Insights to Action Series
[Part 6 – RFM]
By Liz Emery, Senior Director, Product Marketing
Insights to Action Series [Part 6 – RFM]
Welcome back to Affinity’s “Insights to Action” blog series, exploring how to use Consumer Purchase Insights to solve complex business problems. Consumer Purchase Insights provides a complete, granular view of customer and prospect purchase behaviors, across and between brands and categories, to inform a wide array of growth strategies based on deeper audience understanding. This is part 6 of an 8-part series where we dive into different examples of how to gain insights into – who your consumers are, how they spend, and where they buy – to inspire meaningful action. If you want to read about market share, cross shop, new to brand, churn and loyalty, check out the first 5 blogs below.
- Introducing: Insights to Action Series [Part 1 – Market Share]
- Insights to Action Series [Part 2 – Cross-Shop]
- Insights to Action Series [Part 3 – New to Brand]
- Insights to Action Series [Part 4 – Churn]
- Insights to Action Series [Part 5 – Loyalty]
Part 6: RFM
Reach, Frequency, Monetary Value or RFM, is one of the oldest and most widely recognized segmentation frameworks. At its core, RFM is a ranking tool for existing customers. Running this analysis allows marketers to segment customers from high to low based on recency of purchase, frequency of purchase, and total spent or monetary value. This analysis helps answer business critical questions like…
- How recently have customers shopped with my brand?
- How many annual transactions have my customers made?
- How much do customers spend on my brand?
The answers to these questions (and others) about an existing customer base allow marketers to understand the varying levels of engagement with their brand to better tailor marketing strategies as buying behaviors change. Understanding how your customers behave identifies opportunities for stronger personalization in messaging, opportunities for re-engagement and cross-selling.
Being able to react quickly to shifts in customer behavior, for example, a decrease in how often your customers buy, helps protect revenue loss as OR before it happens. If a brand does not have a strategy in place to segment their customers based on behaviors, they are left vulnerable to shifts that impact business health. To get ahead of the game, let’s discuss how RFM analysis can help.
Using Insights to Create an Action Plan
Most analysts group customers together based on RFM segments or deciles. When compiling the segments, the breakpoints or set frequencies/recencies/monetary values are unique to each brand and set using internal data. For example, if you placed an order with a large online retailer yesterday and also made 10+ purchases with them in past 3 months (spending $1,000+), you would be in their top RFM segment, but for a smaller retailer, you only need to have spent $100 in the past 3 months to be considered a “top segment.” The buckets for each segment are customizable based on verticals, purchase cycles and more.
Affinity Solutions has conducted RFM analysis on 3,000+ brands, using actual transaction data. The data is captured daily from over 140 million credit and debit card holders, representing over 8.8 billion annual transactions and $400 billion in annual spend. Affinity segmented every shopper for each of the 3,000+ brands and classified them as High (H), Medium (M) and Low (L) for each of the 3 RFM dimensions – yielding 27 permutations ranging from “High Recency –High Frequency –High Monetary Value” or HHH to “Low Recency – Low Frequency – Low Monetary Value” or LLL.
The 27 permutations or groupings were further classified into 4 high-level segments: Loyalists, Potential Loyalists, Promising and At-Risk. Loyalists, as the name implies, represent the best of the best (High in all 3 categories of RFM), while the At-Risk decile represents shoppers that are trending towards lower scores across all 3 RFM categories. They may not have stopped buying completely but their behavior is showing a downturn in engagement, so they deserve attention.
The table below illustrates the RFM landscape for a large coffee retailer. The left side of the chart quantifies the percentage of the coffee retailer shoppers across the 4 RFM segments we created above from 2019-2022. Here we see the retailer has done a strong job maintaining a healthy Loyalist customer base (~30%), however, they have an equal percentage of customers in the At-Risk segment showing marketing opportunity (in red).
On the right side of the chart, we see the total spend (or monetary value) of each segment from 2019-2022. Here we see the 80/20 rule playing out – where 80% of a brand’s sales come from 20% of their customers (or in this case, a bit higher at 30%, which is often true for dominant brands).
Why does this matter? RFM matters because it creates a framework for insights and differentiated marketing treatments to prevent large swings in revenue. Marketers value their top RFM segments and model against their top RFM deciles. Using these models, they can target look-a-likes within the lower ranking RFMs and across prospecting universes with the goal of increasing purchase frequency, recency, and order size.
The “R” in RFM is especially important to most brands. If you have a customer that is scoring high in frequency and high in monetary value, but has declined to shop recently, they might be an ideal candidate for a reactivation campaign. It is important to track how the brand is doing with all RFM segments – overall, by geography, by demographic, and over time. We also recommend benchmarking how the brand is doing against other brands in the category for brand health. To learn more about Consumer Purchase Insights loyalty reach out to Sales@affinitysolutions.com.
That wraps up Insights to Action [Part 6 – RFM]! Stay tuned for Insights to Action [Part 7 – Brand Overlap] where we dive into how your customers overlap with other brands and how to identify opportunities for collaboration.