|1||=||Customers with an average purchase amount up to $20|
|2||=||Customers with an average purchase amount between $20 and $45|
|3||=||Customers with an average purchase amount greater than $45|
To distribute scores to your customer list, you can simply sort the appropriate column. Starting with Recency, you would sort that column by date of most recent purchase, with the most recent purchase date at the top descending to least recent purchase date at the bottom. A score of 3 should be given to the top 20 percent of customers, a score of 2 to the middle 60 percent of customers, and a score of 1 to the bottom 20 percent of the customers. Then you’ll simply repeat this process for the Frequency and Monetary columns.
At the end of the exercise, you’ll do a final sort on all of your data so that the customers receiving scores of 333 appear together to form a single segment. The customers receiving scores of 323 should appear together to form a single segment, the customers receiving scores of 322 should appear together, and so on.
Guess what? You’ve identified your “best” customer segments by completing this simple exercise (this is the group with the 333 score). You’ve also identified your worst customers and everything in between. The question is: How should you act on this enlightening information?