A Deeper Path to Personalization

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    Understand where traditional customer segmentation is falling short due to changing customer needs

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    Know importance of RFM segmentation and what it means for your business growth

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    Discover deeper path to personalization using RFM segmentation approach

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    Find out how a billion dollar global security software brand executes RFM segmentation

Learn how with RFM segmentation, you can create deeper-level segments and provide personalized engagement

Difference Between RFM Model and Traditional Segmentation Method

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Importance of RFM Segmentation

  • More Insightful
  • Deeper Personalization
  • New Opportunities
  • Highly Effective

Get customer data on a deeper level, and at scale, to forecast customer preferences and engage accordingly.


Insightful data accurately segments customer and empower contextual, personalized customer engagement across channels.


Find new opportunities to upsell, cross-sell and monetize new marketing opportunities


Actual customer data is not based on assumptions but rather based on historical and behavioral data analysis.

Frequently Asked Questions

What is RFM segmentation?

RFM analysis is a proven marketing model for behavior-based customer segmentation. Customer segmentation on the basis of the analysis of recency, frequency, and monetary value of purchases.

Why utilize RFM segmentation?

RFM model is one of the effective approach for digital platforms as all customer data can be integrated. Additionally, RFM segmentation allows categorizing customers based on various factors like loyalty, needs attention, at risk etc.

How does RFM approach provide deeper path to personalization?

As RFM segments customers based on various attributes, it allows marketers to engage customers in a more contextualized manner.

How does MoEngage RFM works?

MoEngage RFM system assign a value to each parameter and rank customers based on that value. Using these values, any marketer can engage customer using a deeper personalization approach.