Paris-Dauphine analytics and data visualization project
Customer Segmentation Dashboard
Clustering, profiling, and dashboarding for marketing decisions
This project combines customer analytics and product thinking. The modeling work identifies meaningful segments, while the dashboard layer makes the output usable by a non-technical team for campaign targeting and profiling.
2,240
Clients
35
Engineered vars
4
Clusters
Problem
Marketing teams need segments that are both statistically meaningful and easy to explore without reopening notebooks or raw data files.
Approach
Prepared the data, engineered customer behavior features, compared K-Means, hierarchical clustering, and GMM, selected four segments, and built a Shiny application with filters, KPIs, and radar profiles.
Results
Recovered four usable customer groups over 2,240 clients and turned the analysis into a live dashboard instead of a static report.
What is in the repository
Role and scope
Unsupervised modeling, feature engineering, visualization, and dashboard delivery
Project context
Paris-Dauphine analytics and data visualization project
Main stack