The ABCs of RFM – and How it Can Help You Retain Your Customers

What’s a more profitable business strategy: attracting new customers or retaining existing ones? Statistically speaking, a business is better off focusing on retention than acquisition.

This isn’t new information.

Way back in 1990, Bain & Company concluded companies can boost profits by almost 100 percent by retaining just 5 percent more of their customers.

That finding remains true even in the digital era.

In the latest edition of their seminal textbook on marketing management, Philip Kotler, one of the world’s leading authorities on marketing, and brand guru Kevin Lane Keller, E. B. Osborn Professor of Marketing at the Tuck School of Business at Dartmouth College, cite multiple eye-opening statistics on customer retention.

• Acquisition of customers can cost five times more than retaining current customers
• A 5 percent reduction to the customer defection rate can increase profits by 25 percent to 85 percent
• The customer profit rate increases over the life of a retained customer

There’s little argument about the merits of retaining customers. The question is, “What exactly should a smart business do to keep those customers happy?”

How to Keep Customers

Simply saying, we need to find out where the problem lies. Why do customers stop coming back to a business? What could solve this issue?

In recent years, companies have benefited from relationship marketing and the concept of customer value. Through data obtained by today’s many customer relationship management technologies, they can now gather a wealth of data on individual customers.

That’s opened the door to development of tailored, personalized products and services and the growth of business strategies based on a customer-centric vision. It’s also advanced the notion of building loyalty, with an emphasis on customer retention.

To identify and understand customers, companies are using a database marketing tool called recency, frequency, monetary analysis (or RFM).

RFM in Customer Retention

RFM analysis segments customers into groups based on three criteria: Recency of the last purchase, Frequency of the customer’s purchases and Monetary value of those purchases.

It enables analysis of a correlation between them: recency versus monetary, recency versus frequency and so on.

Experts describe RFM as a useful method to improve customer segmentation by dividing customers into various groups for future personalization services and to identify customers who are more likely to respond to promotions.

Sometimes results of such a deep analysis are surprising.

It may turn out that clients who generate the highest revenue are casual customers. This information gives a clear signal that you should focus more on this group.

Another outcome of the RFM analysis could be that new clients tend to buy cheap products just to test the company. In such case, a company could benefit by creating an educational lead nurturing campaign to build the trust between the brand and customer.

RFM in Marketing Automation

Marketers can take RFM to the next level by integrating such analysis with a marketing automation engine. This allows for a dynamic division of the customers into segments, meaning that:

1. You won’t need to adapt your actions manually to the migration of your customers between different contact segments (induced by changes in Recency, Frequency or Monetary), since identification of the best customers will become easier than ever.
2. You will have an access to numerous fully automated customer retention actions rooted in the RFM segmentation: sending dynamic emails, SMS and push messages, adding tags, or displaying a personalized, dynamic website content.
3. You can use the benefits of the omnichannel model, decreasing time spent on navigating between different marketing channel such as social media, mobile channel or email marketing.

The RFM model gives a picture of the past, showing what your customers are like. But it’s also a great indicator of what your next objectives should be.

It provides useful data and a foundation for improved performance, including identification of certain behaviors that you can respond to proactively and effectively in the future. Explore the possibilities of RFM analysis and see how it may help you to keep the customers longer.