Five steps from your CRM export to a buying signal model unique to your market, product, and sales motion.
We start from your CRM: every deal you closed over the last 2-3 years.
For each company that became a customer, we replay Sentrion's signal history: funding events, hiring patterns, tech stack shifts, and the specific initiatives they reveal, like a product launch or a new sales framework rolling out.
Which signal combinations showed up again and again before your deals closed?
The same signal pair, three different wins.
Lost deals reveal anti-patterns: what was missing in the deals that never closed.
The second signal never came. That gap is the anti-pattern.
A custom model calibrated to your actual outcomes, not a generic fit score. This model powers everything downstream.
Wins and losses, side by side. The goal is not a report about the past, it is a model that predicts your next deal.
Which signal combinations appeared before your deals closed? The trails that complete are the ones worth chasing.
What was missing in the deals that didn't close? The signal that never arrived is as predictive as the ones that did.
Which patterns preceded fast closes versus slow ones?
Which combinations correlated with larger deal sizes?
Did a specific hire, like a new CRO or VP Sales, appear before fast closes? That hire might be the real buyer.
Not just which signals, but how fast they accumulate. Acceleration matters.
Layoffs, hiring freezes, leadership gaps. Do-not-call signals that save your reps time.
The analysis answers one question: which signals preceded your sales? Those become custom signals, defined precisely enough for Sentrion to track them across your whole market, so every rep watches for the same patterns your wins already proved.
Without closed-won analysis, account scoring is generic. With it, every score is calibrated to what converts for you. And the model gets smarter with every deal outcome: wins confirm patterns, losses reveal what it missed.
Bring your closed-won deals. Sentrion's framework extracts the signals that preceded them and turns them into a model your whole team tracks, with proprietary signal history deepening every lookback.
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