Why You Need a RFM Revamp
Making it through the holidays is the hardest part of a retail marketer's job. But, after the New Year, it's hardly time to sit back and relax. What comes next can make or break how successful the next year could be.
Gift-givers flood our business, and we are so privileged to welcome them to our brand. But as soon as the calendar page turns, we must start the triage in order to engage, nurture, and ultimately activate more purchases across your shopper cohorts by separating new shoppers into categories to help with prioritization and strategic initiatives. The tried-and-true RFM framework (recency, frequency, monetary) is a good place for all retailers to focus to make the most headway with holiday buyers. From there, retailers can layer tactics like AI-driven triggers and KPIs like customer movement to drive more purchases throughout the year.
To manage the flood of recent buyers who represent everything from loyal repeat customers, to reactivated formerly lapsed buyers, to future high-value new customers, and of course plenty of gift-givers we may never see again. So, how to address this diversity?
RFM Revamp: Categorize, Prioritize, Optimize
The age-old approach of RFM (recency, frequency, monetary) modeling is a proven means of sorting through our customers and developing an approach for re engagement. Retailers can triage customers using the basis of RFM best practices with a boost from data, AI, and technology. Used here, RFM is a means of forecasting future value of our customers and reminds even the most sophisticated marketers to think about the future intent of our customers by how recently they bought, how frequently they bought, and how much in total have they spent over time.
The Clock Is Ticking to Further Activate First-Time Buyers
Recency, "R," comes first in the acronym because it's the most important consideration. The probability that one-time buyers will buy again goes down with each passing day in which they have not bought again. Thus, retailers need to act with urgency.
Marketers should work with partners to fully leverage marketing automation to set up onboarding campaign series that automatically re-engages through email, site, or SMS and push notifications. Equally important is to maximize relevancy through personalized recommendations. This is always true but especially so in January when the opportunity for establishing new relationships with new buyers is so ripe for turning them into repeat customers.
Marketers should also be building messaging templates that take advantage of available AI to intelligently introduce recent first-time buyers to things like accessory items or "next best" recommendations, replenishment notices based on past purchases, new items in the same category, and new-to-sale items. Ideally, retailers should be taking into account the signals that shoppers are sending based on their interactions with the brand, and tailor messaging to those signals.
The Opportunity of Multiplying Repeat Buyers
With recent first-time buyers accounted for, it is time to focus on the frequency shoppers. Statistically, repeat buyers are more likely to continue to repeat than one-time buyers. And when they repeat, they tend to spend more. The bottom-line profitability of repeat buyers is infinitely higher than first time buyers. With these repeat buyers, relevance is table stakes.
Use these available signals as they continue to interact with your brand to identify affinities and deliver more compelling touches.
Here are a few things to consider:
- Channel preference dictates which tactic they prefer, be that email, SMS or other. Check response rates often and stay on top of any changes in preference.
- Time of engagement indicates when they are most likely to respond to outbound. Remember that patterns can change over time and might be different by day of the week.
- Replenishment opportunities refer to any patterns that indicate they could benefit from a replenishment notice for things that need to be replaced or updated.
- Brand and category affinity signals help with prioritizing which items to introduce such as new arrivals or previews of items coming soon.
- Discount affinity can be determined using AI and help retailers ensure they are delivering the right discount - or none for shoppers who happily pay full price.
The list of tactics is only limited to our imagination, so retailers need to make the most of their tech investments to power signals-based relevance at every touchpoint. This is where AI and machine learning can do the heavy lifting for you.
Recapturing Your High-Net-Worth Shoppers
The "M" in monetary comes third in the acronym simply because if a buyer is not recent, and not frequent, but they have spent a lot in the past, they are statistically least likely to buy again. However, win back and reactivation campaigns paired with signals-based tactics and AI-driven relevance can help you sweeten the experience.
Here again AI and marketing automation can make very quick work of this part of our post-holiday triage. One approach is to simply pull lists of former top-quartile buyers and build re-engagement tactics. These can include:
- Seasonal campaigns. These capture and act on seasonal engagement patterns this shopper demonstrated in the past and perhaps, even the anonymous browse patterns of the present.
- Anniversary campaigns. Every probability curve has a jump up in probability to purchase as the shopper approaches the anniversary of their last purchase.
- Economics. Statically across all retailers we serve one pattern emerges consistently: Reactivated lapsed buyers spend more in the year during their period of reactivation than they do new buyers. Ironically, retailers spend to acquire new customers compared to what they are spending to reactivate former high-value customers.
This RFM framework is an easy way for us to organize our thoughts and consider the opportunity every new year brings. Remember, everything we do in retail marketing has a long-tail effect because we are not marketing to channels. We are fostering relationships with our brand. But with that, marketers need to capitalize on these short-term strategies in order to drive incremental revenue with what may be your largest shopper file in 2024.
The views and opinions expressed are solely those of the contributor and do not necessarily reflect the official position of the ANA or imply endorsement from the ANA.
Dave Lokes is VP of digital strategy at Bluecore.