固定上游版本 7868cb9251fa,包含 5 个文件。 加搜已生成可下载技能包、原始文件镜像及 7 种 Agent 安装页面。
数据与自动化 · churn-prevention
用户流失挽回 Skill
把取消与支付失败记录整理成用户流失挽回流程,配套问卷、报价和催收邮件。
当 SaaS 订阅流失率超出预期时,这套方法根据用户填写的取消原因匹配对应的折扣或暂停方案。它整理出按天重试的支付催收时间表,并基于登录频率下降等信号输出提前干预的动作清单,直接用于修改产品内的取消流程页面和支付重试规则。
WHAT IT SOLVES
解决的营销问题
把取消与支付失败记录整理成用户流失挽回流程,配套问卷、报价和催收邮件
把取消与支付失败记录整理成用户流失挽回流程,配套问卷、报价和催收邮件。跑完你拿到的是取消挽留页面交互原型图,包含单选题弹窗、动态报价展示位与结束计费周期确认按钮,中间一共 8 步。
最适合的真实场景
- 01
SaaS 运营在新版本上线后收到大量用户取消订阅请求,需要调整挽留报价组合。
- 02
用户增长发现每月有两成以上信用卡支付失败造成的被动流失,需要重设催收邮件。
- 03
产品营销需要重新梳理订阅产品取消流程,测试不同折扣力度对挽回率的影响。
- 04
客户成功找不出具体哪些用户行为导致月度流失率偏高,需要按功能使用数据排查。
- 05
财务团队需要对照失败天数排布支付重试时间表,减少因资金暂缺导致的扣款失败。
你要先准备的资料
- 过去半年的用户取消原因原始记录表,包含具体的勾选选项与用户主动填写的文本。
- 计费后台具备管理权限的测试账号,比如 Stripe 或 Chargebee,用于配置重试规则与邮件触发器。
- 导出过去六个月的用户行为数据明细,包含具体的登录间隔、核心功能使用频次与客服工单数量。
- 针对不同取消原因的挽留报价财务预算表,明确标出允许给出的最大折扣比例与暂停订阅时长上限。
- 如属于 B2B 产品,需提供高价值大客户的名单划分标准,用于匹配专属的人工挽留跟进路径。
跑完你会拿到什么
- 取消挽留页面交互原型图,包含单选题弹窗、动态报价展示位与结束计费周期确认按钮。
- 一份按取消原因分类的挽留方案对照表格,列出主推方案、备选方案与各自的目标受众画像。
- 按扣款失败天数排布的支付重试时间表,配套一整套催收邮件序列文案。
- 基于用户行为数据的流失风险评分表格,列出各项指标权重与不同得分区间对应的干预动作清单。
- 一份取消流程测试实验方案文档,包含对照组设置、变量选择标准与各项核心跟踪指标。
METHOD
Skill 工作流程
梳理当前流失现状 → 核对计费后台配置 → 设计取消问卷 等 8 个环节
一共 8 步。其中 5 项能力决定了换个 AI 会不会更麻烦。
- 梳理当前流失现状收集每月流失率、活跃订阅数和客单价数据。把整体流失拆分为主动取消与被动扣款失败两类,分别统计占比,判断是否已有取消挽留流程。
- 核对计费后台配置确认接入的支付服务商,检查是否开放了订阅暂停或降级功能。排查是否使用了第三方挽留插件,并确认后台是否支持智能重试功能。
- 设计取消问卷设置单个选择题,列出五到八个最常勾选的流失原因选项,按历史数据出现频率降序排列。末尾保留其他选项与补充文本框,避免文案让用户产生负罪感。
- 匹配动态挽留报价根据问卷选择的取消原因展示对应报价。给觉得贵的用户两到三成折扣,给用不到的用户暂停选项,给缺功能的用户展示产品路线图,每次只展示一个主推方案。
- 构建流失风险评分提取登录频率、核心功能使用率、工单情绪和计费状况等指标加权计算得分。得分处于四十到五十九分的区间触发干预邮件,零到三十九分直接推送人工跟进。
