RFM Scores from Transaction Data

RFM (Recency, Frequency, Monetary) analysis is a technique used to identify existing customers who are most likely to respond to a new offer. This technique is commonly used in direct marketing.

Data Considerations

In a transaction data file, each row represents a separate transaction, rather than a separate customer, and there can be multiple transaction rows for each customer. If data rows represent customers with summary information for all transactions (with columns that contain values for total amount spent, total number of transactions, and most recent transaction date), see RFM Scores from Customer Data.

The dataset must contain variables that contain the following information:

• A variable or combination of variables that identify each case (customer).
• A variable with the date of each transaction.
• A variable with the monetary value of each transaction.

Creating RFM Scores from Transaction Data

This feature is available in the Direct Marketing option.

1. From the menus choose:

   Direct Marketing > Choose Technique

2. Select Help identify my best contacts (RFM Analysis) and click Continue.
3. Select Transaction data and click Continue.
4. Select the variable that contains transaction dates.
5. Select the variable that contains the monetary amount for each transaction.
6. Select the method for summarizing transaction amounts for each customer: Total (sum of all transactions), mean, median, or maximum (highest transaction amount).
7. Select the variable or combination of variables that uniquely identifies each customer. For example, cases could be identified by a unique ID code or a combination of last name and first name.