日志 中。
金额采用整数美元美分。每个合成新客户在七天内只归因给最后一次符合条件的付费点击。首次购买收入按每位客户 $80 构建,已扣除折扣并排除税费/运费,且没有固定样本退款。这些是已披露的假设,并非经过独立验证的归因、课程定价或已实现的 LTV。经过核对的计算包 提供了可复现的参考值。
步骤 2 —— 让 AI 从相同输入生成三份草稿
实际提交的提示词 要求在同一次回复中提供创始人摘要、媒介分析和创意简报。它包含简报 v1、数据字典、核对后的 CSV 和营销活动/创意查找表。第一份草稿并未收到之后的背景说明或参考计算包。
所记录的调用在 10 月 29 2026 使用了 DeepSeek V4 Pro。本次调用仅限文本,没有代码执行工具。运行元数据 记录了实际模型、时间戳和输入哈希。原始回复 保持未编辑状态,包括其中的错误。
这份草稿提供了所要求的三个部分,并建议进行事件/版本核对和移动端质量保证。它还未经核验就把计算结果当作报告数字。这些数字会实质性地改变业务的面貌:
| 项目 | 初始草稿 | 对照核对后的数据 |
|---|---|---|
| 每周媒介支出 | 每周 $110,100 | 第 1 周为 $5,462;第 2 周为 $5,512。 |
| 归因首次购买收入 | $43,840 → $38,560 | $37,360 → $28,560。 |
| 第 2 周移动端完成数 | 2,360 | 2,352;占 8,400 次开始的 28%。 |
| 受众构成 | 被描述为稳定 / 基本不作为解释 | 移动端 skeptical 开始占比从 50% 变为 25%;exploring 从 50% 变为 75%。 |
这些是关于这次所记录回复在这些调用条件下的发现。它们不能确立所有模型、带工具的流程或分析师的表现。合成模式是在运行前编写的;它不是发现的客户异常。
提出那个会改变解读的问题
聚焦的追问交流 要求提供分层计数和第 1 周的权重。它朝着认识构成变化靠近,但仍包含算术不一致。原始回复和追问回复都被保留。部分修正并不能验证它们剩余的断言;第二个看似合理的答案也不是独立验证。
经过核对的比较如下:
| 移动端比较 | 完成率 |
|---|---|
| 第 1 周观测值 | 45.00% |
| 第 2 周,采用第 1 周渠道 × 受众 × 创意开始权重 | 35.33% |
| 第 2 周观测值 | 28.00% |
共有十二个移动端分层,每个分层为第 1 周贡献 700 次开始,因此每个基准权重为 1/12。保持这些权重不变,仍有约 9.67 个百分点的下降。第 2 周观测到的比率又比那个固定构成比较低 7.33 个点。在这种明确分解下,构成变化和分层内比率变动都对这 17 个点的下降产生了影响。
这改变了诊断工作顺序:既要核对受众占比如何变化,也要检查移动端旅程和事件定义。这并不能确定任一变动的原因。固定构成计算是一种比较方法,不是因果实验。
步骤 3 —— 添加背景并判断决策
课程把人工判断放在这里:一个具备衡量能力并掌握当前业务背景的人,决定是确认、修改、推迟还是拒绝草稿的建议。仅修正算术是不够的;审核者还必须评估所提议的行动。
在本证据包中,计算和人工智能辅助编辑检查已经执行。真正的所有者/人工放行决定仍待完成。 准备本示例的代理并非人工审核者,虚构的角色指派也不是真正的批准。
补充背景说明 是在初次运行之前编写并记录哈希的。在虚构的时间线中,产品/支持跟进提供了报告团队在 v1 时并不掌握的信息:
- 产品所有者报告,9 月 8 09:00 UTC 开始进行仅限移动端的测验展示修改:新增一个原料信息面板,并更改了下一步标签。
- 支持部门报告,在手机上难以找到下一步控件,但没有工单数量、日期或与付费队列的关联。
- 产品可以在下一个工作日内安排一次复现和事件验证检查;部署、发布和版本分配记录仍然缺失。
这是报告的虚构背景,不是经过验证的发布日志,也不能证明该修改导致了放弃。其时间和设备范围使其值得调查。受众构成检查仍然是必要的。
一项拟议的审核决定是保留诊断性调查,修正财务和队列证据,并把产品/衡量请求变得更具体。请产品提供发布/版本证据和移动端复现;请媒介核对受众分配和事件采集。推迟因果解释、创意胜者和精确预算调整。如果初始草稿已经建议合理的诊断工作,那一部分可以保持不变。
审核记录、简报 v2 和简报变更 保存了拟议决定及其证据。需要带入下一份简报的学习是精确的:该发布处于已报告、待验证状态;45% → 28% 的比率和固定构成比较属于经过核对的数据发现;下一步调查是一项拟议决定。把这些类别分开,可以防止一个看似合理的解释在将来的提示词中变成无需质疑的事实。
步骤 4 —— 产出可用报告并安排下一步行动
这个产出步骤把经过核对的证据和记录在案的审核决定转变成三份一致的交付成果:创始人报告、媒介报告 和内容报告。在人工放行之前,这些都是本示例的编辑草稿,并非经批准的客户指令。
| 报告 | 以“是什么 / 为什么 / 下一步”形式表达的有用发现 |
|---|---|
| 创始人摘要 | 是什么: 付费移动端完成率下降 17 个点,而归因首次购买收入从 $37,360 降至 $28,560。为什么: 考虑阶段和首单产出需要关注,但两个付费队列周无法确定月度收入或利润。下一步: 考虑所指明的诊断工作,并在商业结论之前取得整月核对。 |
| 媒介分析 | 是什么: 第 2 周移动端观测率为 28%,按第 1 周构成计算为 35.33%。为什么: 构成和分层内变动都很重要。下一步: 核对受众/版本/事件定义,并与产品一起调查移动端旅程。 |
| 内容与创意简报 | 是什么: 数据集包含两个说明性信息类别,同时有报告称移动端展示发生了变化。为什么: 当前证据无法孤立信息失败,也无法确立创意胜者。下一步: 在设计受控的信息/点击后测试之前,验证旅程和追踪条件。 |
产出记录 包含一个有边界的回顾性警报,遵循 检测 → 分析 → 路由 → 审核。规则是成熟的付费移动端每周完成率低于 45%,且开始次数分母非零。第 2 周以 28% 满足该条件。分析附上队列窗口、快照和固定构成比较;路由分配媒介和产品跟进;由人决定能否放行领导层/客户建议。
完整的第 2 周七天队列在其观察窗口于 9 月 21 UTC 结束时关闭之前,不能按这条成熟度规则判定。本证据包使用 9 月 22 的较晚快照。未展示任何实时警报、信息送达、自主营销活动变更或已避免的损失。每周诊断随后供月度业务报告和季度假设重置使用。
重复这个示例,然后改编它
从三个文件开始:简报、数据字典 和核对后的 CSV。先读简报;只有把决策、窗口和分母弄清楚之后,CSV 才有意义。然后检查实际提示词、原始回复、经过核对的计算和背景说明,以了解什么变了、为什么变。
请使用组织批准的模型和账户。仅分享客户、组织及服务商协议允许的数据;移除涉及机密、敏感及个人信息的字段,并尽可能使用合成数据或已获批准的汇总数据。未经许可,不要上传客户的数据导出文件。
对于自己的工作,在代之以客户数据之前,先替换业务目标、利益相关者、归因规则和背景。独立核对总额和一个有代表性的分层。保留原始回复,记录审核者决定了什么,并把经过验证的学习带入下一份简报。当成熟度、来源覆盖范围或定义不匹配时,停止比较;当实质性算术、证据或决策权限仍未解决时,停止放行。缺失的知名度、LTV 或增量证据仍为不可用。
这条路径把报告示例的推理和有用证据直接给出,而不是藏起答案。付费课程提供完整的视频教学序列、可复用的完整模板集、深入指南和更广泛的实施材料。这个完整示例展示了从客户假设到报告决策的一条相连路径;它并不意味着已完成七条公开工作流,也不改变课程访问权限和购买者权益。
