<ul data-eligibleForWebStory="true"><li>In online retail, businesses often emphasize Customer Lifetime Value (CLV) but may overlook fulfillment costs, leading to profit erosion.</li><li>A machine learning pipeline was developed to optimize CLV and fulfillment strategy using the UCI Online Retail Dataset and Azure ML.</li><li>The pipeline involved cost estimation, fulfillment cost simulation, feature engineering, training a Random Forest Regressor for CLV prediction, and visualizations.</li><li>An interactive dashboard in Azure ML was created to visualize customer lifetime value accumulation, purchase frequency bins, and country rankings based on CLV.</li></ul>

Optimizing Customer Value and Fulfillment Strategy with Azure ML

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