Project Overview
All-U-Need Mart faced challenges in optimizing its marketing strategy due to limited insights into customer behavior, discount effectiveness, and long-term profitability. This project applied RFM Analysis (Recency, Frequency, Monetary) and Customer Lifetime Value (CLV) to segment customers and enhance retention, profitability, and marketing efficiency.
Objectives
✅ Identify high-value customers through RFM segmentation
✅ Predict Customer Lifetime Value (CLV) to optimize marketing spending
✅ Analyze churn risks and develop retention strategies
✅ Evaluate discount effectiveness to minimize revenue loss
✅ Provide data-driven recommendations for business growth
Tools & Technologies Used
🔹 SQL – Data processing and transformation
🔹 Python – Statistical analysis, CLV prediction, and machine learning
🔹 Tableau – Data visualization and interactive dashboards
Data Processing & Analysis
1️⃣ Data Cleaning & Preprocessing
- Handled missing values using median/mode imputation
- Processed transactional data to extract RFM metrics
2️⃣ Customer Segmentation with RFM Analysis
- Grouped customers into Loyal, VIP, Potential, At-Risk, and Lost segments
- Provided targeted marketing strategies for each group
3️⃣ CLV Prediction & Churn Analysis
- ElasticNet Regression achieved the best predictive performance for CLV
- Identified high-value customers at risk of churning
4️⃣ Discount Impact & Sales Trends
- 38% of customers were discount-dependent, requiring strategy adjustments
Key Insights & Business Recommendations
📌 High CLV customers should receive VIP perks and exclusive early access
📌 Discount-heavy customers need value-based incentives instead of frequent discounts
📌 Loyal customers benefit from reward programs to maintain engagement
📌 Churn-prone customers require personalized win-back campaigns
📌 Weekend promotions can further maximize revenue
By integrating RFM segmentation, CLV prediction, and data-driven marketing strategies, this project helped All-U-Need Mart improve customer retention, optimize promotional efforts, and drive long-term business growth.