Segmenting and targeting “best customers” based on the traditional RFM past-purchase model (1. How recently they’ve purchased; 2. How frequently they’ve purchased; 3. How much money they’ve spent), has long been a cornerstone for retailers and other brands.  And it will and should continue to be.

But there are obvious gaps in this approach—gaps that can be filled with a new metric: Recency and Frequency of attendance, or “RFA,” based on customers’ physical visits to local events, activities and places.

Let’s first look at the shortcomings of purchase-based RFM: 

1. It provides virtually zero insight into current and future buying motivations, leaving brands to make semi-informed guesses as to what content and offers to present, and no idea as to when to present them;
2. It tells brands nothing about the share-of-wallet they’re getting from customers—even their best ones--versus the competition, and gives them nothing to do about it;
3. It doesn’t inform brands on how well their marketing outreach is doing at driving customers into their stores;
4. It gives no insight into whether customers buy for themselves versus for someone else—resulting in wasted retargeting to (and annoyance of) customers who bought gifts for others

Now, let’s see what RFA adds, by looking at a few examples:

Retailer A offers a range of high-end sporting apparel and accessories. With RFA, the brand would know:

1. That a large group of customers that ran in at least three 5K races over the past 90 days, visited one of its stores on average once in that time period, and visited its top competitor three times.
2. That this group is made up of avid runners, receptive to content and offers for running apparel and accessories.
3. To target this group for 48 hours after each race these consumers participate in, and re-target them beginning one week prior to each upcoming race.
4. Exactly how many of these customers visited one of its stores as a result of the outreach.

Retailer B offers a range of maternity and baby clothing, furniture and accessories.  With RFA, the brand would know:

1. That a significant portion of customers that have attended at least four local birthing or parenting classes over the past three months, but very few of them have visited its stores and on average, visited a competitor four times.
2. That these customers are Parents to Be, receptive to content and offers for maternity and newborn clothing and accessories.
3. To target these customers for 48 hours after they attend each class, and re-target them beginning two weeks prior to each upcoming class.
4. Exactly how many of these customers visited one of its stores as a result of the outreach.          

So, while past purchase insights are important, brands can now know the local events and activities customers recently and frequently attend, and know when and where similar events are about to occur, giving them:

1. Conclusive, predictive insight into what customers are personally interested in, so they can present offers aligned to their individual passions;
2. An individualized way to reach them with offers that align to their interests using event based targeting--when they’re most likely to respond;
3. Gives them precise knowledge of the share-of-foot traffic they receive from customers—and the share of visits they lose to competitors--so they can execute campaigns aligned with customers’ current interests to increase share-of-wallet