skills/churn-post-mortem/SKILL.md
Structures a post-churn analysis to identify root causes, missed signals, intervention gaps, and systemic lessons. Produces a documented analysis that prevents the same failure pattern from repeating across the portfolio. Use when asked to analyse a churn, conduct a loss review, identify why an account left, build a post-mortem, or when a customer has churned and the CSM needs to understand what happened and what the team should learn from it. Also triggers for questions about churn analysis, loss review, retention failure investigation, or learning from customer departures.
npx skillsauth add stephenrogan/csm-skills churn-post-mortemInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Structures the analysis of why an account churned. The post-mortem is not blame assignment -- it is pattern recognition. Every churn teaches the team something. The post-mortem captures that lesson so it does not have to be learned again on the next account.
Provide:
One paragraph: who churned, how much ARR, how long they were a customer, and the headline reason.
Most churns have multiple contributing factors. Identify the primary root cause and contributing factors:
| Category | Root Cause Question | Assessment | |----------|-------------------|-----------| | Product fit | Did the product solve their core problem? Did it stop solving it? | [Specific assessment with evidence] | | Value realisation | Did they see measurable ROI? Could they articulate the value? | [Specific assessment] | | Relationship | Was the relationship strong? Were we multi-threaded? Did we have executive coverage? | [Specific assessment] | | Service | Did we deliver on our commitments? Was support responsive? Were escalations resolved? | [Specific assessment] | | Competitive | Did a competitor win the business? What did they offer that we did not? | [Specific assessment] | | Commercial | Was pricing the issue? Did we fail to demonstrate value relative to cost? | [Specific assessment] | | Customer-side | Did their priorities change? Budget cut? Reorg? Champion departure? | [Specific assessment] |
Primary root cause: [The single most important factor] Contributing factors: [Secondary factors that amplified the primary cause]
When did the warning signs appear, and were they detected?
| Date | Signal | Detected? | Action Taken | Outcome | |------|--------|----------|-------------|---------| | [date] | [signal -- usage decline, sentiment shift, competitive mention, etc.] | [Yes/No] | [What was done, or "none"] | [Result] |
Key question: What was the earliest signal that this account was at risk, and how long before churn did it appear?
What was tried to save the account:
| Intervention | When | What Happened | Why It Worked / Failed | |-------------|------|-------------|----------------------| | [action] | [date -- how many days before churn] | [outcome] | [honest assessment of why] |
Key question: Were interventions early enough? Most save plays fail not because the play was wrong but because it started too late.
| Classification | Definition | This Account | |---------------|-----------|-------------| | Preventable | We had the signals, the relationship, and the tools to save this account | [Was it preventable? Why or why not?] | | Partially preventable | Some factors were within our control but the primary driver was not | [Assessment] | | Non-preventable | External factors (acquisition, shutdown, strategic pivot) that no intervention could have changed | [Assessment] |
The most important section. What does this churn teach us about our broader CS operation?
| Lesson | Evidence from This Churn | Portfolio Implication | |--------|------------------------|---------------------| | [lesson 1] | [what happened here] | [how many other accounts share this vulnerability] | | [lesson 2] | [what happened here] | [what needs to change in our process, playbook, or coverage model] |
Examples of systemic lessons:
## Churn Post-Mortem: [Account Name]
**ARR Lost:** EUR [amount] | **Tenure:** [months/years] | **Churn Date:** [date]
**Prepared by:** [CSM name] | **Date:** [date]
### Summary
[One paragraph]
### Root Cause
Primary: [root cause with evidence]
Contributing: [secondary factors]
### Signal Timeline
[Completed table]
### Interventions
[Completed table with assessment]
### Preventability
[Classification with rationale]
### Systemic Lessons
[Lessons with portfolio implications]
### Recommendations
1. [Specific change to prevent this pattern -- process, playbook, coverage, or tooling]
2. [Specific change]
development
Structures the CSM's week based on their portfolio status, upcoming events, overdue items, and strategic priorities. Produces a time-blocked plan that balances reactive demands with proactive account management. Use when asked to plan a week, structure daily priorities, build a weekly schedule, allocate time across accounts, manage a busy week, or when a CSM feels overwhelmed and needs to determine where to focus. Also triggers for questions about time management, weekly planning, account prioritisation for the week, daily priority setting, or how to balance competing demands across a portfolio.
development
Constructs a compelling value narrative for a customer account by connecting product usage to business outcomes in the customer's language. Produces different versions for different audiences -- the champion, the CFO, the board. Use when asked to build a value story, articulate ROI, create a business case for the customer, prepare value evidence for a renewal or QBR, or when a CSM needs to translate usage metrics into business impact the customer will recognise. Also triggers for questions about value articulation, ROI storytelling, customer business case, value evidence, or how to prove the product is worth the investment.
data-ai
Takes raw usage data -- even a spreadsheet export or pasted metrics -- and identifies patterns, risks, and opportunities. Translates product analytics into account intelligence a CSM can act on. Use when asked to interpret usage data, analyse product metrics, make sense of a usage report, identify trends in customer behaviour, flag usage-based risks, or when a CSM has data but does not know what it means for the account. Also triggers for questions about usage analysis, product analytics interpretation, behavioural pattern detection, usage-based risk identification, or turning raw metrics into actionable insight.
development
Builds a structured 30-60-90 day plan for a CSM taking over a new book of accounts or joining a new team. Prioritises accounts by risk and value, identifies immediate relationship actions, and structures the ramp to full productivity. Use when asked to plan a book transition, create a new CSM onboarding plan, structure a territory takeover, build a 30-60-90 plan for a new role, or when a CSM is inheriting accounts and needs a systematic approach to getting up to speed. Also triggers for questions about account transitions, new book ramp-up, CSM onboarding to a portfolio, territory planning, or how to take over accounts from another CSM.