Spring has finally arrived, and for most retailers that means something of a lull in holiday frequency (once Mother’s Day has passed), making it an ideal time to get a fresh perspective on email reporting.
RFM (Recency, Frequency, Monetary) scoring has long been the go-to method of ranking the value of customers on file. Historically, this metric has focused solely on purchase data — or lack thereof, if a customer is in the database but has not bought anything yet.
Adding email engagement on top of your RFM Scoring data can deliver a fresh look at the value of your customers, resulting in potentially new segments and messaging strategies.
What is RFM Scoring?
RFM scoring analyzes customers’ purchase history, including recency of the last purchase, frequency of purchases, and the monetary value of those purchases. This allows retailers to assign a score to each customer and appropriately group them as, for instance, “Loyal,” “Lapsed,” “VIP,” etc.
Marketers can then create messaging tailored to each group, work with analysts to monitor the results, and formulate strategies to increase customer scores in each segment, thereby moving them up the value chain. An RFM best practice has scores being consistently updated to let retailers understand whether or not the messaging strategies are working.
RFM-eRF
Adding email engagement metrics as an additional component to RFM Scoring can create a new perspective on this metric. Let’s begin by focusing on two dimensions of RFM Scoring as it relates to email: Recency and Frequency.
Specifically, how Recently has a subscriber interacted with your email marketing messages and how Frequently does a subscriber interact with your emails. Traditional RFM Scoring typically does not take into account if an email address is even on file for a customer. For this new perspective on RFM Scoring, we will focus only on customers with an email address on file.
In our example, we’ll take an online and catalog retailer, and we’ll shrink the customer universe by using only those customers with an email address on file. This data is pulled from purchase history (email address is given to receive order confirmation and shipment notification messages) as well as email subscription data. This universe is depicted as follows:
In the center is the overlap of customers who have both purchased and opted-in to receive email marketing messages. Because we need both order engagement data (RFM) and email engagement data (eRF) to create the RFM-eRF scoring, we focus on this subset of customers for the analysis.
Scoring
We then scored the 59,930 overlapping customers, splitting the group into engaged and unengaged segments. First, this group was split into two: Engaged and Unengaged. The Unengaged group was defined as anyone who had never opened or clicked an email (even though they had opted in), but had made a purchase in the past. Not surprisingly this split was nearly reflective of the 80/20 rule, resulting in 77% Engaged and 23% Unengaged.
From here, a score of 1-5 was assigned for the recency, frequency and monetary components of the purchase data, with a 1 being low. (For our purposes here we will bypass the criteria defining 1 through 5, but know that a 5 does not necessarily equate to a customer purchasing 5 times, or engaging with an email 5 times).
There are 125 different score combinations, displayed below. For example, if a customer scored as a 515 they would have purchased very recently (score of 5), but not very often (score of 1) and has a high lifetime value (score of 5). The best score possible for a retailer would be a 555.
But obviously 125 groups isn’t a realistic number of segments for marketing. After applying the scores, we identified seven segments.
Engaged Segments
Best Segment = Blue
Repeat Purchasers (dark blue)
Single Purchasers (light blue)
Good Segment = Green
Repeat Purchasers (dark green)
Single Purchasers (light green)
Opportunity within Recency Segment = Yellow (This segment of customers recently purchased, and we have the opportunity to increase their lifetime value through continued email communication)
Repeat Purchasers (dark yellow)
Single Purchasers (light yellow)
Opportunity within Monetary Segment = Violet (This group has a high lifetime value, interacted frequently with email at one time, but not recently and has not purchased recently)
Repeat Purchasers (violet)
Single Purchasers (pink)
Dormant Segment = Purple
Unengaged segments
These are not color-coded or displayed here, but they include:
Unengaged Subscribers with Opportunity (Purchased recently but not interacted with email)
Inactive (Subscribers recommended for suppression)
What do you do with this data?
One idea is to target the 99,000 email subscribers who have not made their first purchase. Targeted messages could be sent to this segment with a strong call-to-action to purchase.
When looking at the best segment’s metrics, we see that they are more likely to be a repeat purchaser if they are engaged with email. This is justification and reiteration to create more relevant communications and to optimize subject lines to increase the likelihood of an open or click, which is more likely to result in another purchase.
The Good segment, shown below, is frequently engaged with email messages, but there is a clear opportunity to increase their frequency of purchase. This requires further investigation to determine why the email messages are resonating with the subscriber but they are not purchasing. A situation like this one would be a great opportunity to look closely at your content and creative and do some testing to see how it’s performing and whether improvements can be made.
Customers in the Violet Segment (Opportunity within the Monetary Segment) have a high lifetime value, interacted frequently with email at one time, but not recently and have not purchased recently. Marketing messages could be developed to “win-back” this segment. If they can be enticed to interact with email, they are more likely to purchase and would be more likely to purchase at a higher average order value. This segment is worth retaining because of their lifetime value to the company.
Bridging the Gap
Remember not to look at email metrics in a vacuum. While open, click-through, click-to-open, and conversion rates are important and indicative of an email campaign’s success; the primary metric of focus should be sales.
Factoring in email metrics with purchase data can bridge the gap between the two and create a focus on segments for your email marketing program. By leveraging data, the segments are accurate and marketers can target messaging with a specific result in mind.
Updating the scores on an ongoing basis allows the marketer to justify the communication messages by showing results through customer score progression — a metric that translates nicely into the real world, where it represents a more frequently-ringing cash register and customers who are more loyal to your brand.
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