- 排布支付重试时间表区分扣款软拒绝与硬拒绝。针对暂时的资金不足等软拒绝,按一天、三天、五天、七天的间隔重试,针对卡挂失等硬拒绝直接发邮件要求用户更换新卡。
- 撰写催收邮件序列按支付失败第一天、第三天、第七天和第十天撰写四封邮件。文案包含直接修改支付信息的链接,告知具体会丢失哪些数据,不使用指责用户的语气。
- 搭建流失测试实验在取消流程中每次只测试一个变量,比如两成与三成折扣对比,或者一个月与三个月的暂停期对比。跟踪接受率、后续留存时长与暂停复购率。
这个 Skill 用到的能力: 定时任务操作前确认读本地资料运行脚本浏览器自动化 。不同 AI 对这些能力的支持程度不一样,所以同一个 Skill 换个 AI,有几步做法会变。
WORKED EXAMPLE
业务示例
在线设计工具 SaaS 团队的流失挽回重构
在线设计工具 SaaS 团队的流失挽回重构
团队月流失率达到百分之六,其中超过三分之一是信用卡过期造成的被动流失。团队需要交付一份重构的计费挽留流程,包含取消问卷的交互原型、针对不同人群的折扣与降级方案表,以及配套的扣款失败重试邮件文案。
- 调取过去六个月的后台数据,拆解主动流失与被动流失比例并导出取消原因选项。
- 梳理出觉得贵、缺功能等四类核心原因,匹配两成折扣、三个月暂停与产品路线图预告。
- 针对被动流失区分软硬拒绝,设置按一天、三天、五天与七天重试的自动计费规则。
- 编写四封催收邮件,附带免登录的信用卡更新直链与具体的账号数据冻结提醒。
- 输出流失风险评分模型,把核心功能连续两周未使用的行为定为高风险触发条件。
预期结果:交付了五步取消挽留流程的原型图,按原因分类的动态报价方案对照表,以及四封催收邮件文案。计费系统重试规则接入和原型视觉设计仍需对应开发人员与设计师人工确认。
PITFALLS · VERIFICATION
能力边界与常见问题
在取消页面隐藏取消按钮,让用户难以找到,会导致差评且违反合规要求
最常踩的坑
- 在取消页面隐藏取消按钮,让用户难以找到,会导致差评且违反合规要求。
- 对所有取消原因都发送统一的打折券,无法解决用户因缺少特定功能而流失的问题。
- 给出五成以上的超大额折扣,会让用户养成只要取消就能拿低价的惯性。
- 暂停账号的时间超过三个月,用户往往不会主动恢复使用,导致复购率极低。
- 对硬拒绝的作废卡进行多次扣款重试,只会增加通道手续费并浪费挽回时间。
怎么确认这次跑对了
- 已经形成可检查的取消挽留页面交互原型图,包含单选题弹窗、动态报价展示位与结束计费周期确认按钮,关键判断能回到输入资料或过程证据。
- 已经形成可检查的一份按取消原因分类的挽留方案对照表格,列出主推方案、备选方案与各自的目标受众画像,关键判断能回到输入资料或过程证据。
- 已经形成可检查的按扣款失败天数排布的支付重试时间表,配套一整套催收邮件序列文案,关键判断能回到输入资料或过程证据。
- 已逐项检查「在取消页面隐藏取消按钮,让用户难以找到,会导致差评且违反合规要求」等高频问题,并记录需要人工确认的下一步。
用户流失挽回 Skill适合哪些岗位使用?
SaaS 运营、用户增长、产品营销、客户成功。典型场景包括SaaS 运营在新版本上线后收到大量用户取消订阅请求,需要调整挽留报价组合;用户增长发现每月有两成以上信用卡支付失败造成的被动流失,需要重设催收邮件;产品营销需要重新梳理订阅产品取消流程,测试不同折扣力度对挽回率的影响。
开始前需要准备什么资料?
至少需要过去半年的用户取消原因原始记录表,包含具体的勾选选项与用户主动填写的文本、计费后台具备管理权限的测试账号,比如 Stripe 或 Chargebee,用于配置重试规则与邮件触发器、导出过去六个月的用户行为数据明细,包含具体的登录间隔、核心功能使用频次与客服工单数量。资料越具体,结果越能直接用于决策。
最后能得到什么可检查的结果?
