Using ML models to personalize offers to loyal customers to increase their purchasing activity Objective: Develop a personalized marketing solution to increase purchasing activity among regular customers.
Data: Four datasets were used, covering customer behavior on the website, revenue generated from customers, time spent on the site, and average monthly profit over the last three months.
Steps:
• Data preprocessing
• Conducted a correlation analysis.
• Built a pipeline to identify the best model among kNN, Decision Tree Classifier, SVC, and Logistic Regression.
• Employed randomized search for hyperparameter tuning.
Analysis of features using SHAP Creation of customer segmentation