Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/thatrebeccarae/claude-marketingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/rules/thatrebeccarae/claude-marketing/retention-churn-prevention)<a href="https://agentmods.dev/rules/thatrebeccarae/claude-marketing/retention-churn-prevention"><img src="https://agentmods.dev/badge/rules/thatrebeccarae/claude-marketing/retention-churn-prevention/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/rules/thatrebeccarae/claude-marketing/retention-churn-prevention"><img src="https://agentmods.dev/badge/rules/thatrebeccarae/claude-marketing/retention-churn-prevention.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.01001 |
| Opus 5 | $0.00020 | $0.00500 |
| Sonnet 5 | $0.00008 | $0.00200 |
| Haiku 4.5 | $0.00004 | $0.00100 |
Grade A, and why
retention-churn-prevention scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Retention & Churn Prevention
Analyze churn, predict at-risk customers, and design retention strategies.
Churn Analysis Framework
Churn Types
| Type | Definition | Signal |
|---|---|---|
| Voluntary | Customer actively cancels | Cancellation request, downgrade |
| Involuntary | Payment failure, card expiry | Failed charge, dunning |
| Silent | Stops using but does not cancel | Usage decline, no logins |
Churn Rate Calculation
Monthly churn rate = Customers lost / Customers at start of month
Annual churn rate = 1 - (1 - monthly rate)^12
Net revenue retention = (Start MRR + Expansion - Contraction - Churn) / Start MRR
Benchmarks
| Metric | Excellent | Good | Concerning |
|---|---|---|---|
| Monthly churn (SaaS) | <1% | 1-2% | >3% |
| Annual churn (SaaS) | <5% | 5-10% | >15% |
| Net revenue retention | >120% | 100-120% | <100% |
Customer Health Scoring
| Signal | Weight | Healthy | At Risk |
|---|---|---|---|
| Product usage | 25% | Daily/weekly | Monthly or less |
| Feature adoption | 20% | 5+ features | 1-2 features |
| Support sentiment | 15% | Positive/none | Negative |
| Billing health | 15% | On time, expanding | Late, downgrading |
| Engagement | 15% | Opens, clicks | Ignores |
| NPS/CSAT | 10% | Promoter (9-10) | Detractor (0-6) |
Early Warning Signals
| Timeframe | Signal | Action |
|---|---|---|
| 7 days | Login frequency drops 50%+ | In-app nudge, value reminder |
| 14 days | Key feature usage stops | CS outreach, usage tips |
| 30 days | No logins for 2+ weeks | Personal CS email, re-engagement |
| 60 days | NPS detractor, unresolved ticket | Executive escalation, save offer |
| 90 days | Cancellation signals | Retention call, custom offer |
Win-Back Campaigns
Timing
| Post-Churn Period | Response Rate | Approach |
|---|---|---|
| 0-7 days | 15-25% | Immediate save, address exit reason |
| 7-30 days | 8-15% | New feature announcement, incentive |
| 30-90 days | 3-8% | Major update, significant discount |
| 90+ days | <3% | Annual check-in |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 109 lines · 41 tokens per session scan A 76a8322e63f6
retention-churn-prevention is a cursor rule published in the GitHub repository thatrebeccarae/claude-marketing (136 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 1,001 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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