retention-strategy

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Chinese

Strategies: Retention

策略：客户留存

Guides customer retention and churn prevention. Acquiring new customers costs 5–25× more than retaining; 5% retention improvement can increase profitability 25–95%. Use this skill when reducing churn, building retention programs, or identifying at-risk customers.

When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.

指导客户留存与流失预防工作。获取新客户的成本是留存老客户的5–25倍；留存率提升5%可使利润增长25–95%。当你需要降低流失率、搭建留存体系，或者识别高风险客户时可使用本技能。

调用规则：首次使用时，如果适用，可以先用1-2句话介绍本技能覆盖的内容及其价值，再提供核心输出。后续使用或者用户要求跳过介绍时，直接输出核心内容即可。

Initial Assessment

初步评估

Check for product marketing context first: If

.claude/product-marketing-context.md

.cursor/product-marketing-context.md

exists, read Sections 4 (Audience), 9 (Documentation).

Identify:

Churn type: Voluntary (active cancel) vs involuntary (payment failure)
Signals: Login frequency, feature usage, support tickets
Stage: Onboarding, expansion, renewal

优先确认产品营销上下文：如果存在

.claude/product-marketing-context.md

或

.cursor/product-marketing-context.md

文件，读取第4节（受众）、第9节（文档）内容。

需要识别以下信息：

流失类型：主动流失（主动取消）vs被动流失（支付失败）
信号：登录频率、功能使用情况、支持工单
所处阶段：新手引导、增值扩张、续费

Churn Types

流失类型

Type	Share	Causes
Voluntary	60–80%	Pricing, missing features, poor onboarding, relationship
Involuntary	20–40%	Payment failures, expired cards, billing

Predictability: Most churn is predictable 30–90 days before cancellation via behavioral signals.

类型	占比	原因
主动流失	60–80%	定价、功能缺失、新手引导效果差、客户关系问题
被动流失	20–40%	支付失败、卡片过期、账单问题

可预测性：大多数流失可在用户取消前30-90天通过行为信号预测。

Proactive vs Reactive

主动干预 vs 被动应对

Approach	Conversion
Reactive (after cancel)	15–20%
Proactive (before decision)	60–80%

Move from lagging indicator to early warning systems.

方案	挽回转化率
被动应对（用户取消后）	15–20%
主动干预（用户做出取消决策前）	60–80%

从滞后指标监控转向早期预警体系建设。

Retention Strategies

留存策略

Strategy	Use
Health scoring	Behavioral + transactional + relationship signals
Loyalty programs	5–15 percentage point retention lift
Segmentation	Predictive modeling for at-risk
Onboarding	Prevent low value realization early
Dunning	Retry logic; pre-expiry card updates for involuntary

策略	用途
健康度评分	整合行为+交易+客户关系信号
忠诚度计划	可提升5-15个百分点的留存率
用户分群	针对高风险用户搭建预测模型
新手引导	尽早避免用户价值感知不足的问题
催缴流程	重试逻辑；针对被动流失场景在卡片到期前更新支付信息

User Value & Feedback

用户价值与反馈

Dimension	Use
Product value	Registration; feature usage; payment
Marketing value	Testimonials; customer stories; webinar guests; feedback, bug reports, feature requests
Feedback analysis	Email, community, reviews—AI-assisted analysis; prioritize by impact; route to product vs ops

Avoid: Treating users only as MAU/registration denominators. See creator-program for creator ecosystem.

维度	用途
产品价值	注册、功能使用、支付相关数据
营销价值	推荐语、客户案例、webinar嘉宾、反馈、bug报告、功能需求
反馈分析	邮件、社区、评论——AI辅助分析；按影响优先级排序；分配给产品或运营团队处理

注意事项：不要仅将用户视为MAU/注册量的统计分母。创作者生态相关内容可参考 creator-program 技能。

Lifecycle Integration

生命周期打通

Retention occurs after conversion; ongoing investment in customer success, not isolated campaigns. Map touchpoints: onboarding → adoption → expansion → renewal.

留存发生在转化之后；需要持续投入客户成功资源，而非孤立的营销活动。梳理全触点：新手引导 → 产品采纳 → 增值扩张 → 续费。