取消挽留页面交互原型图,包含单选题弹窗、动态报价展示位与结束计费周期确认按钮、一份按取消原因分类的挽留方案对照表格,列出主推方案、备选方案与各自的目标受众画像、按扣款失败天数排布的支付重试时间表,配套一整套催收邮件序列文案。每项都可以逐条核对来源和数字。
哪些情况下结果会不可靠?
在取消页面隐藏取消按钮,让用户难以找到,会导致差评且违反合规要求;对所有取消原因都发送统一的打折券,无法解决用户因缺少特定功能而流失的问题。出现这些情况时需要人工复核。
支持哪些 AI Agent?
已适配 WorkBuddy、OpenClaw、Hermes Agent、Codex、Claude Code、TRAE、ZCode 共 7 种,每种都有独立的安装说明和能力对照。
ORIGINAL SOURCE
完整 Skill 内容与版本资料
5 个原始文件,93 个文档章节,固定在 7868cb92
上游原文完整保留在加搜服务器上,可逐节查看,也可以直接下载。 当前镜像共 5 个文件、48.3 KB。
Churn Prevention
You are an expert in SaaS retention and churn prevention. Your goal is to help reduce both voluntary churn (customers choosing to cancel) and involuntary churn (failed payments) through well-designed cancel flows, dynamic save offers, proactive retention, and dunning strategies.
Before Starting
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Gather this context (ask if not provided):
1. Current Churn Situation
- What's your monthly churn rate? (Voluntary vs. involuntary if known)
- How many active subscribers?
- What's the average MRR per customer?
- Do you have a cancel flow today, or does cancel happen instantly?
2. Billing & Platform
- What billing provider? (Stripe, Chargebee, Paddle, Recurly, Braintree)
- Monthly, annual, or both billing intervals?
- Do you support plan pausing or downgrades?
- Any existing retention tooling? (Churnkey, ProsperStack, Raaft)
3. Product & Usage Data
- Do you track feature usage per user?
- Can you identify engagement drop-offs?
- Do you have cancellation reason data from past churns?
- What's your activation metric? (What do retained users do that churned users don't?)
4. Constraints
- B2B or B2C? (Affects flow design)
- Self-serve cancellation required? (Some regulations mandate easy cancel)
- Brand tone for offboarding? (Empathetic, direct, playful)
How This Skill Works
Churn has two types requiring different strategies:
| Type | Cause | Solution |
|---|---|---|
| Voluntary | Customer chooses to cancel | Cancel flows, save offers, exit surveys |
| Involuntary | Payment fails | Dunning emails, smart retries, card updaters |
Voluntary churn is typically 50-70% of total churn. Involuntary churn is 30-50% but is often easier to fix.
This skill supports three modes:
- Build a cancel flow — Design from scratch with survey, save offers, and confirmation
- Optimize an existing flow — Analyze cancel data and improve save rates
- Set up dunning — Failed payment recovery with retries and email sequences
Cancel Flow Design
The Cancel Flow Structure
Every cancel flow follows this sequence:
Trigger → Survey → Dynamic Offer → Confirmation → Post-Cancel
Step 1: Trigger Customer clicks "Cancel subscription" in account settings.
Step 2: Exit Survey Ask why they're cancelling. This determines which save offer to show.
Step 3: Dynamic Save Offer Present a targeted offer based on their reason (discount, pause, downgrade, etc.)
Step 4: Confirmation If they still want to cancel, confirm clearly with end-of-billing-period messaging.
Step 5: Post-Cancel Set expectations, offer easy reactivation path, trigger win-back sequence.
Exit Survey Design
The exit survey is the foundation. Good reason categories:
| Reason | What It Tells You |
|---|---|
| Too expensive | Price sensitivity, may respond to discount or downgrade |
| Not using it enough | Low engagement, may respond to pause or onboarding help |
| Missing a feature | Product gap, show roadmap or workaround |
| Switching to competitor | Competitive pressure, understand what they offer |
| Technical issues / bugs | Product quality, escalate to support |
| Temporary / seasonal need | Usage pattern, offer pause |
| Business closed / changed | Unavoidable, learn and let go gracefully |
| Other | Catch-all, include free text field |
Survey best practices:
- 1 question, single-select with optional free text
- 5-8 reason options max (avoid decision fatigue)
- Put most common reasons first (review data quarterly)
- Don't make it feel like a guilt trip
- "Help us improve" framing works better than "Why are you leaving?"
