https://github.com/shwetam19/data-science-assignment-zeotap
https://github.com/shwetam19/data-science-assignment-zeotap
business-insights data-science prediction
Last synced: about 2 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/shwetam19/data-science-assignment-zeotap
- Owner: shwetam19
- Created: 2025-01-27T13:07:06.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-01-27T13:16:15.000Z (4 months ago)
- Last Synced: 2025-02-04T13:41:25.223Z (4 months ago)
- Topics: business-insights, data-science, prediction
- Language: Jupyter Notebook
- Homepage:
- Size: 577 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Data Science Assignment: eCommerce Customer Analysis📊
This project involves analyzing customer data to uncover actionable business insights, implement a lookalike model, and perform customer segmentation using clustering techniques.
## Features
1. **Exploratory Data Analysis (EDA)**:
- Uncovered trends in customer demographics, transaction patterns, and product sales.
- Generated insights to guide business strategies.
2. **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`.
3. **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`.