RFM/RFE Modelling with SAP CDP: Basic, Advanced and Custom

[kai_lemke]

Understanding customer behavior is  key to personalized marketing — and RFM/RFE modeling helps you do exactly that in SAP Customer Data Platform.

RFM modeling is a standard marketing analysis technique used to segment customers based on their purchasing behavior. It helps businesses understand and predict customer value by looking at three key factors:

• Recency (R):
  How recently has the customer made a purchase?
  Customers who purchased recently are more likely to respond to promotions than those who haven’t purchased in a while.
  
  
• Frequency (F):
  How often does the customer make purchases?
  Frequent customers are typically more engaged and valuable.
  
  
• Monetary value (M):
  How much money has the customer spent?
  High spenders are usually more profitable and potentially more loyal.

Every factor is scored individually for every customer, typically on a scale from 1 (worst) to 5 (best). 
Then a total sum of all three factors can be made giving every customer a score of in between 3 and 15. This then enables targeted and personalized marketing with better marketing ROI.

SAP CDP RFM Score Calculation

Some business models are less about purchases but more about engagement. This variation is then called RFE modelling, with E for Engagement.

SAP Customer Data Platform provides RFM/RFE analysis out of the box with an intuitive wizard. 

Let me show you how to use it for basic, advanced or custom use cases.

Basic

RFM Wizard - Basic

For most use cases it's very simple. As you can see here you just need to create an RFM indicator, choose the time frame you want to have evaluated, basic setup (default) and save. That's it!

Advanced

RFM Wizard - Advanced

In the basic setup recency, frequency and monetary value will have equal weight. If you want to change the relative weights you can do so in the advanced setup. As you can see here for example giving 50% to the monetary value and only 25% to recency and frequency each.

RFM will evaluate SAP CDP's out-of-the-box order activity. How to use a different activity I will show you in the custom section.

For RFE it's the same with the only difference that you can choose an activity which represents the engagement.

RFE Wizard

Both RFM and RFE work for profiles and groups, e.g. accounts.

Custom

Now there may be use cases for which you want to give more specific instructions on how to segment your customers by different factors into several buckets or tiers. For example if you're using other activities then the default order activity, like if you're tracking online and offline purchases in different activities. Or if you want to limit the evaluation time of certain factors like monetary value (SAP's default: all time).

Let me show you how to do this.

First for every factor you need to create an activity indicator that calculates it. Take a look at how recency would be calculated individually, but for the last 5 years (5x365 days = 1825 days):

Custom Recency Activity Indicator

Then with the help of our new generic percentile ranking feature you can create a custom indicator for profiles or groups which evenly distributes all profiles or groups into the number of percentile buckets that you specify, 5 in below example (meaning 20% per bucket):

Custom 5 Buckets for Recency

This results in recency score from 1 to 5 just like the standard CDP RFM model does it, but with this custom approach you can choose other activities, choose a different time frame, choose other factors. The possibilities are endless! Think of evaluating return frequency or amount to identify customers who order a lot but also return a lot, thus judging how profitable your customers really are.

Once you have created all activity indicators for all factors relevant to your business model together with the generic percentile ranking custom indicators you can create one final custom indicator which simply adds them together, like CDP RFM in standard does it. Here you can also apply weight factors if you want to. Like in this example (not related to RFM modelling but still showing how to do the math):

Weight Factors

In B2B business models you can aggregate activities from contacts up to accounts and even up through the account hierarchy with the help of child indicators. Here as well you can apply the generic percentile ranking for targeted segmentation. But that's probably a topic for a separate blog.

Conclusion

SAP Customer Data Platform seamlessly brings together front-office and back-office data so that customer engagements become meaningful and in the back-office business decisions can be made, powered by contextual customer insights. 

With SAP CDP’s flexible RFM and RFE capabilities, businesses gain a 360° view of customer behavior. Whether you're targeting recent high spenders or loyal engagers, these insights help drive targeted action with measurable impact.

Let us know what cool use cases you're implementing with the help of SAP Customer Data Platform!

More Information

For further information refer to SAP Customer Data Platform or to SAP Customer Data Platform | SAP Help Portal.

In detail refer to 

• Creating an RFM Indicator
• Creating an RFE Indicator
• Generic Percentile Ranking 
• Creating a Child Indicator