Dynamic Save Offers
The key insight: match the offer to the reason. A discount won't save someone who isn't using the product. A feature roadmap won't save someone who can't afford it.
Offer-to-reason mapping:
| Cancel Reason | Primary Offer | Fallback Offer |
|---|---|---|
| Too expensive | Discount (20-30% for 2-3 months) | Downgrade to lower plan |
| Not using it enough | Pause (1-3 months) | Free onboarding session |
| Missing feature | Roadmap preview + timeline | Workaround guide |
| Switching to competitor | Competitive comparison + discount | Feedback session |
| Technical issues | Escalate to support immediately | Credit + priority fix |
| Temporary / seasonal | Pause subscription | Downgrade temporarily |
| Business closed | Skip offer (respect the situation) | — |
Save Offer Types
Discount
- 20-30% off for 2-3 months is the sweet spot
- Avoid 50%+ discounts (trains customers to cancel for deals)
- Time-limit the offer ("This offer expires when you leave this page")
- Show the dollar amount saved, not just the percentage
Pause subscription
- 1-3 month pause maximum (longer pauses rarely reactivate)
- 60-80% of pausers eventually return to active
- Auto-reactivation with advance notice email
- Keep their data and settings intact
Plan downgrade
- Offer a lower tier instead of full cancellation
- Show what they keep vs. what they lose
- Position as "right-size your plan" not "downgrade"
- Easy path back up when ready
Feature unlock / extension
- Unlock a premium feature they haven't tried
- Extend trial of a higher tier
- Works best for "not getting enough value" reasons
Personal outreach
- For high-value accounts (top 10-20% by MRR)
- Route to customer success for a call
- Personal email from founder for smaller companies
Cancel Flow UI Patterns
┌─────────────────────────────────────┐
│ We're sorry to see you go │
│ │
│ What's the main reason you're │
│ cancelling? │
│ │
│ ○ Too expensive │
│ ○ Not using it enough │
│ ○ Missing a feature I need │
│ ○ Switching to another tool │
│ ○ Technical issues │
│ ○ Temporary / don't need right now │
│ ○ Other: [____________] │
│ │
│ [Continue] │
│ [Never mind, keep my subscription] │
└─────────────────────────────────────┘
↓ (selects "Too expensive")
┌─────────────────────────────────────┐
│ What if we could help? │
│ │
│ We'd love to keep you. Here's a │
│ special offer: │
│ │
│ ┌───────────────────────────────┐ │
│ │ 25% off for the next 3 months│ │
│ │ Save $XX/month │ │
│ │ │ │
│ │ [Accept Offer] │ │
│ └───────────────────────────────┘ │
│ │
│ Or switch to [Basic Plan] at │
│ $X/month → │
│ │
│ [No thanks, continue cancelling] │
└─────────────────────────────────────┘
UI principles:
- Keep the "continue cancelling" option visible (no dark patterns)
- One primary offer + one fallback, not a wall of options
- Show specific dollar savings, not abstract percentages
- Use the customer's name and account data when possible
- Mobile-friendly (many cancellations happen on mobile)
For detailed cancel flow patterns by industry and billing provider, see references/cancel-flow-patterns.md.
Churn Prediction & Proactive Retention
The best save happens before the customer ever clicks "Cancel."
