What is RFM analysis?
RFM analysis is one of the best-known methods in marketing, which focuses on the buying behavior of customers. The goal is to develop targeted marketing strategies. This behavior-based method is a scoring procedure. Customers are divided into different target groups or segments. RFM analysis can be used in various marketing areas, such as direct marketing or e-mail marketing.
The abbreviation RFM stands for Recency, Frequency and Monetary Value.
Recency: When was the last time someone made a purchase?
The first factor is also the most important factor of the entire analysis. It indicates how long ago a person last made a purchase. If a purchase was made only a short time ago, it is highly likely that customers will buy something again or react positively to marketing campaigns.
Frequency: How often are purchases made?
This factor refers to the recency of the last purchase or interaction with the company within a defined period of time. This can be a year, for example. The more often a purchase is made, the more likely it is to be made again.
Monetary Value: How much money was spent?
The last factor comprises the monetary value of the purchases made within a time period. The more money spent, the higher the probability that customers will react positively to an offer or buy something again.
Scoring Procedure
By combining these three criteria, customers can be divided into different segments. A scoring procedure is used for this. For each individual factor, a customer is given a score of 1 to 5. The higher the score, the stronger the person's purchasing power. Other classifications can also be used.
Recency: based on the last purchase, a customer receives a score. For example, if the last purchase was made one day ago, the person receives a score of 5.
Frequency: A score can also be assigned for the frequency of purchases. The more purchases made, the higher the score.
Monetary Value: Finally, a score is assigned for the monetary value. The highest rating here refers to the largest purchase value.
The three scores are now added or concatenated. Thus, with three factors with five classifications, there are 125 possible RFM scores. The higher the combined score, the higher the probability of a positive response to an offer. There is not much that can be done with the scoring process in this way. Therefore, segments are assigned to the scores.
Which Segments Can Be Created?
There are various approaches to dividing customers into segments. We recommend dividing them into four target groups.
Champions (VIP customers): Customers with high RFM value, who have usually bought recently, buy often, and spend a lot of money. These customers are very valuable to the company and should be targeted with marketing activities to maintain customer loyalty. Upsell and cross-sell campaigns are super suitable.
Potential Loyalist (potential existing customers): Customers who have purchased recently, but not frequently. This group has the potential to become existing customers.
Passive Customer: Customers who have not bought anything for a long time, but who used to buy frequently with high value. This segment must be convinced of the company's products and values. Storytelling and personalized campaigns are suitable. Surveys help to understand the decline in purchasing behavior.
Inactive Customer (At Risk): Customers who have not purchased often or recently and who spend little money. This group is less valuable to the company. Nevertheless, targeted marketing measures can help to increase their purchase frequency and purchase amount.
What Does The RFM Analysis Do?
With the help of RFM analysis, customer groups can be identified and analyzed. The customer segment with the highest purchasing power comes into its own here. However, one should not focus exclusively on this group, but also look at the weaker segments. Inactive and passive customers can be reactivated and persuaded with the help of targeted campaigns. The following applies to all target groups: loyalty and purchasing power can be increased with attractive offers, exciting and personalized content, and discounts. Purchases and sales of the online store can ultimately increase.
RFM analysis can be applied not only to e-commerce, but also to other areas. For example, instead of online store purchases, website visits or product usage can be considered. The third factor, monetary value, then relates to engagement or time of use.
Advantages At A Glace
+ Analyze buying behavior
+ Identify strong and inactive customers
+ Create target groups
+ Send personalized email campaigns
+ Increase your online sales
RFM Analysis with JUNE
With JUNE Automation, you can directly apply the RFM method. All you need is a store integration to link your online store with JUNE.
This will help you send targeted automated email campaigns with valuable content. You can find the RFM Matrix widget on your dashboard.
What is possible?
Automatic collection of the three scores of your customers
Calculation of a summary score
User defined time period
Easy creation of segments based on the score values
Division into any number of target groups
Segmented campaign creation