Customer Segmentation and Lifetime Value Prediction

Wishlist Share
Share Course
Page Link
Share On Social Media

About Course

  • Tech Stack: Python (K-means, DBSCAN, XGBoost), Tableau, SQL, Flask, AWS (Redshift, Lambda, S3), Airflow
  • Objective: Build a customer segmentation model using clustering techniques and a predictive model for customer lifetime value (LTV). The model will help a retail company target customers based on their predicted future spending and segment them for personalized marketing.
  • Skills Needed: Clustering algorithms (K-means, DBSCAN), LTV modeling (XGBoost), data pipelines (Airflow), cloud data storage and processing (AWS), Tableau for visual insights.

Student Ratings & Reviews

No Review Yet
No Review Yet