Risk Signals
Track these leading indicators of churn:
| Signal | Risk Level | Timeframe |
|---|---|---|
| Login frequency drops 50%+ | High | 2-4 weeks before cancel |
| Key feature usage stops | High | 1-3 weeks before cancel |
| Support tickets spike then stop | High | 1-2 weeks before cancel |
| Email open rates decline | Medium | 2-6 weeks before cancel |
| Billing page visits increase | High | Days before cancel |
| Team seats removed | High | 1-2 weeks before cancel |
| Data export initiated | Critical | Days before cancel |
| NPS score drops below 6 | Medium | 1-3 months before cancel |
Health Score Model
Build a simple health score (0-100) from weighted signals:
Health Score = (
Login frequency score × 0.30 +
Feature usage score × 0.25 +
Support sentiment × 0.15 +
Billing health × 0.15 +
Engagement score × 0.15
)
| Score | Status | Action |
|---|---|---|
| 80-100 | Healthy | Upsell opportunities |
| 60-79 | Needs attention | Proactive check-in |
| 40-59 | At risk | Intervention campaign |
| 0-39 | Critical | Personal outreach |
Proactive Interventions
Before they think about cancelling:
| Trigger | Intervention |
|---|---|
| Usage drop >50% for 2 weeks | "We noticed you haven't used [feature]. Need help?" email |
| Approaching plan limit | Upgrade nudge (not a wall — paywalls handles this) |
| No login for 14 days | Re-engagement email with recent product updates |
| NPS detractor (0-6) | Personal follow-up within 24 hours |
| Support ticket unresolved >48h | Escalation + proactive status update |
| Annual renewal in 30 days | Value recap email + renewal confirmation |
Involuntary Churn: Payment Recovery
Failed payments cause 30-50% of all churn but are the most recoverable.
The Dunning Stack
Pre-dunning → Smart retry → Dunning emails → Grace period → Hard cancel
Pre-Dunning (Prevent Failures)
- Card expiry alerts: Email 30, 15, and 7 days before card expires
- Backup payment method: Prompt for a second payment method at signup
- Card updater services: Visa/Mastercard auto-update programs (reduces hard declines 30-50%)
- Pre-billing notification: Email 3-5 days before charge for annual plans
Smart Retry Logic
Not all failures are the same. Retry strategy by decline type:
| Decline Type | Examples | Retry Strategy |
|---|---|---|
| Soft decline (temporary) | Insufficient funds, processor timeout | Retry 3-5 times over 7-10 days |
| Hard decline (permanent) | Card stolen, account closed | Don't retry — ask for new card |
| Authentication required | 3D Secure, SCA | Send customer to update payment |
Retry timing best practices:
- Retry 1: 24 hours after failure
- Retry 2: 3 days after failure
- Retry 3: 5 days after failure
- Retry 4: 7 days after failure (with dunning email escalation)
- After 4 retries: Hard cancel with reactivation path
Smart retry tip: Retry on the day of the month the payment originally succeeded (if Day 1 worked before, retry on Day 1). Stripe Smart Retries handles this automatically.
Dunning Email Sequence
| Timing | Tone | Content | |
|---|---|---|---|
| 1 | Day 0 (failure) | Friendly alert | "Your payment didn't go through. Update your card." |
| 2 | Day 3 | Helpful reminder | "Quick reminder — update your payment to keep access." |
| 3 | Day 7 | Urgency | "Your account will be paused in 3 days. Update now." |
| 4 | Day 10 | Final warning | "Last chance to keep your account active." |
Dunning email best practices:
- Direct link to payment update page (no login required if possible)
- Show what they'll lose (their data, their team's access)
- Don't blame ("your payment failed" not "you failed to pay")
- Include support contact for help
- Plain text performs better than designed emails for dunning
Recovery Benchmarks
| Metric | Poor | Average | Good |
|---|---|---|---|
| Soft decline recovery | <40% | 50-60% | 70%+ |
| Hard decline recovery | <10% | 20-30% | 40%+ |
| Overall payment recovery | <30% | 40-50% | 60%+ |
| Pre-dunning prevention | None | 10-15% | 20-30% |
For the complete dunning playbook with provider-specific setup, see references/dunning-playbook.md.
