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growth-hacking-playbook

核心功能涵盖增长模型定义、漏斗约束定位、可测试假设撰写、ICE/RICE优先级排序,提供获客、激活等全漏斗实验库,配套周执行节奏与决策规则。适用于初创企业搭建实验backlog、做增长实验排序、搭建推荐/UGC循环等场景。输入为企业增长需求,输出含漏斗基线、排序实验backlog、实验卡片、周日历及决策日志,全程拒绝黑帽手段,以用户价值为先。

gingiris-1031
gingiris-1031
热度 62.84
最近更新 2026-09-05 11:20:54
分类:营销依赖:纯提示词应用场景:市场分析 / 报告撰写 / 工作流 / 任务管理

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执行命令安装此 skill: npx secure-skills-cli add growth-hacking-playbook
Metadata
name
growth-hacking-playbook
description
Design, prioritize and run measurable growth experiments across acquisition, activation, retention, referral and revenue. Use when a startup needs an experiment backlog, ICE/RICE prioritization, referral or UGC loops, rapid weekly testing, causal measurement, or stop conditions without spam, fake accounts or dark patterns.

Growth Experiment System — From Idea to Decision

Do not start from a list of hacks. Start from the constrained stage of the funnel and run the smallest experiment that can change a decision.

1. Define the growth model

Record:

ICP | value event | acquisition source | activation event | retained-use event | paid event | referral event

Build the baseline funnel by cohort. For consumer products include D1/D7/D30 retention; for B2B include qualified pipeline, sales cycle and collected revenue. If the events are not instrumented, instrumentation is experiment zero.

2. Find the constraint

Signal Constraint Do next
Low qualified traffic acquisition test one audience/channel-message pair
Signup but no value event activation remove the highest-friction step
Activation but low repeat use retention interview churned and retained cohorts
Retained but no payment revenue test packaging, price or sales assist
Happy retained users, low sharing referral add a value-aligned share loop

Never scale acquisition into a broken activation or retention funnel.

3. Write testable hypotheses

Use:

For [segment], changing [one variable] from [control] to [variant]
will move [primary metric] from [baseline] to [threshold] within [window],
because [evidence]. Guardrails: [retention, quality, complaints, cost].

Every experiment needs an owner, start/end date, audience, sample/decision rule, source tracking, maximum cost and rollback.

4. Prioritize without fake precision

Score Impact, Confidence and Ease from 1–10. Confidence must cite evidence:

  • 9–10: repeated internal behavior or completed experiment;
  • 6–8: interviews plus behavioral data or strong adjacent case;
  • 3–5: external benchmark only;
  • 1–2: opinion.

Use ICE only to order the backlog. It does not replace judgment about dependencies, ethics or sample size.

5. Experiment library

Acquisition

  • 200-person founder outreach with segment/source/reply/activation tracking;
  • competitor comparison or migration page;
  • community-native Reddit/HN/tutorial post with disclosed affiliation;
  • creator/KOL pilot with individual UTMs;
  • SEO/GEO evidence page answering one high-intent question.

Activation

  • shorten time to first value;
  • replace generic onboarding with use-case routing;
  • preload a safe example project;
  • move permissions to the moment they are needed;
  • trigger human help after a repeated failure.

Retention

  • interview retained and churned cohorts separately;
  • improve the recurring job, not notification volume;
  • lifecycle reminder tied to unfinished value;
  • weekly progress artifact the user would miss;
  • team collaboration only where it improves the job.

Referral and UGC loops

Design the loop:

retained user → natural share trigger → useful artifact/invite → qualified recipient → activation → new share trigger

UGC works when the output itself is valuable or identity-enhancing. Track share rate, recipient activation, viral coefficient K = invites per user × invite conversion, retention and incentive cost. Do not pay for empty invitations or reward low-quality accounts.

Revenue

  • willingness-to-pay interviews followed by real checkout behavior;
  • packaging test around value/usage boundaries;
  • sales assist triggered by team/product signals;
  • annual-plan or expansion test with churn guardrails.

6. Weekly cadence

  • Monday: review funnel and select at most three independent tests.
  • Tuesday: QA instrumentation and launch.
  • Wednesday–Thursday: monitor guardrails; do not change the variant mid-test.
  • Friday: decide keep, iterate or kill and write the learning in the backlog.

Parallel tests must not target the same users or metric unless interaction effects are explicitly designed.

7. Decision rules

Keep only when the primary metric crosses the threshold and guardrails remain healthy. Iterate when direction is positive but the mechanism is unclear. Kill when the effect is below the minimum useful lift, cost exceeds the cap, quality declines or the channel creates policy/community risk.

Do not report impressions as growth. Report activated, retained, referred and paid cohorts plus CAC/LTV where mature enough.

Historical evidence boundary

The Gingiris library contains a planning case with a ¥1M budget and 500K-registration target (implied CAC ¥2), using UGC/ambassador and referral loops. It is a target model, not a verified result. Use it to audit arithmetic and assumptions, never as proof of achieved CAC.

Required output

Return:

  1. funnel baseline and constraint;
  2. ranked backlog with evidence-based confidence;
  3. experiment cards with hypothesis, owner, metrics, guardrails and rollback;
  4. weekly calendar;
  5. decision log and next experiment.

Compliance

Reject spam, bought engagement, sockpuppets, fake reviews, undisclosed promotion, scraping private data, coercive referrals and dark patterns. Optimize user value before virality.