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  • E-commerce Attribution
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  • Shopify
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RFM Segmentation

RFM Segmentation

Server-side tracking

Tracking for ShopifyTracking for ShopifyTracking for Magento 2Tracking for Magento 2Tracking for FirmhouseTracking for Firmhouse🔌Event spec🌐UTM parameter guide

Insights

E-commerce AttributionE-commerce AttributionEmail PerformanceEmail PerformanceOnline Store PerformanceOnline Store PerformancePaid PerformancePaid PerformanceRFM SegmentationRFM SegmentationSubscription PerformanceSubscription PerformanceWebsite PerformanceWebsite Performance

Sources

Amazon Seller PartnerAmazon Seller PartnerBol.comBol.comCopernicaCopernicaFacebook AdsFacebook AdsFirmhouseFirmhouseGoogle AdsGoogle AdsGoogle Analytics 4Google Analytics 4Google Search ConsoleGoogle Search ConsoleKlaviyoKlaviyoLinkedInLinkedInMagento 2Magento 2Microsoft AdvertisingMicrosoft AdvertisingPinterestPinterestShopifyShopify

Destinations

Google Ads conversionGoogle Ads conversionGoogle Analytics 4 Google Analytics 4 Meta AdsMeta AdsTikTok AdsTikTok Ads

How-to guides

🔐Configure SSH access for Magento⚖️Attribution models and how to use them

RFM Segmentation

RFM (Recency, Frequency, Monetary) segmentation is a powerful framework for understanding customer behavior and driving personalized marketing. By analyzing how recently a customer purchased (Recency), how often they purchase (Frequency), and how much they spend (Monetary), you can uncover actionable insights that improve retention, increase customer lifetime value, and optimize campaign targeting.

RFM segments customers based on their interactions with your store, allowing you to group them by value and engagement. This model helps you tailor marketing strategies for each group: rewarding your best customers, re-engaging those at risk of churning, and nurturing new buyers into loyal fans.

Segment Descriptions

  • Champions: Your most valuable customers. Recent, frequent, and high-spending buyers who engage regularly and drive the most revenue.
  • Loyal Customers: Repeat customers with consistent purchasing behavior who may not spend the most but are highly engaged.
  • Recent Customers: New buyers who made their first purchase recently but haven’t yet shown long-term engagement.
  • Promising: Customers who’ve bought recently and show potential to become loyal if nurtured with the right messaging.
  • Potential Loyalists: Active and moderately frequent buyers who are on the path to becoming loyal customers.
  • Need Attention: Previously active customers with decent purchase history who haven't interacted in a while.
  • At Risk: High-value customers who haven’t purchased recently and are at risk of churning without re-engagement.
  • Can't Lose: Previously top-tier customers showing a significant drop in activity, critical to win back.
  • About to Sleep: Infrequent or lower-spending customers who haven't engaged recently and are nearing churn.
  • Hibernating: Long-time inactive customers with low frequency and monetary value who may need reactivation campaigns.

Available sources

RFM Segmentation is powered by data from the following sources:

ShopifyShopifyMagento 2Magento 2

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  • RFM Segmentation
  • Segment Descriptions
  • Available sources
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