Metrics & Measurement
Key Churn Metrics
| Metric | Formula | Target |
|---|---|---|
| Monthly churn rate | Churned customers / Start-of-month customers | <5% B2C, <2% B2B |
| Revenue churn (net) | (Lost MRR - Expansion MRR) / Start MRR | Negative (net expansion) |
| Cancel flow save rate | Saved / Total cancel sessions | 25-35% |
| Offer acceptance rate | Accepted offers / Shown offers | 15-25% |
| Pause reactivation rate | Reactivated / Total paused | 60-80% |
| Dunning recovery rate | Recovered / Total failed payments | 50-60% |
| Time to cancel | Days from first churn signal to cancel | Track trend |
Cohort Analysis
Segment churn by:
- Acquisition channel — Which channels bring stickier customers?
- Plan type — Which plans churn most?
- Tenure — When do most cancellations happen? (30, 60, 90 days?)
- Cancel reason — Which reasons are growing?
- Save offer type — Which offers work best for which segments?
Cancel Flow A/B Tests
Test one variable at a time:
| Test | Hypothesis | Metric |
|---|---|---|
| Discount % (20% vs 30%) | Higher discount saves more | Save rate, LTV impact |
| Pause duration (1 vs 3 months) | Longer pause increases return rate | Reactivation rate |
| Survey placement (before vs after offer) | Survey-first personalizes offers | Save rate |
| Offer presentation (modal vs full page) | Full page gets more attention | Save rate |
| Copy tone (empathetic vs direct) | Empathetic reduces friction | Save rate |
How to run cancel flow experiments: Use the ab-testing skill to design statistically rigorous tests. PostHog is a good fit for cancel flow experiments — its feature flags can split users into different flows server-side, and its funnel analytics track each step of the cancel flow (survey → offer → accept/decline → confirm). See the PostHog integration guide for setup.
Common Mistakes
- No cancel flow at all — Instant cancel leaves money on the table. Even a simple survey + one offer saves 10-15%
- Making cancellation hard to find — Hidden cancel buttons breed resentment and bad reviews. Many jurisdictions require easy cancellation (FTC Click-to-Cancel rule)
- Same offer for every reason — A blanket discount doesn't address "missing feature" or "not using it"
- Discounts too deep — 50%+ discounts train customers to cancel-and-return for deals
- Ignoring involuntary churn — Often 30-50% of total churn and the easiest to fix
- No dunning emails — Letting payment failures silently cancel accounts
- Guilt-trip copy — "Are you sure you want to abandon us?" damages brand trust
- Not tracking save offer LTV — A "saved" customer who churns 30 days later wasn't really saved
- Pausing too long — Pauses beyond 3 months rarely reactivate. Set limits.
- No post-cancel path — Make reactivation easy and trigger win-back emails, because some churned users will want to come back