检查工作文件
数据字典
GreenLeaf 报告数据词典——v1 语义契约
**撰写:**2026-10-29 · 状态: 合成示例数据生成前已冻结的源规范;英文编辑输入。CSV 是新的合成重建,并非恢复的课程数据。简报 管理决策;来源映射 管理出处。不包含真实客户、健康信息或客户账户。 引用证据中的数字保留英文原始资料的格式:逗号分隔千位,句点表示小数,金额以USD计。页面上的摘要指标则可能按所选语言和地区显示。
粒度、窗口与归因
一条规范行是英国境内一个 UTC 付费点击日期 × 渠道 × 设备 × 受众 × 创意。十四个日期 × 三个渠道 × 两种设备 × 两种受众 × 两种创意 = 336 行。原始导出有 337 行,包括一条完全重复行。活动属于渠道,不增加维度。
第 1 周:2026-09-01–2026-09-07(含)。第 2 周:2026-09-08–2026-09-14(含)。快照:2026-09-22T23:59:59Z。日期为 UTC,date 始终表示付费点击队列日期,而非购买/事件日期。漏斗事件和首次购买在合格付费点击后的七天内观察。不导出精确事件时间戳;七天归因/观察窗口是生成器构造假设。两个完整期间在快照时均已成熟。所有已发布的主行均具有 is_provisional=false。
支出、展示量和点击量描述分配给该队列日期的获客活动。落地、测验和购买计数跟随其带来源标签的付费点击队列和设备/受众/创意分组。每个合成的首次购买客户和收入金额只分配一次,分配给七天内的最后一次合格付费点击;所有事件阶段遵循相同的排他性分配。不测量跨设备身份对账。排他性由构造保证,并非由这一聚合文件独立确立。
字段
| 字段 | 类型/单位 | 含义与验证 |
|---|---|---|
row_id | 非空字符串 | 稳定且唯一的规范行 ID。原始完全重复行会重复该 ID;具有相同 ID 的冲突行属于错误。 |
date | ISO YYYY-MM-DD | UTC 源付费点击队列日期,在九月 1–14 内。 |
market | 枚举 | 仅限 UK;范围是虚构英国发布中的付费队列。 |
channel | 枚举 | google-search、linkedin、reddit-paid。排除自然 Reddit 活动。 |
campaign_id | 规范化后枚举 | 每个渠道一个活动;查找见下文。 |
device | 枚举 | mobile 或 desktop,所分配源付费点击的设备。 |
audience_id | 枚举 | skeptical 或 exploring;在渠道内构建的互斥分组,并非经过验证的客户特征。 |
creative_id | 枚举 | traceability 或 value;具有渠道特定格式的信息假设,查找见下文。 |
spend_cents | 非负整数 USD 美分 | 仅媒体成本。不含代理、创意、工具、薪资或其他获客成本。 |
impressions | 非负整数 | 该分组中的获客广告展示量;不是独立人数或频次。 |
clicks | 非负整数 | 分配给该分组的付费点击;不是独立访客。 |
landing_sessions | 非负整数 | 在合格付费点击后七天内观察到的带来源标签落地会话。每个合成漏斗旅程最多保留一次会话。 |
quiz_starts | 非负整数 | 在同一七天窗口内开始的不同保留带来源标签测验旅程;每个旅程保留一次开始。完成率分母。 |
quiz_completions | 非负整数 | 在同一七天窗口内完成的已保留测验旅程;不重复计算完成。 |
attributed_new_customers | 非负整数 | 在七天内完成此构建的测验主导漏斗的首次购买客户,按声明的最后付费点击规则仅分配一次。并非全站新客户。 |
attributed_first_purchase_revenue_cents | 非负整数 USD 美分 | 来自这些客户的首次购买收入,为折扣后、不含税费和运费的金额。本合成示例数据中无退款;无续费收入。为算术清晰,生成器为每位首次购买客户分配 USD $80(8,000 美分);这是重建假设,并非课程定价或 LTV。 |
is_provisional | 布尔值 | false 表示该行的七天观察窗口在声明快照时已成熟。拒绝不支持的字符串/布尔强制转换。 |
逐行不等式:impressions >= clicks >= landing_sessions >= quiz_starts >= quiz_completions >= attributed_new_customers。这是显式的简化测验主导漏斗构造,并非广告导出的普遍属性。客户数为零的行必须具有零首次购买收入;客户数为正的行必须具有正收入。这些约束不提供个人层面的证据。
规范查找与原始清理
| 渠道 | 规范活动 ID | 显示名称 | 允许的原始活动 ID 别名 |
|---|---|---|---|
google-search | gl-uk-google-search | GreenLeaf UK 搜索 | gl_uk_search → gl-uk-google-search |
linkedin | gl-uk-linkedin | GreenLeaf UK LinkedIn | 无 |
reddit-paid | gl-uk-reddit-paid | GreenLeaf UK Reddit 付费 | 无 |
受众 skeptical:为寻求证据、比较采购来源/剂量证据的买家构建的分组;灵感来自 Oliver 未经验证的人物设定。受众 exploring:为探索品类并考虑价值的买家构建的分组。它们既不是真实定向规范,也不是随机化处理分配;不推断任何身份、职业或健康状况。
创意 traceability:示例性 “Know what is in every serving”(了解每份产品含有哪些成分) 信息。创意 value:示例性 “Compare the value of a clearly dosed serving”(比较成分剂量标示清楚的每份产品的价值) 信息。对于 Google 搜索,这些是文字广告信息假设;对于 LinkedIn,是赞助信息流文案假设;对于 Reddit 付费,是推广帖文案假设。创意 ID 是各渠道内共享的信息类别,并非完全相同的成品广告资产或获批声明。未提供任何功效证明或实际产品认证。
仅删除逐字节/字段完全相等的重复行,并记录其源行 ID。仅规范化已声明的别名并记录数量。未知 ID、意外市场、缺失字段、格式错误的日期、非整数美分/计数、负值、冲突重复行或不可能成立的漏斗都必须验证失败,而不是被静默修复。保留一个有记录的零分母行,以验证不可获得比率的处理。对账原始/规范计数和所有维度总计。合成示例数据生成记录必须标明完全重复行、别名行和零分母行;本词典不假装这些行已经存在。
指标与比较规则
在所选队列/维度内求和,然后相除;永远不要对行级比率取平均。保留完整的中间精度。仅在呈现时通过除以 100 将美分显示为 USD。零分母产生不可获得,绝不是零/无穷;对零先验值的百分比变化为不可获得。
| 指标 | 定义 | 解释 |
|---|---|---|
| 测验完成率 | sum(quiz_completions) / sum(quiz_starts) | 主要漏斗 KPI;付费移动端第 1/2 周必须校准到 45%/28%。 |
