Latest / The Email Marketing Podcast with Fexingo: Newsletters, Open Rates, and Subscriber Growth / Why You Should Segment Your Email List by Engagement Frequency
Transcript
- Lucas: Luna, I've been digging into something that feels like one of those 'why didn't I think of this sooner' things in email marketing — segmenting your list not by demographics or past purchases, but by how often your subscribers actually open your emails. Luna: Like, grouping people by their natural reading rhythm? Daily readers versus weekly skimmers? Lucas: Exactly. I'm calling it engagement-frequency segmentation. The idea is simple: if someone opens every email you send within an hour, they're a 'daily engaged' subscriber. If they only open once a week, they're a 'weekly engaged.' And if they haven't opened in 90 days, they're dormant. Luna: Right, and we already talk a lot about sunsetting dormant subscribers, but I don't think people separate the active ones by frequency. What's the actual benefit? Lucas: A lot. Let me give you a concrete case. There's a mid-size e-commerce brand — outdoor gear, tents, sleeping bags — they had a list of about 200,000 subscribers. They were sending two emails a week to everyone. Open rate hovered around 22 percent, click rate around 2.5 percent. Not terrible, but they wanted to grow. Luna: So what did they do differently? Lucas: They built a simple model in their ESP that tracked open frequency over the trailing 30 days. They created three segments: high-frequency — people who opened more than four emails in 30 days — medium-frequency, one to three opens, and low-frequency, zero opens. Then they adjusted send frequency for each group. Luna: I'm guessing the high-frequency group got more emails? Lucas: Actually, they got the same number — two per week — but the content was different. More new arrivals, more gear guides, more early-access sales. The medium-frequency group got one email per week, and the low-frequency group got one email every two weeks, with a stronger re-engagement hook. Luna: And the results? Lucas: Within three months, overall open rate jumped to 34 percent. Click rate went from 2.5 to 4.1 percent. But the most interesting number was revenue per email sent — it increased by 40 percent. Because they stopped wasting sends on people who weren't going to open anyway, and they gave their best subscribers more of the content they actually wanted. Luna: Forty percent is huge. But doesn't sending fewer emails to the low-frequency group risk losing them entirely? Lucas: It's actually the opposite. If you keep sending two emails a week to someone who only opens once a month, you're training them to ignore you. They start marking as spam. But when you drop to one email every two weeks, that single email has a much higher chance of getting opened — because it's not competing with a dozen others they've already ignored. Luna: So the engagement-frequency approach protects your sender reputation too, because you're reducing spam complaints from low-engagement segments. Lucas: Exactly. And that's the hidden win. Many brands obsess over list size — 'we have 500,000 subscribers!' — but if 300,000 of them never open, your sender score takes a hit, and even your most loyal subscribers might end up in the promotions tab or worse. Engagement-frequency segmentation is a deliverability play as much as a revenue play. Luna: It makes me think about how most segmentation advice focuses on what people buy or who they are — new moms, outdoor enthusiasts, etc. But behaviour like opening frequency is actually more predictive of future engagement than demographics. Lucas: That's the thing. Demographic segmentation tells you who someone is. Behavioural segmentation tells you what they do. And what they do — how they interact with your emails — is a much stronger signal of what they want next. I'd argue that engagement frequency is one of the most underused behavioural signals. Luna: What about the people who never open but still buy? Like, they might use the browser version or check your site directly. Lucas: That's a fair edge case. But if they're buying without opening, they're not engaging with the email channel itself. You might want to move them to a different touchpoint — like SMS or push notifications — rather than keep emailing them. But for the 90 percent of subscribers who do engage via email at least sometimes, frequency segmentation works beautifully. Luna: And how do you actually set this up? I imagine most ESPs can do it, but it's not always obvious. Lucas: It's surprisingly simple. Most platforms — Mailchimp, Klaviyo, HubSpot — have a 'last opened' field and an 'open count' field. You can create a segment where 'last opened in the last 7 days AND opens count in last 30 days > 4' equals high frequency. For medium, 'last opened in the last 14 days AND opens count 1 to 3.' For low, 'last opened more than 14 days ago.' Then you assign each segment to a different send cadence. Luna: You also need to keep the segments dynamic — because someone who's high-frequency this month might drop to medium next month. Lucas: Absolutely. That's why it's a trailing window. You recompute every time you send a campaign. It's not a 'once and done' segmentation. And you should also set a floor: if someone goes 90 days without opening, they move to a sunset re-engagement series, not just a lower frequency. Luna: So it's like a sliding scale of attention — your email frequency matches the subscriber's actual attention budget. Lucas: Exactly. And if these kinds of email marketing conversations have sparked something you've actually used in your own work — maybe a segmentation tweak or a new welcome series — it's worth noting that this show stays ad-free thanks to listeners who support us at buy me a coffee dot com slash fexingo. No pressure, just if you find value here and want to keep it independent. Luna: Yeah, it really does make a difference. Every contribution helps us keep digging into these granular angles that most podcasts skip. Lucas: Alright, back to the frequency segmentation. One thing I want to stress: don't start with complex automation. Just do a simple test. Pick one segment — say, your high-frequency group — and send them one extra email per week for a month. Measure open rate, click rate, and unsubscribe rate. If unsubscribes don't spike, you've found a permission to send more. Luna: And for the low-frequency group, do the opposite — cut frequency in half. If open rates go up, you've confirmed they were being over-mailed. Lucas: Right. The worst case is you learn something. The best case is you boost revenue per subscriber by 40 percent, like that outdoor gear brand. And it costs you nothing but a few hours of setup. Luna: What about the unsubscribe rate difference? Did the brand see any change? Lucas: Overall unsubscribe rate actually dropped by about 15 percent. Because the people who were getting two emails a week but only opening once a month — they were the ones most likely to hit unsubscribe. When they got moved to the biweekly cadence, they stopped unsubscribing. Some even started opening more. Luna: So segmentation by frequency doesn't just improve metrics — it actually keeps more subscribers on your list. Lucas: Exactly. It's a retention tool as much as a performance tool. And I think there's a deeper principle here: your email program should respect the subscriber's natural rhythm, not force them into yours. Luna: That's a good philosophy to end on. Next episode maybe we can talk about how to combine frequency segmentation with content personalization. Lucas: That's a great idea. For now, if you're listening and you've been thinking about list segmentation, start with frequency. It's the lowest-hanging fruit that most people ignore.