An open API service indexing awesome lists of open source software.

https://github.com/dpb24/customer-segmentation

🎯 Customer segmentation using RFM analysis
https://github.com/dpb24/customer-segmentation

customer-segmentation data-driven-decisions digital-marketing k-means-clustering rfm-analysis scikit-learn

Last synced: 8 months ago
JSON representation

🎯 Customer segmentation using RFM analysis

Awesome Lists containing this project

README

          

# 🎯 Customer Segmentation using RFM analysis

**Libraries:** `scikit-learn`, `matplotlib`, `seaborn`, `plotly.express`, `geopandas`

**Dataset:** proprietary, annoymised customer-level booking data

This project explores customer segmentation for the fictional hospitality brand XYZ Entertainment Center, aiming to identify customers most likely to respond to targeted promotions that encourage weekday bookings.

## 🧠 Analytical Approach
- **RFM feature engineering** to quantify customer behaviour
- **K-Means clustering** to segment customers by value and engagement
- **Visual analytics** to interpret booking patterns and segment characteristics
- **Campaign strategy design** focused on high-potential, weekday-receptive segments

## ✨ Results
- Identified **4** meaningful customer segments
- Selected **2** clusters for campaign targeting, covering **56.6%** of the customer base
- Developed a segmentation-informed campaign recommendation framework for weekday growth

📖 Jupyter Notebook: [GitHub](https://github.com/dpb24/customer-segmentation/blob/main/notebooks/Customer_Segmentation_for_XYZ_Entertainment.ipynb) | [CoLab](https://colab.research.google.com/drive/1riolBlBa0T5GyXE4dJXOTh7B0Bq_p01L)

👨🏻‍🏫 Presentation: [GitHub](https://github.com/dpb24/customer-segmentation/blob/main/reports/Customer_Segmentation_for_XYZ_Entertainment.pdf)