| 点击到开始率 | sum(quiz_starts) / sum(clicks) | 诊断指标;区别于测验完成率。 |
| 点击到落地率 | sum(landing_sessions) / sum(clicks) | 诊断指标,并非经验证的跳出率。 |
| 完成到购买率 | sum(attributed_new_customers) / sum(quiz_completions) | 构建的测验主导漏斗诊断指标。 |
| CTR | sum(clicks) / sum(impressions) | 优化指标;不是认知度。 |
| CPC(USD) | sum(spend_cents) / sum(clicks) / 100 | 每次点击媒体成本。 |
| CPM(USD) | sum(spend_cents) / sum(impressions) * 1000 / 100 | 每 1,000 次展示的媒体成本。 |
| 媒体 CPA(USD) | sum(spend_cents) / sum(attributed_new_customers) / 100 | 仅媒体代理指标;不是完整 CAC。 |
| 归属首单 ROAS | sum(attributed_first_purchase_revenue_cents) / sum(spend_cents) | 收入/支出比率;不是利润、增量或 LTV。 |
| 首次购买收入(USD) | sum(attributed_first_purchase_revenue_cents) / 100 | 仅付费队列归因;不是对 $60K 整月目标的判定。 |
比率的百分点变化为 (Week 2 rate - Week 1 rate) * 100。当第 1 周为正时,相对变化为 (Week 2 rate / Week 1 rate - 1) * 100。所撰写的 45% → 28% 等于 −17 个百分点,相对降幅约为 −37.8%;本来源契约未预先确定任何其他结果。
在诊断移动端聚合变动之前,按渠道 × 受众 × 创意对移动端分层。对于分层 s,设定固定权重 w_s = Week 1 starts_s / Week 1 total starts。比较 sum(w_s * Week 1 completion_rate_s) 与 sum(w_s * Week 2 completion_rate_s),并将二者均与观察到的比率比较。发布权重和计数。权重为正的分层若没有定义的第 2 周比率,则完整的固定组合比较不可获得;任何明确受限的公共分层比较都必须披露被排除的计数/权重,且不能静默替代整体。权重为零的分层贡献为零,不需要比率。构成变化与层内变动可能同时存在。二者都不证明原因;这些队列并非随机化。
不完整的快照或临时主行会使两个完整期间不稳定/不可比较。不得将未观察到的结果视为零。具有相同成熟覆盖的单独选择对比必须说明所选日期、排除项和已改变的问题。
不可获得的证据与来源冲突
不可获得:完整 CAC、利润、留存、已实现的 12 个月 LTV、认知度、增量、真实全渠道/月度收入、频次、展示份额、跳出率、事件/发布日志、客户访谈和因果解释。来源资产中单独的 4.2% “quiz CVR” 在此处没有足够的共享分母定义;不要导入它。任何截图的损失估计、细分倍数、预算指示或自然到付费的因果叙述都不是得出的合成示例数据结果。关于课程事实与新撰写的假设,请参阅来源映射。
编辑审核记录
审核中发生了哪些变化
虚构 GreenLeaf UK,9 月 1–14 日付费点击队列,2026;快照时间 9 月 22 日 23:59:59 UTC。本记录由 AI 辅助编辑审核和独立核对计算编制。它不是已完成的人类批准、客户审核或受控的人与 AI 对照实验。负责人的发布/核验决定仍待定。原始模型回复未更改。
先做决定,再谈措辞
初稿建议在创意或预算转向之前先进行诊断。这个方向是合理的,但有几个数字和解释是错误的。一个看似合理的建议不能让其支撑证据变得可以安全发布。
| 初稿陈述 | 已核对证据 | 审核决定 |
|---|---|---|
| 每周支出各为 $110,100 | 第 1 周:$5,462;第 2 周:$5,512 | 否决两个草稿总额及基于它们的所有派生 CPA/ROAS |
| 新客户为 548 → 482 | 规范付费队列数量:467 → 357 | 替换;这些是归因首购,不是增量订阅者 |
| 首购收入为 $43,840 → $38,560 | $37,360 → $28,560 | 替换;不能由此得出因果性收入损失估计 |
| 移动端第 2 周有 2,360 次完成 | 2,352 / 8,400 = 28% | 替换数量/比率;保留第 1 周已核对的 3,780 / 8,400 = 45% |
| 移动端受众/创意份额稳定,构成效应基本不存在 | 怀疑型占移动端开始比例:50% → 25%;探索型:50% → 75% | 否决组合解释 |
| 固定第 1 周组合约可得 35.3%–35.5% | 显示取整前精确为 35⅓% | 使用 35.33%;说明组合变化和组内变化都很重要 |
| 创始人应冻结支出再分配 | 仅凭 CSV 无法确立所有商业/风险决策应是什么 | 收窄到 “do not recommend a budget move from this evidence alone”(不要仅凭这些证据建议调整预算);保留现有授权风险流程 |
| 若完成率回到 45% 附近,诊断即为成功 | 回到目标不是因果检验设计 | 要求经核实的事件定义、版本/队列证据和明确的比较计划 |
原始回复中的所有渠道、桌面端、受众和创意表仍为未批准。最终编辑草稿改用已核对指标包。模型调用是纯文本的,没有计算执行工具。这是关于本次运行的证据,不是关于每个 AI 分析产品的证据。
聚焦追问做了什么
第二个回复识别出受众组合变化,并给出第 2 周各层的正确开始数:怀疑型 350,探索型 1,050。它仍报告 2,360 次总完成,将 Reddit/探索型/价值单元格误报为 245 而非 252,并算错了一个加权贡献。使用记录的追问来检查迭代;不要静默地用它替代已验证的数学。
生产草稿的已批准事实
| 指标 | 第 1 周 | 第 2 周 |
|---|---|---|
| 全付费媒体支出 | $5,462 | $5,512 |
| 全付费测验开始 | 15,040 | 15,120 |
| 全付费测验完成 | 6,770 | 5,460 |
| 归因首购客户 | 467 | 357 |
| 归因首购收入 | $37,360 | $28,560 |
| 媒体 CPA | $11.70 | $15.44 |
| 归因首单 ROAS | 6.84 | 5.18 |
| 移动端测验开始 | 8,400 | 8,400 |
| 移动端测验完成 | 3,780 | 2,352 |
| 移动端完成率 | 45% | 28% |
| 桌面端完成率 | 45.03% | 46.25% |
移动端变化:−17 个百分点;约 −37.8% 相对变化。固定第 1 周渠道 × 受众 × 创意权重,第 2 周移动端比率为 35.33%。在这种特定的基线权重分解下,组内分量为 −9.67 个百分点,剩余构成分量为 −7.33 个百分点。另一种分解顺序可能以不同方式分配交互效应;这是描述性的,不是因果归因。所有 12 个可比移动层均下降。
新的虚构背景及其影响
