31 / Banking & Finance
Pine Labs Merchant Discovery + Retention
We built a platform that continuously measures how healthy each Pine Labs merchant relationship is and flags the ones about to churn early, using Pine-specific signals a generic churn model would miss.
- Client
- Pine Labs Ltd
- Stack & approach
- FinTechMerchant RetentionChurn PredictionField AppSignal Explorer
The problem
Pine Labs merchant churn was managed through manual downloads and spreadsheet analysis, so at-risk merchants were identified late. Generic churn models miss Pine-specific signals across POS, QR, EMI, BNPL, gift cards and settlements, with no unified view of relationship health.
Solution & architecture
A Merchant Health & Retention Intelligence Platform, not a generic churn model. It continuously measures relationship health, detects product-level disengagement early, and surfaces targeted interventions. 3 surfaces: a field discovery app for IC visits, a research panel for portfolio analysis, and a retention workspace with a Signal Impact Explorer and What-if Simulator.
Why it is built this way
Pine-specific signals
EMI, settlement, attachment - not generic churn
Early, not late
At-risk merchants flagged before they leave
Actionable
What-if simulator projects the fix