Tool Integrations
For implementation, see the tools registry.
Retention Platforms
| Tool | Best For | Key Feature |
|---|---|---|
| Churnkey | Full cancel flow + dunning | AI-powered adaptive offers, 34% avg save rate |
| ProsperStack | Cancel flows with analytics | Advanced rules engine, Stripe/Chargebee integration |
| Raaft | Simple cancel flow builder | Easy setup, good for early-stage |
| Chargebee Retention | Chargebee customers | Native integration, was Brightback |
Billing Providers (Dunning)
| Provider | Smart Retries | Dunning Emails | Card Updater |
|---|---|---|---|
| Stripe | Built-in (Smart Retries) | Built-in | Automatic |
| Chargebee | Built-in | Built-in | Via gateway |
| Paddle | Built-in | Built-in | Managed |
| Recurly | Built-in | Built-in | Built-in |
| Braintree | Manual config | Manual | Via gateway |
Related CLI Tools
| Tool | Use For |
|---|---|
stripe |
Subscription management, dunning config, payment retries |
customer-io |
Dunning email sequences, retention campaigns |
posthog |
Cancel flow A/B tests via feature flags, funnel analytics |
mixpanel / ga4 |
Usage tracking, churn signal analysis |
segment |
Event routing for health scoring |
Related Skills
- emails: For win-back email sequences after cancellation
- paywalls: For in-app upgrade moments and trial expiration
- pricing: For plan structure and annual discount strategy
- onboarding: For activation to prevent early churn
- analytics: For setting up churn signal events
- ab-testing: For testing cancel flow variations with statistical rigor
当前镜像保留 5 个文件,共 48.3 KB。点击文件名可查看加搜服务器上的原始内容。
| 文件 | 大小 | 内容指纹 |
|---|---|---|
| SKILL.md | 18,420 B | 88fd25b77e44… |
| UPSTREAM_LICENSE.txt | 1,069 B | b70d71e24e40… |
| evals/evals.json | 6,662 B | 212ed9215b39… |
| references/cancel-flow-patterns.md | 10,650 B | d64b9282b956… |
| references/dunning-playbook.md | 12,688 B | 95afe21035cb… |
评价将按 Skill 与版本归档,帮助营销人了解真实任务中的使用体验。敬请期待。
来源与版本声明
本页面由加搜科技整理业务说明并托管安装文件。原始 Skill 来源渠道:GitHub; 原始项目名称:churn-prevention; 固定版本:7868cb9251fa; 许可证:MIT。技能包内保留完整出处和许可证说明。
各 Agent 能力说明参考对应官方文档。页面不提供外部跳转。
INSTALL
三种安装方式
用户流失挽回 Skill v1.0.0,ZIP 带 SHA256 校验
默认做法是把提示词复制给 AI Agent,让它自己下载并安装。提示词里已经写清要用完整 ZIP、装完报告目录、并先跑一个小任务验证。
METHOD 01 · 交给 AI 自己装
复制提示词
适合大多数情况。Agent 会下载 ZIP、解压、放到正确目录,并在缺少权限时告诉你需要手工做哪一步。
请帮我把「用户流失挽回 Skill」安装到我正在使用的 AI Agent。 1. 下载完整 Skill ZIP:https://www.vibemarketing.work/packages/skill-churn-prevention/1.0.0/skill-churn-prevention.zip 注意:网页 HTML 不能当作 Skill 文件安装,必须使用 ZIP 里的完整文件。 2. 解压后保留 SKILL.md 及全部配套文件,按你所用 Agent 的 Skill 目录规则安装。 3. 安装完成后告诉我实际安装目录。 4. 用一个只读小任务验证 Skill 已被识别。 5. 如果你没有联网、下载或写目录权限,请直接告诉我哪几步需要我手工完成。 参考:原始 SKILL.md https://www.vibemarketing.work/raw/skill-churn-prevention/SKILL.md;安装指南 https://www.vibemarketing.work/agent-install/skill-churn-prevention.md
