Closed-won analysis is the practice of mining 2-3 years of your won deals to find the buying signals that preceded them. For each customer you look back 12-24 months at hiring, executive, and funding activity, find the patterns that repeat across wins, and turn them into a repeatable targeting model.
Ask most sales leaders why they win and you get a story: good champion, right timing, strong product fit. Ask them to prove it with data and the room goes quiet. Closed-won analysis replaces the story with a pattern, one you can point new pipeline at.
This is the first stage of the GTM intelligence flywheel. Before you can find companies that look like your best customers, you have to know what your best customers looked like before they bought.
What is closed-won analysis?
It is a backward look at your won deals to find the external signals that showed up before the deal existed. Not the CRM fields you already track (source, stage, close date), but what was happening inside the account: who they hired, who they promoted, what they filed, how their team grew. Every buyer leaves a trail before they buy. Closed-won analysis reads it.
How do you run a closed-won analysis?
- Pull every closed-won deal from the last 2-3 years. You want enough volume to see a pattern, not a coincidence.
- For each account, look back 12-24 months before the close date at external activity: hiring patterns, executive hires, tech stack shifts, org restructuring, and funding events.
- Find what repeats across wins. If 8 of your last 10 enterprise deals hired a new VP of Sales in the year before they bought, that is a pattern, not a fluke.
- Run the same pass on closed-lost deals. What was present in the wins and missing in the losses is often more telling than the wins alone.
- Segment everything by ICP, vertical, company size, and deal type. A pattern that predicts a logistics win will not predict a cybersecurity one.
What signals should you look for?
You are not looking for a single trigger. You are looking for combinations, because one signal is coincidence and stacked signals are a pattern. These are the categories worth pulling for every won deal:
| Analysis | The question | What it tells you |
|---|---|---|
| Win signals | Which signals appeared before deals closed? | The core pattern to target on net-new accounts |
| Speed signals | Which appeared before fast closes vs slow ones? | Which accounts to prioritize this quarter |
| Size signals | Which correlated with larger deal size? | Where to point your senior reps |
| Champion detection | Did a specific hire precede fast closes? | That hire may be the real buyer to watch for |
| Negative signals | Layoffs, hiring freezes, leadership gaps | The do-not-call list that saves rep time |
“Most companies have never seen their own win data analyzed against external signals.”
Sentrion, Pillar 1: LEARN
Who owns it, and who runs it?
The mandate belongs to the VP of Sales or CRO. They own the question "why do we win," and the answer changes how the team targets, prioritizes, and staffs deals. RevOps executes: pulling the export, doing the lookback, and segmenting the results. The leader sets the question, the operator produces the pattern, and the whole team sells against it.
Can you run closed-won analysis manually?
Yes, for a first pass. Export your deals, pull public history on each account by hand, and eyeball the patterns. It works up to a few dozen deals. Past that, reconciling 12-24 months of hiring, executive, and filing history per account by hand stops scaling, and the lookback data gets thin the further back you go.
| Manual | Automated | |
|---|---|---|
| History depth | Whatever you can find today | 6 years of structured signal history |
| Coverage | A few dozen deals before it breaks | Your full closed-won book |
| Refresh | One-time snapshot | Re-scored as new outcomes land |
| Sources | Manual searches, one account at a time | 230+ job boards, exec moves, SEC filings cross-referenced |
Sentrion runs this analysis against 6 years of structured signal data, then turns the pattern it finds into a live scoring model, which is the FIND stage of the flywheel. The manual version proves the concept. The automated version keeps it running.
Frequently asked questions
What is closed-won analysis?
It is the practice of mining your won deals to find the external buying signals that preceded them. For each customer you look back 12-24 months at hiring, executive, and funding activity, find the patterns that repeat across wins, and use them to target new accounts.
How many closed-won deals do you need?
Enough to tell a pattern from a coincidence. A few dozen deals within one ICP is usually enough to see repeating signals; below roughly 10 you are reading noise. Segment by vertical and size so you are comparing like with like.
How far back should you look for each deal?
12-24 months before the close date. Buying signals like a new executive hire or a funding round typically appear a year or more before a deal closes, well before web-intent data would ever flag the account.