背景说明在运行前已预先编写并哈希。它报告自 9 月 8 日 09:00 UTC 开始的移动端呈现改版,以及一项无法关联的关于找不到下一步控件的支持问题。发布审计、发布占比、工单数量和与付费队列的关联均缺失。
结论:修订解释并收窄下一步行动;确认诊断优先的方向。 请产品负责人和媒体负责人核实移动端旅程和事件定义,调取版本分配/发布证据,并在证据允许的情况下对同类组进行比较。产品负责人所称可在下一个工作日进行检查是虚构背景,不是检查已经发生的证据。产品原因、创意失败或收入损失仍然未知。
将改版报告带入简报 v2,作为待核实的已报告背景,绝不能作为已确认的原因。未批准任何自动暂停、支出变更或外部警报。
对生产环节的指示
在三个草稿中保留已批准表格、不确定性和上述决定:
- 创始人/CEO:趋势和诊断决定,最多三项行动及角色负责人。
- 媒体:期间/渠道/设备细节、固定组合比较和调查工作顺序。
- 内容/创意:将消息假设与证据区分开;在提出消息测试之前先检查点击后背景。不要提出因果性创意赢家,也不要建议媒体预算变更。
关于回顾性警报:在已确定的付费移动端完成率低于所述 45% 目标时触发。采用日终点击队列和七天观察规则,完整第 2 周比较首次合理的时机是 9 月 21 日 23:59:59 UTC;所提供的快照是 9 月 22 日 23:59:59 UTC。检测 → 分析 → 路由 → 审核是静态演示。产品负责人/媒体负责人负责诊断;具备测量能力和发布权限的审核人负责面向客户的批准。没有发生任何人类批准或对外交付。下一周期重新检查规则/背景,并将缺失的定义或证据上报给营销负责人,而不是做出确定性的声明。
来源
依据所提供的对账后 CSV、经独立审核的确定性计算和 data/analysis.json 进行核对。原始初始回复和追问回复仍是可下载证据。最终编辑草稿中的数字声明必须对应声明台账。这里的 “Approved” 表示已批准用于本次 AI 辅助编辑生产环节;它不能代替负责人的人类发布关口。
对记录的生产环节的检查
记录的格式处理环节保留了已核对的期间/设备数量和财务比率。它还引入了 “hold the diagnostic decision until role owners complete their checks,”(在各负责人完成检查前,暂缓作出诊断决定),这可能被解读为推迟我们打算开始的调查。该措辞未保留在单独的编辑报告中。其内容部分将 “targeting/mix changes”(定向与受众构成变化) 归入假设:组合变化是在合成数据中观察到的;造成它的原因仍是假设。
所提供的创始人/媒体/内容文件是基于同样已批准事实分别准备、检查过的编辑草稿。它们不会被宣传为格式处理回复的逐字副本。原始生产输出保持未更改,以便读者也能检查这最后一道审核边界。
更新后的报告简报 v2
GreenLeaf 汇报简报 v2 — 把学习带到下一步
状态: AI 辅助编辑草稿;等待人类发布/核验批准。虚构案例,不是客户运营证据。这是对完整简报 v1的补充更新,不是用更短提示替换它。下一周期请同时阅读两者。
v1中的业务目标、KPI 定义、相关方职责、归因规则、目标期间和节奏保持不变。新知识按证据类别分列如下。
已核对的数据发现
- 付费移动端完成率第 1 周为 3,780/8,400 = 45%,第 2 周为 2,352/8,400 = 28%。
- 移动端怀疑型/探索型开始占比从 50%/50% 变为 25%/75%。
- 使用固定第 1 周渠道/受众/创意权重,第 2 周完成率为 35.33%。构成变化和组内变化在描述性上都起作用;所有 12 个移动层均下降。未证明因果关系。
- 首个纯文本 AI 回复及其聚焦追问包含算术错误。请复用已核对的指标包和声明引用,而不是那些回复中未经核实的数字。
已报告的虚构背景 — 核实待定
产品负责人报告称,自 9 月 8 日 09:00 UTC 起开始移动端测验呈现改版。支持负责人报告称在手机上难以找到下一个控件,但没有日期、数量或与付费队列的关联。没有提供部署审计、发布占比或版本分配证据。这些报告用于优先安排调查;它们不是经核实的发布日志,也不是因果诊断。
下一周期工作顺序
| 负责人角色 | 所需证据/行动 | 停止条件 |
|---|---|---|
| 产品负责人 | 复现移动端流程并调取发布/版本/QA 证据 | 缺少分配/日志则无法做出版本特定的因果声明 |
| 媒体负责人 | 核对事件含义、队列标记和可比的设备/受众/创意切分 | 定义不一致或观察窗口不成熟则无法形成确定的比较 |
| 内容负责人 | 在测量/旅程检查后,检查消息和点击后预期 | 没有确认的消息问题,就不能声称某个钩子获胜或失败 |
| 具备当前测量知识和发布权限的审核人 | 在面向客户发布前,检查决策和所有相关方草稿 | 没有批准就不能对外交付 |
必须保持为假设的假设
呈现摩擦、追踪变化、定向/组合变化和其他影响可能都在起作用。支持报告不能确立普遍性或放弃率。没有确立任何由测验导致的收入损失、增量提升、利润、已实现 LTV、完整 CAC 或月度业务目标结论。
在下一汇报周期重新审视背景、规则和证据要求;移除过时假设,或明确将其保留为未解决。本次更新及其复用都不能证明未来产出会改善。
简报中变化了什么
简报 v1 与 v2 之间有哪些变化
虚构 GreenLeaf 示例。AI 辅助编辑审核;等待人类发布。
| 领域 | v1 | v2 | 证据类别 |
|---|---|---|---|
| 移动端信号 | 目标和编写的教学信号;尚无可核对输出 | 已核对 3,780/8,400 → 2,352/8,400 | 重建的 CSV,已验证计算 |
| 受众组合 | 诊断前先比较 | 移动端开始从均等份额变为 25% 怀疑型 / 75% 探索型 | 重建的 CSV,已验证计算 |
| 可比组 | 必需的分析检查 | 固定组合第 2 周比率 35.33%;所有 12 个层均下降 | 描述性计算,无因果解释 |
| 产品历史 | 未知;向负责人索取 | 报告了移动端改版;缺少审计/分配/发布占比 | 预写的虚构背景,核实待定 |
| 支持历史 | 未知 | 报告了无法关联的找不到下一步控件困难 | 虚构轶事,无普遍性估计 |
| 下一步 | 在过早干预之前先诊断 | 优先与产品/媒体负责人核实移动端/事件 | 编辑决策,已提出未完成 |
| AI 数字 | 必须核对 | 记录了初始/追问错误;使用已核对指标包 | 实际记录回复加独立核对 |
| 业务目标和未知项 | 四个目标,缺少因果/LTV/认知/经济性证据 | 保持不变 | 课程情景和证据限制 |
没有从 v1 中故意删除任何已知历史。后续背景是在初始运行之前编写的,代表虚构团队后来了解到的信息。这个顺序不是对人类优越性的受控测试,也不是产品缺陷或可衡量节省的证明。
产出与路由记录
一项发现到达正确的负责人
静态回顾性教学示例。 没有监控服务、外部消息、自动化活动变更或已完成的人类发布。所提议的报告是 AI 辅助编辑草稿。
检测
规则:已确定的付费移动端测验完成率低于情景的 45% 目标。第 2 周为 2,352/8,400 = 28%。这是一个明确的测验规则,不是媒体 CPA 与完整 CAC 的比较。
点击队列覆盖 9 月 8–14 日,2026,UTC,采用七天观察窗口。在日终成熟度惯例下,完整第 2 周比较首次合理的时机是 9 月 21 日 23:59:59 UTC。本示例使用 9 月 22 日,23:59:59 UTC 的快照。它无法演示第 2 周期间的早期检测,也无法证明损失本来可以避免。
分析
