RFM model is used to analyze customer value, which needs to provide three data, namely, Recency, Frequency and Monetary. The latest consumption refers to the gap time value obtained by subtracting the latest consumption time of users from the survey time point, and the unit is days or months or weeks or average years, subject to the actual business situation. Consumption frequency refers to the number of times users spend in the research data category, and consumption amount refers to the total consumption amount of users in the research data category.

The principle of RFM is to classify the three data of RFM. The score of 1~5 is divided into two groups (high value group and low value group) according to the average value of 1~5. Finally, RFM provides targeted marketing strategies for two groups, that is, 2*2*2=8 combinations, and 8 combinations correspond to 8 value groups.

RFM model studies customer value, and finally divides customers into 8 different categories (8 user types). In RFM model, the internal calculation of how to divide data into eight categories of users is divided into two steps;

The first step is to convert the data into a scoring method of 1~5 (the higher the score after conversion, the higher the value). By default, SPSSAU counts data as 1~5 according to 20%/40%/60%/80% quantile. The specific scoring method of SPSSAU is shown in the following table:

Step 2, divide the score of 1~5 into 0 and 1 according to the corresponding average, where the number 0 represents the low value group and the number 1 represents the high value group. As shown in the following table:

Finally, the grouping of RFM is combined, and there are 2*2*2=8 combinations, namely 8 user types, as shown in the following table:

You can use SPSSAU for analysis.