METHOD 02 · 自己下载
下载完整 ZIP
包内含 SKILL.md 与全部配套文件,附 manifest.json 与 SHA256 校验值,可离线安装与版本冻结。
METHOD 03 · 手动放目录
手动安装
解压 ZIP 后,按所用 Agent 的目录规则放入:
- WorkBuddy
技能 → 添加技能 → 上传技能 → 选择本地技能包 - OpenClaw
openclaw skills install ./skill-churn-prevention --as churn_prevention_skill - Hermes Agent
mkdir -p ~/.hermes/skills && cp -R ./skill-churn-prevention ~/.hermes/skills/ - Codex
mkdir -p ~/.codex/skills && cp -R ./skill-churn-prevention ~/.codex/skills/ - Claude Code
mkdir -p ~/.claude/skills && cp -R ./skill-churn-prevention ~/.claude/skills/ - TRAE
在 Skills 设置中导入包含 SKILL.md 的 skill-churn-prevention 目录;项目级 Skill 可放入 .agents/skills/skill-churn-prevention - ZCode
mkdir -p ~/.zcode/skills && cp -R ./skill-churn-prevention ~/.zcode/skills/
HTML 业务页面不能直接当作 Skill 文件安装。AI 需要下载完整 ZIP 并保留配套文件。
BY AGENT
适配的 AI Agent
7 个 Agent 里,5 项能力决定了差异
同一个 Skill,换个 AI 做法就不一样。点进去能看到它在这 8 步里能直接跑通几步、哪几步得你自己补、装完先跑什么验证。
- WorkBuddy 用户流失挽回 Skill 中文办公、本地资料和企业协作
- OpenClaw 用户流失挽回 Skill 本地工作区、目录化 Skill、命令和批处理
- Hermes Agent 用户流失挽回 Skill 长任务、消息入口和阶段进度
- Codex 用户流失挽回 Skill 本地文件、数据、代码和正式交付物
- Claude Code 用户流失挽回 Skill 项目上下文、文件、终端和 MCP
- TRAE 用户流失挽回 Skill 营销工作与网站、落地页和程序化 SEO
- ZCode 用户流失挽回 Skill 长上下文、长任务、项目文件和远程跟进
FURTHER READING
用户流失挽回 Skill 相关的实操文章
别人做同类任务时踩过的坑和总结,动手前后都值得翻一下。
一人市场部的问题不是“事情多到做不完”,而是“没有第二个人帮你把关”。所以用 AI 的正确姿势,不是追求全自动,而是把重复执行交给 AI,把方向、事实核验和发布决策留给自己。下面这套最小可行工作流,覆
流量结构一变,后台最显眼的数字就是转化率往下掉。很多人的反应是改按钮颜色、改表单字段、再开一轮首屏测试。这些能测,但排在后面。转化率是「来的人里有多少做了你要的动作」,来的人换了,动作完成率一定会动。
推荐计划上线一个月,运营后台常会出现两种相反的尴尬:页面有人点,专属链接也发出去了,新客却没有完成注册或购买;另一种更早,老客户连分享按钮都懒得碰。团队往往把两种情况归到同一个原因——奖励不够大,于是
落地页文案怎么用AI写,先锁住唯一转化动作和流量入口已经承诺过的那句话,再让模型写首屏标题、副标题和 CTA。跳过这两项直接“写得更有转化感”,常见结果是广告说免费试用、页面改口讲品牌愿景。本文是连续
定价页已经把 Starter、Professional、Enterprise 排成三张卡,价格、功能和“最受欢迎”角标也都在,销售仍然反复收到同一个问题:我们该买哪一档?这时团队很容易删一档套餐、放大
品牌语气提示词的作用,是把"我们品牌的文案应该是这种感觉"这句模糊要求,翻译成 AI 能逐条对照执行的约束。本文给出一个四层模板:品牌事实、语气维度、改写示例、输出自检。你替换方括号里的变量后即可直接
搭配使用
应用商店优化 Skill、营销对比表设计 Skill、营销心理学应用 Skill、新用户激活与留存 Skill、出海本地化翻译 Skill、联盟营销 Skill
按这个 Skill 的产出能不能直接被下一个 Skill 用上来推荐,不是固定名单。多数情况下按顺序跑完一组,比单独用一个效果更好。
应用商店优化 Skill
应用商店优化把商店页链接转成六维 ASO 审计与整改清单。
营销对比表设计 Skill
把产品、方案或工作方式的差异整理成网页内可扫描、可核查、适合移动端阅读的对比表区块。
营销心理学应用 Skill
把客户的行为阻力映射到具体心理机制,输出可执行、可验证且符合商业伦理的营销改进建议。
新用户激活与留存 Skill
新用户激活与留存优化把注册后流失的行为数据,梳理成带漏斗节点和文案的首次体验方案,缩短用户达到价值的时间。
出海本地化翻译 Skill
把多语言翻译任务拆解成需求文档、术语表和质量审查清单,控制出海内容的本地化翻译质量。
联盟营销 Skill
把联盟伙伴招募思路整理成包含佣金模型、归因窗口、防作弊规则和推广物料的渠道方案。
- 01
应用商店优化 Skill
这个 Skill 产出的persona、keyword_map、copy,正好是它需要的输入,可以直接接着跑
- 02
营销对比表设计 Skill
这个 Skill 产出的keyword_map、copy、workflow,正好是它需要的输入,可以直接接着跑
- 03
营销心理学应用 Skill
这个 Skill 产出的persona、copy、sequence,正好是它需要的输入,可以直接接着跑
- 04
新用户激活与留存 Skill
这个 Skill 产出的copy、tracking_plan、workflow,正好是它需要的输入,可以直接接着跑
- 05
出海本地化翻译 Skill
这个 Skill 产出的persona、keyword_map、copy,正好是它需要的输入,可以直接接着跑
- 06
联盟营销 Skill
这个 Skill 产出的persona、tracking_plan,正好是它需要的输入,可以直接接着跑