How evo Uses RFM to Refine Segmentation and Make Messaging More Relevant with Attentive

Building on a detailed segmentation strategy

evo serves customers across a broad product catalog, so audience decisions have to reflect different shopping patterns. Jess Tamez already used time since last purchase, site visits, abandonment behavior, and category purchase history to decide who should receive a message.

RFM wasn’t new to Jess. She’d used RFM models in previous email platforms and worked with an in-house model at a prior company that accounted for differences across the product catalog. Any new model had to add value without losing the business context she already used.

During the AI Pro segmentation beta, evo added RFM to its existing segmentation strategy.

“We still use these metrics, but then layer in RFM so we are hyper personalizing our messaging.”

— Jess Tamez, CRM Manager, evo

Putting customer value in evo’s context

RFM looks at how recently customers purchased, how often they buy, and how much they spend. Because the scoring reflected evo’s own subscriber data, it gave the team a customer-value signal grounded in the business.

That signal showed up in the performance data: from January 1–September 21, Champion and Loyal customers had a 22% higher conversion rate than evo’s other purchaser RFM groups combined.

“We layer in RFM to further identify cohorts of customers (usually Loyal / Champion) that will be responsive to our messaging, and exclude customers (usually Never Purchasers or Inactive) to drive our message efficiency.”

— Jess Tamez, CRM Manager, evo

Connecting loyalty points to a relevant offer

One practical use pairs RFM groups with loyalty points. For a sale, evo can reach Champion or Loyal customers who have redeemable points for eligible items, then add recency criteria to narrow the audience further.

Each signal answers a different question. RFM adds purchase history and customer value. Recent activity shows engagement. Loyalty points and sale eligibility connect that context to a reason to shop.

Together, those signals help evo build the audience around the offer. evo can apply the same approach within its product categories, where purchase behavior and catalog knowledge already shape campaign decisions.

Refining audiences for more relevant messaging

RFM helps evo decide which customers are most relevant for each send, narrowing or broadening audiences based on the message, priorities, and performance. That sharper targeting can also help the team use channel budget more efficiently.

From January 1–September 21, Champion customers generated 28% more attributed revenue per delivered message than evo’s other purchaser RFM groups. From August 1–21 to September 1–21, attributed revenue from Champion customers increased 111% as delivered volume rose 26%.

“Audience efficiency has been a focus of ours to maximize channel budget. Using RFM to identify and target more appropriately for the message we are sending allows us to expand our budget further.”

— Jess Tamez, CRM Manager, evo

Pairing RFM with marketer judgment

RFM adds another signal to evo’s decision-making, but business and product knowledge still matter.

“RFM is another tool in the marketing toolbox to pair with your own knowledge of your file that strips away bias and helps identify customers that meet parameters. Pair that with your own knowledge of your file and product catalog, then 1+1=3.”

— Jess Tamez, CRM Manager, evo