Find what your wins, losses, and churn share.
“Why do we win some deals and lose others, and which active accounts look like the ones that churned?”
Reads closed-won, closed-lost, and churned accounts, then hands back a ranked list of lookalike accounts to work.
What this skill does
This skill reads your closed-won, closed-lost, and churned accounts and finds the repeating patterns inside them. It runs in three modes. WON tells you what your winning deals have in common and generates a ranked list of active accounts that look like them. LOST tells you where, how, and to whom you lose, with the objections rolled up. CHURN groups your lost customers into named themes and then scans your active book for accounts that match those themes before they leave.
Inputs
- Works today with: exports of your closed-won, closed-lost, and churned accounts, with fields like size, industry, loss reason, and competitor. Paste or upload.
- More powerful connected to a CRM: the three cohorts and their fields, live.
- More powerful connected to a product-analytics tool: engagement decay, which powers the predictive-churn scan.
- Sharper with a conversation-intelligence tool (objections, competitive mentions) and a support tool (churn-ticket patterns).
How it works
- 1WON mode
Cohort: trailing 6 months of closed-won. Extract buying-committee shape, deal velocity, primary entry point, dominant signals, tech-stack overlap. Score active accounts against the winning pattern and rank the closest matches.
- 2LOST mode
Cohort: trailing 6 months of closed-lost. Competitive head-to-head by stage and deal size. Objection theme rollup from transcripts. Stage-of-loss distribution.
- 3CHURN mode
Cohort: trailing 12 months of churned customers. Group churns into named causes (consolidation, layoff, vendor switch, product gap, champion left, acquisition). Scan active accounts for matches to each theme and surface them with a confidence tag, ranked by risk.
Output format
PATTERN ANALYSIS · Q2 Lookback
WON (n=14):
Channel: Product 57% / Inbound 29% / Outbound 14%
Dominant signal: sales-team hiring (78% of wins)
Top lookalikes: Account A 91%, Account B 88%, Account C 87%
LOST (n=21):
Stage-of-loss: Solution Validation 52%
Top reason: "no compelling differentiation vs incumbent" (n=9)
Lost to Competitor 1: 5 (at Proposal, "team already trained")
CHURN (n=8, 12 months):
Consolidation / layoff (n=3), acquisition (n=2), feature gap (n=2)
PREDICTIVE WATCH:
Account F, consolidation pattern (73%): team 22 to 14, activity -47%
Account G, champion-left pattern (68%): champion changed jobs 21d ago
Tips
- Pattern extraction is statistically meaningful. The skill requires at least 5 occurrences before it calls something a pattern. Below that it returns "insufficient data, expand the window."
- Lookalike candidates are similarity-scored, with the named dimensions behind the score.
- Predictive churn calls are confidence-tagged with the evidence behind them. A low-confidence match is labeled low, not dropped.
Start any analysis without connecting a thing.
Tells you exactly what to hand over, takes it in whatever shape you have, and feeds it to the analyst skill. Connectors optional.
Get a ranked slate of customers to interview.
Scores every paying customer against your ICP and returns a prioritized list with a verdict and reason each.