How to Build an Email List Segmentation Strategy That Drives Sales

Some brands send the same emails to everyone. This is a missed opportunity as content isn’t relevant and deliverability issues often emerge. Other brands have so many segments it’s hard to manage, track over time, and create enough content for the campaigns to be relevant.

A smart segmentation strategy solves this. Brands that sort their list into groups based on how customers actually behave can send each group something relevant, driving more revenue.

Labyrinth’s approach balances the two common pitfalls.

Segmentation Is Grouping Customers by Behavior

Segmentation takes information a brand already knows about subscriber intent, and groups similar customers together. Knowing how long customers have been on the list, how many times they’ve purchased, and how active they have been recently provides a reliable idea of future intent.

The differences in segmentation approach come down to which metrics define the groups, and how the messaging shifts between each group once they’ve been sorted.

Starting requires a few metrics, and a plan for what to send to each group.

Pick the Right Sorting Metrics

Some data points about customers are more useful than others. Obviously, identifiers are useful for distinguishing profiles. Otherwise, three criteria matter:

Use data that already exists. Most email platforms track plenty of customer behavior by default, and that data is what strong segmentation is built on.

Use predictive metrics. What predicts future purchases? Past purchases. Customers who have bought are more likely to buy again. Recent activity like opens, clicks, and site visits suggests intent to buy.

Use metrics that change over time. Not just “has purchased” or “has clicked”, but how long ago the purchase or click occurred? Last 30 days? Last 90 days? In the last year? Time-bounded metrics create segments that change over time and allow marketers to track how people move through them.

Applying those criteria, for most ecommerce brands, Labyrinth recommends starting email list segmentation with two metrics: purchase activity and click activity. Purchases are the best signal that a customer values the brand. Recent activity shows customer engagement with the email channel. Together, these two metrics identify who the subscriber is, and how engaged they currently are with email.

For purchases, things are pretty simple. There are non-purchasers, purchasers, and multi-purchasers. These break down further based on recency of purchase. For activity, it’s similar: unengaged and engaged, broken down by recency of engagement: last 90 days, last 91-365 days, more than a year ago. Sure, individual activities could be counted, but it’s simpler to start. 3 (purchase groups) x 3 (activity groups) = 9 (segments).

Clicks > Opens. Apple’s Mail Privacy Protection basically automatically opens emails on iPhones. This makes open rates not as reliable as they once were. Click rate is still a reliable signal of genuine engagement.

Number of purchases > $ of purchase. One big order doesn’t prove loyalty nearly as well as multiple purchases. Number of purchases is a better predictor of future purchases.

Flexible time windows. 90 days is arbitrary, 365 days is arbitrary. Different brands work differently, so Labyrinth analyzes each client’s data to set cutoffs that fit their brand.

Tracking Changes in Email List Segmentation

Coming up with metrics and combining them into segments is the easy part, at least for experienced marketers. The strategy is the human part. Keeping the segments accurate over time is the ongoing data-wrangling work.

Export the customer list data from the email platform, including email address, number of purchases, last purchase date, last click activity date, and any other metrics worth including. Assign each customer to a segment based on the defined cutoffs. Build those segments back in the email platform. Repeating this monthly, or weekly, allows the team to track how people move from segment to segment, validating whether the method is working. Seeing lots of unengaged customers move into the recent purchase segments signals that the strategy is working.

Mailing Strategy for Each Segment

Once the groups are established, what to send them becomes much easier. This changes from client to client, depending on product category. A strong starting framework:

Number of Purchases / Most Recent Activity: 

• 0 / <90 days – Interested, haven’t bought it yet. Onboard them to the brand, with the goal of driving first purchase.
• 0 / 91-365 – Lapsing interest, bring back with social proof, reviews, or something targeted to what they were looking for.
• 0 / >365 – Drifted away, try to re-engage, then rest. Suppressing profiles reduces email platform costs.
• 1 / <90 days – New customers, very valuable. Strengthen relationship with the brand, and a great opportunity to drive a second purchase.
• 1 / 91-365 – Lapsing customers, so remind them of their purchase, then cross-sell.
• 1 / >365 – Lapsed customers, try an offer to re-engage, then suppress afterwards to reduce platform costs.
• 2+ / <90 days – Best customers, lead with recognition (perks, early access, VIP treatment) instead of discounts. They’re already buying.
• 2+ / 91-365 – Loyal but drifting. Something personal beats generic here.
• 2+ / >365 – Loyal, disappeared, still might buy again. Try something generous to re-engage, then rest the profile after.

Email List Segmentation Starts Simple, Then Expands

The best part of email list segmentation is realizing that most brands already have everything they need. Pick two metrics that describe customers, sort them into a few groups; the result is a pulse on the entire email list, and visibility into how people move in response to campaigns. Handle the tracking on a regular cadence and the team can focus on strategy.

Consistently using an email segmentation strategy based on purchase and engagement activity helps marketers uncover trends, deliver more relevant communications, and maximize the ROI of their email program.