This post is our third in a series about recency, frequency, monetary (RFM) analysis, and why understanding how to leverage its concepts with data is crucial to your online business.

Suppose that you’re the co-founder of a footwear retailer, operating a wildly popular website with established partnerships with brick-and-mortar retailers. You and your CMO have used RFM analysis to develop your 2017 marketing strategy.

And so far, business is booming. You’ve established your transactional churn rate to determine when your customers are likely to not return — and have set up a massive retargeting campaign to win those customers back at the most crucial time period. You have also noticed that the most loyal repeat customers tend to order at a frequency of every 6 months, but can be convinced to return sooner with incentives like a seasonal sale. Your strategy appears to be paying off, but you and your CMO agree on a key question you both have. How can you determine whether your marketing strategy is effectively capturing the best customers? 

Who are your best customers, anyway? It’s a simple question with a simple answer. Your best customers are the ones contributing the most revenue to your business. This attribute, the monetary value of a customer, is crucial to understanding RFM analysis.

First, let’s recap what we’ve learned from the RFM mindset so far:

  • Frequent customers create recurring revenue. As a transactional business, many of your customers will purchase at a bumpy, atypical frequency — unless you build customer loyalty. A customer base with a regular cadence is healthy, predictable, and keeps your customer acquisition cost low.
  • Frequent customers create reliable revenue. The more loyal a customer becomes, the more likely there are to remain a customer indefinitely. 
  • Recent customers are inherently more valuable customers.

Predicting a customer’s lifetime value is a simple as assuming that each customer has a variable for R, F, and M.

  • R (recency) is a proxy for retention, i.e., will this customer continue purchasing my products in the future? 
  • F (frequency) accelerates the growth of the lifetime revenue, i.e., how quickly will this customer return to my storefront?
  • M (monetary) is the per-order value of the customer, i.e., how expensive are those purchases anyway? 

Understanding monetary value

The monetary variable of RFM, to be fair, is the most straight-forward one. What’s the average order value of your customers? Truly grasping customer purchase value isn’t much complicated than this. That said, if you have access to a warehoused version of your data, you should be tracking all of the below:

  • Does AOV differ for new customers, as opposed to repeat customers? Does that average steadily increase as the customer gets older, or does it shrink?
  • Does AOV differ across segments like geographic location, customer type, or acquisition channel?

Options to take action

As in our previous posts, it’s important to recognize what about your customers’ behavior is possible to change. Average order value might be a function of the product catalog that you sell – and unless your marketing strategy utilizes add-on products and upsells as a primary means of maximizing revenue, you might want to form a strategy around increasing purchase retention or frequency.

If you customer base is sticky and loyal, however, you can aim to optimize that monetary variable. Here are some top-level approaches:

  • Incentive customers to add products to carts and increase their baskets
  • Find customers who loyally purchase one product, and attempt cross-selling a second product to them
  • Bundle individualized products together

Naturally, none of these approaches take place in a vacuum. Every customer you’ve ever served is somewhere in a spectrum of recency, frequency, and monetary activity. Understanding how you can take advantage of those customer habits starts with using data to develop your best next move.