Understand your customer behaviorpurchasing patternsvaluable insightsdata-driven decisionscustomer segments
Segment customers using Recency, Frequency, and Monetary analysis powered by machine learning to uncover actionable business insights.
What is RFM & Customer Segmentation?
RFM Analysis is a data-driven method used to understand customer behavior based on transaction history. By combining Recency, Frequency, and Monetary metrics, businesses can segment customers effectively and make better strategic decisions.
Powered by Machine Learning
This system uses K-Means clustering to automatically group customers with similar purchasing behavior after RFM calculation and normalization.
RFM Analysis is widely used in many industries
How It Works
A simple process to understand your customers
Upload Data
Upload customer transaction data in CSV or Excel format.
RFM Calculation
Calculate Recency, Frequency, and Monetary values for each customer.
ML Clustering
Group customers with similar behavior using K-Means algorithm.
Insights
Explore customer segments through interactive visualizations.