Rfm Analysis – Applications and Limitations

Published 24/12/2019 11:35 | Tech News | comments

RFM analysis is a tested marketing model that helps in customer segmentation. It offers a lot more than just segmentation, but the basic goal is this. What is RFM? It is a model that distinguishes customers based on their activities. The customers are segmented according to their recent transactions, the frequency of purchase, and the money they spend on it. The reason to segment customers is to predict future services and strategies.

Customer segments

10-12 customer groups are generated based on the data collected by RFM analysis. These groups encompass the best, good, and bad customers. And are segmented upon recency, frequency, and monetary value.

E-mail marketing

The most disappointing thing in your business is the lack of response from the audience. You try your best, do everything you can, customize emails, make them short and concise and then you wait for the reply or your desired action by your customers. But at the end of the day, you get a response of 1%. Isn’t is discouraging.

But everything has a backstory. You need to think and point out what you’ve missed. The answer is targeting. You didn’t realize that all your customers do not belong to the same tier or group and hence they won’t do what you want them to do. Only some will.

Enters RFM

Here’s how RFM helps you out. By analyzing certain data of customer behavior, you can single out the audience that is predicted to give you the desired response that can be either clicking or making a purchase. In one statement, RFM analysis can yield higher conversion rates saving a lot of time and money of the marketer. Not all that glitters is gold. RFM works on this principle and picks the golden customers out of the bulk.

How can it help you?

RFM helps a marketer to answer some basic questions regarding his investment, future decisions, and product strategies. These questions can be of ideal customers, the targeted groups, offers, and subscriptions that are given to loyal customers, how to deal with the customers who are not recent but invest more.

In addition to that, you can always predict the outcome of certain marketing campaigns. Based on your data you can picture how much response you will receive and what your desired customers are.

The Pareto principle

Vilfredo Pareto in 1906 gave the idea of response-cause-ratio. He said that the first 20% of your effort you put into anything brings out 80% of the outcome. That means a major portion of the response depends on the 20% of the causes or sources. Linking it to e-commerce, it means that 80% of your total revenue is generated by the investments of 20% of the customers. These are your target audience and these are the ones you don’t want to lose.

RFM calculation

Now that you know what is RFM, the next step is to calculate it. Various methods are used to calculate the total value. These include the method of simply fixed ranges. You have decided points based on the three parameters. For example, if someone has bought in the last 24 hours, you award them 5 points out of 5. The other method used is of quintiles.

Quintiles are like the percentiles in mathematics. For example, if you are the fourth smartest person in a class of 20, 80% of the students fall behind you, which means you are the 80th percentile. We calculate quintiles in a somewhat similar manner during RFM analysis.

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