Top 10 Used

RFM Segmentation

Segment Customers by Loyalty for Targeted Campaigns

RFM segmentation categorizes customers based on recency, frequency, and monetary value of their purchases into 11 segments. This proven framework helps you identify your most valuable customers, at-risk segments, and growth opportunities. For example, target high-frequency buyers with VIP campaigns or reengage customers who haven’t purchased recently. Trigger segmented marketing campaigns to drive customer loyalty and revenue per visitor.

Channel

Products:

Marketing Automation

Industries:

Ecommerce Retail

Goal:

Analyse Data

Metrics:

CLTV Purchase Frequency Retention Rate

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Why Marketers Use Bloomreach for RFM Customer Segmentation

Without proper customer segmentation, you’re blind to which customers drive the most value and which are at risk of churning. Manual RFM analysis is time-consuming and often outdated by the time you act on it. Bloomreach Engagement automates RFM segmentation with real-time data, giving you instant visibility into customer behavior patterns. You can quickly identify loyal customers, potential churners, and growth opportunities, then trigger targeted campaigns automatically based on segment changes.

Run Smarter Campaigns With RFM Segmentation

Analytics Dashboard

RFM Segmentation

Prebuilt Use Case

Visualize trends in your customer base with a real-time automated dashboard segmenting your customers into 12 groups: lost customers, losing but engaged, hibernating, cannot lose them, at risk, about to sleep, needs attention, promising, new customers, potential loyalists, loyal, and champions.

An RFM segmentation can be used to segment and trigger marketing campaigns to drive customer loyalty and RPV. The dashboard lets you learn about the revenue and the parts of the customer base it’s coming from.

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“Segment your customer base according to RFM and get a holistic overview of better campaign targeting based on customer loyalty. Plus, you can learn which customer segments bring in the most revenue.”

How It Works

Bloomreach Engagement automatically analyzes your customer purchase data to calculate RFM factors:

– Recency (how recently they bought)

– Frequency (how often they buy)

– Monetary value (how much they spend)

The platform creates dynamic customer segments that categorize customers into 11 groups (e.g, champions, loyal customers, at risk, new customers) in real time.

A visual dashboard displays your customer distribution across RFM segments, showing revenue contribution and segment size to help you prioritize marketing efforts.

Track key metrics like customer lifetime value (CLTV), purchase frequency, and retention rate across segments to measure the impact of your targeted campaigns.

Use segment insights to personalize email campaigns, SMS messages, and web experiences — for example, offer VIP perks to champions or win-back discounts to at-risk customers.

Retail Thousands Personalized variants

Toolstation Uncovers Significant Revenue Opportunity With AI-Powered Customer Segmentation

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Campaigns Built Using RFM Segmentation

Toolstation, a leading European tools and building supplies retailer serving over 25,000 products, partnered with Bloomreach and HyperFinity to implement AI-powered RFM (recency, frequency, monetary value) segmentation. By analyzing purchase patterns, the brand identified critical customer segments: frequent high spenders, regular low spenders, and single shoppers. Customer segmentation revealed significant untapped revenue opportunities, enabled targeted retention strategies for high-value customers, and activated spending from less frequent shoppers through precision engagement. The result: scalable personalization from a handful of variants to thousands of them and a measurable framework for maximizing customer lifetime value.

Target Audience for RFM-Based Marketing

Retail brands seeking to maximize customer lifetime value, subscription businesses tracking customer health, and ecommerce companies with diverse customer segments.

Particularly valuable for businesses with established customer bases looking to identify high-value segments and prevent churn through data-driven targeting.