Customer behavior changes are being driven by COVID-19 — Segments that were once predictable are nowhere to be found. New customers are popping up that weren’t even on the radar. It’s tough for marketers to get a grip on all of this, but with adversity comes opportunity, right? The fact is, marketers can figure out these changes easily, fast and with actionable insight. An enhanced Recency, Frequency, Monetary Value (RFM) analysis can score their best customers to create a lookalike audience.
The enhanced RFM analysis produces targetable segments with a few new data points that identify your most valuable customers now. “Now” being the important part of the equation. Your most valuable customers nowprobably aren’t the same as six months ago, so looking at today’s data is more important than ever. That is how we create the enhanced RFM analysis: we take a separate cross-section of customers.
For example we conducted a survey that revealed customers who dine within the first week of a restaurants reopening are less concerned about COVID-19 precautions. If we take that group of customers and overlay over our RFM analysis, we are able to include non-COVID messages to those that most reflect our top customers.
Run the Analysis
Running the Enhanced RFM Analysis will divide your customer list into segments based on a score based on how recently they purchased from you, how frequently and how much money they spent.
The basic RFM segments and how to engage them include:
These are your best customers who bought the most recent, most often and spent the most. They have proven through repeat, high value purchases that they are fans, so you don’t need to try to discount them into their next purchase. Instead, focus on add-on purchases like new or complementary products. Loyalty programs are perfect for this segment.
These customers buy most often. They may not spend as much as the best customers, but they’re regular and predictable. For this segment, you can try to increase their average purchase with offers like “Free Shipping When You Spend $______!” Loyalty programs are also good for this segment.
These customers have spent the most with your company, but it could be in one or a few purchases rather than a lot of low to medium sized purchases over time. Because they have a propensity to spend big, you don’t have to discount. Try to drive more frequent purchases with subscriptions, recommendations and upsells. These customers often respond well to VIP offers as well.
This customer segment visits often, but doesn’t spend a whole lot with each visit. The goal here is to increase the average order, so add-on products and recommendations are a good fit.
These are your new customers. In today’s COVID climate, you want to pay particular attention to this segment as they may form your “new normal” customer. It’s important to have a customer journey in place to onboard new customers to educate them on how to get the most value out of your products and services. Also, asking for reviews and referrals are great ways to reach additional like minded consumers.
The Ex segment is just that – they’ve broken up with you. Things used to be great, but they haven’t been back in a long time. Sometimes situations change and you won’t win these customers back. It is worth sending out some periodic touches with special promotions and new products/services to generate and pick some of these folks back up.
Find Your New Best Customers
Once you’ve identified your customer segments and determined what marketing approach you want to take within those segments, it’s time to use your data to find your new customers – ones that will behave like your best customers.
The move here is to create lookalike audiences to test your offers to. The biggest players in technology have opened up their AI supercomputers to allow us to harness their massive data sets so we can find people who look like our best customers.
Here are a few links to get started:
Google – Similar Audiences and Customer Match
Facebook/Instagram – Lookalike Audiences
LinkedIn – Lookalike Audiences using Matched Audiences
There are some nuances to how to create lookalike audiences on each of the platforms, but the idea is the same.
Take the RFM segment you want to find more of (for this we’ll assume Besties) and import the appropriate data to the platform to create a targetable audience. These are your best current customers, so that audience has value in itself for retargeting on the platform.
Once you have the Besties RFM segment in the system, you create a lookalike audience on the platform using their big data and computing horsepower. The result will be a second custom audience that should look a lot like your Besties. This allows you to put your offers in front of these highly target prospects to win new customers.
Different companies, industries, offers, timing — all produce different results. Your results will vary, but it’s definitely a data-driven method worth testing to see how your customer acquisition costs compare using enhanced RFM analysis and lookalike models versus other methods.