先核对数量和定义,再做可比组比较。固定第 1 周组合得到 35.33%,而不是 28%:构成变化和组内变化都很重要。所报告的移动端改版/支持问题支持诊断假设,不构成原因。不可得的结果仍然不可得。
路由
| 接收方 | 接收内容 | 职责 |
|---|---|---|
| 产品负责人 + 媒体负责人 | 移动端诊断工作顺序和相关队列 | 核实旅程/事件并调取发布/版本证据 |
| 创始人 / 营销负责人 | 面向业务的摘要 | 在证据和建议通过审核后确定优先级 |
| 内容负责人 | 消息/点击后简报 | 检查交接,只提议有依据的测试 |
没有实时电子邮件/Slack 投递。该表是虚构工作流中的路由记录。
审核
发布状态:等待人类审核。 具备当前测量能力和发布权限的审核人必须批准面向客户的建议。绿色测试、模型回复或另一个代理的审核都不能提供该批准。
每周诊断节奏;月度业务叙述;季度规划重置。在下一汇报周期重新审视规则和背景。将缺失定义、过时背景或不可得的版本证据上报给营销负责人;保留不确定性,而不是发布自信的警报。不虚构任何确切的未来审核日期、已完成的诊断或结果。
所记录运行的证据
AI调用记录,保留英文原文。
初始提交的提示词
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
追问回复
# 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.追问提示词
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.产出提示词
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": {
"spend_cents": 174400,
"impressions": 131040,
"clicks": 7280,
"landing_sessions": 6160,
"quiz_starts": 5040,
"quiz_completions": 1722,
"attributed_new_customers": 105,
"attributed_first_purchase_revenue_cents": 840000,
"rows": 56,
"settled": true,
"quizCompletionRate": 0.3416666666666667,
"mediaCpaCents": 1660.952380952381,
"attributedFirstOrderRoas": 4.81651376146789,
"ctr": 0.05555555555555555,
"cpcCents": 23.956043956043956,
"cpmCents": 1330.8913308913309
}
},
"linkedin": {
"week1": {
"spend_cents": 229600,
"impressions": 138320,
"clicks": 7280,
"landing_sessions": 6160,
"quiz_starts": 5040,
"quiz_completions": 2268,
"attributed_new_customers": 154,
"attributed_first_purchase_revenue_cents": 1232000,
"rows": 56,
"settled": true,
"quizCompletionRate": 0.45,
"mediaCpaCents": 1490.909090909091,
"attributedFirstOrderRoas": 5.365853658536586,
"ctr": 0.05263157894736842,
"cpcCents": 31.53846153846154,
"cpmCents": 1659.919028340081
},
"week2": {
"spend_cents": 230400,
"impressions": 138320,
"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,
"attributed_first_purchase_revenue_cents": 1272000,
"rows": 56,
"settled": true,
"quizCompletionRate": 0.47580645161290325,
"mediaCpaCents": 899.37106918239,
"attributedFirstOrderRoas": 8.895104895104895,
"ctr": 0.05,
"cpcCents": 19.972067039106147,
"cpmCents": 998.6033519553073
},
"week2": {
"spend_cents": 146400,
"impressions": 145600,
"clicks": 7280,
"landing_sessions": 6160,
"quiz_starts": 5040,
"quiz_completions": 1918,
"attributed_new_customers": 133,
"attributed_first_purchase_revenue_cents": 1064000,
"rows": 56,
"settled": true,
"quizCompletionRate": 0.38055555555555554,
"mediaCpaCents": 1100.751879699248,
"attributedFirstOrderRoas": 7.26775956284153,
"ctr": 0.05,
"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,
"attributedFirstOrderRoas": 6.73469387755102,
"ctr": 0.05263157894736842,
"cpcCents": 25.128205128205128,
"cpmCents": 1322.5371120107961
},
"week2": {
"spend_cents": 275600,
"impressions": 207480,
"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": {
"week1": {
"spend_cents": 271800,
"impressions": 205080,
"clicks": 10800,
"landing_sessions": 9140,
"quiz_starts": 7480,
"quiz_completions": 3494,
"attributed_new_customers": 236,
"attributed_first_purchase_revenue_cents": 1888000,
"rows": 84,
"settled": true,
"quizCompletionRate": 0.46711229946524063,
"mediaCpaCents": 1151.6949152542372,
"attributedFirstOrderRoas": 6.946284032376748,
"ctr": 0.0526623756582797,
"cpcCents": 25.166666666666668,
