Customer Segmentation Using RFM Analysis
Take customer segmentation to the next level by combining RFM Analysis with Machine Learning Clustering. Gain actionable insights for each cluster to understand behavior and optimize your marketing strategies.
Recency tracks how recently a customer made a purchase. Chartsy measures this to show how engaged customers are with your brand.
Frequency measures how often a customer makes a purchase. Chartsy analyzes this to help you identify loyal shoppers with consistent buying habits.
Monetary measures how much a customer spends. Chartsy analyzes this to help you identify high-value customers who drive revenue.
Out with the old, In with the new!
Unlike traditional methods, we use advanced algorithms to group customers into dynamic clusters like Loyal Customers, Potential Loyalist, At Risk, Lost Customers, etc.
This allows you to tailor your marketing strategies, personalize outreach, and identify opportunities to re-engage lapsed customers or reward loyal ones effectively.
Up close and personal with your Customers
Dive deep into each customer cluster and filter individual customers to view their unique RFM scores. This lets you see the exact Recency, Frequency, and Monetary values that define their behavior, giving you a clear, personalized view of each customer’s engagement level.
As customer behavior changes, customers may shift clusters, and Chartsy keeps you updated on these changes.
