retention
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 iden
Install
npx skills add https://github.com/cbrock84/headcount/tree/main/plugins/revenue/skills/retention
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install cbrock84-headcount@llmmart
git clone https://github.com/cbrock84/headcount.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole cbrock84/headcount collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
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.
Sources
references/sources.md in this skill lists the outside authorities that settle the questions
here — what each one is authoritative for, and what you may do with it. Check them before
answering on anything they cover, and cite what you used. Most are free to read and not free
to reproduce; the use note on each is binding.
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.
Files (headcount)
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references
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sources.md 1.6 KB
# Sources — `revenue:retention` <!-- Generated by scripts/build-sources.py from sources/*.toml. Do not edit. --> Check these before answering on anything they cover, and cite what you used. The use note on each one is binding: most of what a professional cites is free to read and not free to reproduce. ## 15 U.S.C. 8403 — Restore Online Shoppers' Confidence Act US Congress, via the Office of the Law Revision Counsel · US · public domain (US government) — quote freely <https://uscode.house.gov/view.xhtml?req=granuleid:USC-prelim-title15-section8403&num=0&edition=prelim> **Authoritative for:** Whether an online auto-renewal offer is lawful — clear disclosure of material terms before billing, express informed consent, and a simple cancellation mechanism. This area has seen rules issued and struck down, so cite the statute rather than a rule summary. ## California Automatic Renewal Law, Business and Professions Code 17600-17606 California Legislative Counsel · US-CA · public domain — quote freely <https://leginfo.legislature.ca.gov/faces/codes_displayText.xhtml?division=7.&chapter=1.&part=3.&lawCode=BPC&article=9.> **Authoritative for:** The concrete cancellation obligations a subscription business actually has to meet, because California's requirements are stricter than the federal floor and apply to any California customer — which in practice makes them the binding ones. --- Sources are maintained in `sources/` upstream, not here. If one is wrong, out of date, or missing, fix it there — this file is regenerated and an edit to it is lost.
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SKILL.md 3 KB
--- 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. ## Sources `references/sources.md` in this skill lists the outside authorities that settle the questions here — what each one is authoritative for, and what you may do with it. Check them before answering on anything they cover, and cite what you used. Most are free to read and not free to reproduce; the use note on each is binding. ## 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.
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