Grow Customer Lifetime Value with RFM Segmentation.
It’s not that I love acronyms, but sometimes I forget not everyone is familiar with CLV and RFM. CRM, sorry… Customer Relationship Management, is a discipline that businesses invest in to increase customer lifetime value (CLV).
The strategy: to grow purchase frequency and AOV.
The tactics: loyalty programs, content personalisation, marketing automation, concierge services, exclusive offers, etc.
Technology is advancing at such a rapid pace that new AI-powered solutions are making it ever easier for D2C brands to simply plug their website into marketing automation and loyalty platforms and deploy personalised multi-channel communications at scale. However, while this is a great solution for fast-growing brands with relatively small teams, much of the detail which could be leveraged to truly accelerate growth is lost. Enter RFM segmentation…
RFM Segmentation is a method for dissecting your customer database by purchase behaviour (past, present, future):
Recency will tell you who of your customers are still active, who you could expect to have already shopped again and who have jumped ship. Recency could be calculated using static numbers that make sense for your business, or more dynamic values that are calculated for each customer based on their unique purchase history.
Frequency will highlight those customers that have only ever shopped once, those that are repeat buyers, and your hardcore fans that just can’t stop shopping with you.
Monetary value really does what it says on the tin. How much have your customers spent? You could calculate this over the customers lifetime (suitable for consumer goods purchased very infrequently, such as furniture) or over a certain period, e.g. 12 months (better suited to faster moving consumer goods such as skincare or apparel). You may also wish to set different spend thresholds for low, mid and high spenders based on their purchase frequency. A customer that has purchased only once and spent a quarter of what a loyal VIP spends, should be identified for having the potential to reach VIP status.
An example of RFM logic. In this case, a Lapsed Single Buyer VIPs is a customer that spent over £400 on their first order over 121 days (4 months) ago, but has not returned to shop.
Put another way…
Your frequent high spenders (whales – see chart below) will generate a disproportionately large sum of revenue for your business.
Your infrequent high spenders (calves, or young whales) will also be a relatively small cohort that have the potential to become whales, if they can be encouraged to shop more often.
Your frequent low-spenders (swordfish) will likely represent a proportionate sum of total business revenue in relation to their size.
The size of your infrequent low-spending segment (minnows) will far outweigh the commercial value they represent.
‘Whales’ represent only a small proportion of your customer base but will spend a significant amount of money with you - you should keep in close contact with these customers, regardless of their recency. ‘Minnows’ on the other hand will spend little and infrequently and you should therefore have a much less resource-intensive strategy for staying in touch with these customers.
If you then layer on recency data you can start to identify the right moment to contact your customers again, with the best proposition and most appropriate method of communication to achieve your objectives.
But what are your objectives? Taking the time to understand what success looks like, and which KPIs you should use to measure performance is key. It may look like this…
Increase the absolute number of 12-month VIPs who contribute a significant proportion of total revenue.
Drive a second purchase from single buyers (a strong indication of future loyalty).
Increase frequency, and therefore lifetime value of repeat buyers.
Reduce the rate of customer churn (i.e. reactivate more lapsing / lapsed customers).
An example of a comms strategy for single buyers that is differentiated based on recency and monetary value status.
Now you have a strategy for contacting the different segments of your customer database, you can start to establish the technology needed to execute it. This could be a CRM tool such as Hubspot, Salesforce or Sugar CRM; a machine learning personalisation solution such as Nosto, Algonomy or Yieldify; or even a CDP (Customer Data Platform) such as Optimove or Amperity.
If you’re looking to evaluate your CRM strategy and need support to understand the best approach, please feel free to get in touch for a free and informal chat.