Dillard's Black Friday Return Prediction

ML pipeline to predict purchase vs. return outcomes

Quick Summary

  • Built ML pipeline to predict Black Friday purchase vs. return outcomes, reducing return-related costs for Dillard’s
  • Queried 160M+ POS records and applied SMOTE for class imbalance; trained K-means + Logistic Regression ensemble
  • Achieved 78% purchase precision and 58% return recall with 227% projected ROI (~$590K)

Tools: Python, Scikit-learn, PostgreSQL

Project Report

For more detailed project information, please visit the GitHub repo: https://github.com/nu-mlds-group/dillards-return-prediction