Pipeline IntelligenceADA Asia2022 – 2024Production

Demand Generation Potential Model

Estimates pipeline contribution from opportunities not yet visible in the CRM (the unseen quarter contribution).

20–61%

Historical Contribution Range

~40%

Average Contribution

The Problem

Record-level propensity models can only score opportunities already in the system. Historically, 20–61% of quarter-end bookings came from deals created and closed within the same quarter, not captured by existing scoring.

What Was Built

Built two modes: (1) Heuristic: rolling average of historical same-quarter origination rates per day applied to current day forward. (2) ML: XGBoost Regressor trained on calendar features, cumulative quarter actuals, marketing spend, and macroeconomic controls to predict remaining unseen contribution.

Business Impact

Prevented systematic under-projection of EOQ totals by accounting for 20–61% of quarter-end pipeline that originates from same-quarter deal creation.

Tech Stack

PythonXGBoostscikit-learnBigQuery

Domain Tags

Demand GenerationPipeline ForecastingHeuristic FallbackRevenue Intelligence

Details

Role
Primary Owner
Status
Production
Tier
Tier 1
Period
2022 – 2024
Employment
ADA Asia