"cpmCents": 1325.3364540667058
},
"week2": {
"spend_cents": 275600,
"impressions": 207480,
"clicks": 10920,
"landing_sessions": 9240,
"quiz_starts": 7560,
"quiz_completions": 2835,
"attributed_new_customers": 196,
"attributed_first_purchase_revenue_cents": 1568000,
"rows": 84,
"settled": true,
"quizCompletionRate": 0.375,
"mediaCpaCents": 1406.1224489795918,
"attributedFirstOrderRoas": 5.689404934687953,
"ctr": 0.05263157894736842,
"cpcCents": 25.238095238095237,
"cpmCents": 1328.3208020050126
}
}
},
"byAudience": {
"skeptical": {
"week1": {
"spend_cents": 274400,
"impressions": 207480,
"clicks": 10920,
"landing_sessions": 9240,
"quiz_starts": 7560,
"quiz_completions": 4200,
"attributed_new_customers": 301,
"attributed_first_purchase_revenue_cents": 2408000,
"rows": 84,
"settled": true,
"quizCompletionRate": 0.5555555555555556,
"mediaCpaCents": 911.6279069767442,
"attributedFirstOrderRoas": 8.775510204081632,
"ctr": 0.05263157894736842,
"cpcCents": 25.128205128205128,
"cpmCents": 1322.5371120107961
},
"week2": {
"spend_cents": 275600,
"impressions": 183540,
"clicks": 9660,
"landing_sessions": 7980,
"quiz_starts": 6300,
"quiz_completions": 3108,
"attributed_new_customers": 203,
"attributed_first_purchase_revenue_cents": 1624000,
"rows": 84,
"settled": true,
"quizCompletionRate": 0.49333333333333335,
"mediaCpaCents": 1357.6354679802955,
"attributedFirstOrderRoas": 5.8925979680696665,
"ctr": 0.05263157894736842,
"cpcCents": 28.530020703933747,
"cpmCents": 1501.5800370491445
}
},
"exploring": {
"week1": {
"spend_cents": 271800,
"impressions": 205080,
"clicks": 10800,
"landing_sessions": 9140,
"quiz_starts": 7480,
"quiz_completions": 2570,
"attributed_new_customers": 166,
"attributed_first_purchase_revenue_cents": 1328000,
"rows": 84,
"settled": true,
"quizCompletionRate": 0.34358288770053474,
"mediaCpaCents": 1637.3493975903614,
"attributedFirstOrderRoas": 4.885945548197204,
"ctr": 0.0526623756582797,
"cpcCents": 25.166666666666668,
"cpmCents": 1325.3364540667058
},
"week2": {
"spend_cents": 275600,
"impressions": 231420,
"clicks": 12180,
"landing_sessions": 10500,
"quiz_starts": 8820,
"quiz_completions": 2352,
"attributed_new_customers": 154,
"attributed_first_purchase_revenue_cents": 1232000,
"rows": 84,
"settled": true,
"quizCompletionRate": 0.26666666666666666,
"mediaCpaCents": 1789.6103896103896,
"attributedFirstOrderRoas": 4.470246734397678,
"ctr": 0.05263157894736842,
"cpcCents": 22.627257799671593,
"cpmCents": 1190.9083052458734
}
}
},
"byDevice": {
"mobile": {
"week1": {
"spend_cents": 274400,
"impressions": 223440,
"clicks": 11760,
"landing_sessions": 10080,
"quiz_starts": 8400,
"quiz_completions": 3780,
"attributed_new_customers": 259,
"attributed_first_purchase_revenue_cents": 2072000,
"rows": 84,
"settled": true,
"quizCompletionRate": 0.45,
"mediaCpaCents": 1059.4594594594594,
"attributedFirstOrderRoas": 7.551020408163265,
"ctr": 0.05263157894736842,
"cpcCents": 23.333333333333332,
"cpmCents": 1228.0701754385964
},
"week2": {
"spend_cents": 275600,
"impressions": 223440,
"clicks": 11760,
"landing_sessions": 10080,
"quiz_starts": 8400,
"quiz_completions": 2352,
"attributed_new_customers": 147,
"attributed_first_purchase_revenue_cents": 1176000,
