RFM Analysis for E-commerce – An in-depth Guide

RFM Analysis for Ecommerce

RFM analysis is vital to maximizing e-commerce revenue and sales. 

E-commerce organizations make leverage CRM data to know more about their existing and potential customers. To effectively scale your e-tail business, it is essential to understand how your customers feel and think about the products and services. 

The primary benefit of RFM analysis is that you get a chance to market your product in a more personalized manner. Personalized marketing helps in increasing engagement and boosting sales. With the correct analysis of the target audience, it is easy to develop relevant offers and marketing campaigns as now you know what your audience would prefer. RFM analysis has another great benefit of increasing customer retention. 

This article will help you explore the full benefits and guide RFM Analysis with examples and data to substantiate the arguments and rationale of using it in e-commerce operations. It will also reveal the power of RFM segmentation which helps in maximizing Return of Investment (ROI).

What is RFM Analysis?


RFM analysis refers to recency, frequency, and monetary value. RFM analysis is one of the data-driven strategies which help in understanding the behavior of potential customers. Behavioral segmentation of customers promotes better conversions and sales. Therefore, RFM analysis plays a significant role in customer segmentation. RFM customer segmentation is done based on three fundamental measures:

  • When was their last buy?
  • How often have they been purchasing in the past?
  • The amount they spent in each transaction.

Each of the three of these actions has demonstrated to be clear indicators of a customer’s eagerness to participate in promoting offers and campaigns.

The emergence of RFM was through emailing service, but it has now become an important tool to run an E-commerce brand. 

Benefits of RFM Analysis


As basic as it may sound, RFM analysis has excellent benefits. RFM is a method of customer segmentation. Running research on your customer database and designing exclusive marketing strategies that suit the interests of each client drive enormous benefits for an e-commerce brand.

  • Personalization – By RFM segmentation, the ease of designing relevant and exclusive offers is increased.
  • Improved conversion rates – With personalized marketing campaigns, customers will engage better with products and services. Hence, it will promote better sales and revenue.
  • Increment in income and benefits.

RFM Segmentation Model


RFM model is straightforward to comprehend. It is used to cluster customers of similar interests and then design marketing models. Specific measures of this model help gather customer’s focus on a particular area. 

The three pillars of this model are:

  • Recency – When was the last time the customer made a purchase?
  • Frequency – How frequently a customer purchases?
  • Monetary – How much in total has the customer spent in the past?

The RFM model helps to predict the future behavior of a client. This prediction analysis helps in the high rate of customer response. In addition, this extensive data of purchase and browsing history and customer response on marketing campaigns done in the past helps improve marketing and customer segmentation. 

Why is RFM Analysis Critical?

RFM Analysis comes in as a crucial tool for e-commerce growth for the following reasons; 

  • It uses plain and mathematical scales that result in a compact and valuable factual level portrayal of customers. 
  • Basic – advertisers can utilize it viably without the requirement for information researchers or complex programming. 
  • Intuitive – the yield of this division technique is straightforward and deciphering.

Steps to RFM Analysis 

Here is an example guide to RFM analysis examples in Excel.

Step 1: Assign recency, frequency, monetary values to each of the customers. You can find this raw data in the CRM of the organization.

Step 2: Divide customers into three groups:

  • Recency
  • Frequency
  • Monetary
Recency Frequency Monetary
Tier 1 (most recent) Tier 1 (most recent) Tier 1 (most recent)
Tier 2 Tier 2 Tier 2
Tier 3 Tier 3 Tier 3
Tier 4 (least recent) Tier 4 (least recent) Tier 4 (least recent)

The following table will give us 64 segments of customers.

Step 3: Based on RFM customer segments, select the segments to whom particular messages and emails would be sent. 

For example;

  • Best Clients – Customers with a score of 1-1-1 (Recency: Tier 1, Frequency: Tier 1, Monetary: Tier 1) means they have purchased recently, they are buying the most, and they have spent the most amount. 
  • Highest-Spending New Clients – Clients who score 1-4-2 and 1-4-1. Customers who made a recent purchase but the first purchase and paid a higher amount than others. 
  • Lowest-Spending Active Clients – Clients who score 1-4-3 and 1-1-4. Customers who made a recent purchase but a new purchase and paid the least amount.
  • Disappeared Best Clients – Clients who score 4-1-1, 4-1-2, 4-2-1, 4-2-2. Clients who frequently purchased and paid a higher amount than others have been quite a long since they made a purchase.

According to this data, you can design personalized and exclusive text messages and emails and send them to each customer. Therefore, the focus of marketers should be on this raw data when creating marketing campaigns to retain clients.

Step 4: The fourth step is curating special emails and messages for specific customer segments. RFM advertising permits advertisers to speak with clients in a significantly more successful way by focusing on the pattern of activities of customers. RFM analysis examples can be:

  • Best Customers – Communication with these types of customers should make them feel unique.
  • Highest-spending new clients – It is essential to retain these customers, so your communication should make them feel welcomed and valued.
  • Lowest-spending active customers – These types of customers spend the lowest but are functional and loyal. The communication should be such that the customers feel that they are missing out on crazy deals and should encourage them to spend more. 
  • Disappeared best clients – These types of customers should feel that the company has not forgotten them. Communication should make them feel valued.

Apart from the manual customer segmentation, Wigzo offers RFM automation services that help extract data and insights about the customer without any manual compilation of data. Wigzo’s analytical tools empower your brand’s RFM automation so that you can boost sales and increase customer retention. Wigzo automatically creates smart customer segments based on your customer data. 

You can also set custom parameters to segment your customers based on their purchase Recency, Frequency, and Monetary value. 

It is now relatively easy to automate communications between the brand and customers as Wigzo can address any customer behavior changes and increase customer retention.  You can now start growing your business with the best RFM automation platform. 

Closing Note

RFM analysis can be a great tool in the marketing world for customer segmentation. However, it might get a little intimidating if you have an extensive customer database. 

To ease your manual process and cumbersome calculation, we invite you to try out Wigzo. It is a full-suite marketing automation platform that automatically extracts insights from your customer data and automatically creates RFM-based smart customer segments. 

With Wigzo, you get RFM analysis automatically in minutes for quick action!

Saad Mohammad

Saad Mohammad

Full-time marketer, part-time guitar player, and a football fanatic. Saad is a Digital Marketer with 6+ years of experience in the industry.

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