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Packitoo

AI-Driven Pricing & Revenue Optimization

Manufacturing – Pricing Optimization

Propensity scoring and what-if pricing simulator using XGBoost with SHAP/LIME explainability, enabling sales teams to optimize margins with actionable price corridors.

±100%

Price Range Simulation

SHAP

Full Explainability

E2E

Production Pipeline

TS-CV

Robust Validation

Pricing Impact

Data-driven pricing optimization for manufacturing

Project Details

Client

Packitoo

Sector

Manufacturing – Pricing Optimization

Year

2024–2025

Key Technologies

PythonXGBoostOptunaSHAPLIMEscikit-learn

Mission

Lead Senior Data Scientist – Pricing & Revenue Optimization

Pricing Optimization & Propensity Scoring

Mission in progress

Modeling the acceptance probability of quotes (accepted/not accepted) and recommending the optimal price to maximize margin. Classification & scoring using XGBoost (logistic) for propensity estimation per quote. What-if simulation engine varying price from -99% to +100% to explore acceptance-margin trade-offs.

Contexte & Environnement

Packitoo needed to optimize their quote pricing by analyzing multiple explanatory criteria (product, client, commercial context) to arbitrate between price and acceptance probability. The goal was to provide sales and finance teams with a price simulator and actionable recommendations to increase margins without degrading conversion.

Team

Lead Senior Data Scientist bridging Sales, Revenue, Finance, Data, and IT stakeholders

Environment

Python ML pipeline with batch and/or API scoring, performance dashboards

Objectifs Cles

1XGBoost propensity scoring with Time Series Cross-Validation for robust generalization

2What-if simulation engine: -99% to +100% price variation with projected margins per segment

3SHAP & LIME for local and global explainability reports for business adoption

4End-to-end production pipeline: data to model to API/batch to dashboard

5Standardized TS-CV generalization metrics with RMSE, LogLoss, AUC/PR and drift monitoring

Technologies & Infrastructure

PythonPandasNumPyscikit-learnXGBoostOptunaHyperoptSHAPLIME

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