retention
GitHub诊断并降低用户流失，区分自愿与非自愿流失。涵盖取消流程优化、挽留策略、风险账户检测及流失原因分析，适用于流失率上升或异常场景。
Trigger Scenarios
Install
npx skills add cbrock84/headcount --skill retention -g -y
SKILL.md
Frontmatter
{
"name": "retention",
"description": "Diagnoses and reduces churn — cancellation flows, save offers, failed-payment recovery, at-risk detection, and the product and service causes underneath. Use this when churn is rising or unexplained, to design a cancellation or win-back flow, to recover involuntary churn, to identify at-risk accounts before they leave, or to decide whether a retention problem is a product problem."
}
Retention
Separate the two churns first
They have nothing in common but the outcome, and conflating them wastes effort:
- Involuntary — payment failed. Often a large share of total churn, entirely mechanical, and the cheapest thing to fix in the whole business.
- Voluntary — they chose to leave.
Fix involuntary first. Card retries on a sensible schedule, dunning emails that reach a human, pre-expiry notification, and a grace period that does not immediately cut off access. This is recoverable revenue sitting untouched in most companies.
Diagnosing voluntary churn
Ask when the decision was actually made. It is almost never at cancellation — it is weeks earlier, at a failed expectation, an unresolved support issue, or a champion leaving.
Segment churn by tenure, plan, acquisition channel, and activation status. Concentrations tell you the cause:
- Early churn — activation problem, not retention. Fix onboarding.
- Churn at renewal — value not visible enough to justify the line item.
- Churn after a specific event — find the event: a price change, an outage, a redesign, a champion departure.
- Churn concentrated in one channel — an acquisition problem. You are buying the wrong customers, and no retention work fixes that.
Cancellation flow
Make canceling straightforward. Obstruction generates chargebacks, public complaints, and in a growing number of jurisdictions, regulatory exposure.
Do ask why, with specific options plus free text — this is the highest-quality product feedback you will ever receive, from people with no reason to be polite.
Offer a save only where it addresses the stated reason. A discount offered to someone leaving because a feature is missing confirms you were not listening. Pause is often the better offer and is rarely available.
At-risk detection
Build a simple signal from declining usage, a support escalation, a champion going quiet, or a seat count dropping. Then act on it while intervention is still possible — a health score nobody works is a dashboard, not a program.
Never
- Count a saved cancellation as retained without checking whether they stayed a quarter later.
- Treat retention as a service problem when the data says it is a product or acquisition problem.
- Make cancellation require a phone call.
Version History
- d58a7ee Current 2026-09-02 21:10
