Lead Propensity Model
Scores each lead's conversion likelihood across four quarter horizons (CQ/NQ/NQ+1/NQ+2) using engagement patterns and journey sequences.
Akash Sharma
Primary Owner
4
Quarter Horizons Scored
Daily
Scoring Frequency
Overview
XGBoost Classifier trained on lead attributes, activity/engagement patterns, journey sequences, funnel stage timestamps, and derived velocity metrics. Multi-quarter scoring: separate probability per quarter horizon. Feature selection via Feature Importance + Chi-squared + ANOVA F-test. Heuristic fallback for low-data customers using segment conversion rates.
The problem
Sales teams had large lead lists with no per-lead conversion likelihood ranking. Pipeline projections at the lead level used flat segment-level rates rather than individual characteristics.
Results
Replaced flat conversion rates with ML-scored per-lead conversion likelihoods, feeding the Sales Pipeline Forecasting with more accurate record-level contributions.
Related Propensity & Scoring Projects
Account Propensity Model
Dual propensity scoring system assigning Base Fit (long-term ICP fit) and 3-Month (short-term conversion likelihood) scores to every account.
Opportunity Propensity Model
Predicts each opportunity's close likelihood per quarter, replacing static CRM probability fields with dynamically scored multi-quarter estimates.
Multi-Horizon Account Propensity
Monthly-granularity refactor of the Account Propensity model, enabling month-level account prioritization alongside quarterly scores.