"rows": 84,
"settled": true,
"quizCompletionRate": 0.28,
"mediaCpaCents": 1874.8299319727892,
"attributedFirstOrderRoas": 4.267053701015965,
"ctr": 0.05263157894736842,
"cpcCents": 23.435374149659864,
"cpmCents": 1233.44074471894
}
},
"desktop": {
"week1": {
"spend_cents": 271800,
"impressions": 189120,
"clicks": 9960,
"landing_sessions": 8300,
"quiz_starts": 6640,
"quiz_completions": 2990,
"attributed_new_customers": 208,
"attributed_first_purchase_revenue_cents": 1664000,
"rows": 84,
"settled": true,
"quizCompletionRate": 0.4503012048192771,
"mediaCpaCents": 1306.7307692307693,
"attributedFirstOrderRoas": 6.12214863870493,
"ctr": 0.05266497461928934,
"cpcCents": 27.289156626506024,
"cpmCents": 1437.1827411167512
},
"week2": {
"spend_cents": 275600,
"impressions": 191520,
"clicks": 10080,
"landing_sessions": 8400,
"quiz_starts": 6720,
"quiz_completions": 3108,
"attributed_new_customers": 210,
"attributed_first_purchase_revenue_cents": 1680000,
"rows": 84,
"settled": true,
"quizCompletionRate": 0.4625,
"mediaCpaCents": 1312.3809523809523,
"attributedFirstOrderRoas": 6.095791001451379,
"ctr": 0.05263157894736842,
"cpcCents": 27.341269841269842,
"cpmCents": 1439.014202172097
}
}
},
"mobile": {
"week1Rate": 0.45,
"week2Rate": 0.28,
"week1Starts": 8400,
"week2Starts": 8400,
"week1Completions": 3780,
"week2Completions": 2352,
"percentagePointChange": -17,
"relativeChange": -0.3777777777777777,
"comparableStrata": true,
"fixedMixWeek2Rate": 0.3533333333333334,
"strata": [
{
"key": "google-search/exploring/traceability",
"week1Starts": 700,
"week2Starts": 1050,
"week1Completions": 175,
"week2Completions": 182,
"week1Rate": 0.25,
"week2Rate": 0.17333333333333334,
"baselineWeight": 0.08333333333333333
},
{
"key": "google-search/exploring/value",
"week1Starts": 700,
"week2Starts": 1050,
"week1Completions": 203,
"week2Completions": 210,
"week1Rate": 0.29,
"week2Rate": 0.2,
"baselineWeight": 0.08333333333333333
},
{
"key": "google-search/skeptical/traceability",
"week1Starts": 700,
"week2Starts": 350,
"week1Completions": 378,
"week2Completions": 154,
"week1Rate": 0.54,
"week2Rate": 0.44,
"baselineWeight": 0.08333333333333333
},
{
"key": "google-search/skeptical/value",
"week1Starts": 700,
"week2Starts": 350,
"week1Completions": 406,
"week2Completions": 168,
"week1Rate": 0.58,
"week2Rate": 0.48,
"baselineWeight": 0.08333333333333333
},
{
"key": "linkedin/exploring/traceability",
"week1Starts": 700,
"week2Starts": 1050,
"week1Completions": 196,
"week2Completions": 203,
"week1Rate": 0.28,
"week2Rate": 0.19333333333333333,
"baselineWeight": 0.08333333333333333
},
{
"key": "linkedin/exploring/value",
"week1Starts": 700,
"week2Starts": 1050,
"week1Completions": 224,
"week2Completions": 231,
"week1Rate": 0.32,
"week2Rate": 0.22,
"baselineWeight": 0.08333333333333333
},
{
"key": "linkedin/skeptical/traceability",
"week1Starts": 700,
"week2Starts": 350,
"week1Completions": 406,
"week2Completions": 168,
"week1Rate": 0.58,
"week2Rate": 0.48,
"baselineWeight": 0.08333333333333333
},
{
"key": "linkedin/skeptical/value",
"week1Starts": 700,
"week2Starts": 350,
"week1Completions": 434,
"week2Completions": 182,
"week1Rate": 0.62,
"week2Rate": 0.52,
"baselineWeight": 0.08333333333333333
