Score every account on readiness to buy — before your competition does.
Without a data-driven view of which accounts are ready to buy, effort gets spread thin across low-probability targets while high-intent customers go uncontacted. Reps waste time on dead leads and miss the moments when the right customer is primed to act.
The result: lower conversion rates, longer sales cycles, and a pipeline that looks busy but produces less than it should.
Transaction recency, frequency & value · Product affinity patterns · Engagement momentum · Firmographic & firmographic change signals · Seasonal & lifecycle triggers · Cross-category purchase history
We ingest and harmonise your transaction history, CRM engagement data, firmographic attributes, and any third-party enrichment — building a reliable feature set that reflects real buying behaviour.
We construct features that capture buying intent: recency and frequency patterns, product affinity decay, engagement momentum, and cross-category co-purchase signals specific to your catalogue.
We train gradient-boosted and ensemble models calibrated to your sales cycle length and deal dynamics, validating against historical won/lost outcomes to ensure real-world accuracy.
Daily or real-time propensity scores are surfaced in your CRM, Power BI dashboard, or data warehouse — with explainability so reps understand why an account is flagged, not just that it is.
A Fortune 500 manufacturer deployed propensity models across 11 million customers and 1.6 million SKUs — delivering daily buying signals to 7,000 sales leaders worldwide.
Read the case study →Opportunity lifecycle analysis — informed by propensity and conversion signals — drove a measurable 40% improvement in win rates after sales teams changed their practices based on the data.
We can run a no-obligation signal assessment against your existing data to show you what propensity modelling could surface.
Request a signal assessment