Turn churn themes into an early-warning system.
“What do the customers who left have in common, and who looks like them right now?”
Reads churned and downgraded accounts, extracts the themes, and flags active accounts that resemble recent churners.
What this skill does
Reads your churned and downgraded accounts and pulls out why they left: the themes, the shared conditions, the moments it started slipping. It turns those causes into an early-warning checklist, then runs that checklist across your active book and flags the customers who look like the ones that just walked. The point is not a churn number for the board. It is a short list of current accounts to save while there is still time.
Inputs
- Works today with: a list of your churned and downgraded accounts, with segment or size, contract value, tenure, churn or downgrade date, the reason (if captured), and any renewal notes. And, if you have it, a list of your active accounts to score against. Paste it or upload a CSV.
- More powerful connected to a CRM: it reads churn, downgrades, renewal dates, and notes automatically, across the whole book.
- Sharper with a product-analytics tool: adds usage decline, the single strongest churn tell, so a quiet account gets caught before the renewal call.
- Sharper with a support or ticketing tool: adds ticket volume and sentiment, so a frustrated account surfaces early.
How it works
- 1Churn theme extraction
Group every churned and downgraded account across reason, segment, tenure, value, and (if connected) usage. Report only the themes that clear MIN_SAMPLE. For each theme, show the share of churn, the revenue behind it, and the average tenure at churn, so a high-count theme and a high-dollar theme are both visible. Treat a downgrade as churn's early cousin, not a separate story: the same causes usually run underneath.
- 2Cause vs symptom
Separate what you can see from what actually drove it. A dead login count is a symptom. The cause is usually one of a few things: the champion left, the value was never realized, onboarding stalled, a merger or budget cut hit, or a competitor displaced you. Name the cause, because the checklist has to catch the cause early, not the symptom at renewal.
- 3Early-warning checklist
Turn the top causes into a short list of observable signals that appear before churn, not at it: usage down X percent over N weeks, champion gone quiet or departed, no executive contact in the last quarter, support tickets spiking, a renewal inside 90 days with no engaged buyer. Each signal is something you can check on a live account today.
- 4Predictive read (active book)
Run the checklist across your active accounts and score each one by how many warning signals it hits. Return a ranked watchlist, highest risk first, with the exact signals each account trips and how closely it resembles a specific churn theme. This is the payoff: the accounts to save this quarter, named, before the renewal call.
Output format
CHURN ANALYSIS · 23 churned + downgraded, trailing 4 quarters
Churn themes
Theme Share Revenue Avg tenure
Champion left, no backup 35% $180K 14 months
Never reached first value 26% $130K 7 months
Price at renewal 22% $95K 22 months
Merger / budget cut 17% $70K 19 months
Early-warning checklist (the signals that came first)
[ ] Usage down 40%+ over trailing 8 weeks
[ ] Champion departed or dark 60+ days
[ ] No exec contact in the last quarter
[ ] Renewal inside 90 days, no engaged buyer
[ ] Support tickets spiking
Active accounts that look like recent churners (highest risk first)
Account Signals tripped Resembles
Kestrel Co usage -52%, champion dark "champion left"
Alderman onboarding stalled, low usage "never reached value"
Pentworth renewal in 60d, no buyer "price at renewal"
Next move:
1. Kestrel. Find a second champion now. The first one is gone.
2. Alderman. Restart onboarding before renewal. It never got to value.
3. Add a usage feed. It is your single strongest early tell and it is missing.
Tips
- No theme reported below MIN_SAMPLE. One angry cancellation is not a pattern.
- Usage-decline claims show the trend, not a single reading. A quiet week is not churn.
- Every at-risk account lists the specific signals it trips, never just a risk score.
- Cause is grounded in a field, a note, or a usage trend, never assumed from the logo.
Extract the repeatable reason you win.
Reads your won deals, finds the signals, personas, and motions that repeat, and ranks active lookalikes to work.
Categorize your losses and name the fix.
Sorts lost deals into no-decision, price, competitor, timing, or fit, pulls competitive intel, and splits preventable from structural.