Leveraging the power of RFM (Recency, Frequency, Monetary) analysis, this project equips Odeal with actionable insights to enhance customer value perception and drive marketing performance.
Our suite features a robust component:
- RFMAnalysis.py: A comprehensive script that transforms transactional data into insightful scores and segments, categorizing customers by their purchasing behavior.
- Customer Segmentation: Distinguishes customers into distinct groups based on transaction activity, paving the way for tailored marketing approaches. 🎯
- Resource Allocation: Allocates marketing resources efficiently, focusing on the most lucrative customer segments. 💼
- Customer Retention: Pinpoints those more likely to engage with retention campaigns, bolstering customer loyalty. 💡
- Increased ROI: Directs attention towards customers with potential for higher-value transactions, enhancing profit margins. 💰
- Load Data: It begins with the ingestion and processing of transactional data to carve out essential RFM metrics.
- Calculate Scores: Each customer receives a unique score reflecting their recency, frequency, and monetary contributions.
- Segmentation: Based on these scores, customers are methodically categorized into segments such as 'Platinum', 'Gold', 'Silver', and 'Bronze'.
Embark on your journey by cloning this repository. Ensure your data is primed with the required fields as per the script guidelines. With your data in shape, execute RFMAnalysis.py to uncover the analytical treasure, and then deploy Treemap_Visualization to visualize the segmentation saga.
This project embraces open source values and is protected under the Apache License, Version 2.0. For the detailed legal lexicon, please refer to the LICENSE document housed in this repository.