This project involves analyzing customer data to uncover actionable business insights, implement a lookalike model, and perform customer segmentation using clustering techniques.
-
Exploratory Data Analysis (EDA):
- Uncovered trends in customer demographics, transaction patterns, and product sales.
- Generated insights to guide business strategies.
-
Lookalike Model:
- Recommended top 3 similar customers for each target customer (C0001–C0020).
- Used feature engineering and cosine similarity for precise recommendations.
- Output stored in
Lookalike.csv.
-
Customer Segmentation:
- Identified 5 distinct customer groups using K-Means clustering.
- Evaluated clusters with a Davies-Bouldin Index (DB Index) of 0.809.
- Visualized clusters using PCA and stored results in
Clusters.csv.