},
{
"key": "reddit-paid/exploring/traceability",
"week1Starts": 700,
"week2Starts": 1050,
"week1Completions": 217,
"week2Completions": 224,
"week1Rate": 0.31,
"week2Rate": 0.21333333333333335,
"baselineWeight": 0.08333333333333333
},
{
"key": "reddit-paid/exploring/value",
"week1Starts": 700,
"week2Starts": 1050,
"week1Completions": 245,
"week2Completions": 252,
"week1Rate": 0.35,
"week2Rate": 0.24,
"baselineWeight": 0.08333333333333333
},
{
"key": "reddit-paid/skeptical/traceability",
"week1Starts": 700,
"week2Starts": 350,
"week1Completions": 434,
"week2Completions": 182,
"week1Rate": 0.62,
"week2Rate": 0.52,
"baselineWeight": 0.08333333333333333
},
{
"key": "reddit-paid/skeptical/value",
"week1Starts": 700,
"week2Starts": 350,
"week1Completions": 462,
"week2Completions": 196,
"week1Rate": 0.66,
"week2Rate": 0.56,
"baselineWeight": 0.08333333333333333
}
]
},
"unavailable": [
"true-cac",
"incrementality",
"awareness",
"realized-ltv",
"profitability"
]
}
原始产出回复
# 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%**运行来源与限制
{
"version": 1,
"status": "editorial-review-human-release-pending",
"fictionalCampaign": true,
"actualModelInvocations": true,
"provider": "deepseek",
"requestedModel": "deepseek-v4-pro",
"returnedModel": "deepseek-v4-pro",
"sourceCommit": "40fbb5bbf84f77e38205bfc9c88a34ab3100a289",
"initialAttachedFiles": [
"en/brief-v1.md",
"en/dictionary.md",
"data/reconciled.csv",
"data/campaigns.csv",
"data/creatives.csv"
],
"precommittedContext": {
"path": "context-note.md",
"sha256": "ae57dd174c3b596afd097ff89a3d665ab27b809767713a98ef9d6e03e9646dec",
"includedInInitialPrompt": false,
"explanation": "The legacy inputHashes field also records the precommitted context hash. The actual request messages exclude its contents; it is provenance, not an initial attachment."
},
"evidence": {
"prompt.md": "b7526a2e10958f90e1527b57852e4a946369dc571be041584a3de8578ed2dc2b",
"response.md": "af3417c37a8e507c504ae99192b805af300f5c4d4f1ba18f3bceef070d504677",
"draft-attempt-01.json": "58ffc1a277245483703d2e239f98cf6e855f8ef1acc102bac6e9092188a7f92b",
"draft-result.json": "5c38314c6b12a5cb891a6fc944239364fe03528569cd6581abe5c377e3cf257e",
"draft-source.json": "268a719071e323171ad784011db92006a4aac952c6fd3bb5f38d5bb7044f1f68",
"analysis-prompt.md": "92114f776445befa6c3ad94301b3387fd1671c32acbeb8159466511691bd3fb0",
"analysis-followup.md": "cbc408a78a97010c8d27790257d0311f813bc2a666ecc0d17341c51038a274fb",
"analysis-attempt-01.json": "fdcd45729f5a633fbd8b2c307b597e6bd7e5f74b5315931164626d910f0127f9",
"analysis-result.json": "1e93962f23469e14b4ecbc38fc585256f71478d03e6c645761d179ffd9244945",
"analysis-source.json": "268a719071e323171ad784011db92006a4aac952c6fd3bb5f38d5bb7044f1f68",
"context-note.md": "ae57dd174c3b596afd097ff89a3d665ab27b809767713a98ef9d6e03e9646dec",
"production-prompt.md": "130af408bec4c0d6394e89df364f1604bf2c4c6c9c41a2fdcd5a8aaa284fad09",
"production-response.md": "9a59340818e12170f94589818b7f99dbfd00bf7550c49230ceeef59627c3cea2",
"production-attempt-01.json": "e7b921293b530f126e8cfeef9e0e894f905274c131b3c68b84b2b756f4603b9f",
"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."
}
预记录的虚构背景说明
# 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.