Pricing & CLV Analytics

Overview

This project turns pricing strategy into something you can test. Instead of one-off forecasts, it provides explainable predictions and interactive scenario simulation so decision-makers can understand the “why” behind changes in CLV and retention.

What I Built

• CLV / churn models with evaluation and calibration checks.
• Interpretability layer: feature contributions, local explanations, sensitivity views.
• Scenario simulation: price / promotion / bundle changes → CLV distribution and retention impact.

Results (fill in)

• Model metrics: AUC / RMSE / calibration (add numbers).
• Key drivers: what features explain CLV changes; marginal effect of pricing shifts.
• One before/after scenario case study with a clear chart.

Artifacts

• Dashboard / notebook: TODO
• Demo video: TODO
• Method notes: TODO