Latest / The Newsletter Podcast with Fexingo: Substack, Beehiiv, and Email Newsletter Business / How Newsletters Use Automated Segmentation to Double Open Rates
Transcript
- Lucas: There's this stat that gets thrown around a lot in newsletter circles: the average email list decays at about twenty-two percent per year. People churn, addresses go stale, engagement drops. Luna: Right — and most creators respond by just writing better subject lines or sending more frequently. Lucas: Exactly. But there's a more structural fix that a lot of people overlook, and it's one of the biggest levers you can pull without spending a dime on ads. I'm talking about automated segmentation. Luna: Segmentation isn't new — marketers have done it for decades. But what's changed is that tools like Beehiiv and Mailchimp now let you do it automatically, based on real-time behavior, with zero manual work. Lucas: Yeah. And the impact can be dramatic. I was looking at a case study recently from a mid-size newsletter — about fifteen thousand subscribers, B2B SaaS focus — and they implemented a pretty simple behavioral segmentation. Just a 'clicked in the last thirty days' versus 'did not click' split. Luna: And what happened? Lucas: Their open rate went from thirty-two percent to sixty-one percent in six weeks. They didn't change the subject lines. They didn't change the sending frequency. They just started sending different content to the active group and a separate re-engagement sequence to the inactive group. Luna: That's a huge jump. But it makes sense — if you're sending the same newsletter to someone who opened your last three emails and someone who hasn't opened in six months, you're basically spamming half your list. Lucas: Exactly. And the thing is, you don't need a sophisticated data science team to do this. The core idea is simple: tag subscribers based on their behavior, then route them into different content streams. Luna: So what are the key behaviors you should track? Lucas: I'd say three. First, opens — but opens are less reliable now with Apple's Mail Privacy Protection. Second, clicks — that's probably the most actionable signal. And third, conversion — like if they clicked through and actually bought something or signed up for a webinar. Luna: Right. Clicks tell you interest, not just curiosity. Lucas: Exactly. So you can build segments like 'frequent clickers' — people who clicked on any link in the last two weeks. 'Recent opens, no clicks' — they're still engaged but not converting. And then 'no engagement in ninety days' — that's your churn risk bucket. Luna: And what do you send to each? Lucas: To the frequent clickers, you send your best content — deep dives, product launches, maybe even sponsorship offers. They're your super-users. To the 'recent opens, no clicks' group, you send something more direct — maybe a single link with a clear call to action, test if they just need a simpler ask. And the churn risk group gets a re-engagement sequence: 'Hey, we noticed you haven't opened lately, here's what you missed, do you still want to be here?' Luna: And if they don't engage with that — cut them. It hurts, but a smaller active list is better than a big dead one. Lucas: Totally. And this is where tools matter. Beehiiv has built-in automation for this — you can create segments based on any combination of opens, clicks, and growth metrics. Mailchimp has similar functionality but it's a bit clunkier. Substack, interestingly, doesn't really support this natively — you have to export your subscriber list and do it manually or use a third-party tool. Luna: That's actually a big limitation for Substack writers who want to do serious segmentation. I've heard some people just use a separate tagging system with Zapier. Lucas: Right. But for most independent newsletter operators, the simplest starting point is just one rule: send a different email to anyone who hasn't clicked a link in thirty days. That alone can improve deliverability and engagement dramatically. Luna: It's also a way to test your content quality. If your open rate is fine but your click rate is dropping, that tells you the subject line is working but the content isn't delivering. Lucas: Exactly. And segmentation lets you diagnose that more precisely. You might find that your 'recent subscribers' click at a high rate but your 'subscribers for more than six months' don't — that could mean your content is getting stale for long-term readers. Luna: And then you can create a segment for 'subscribers older than six months' and test a different format or topic mix on them. Lucas: Yeah. And the feedback loop is tight — you see results in days, not months. Which brings me to another point: the data you actually need to collect. You don't need to track everything. Really, just two things: did they open? Did they click? That's enough to start. Luna: That's refreshingly simple. A lot of people overthink it and try to build a complex CRM. Lucas: Right. And the other trap is not cleaning your data. If you have a lot of inactive subscribers, your open rate looks artificially low, and your segmentation becomes less accurate. So you need to prune regularly. Luna: How often should you prune? Lucas: Quarterly is a good cadence. Remove anyone who hasn't opened or clicked in six months — unless you have a specific reason to keep them, like a paid subscriber who just doesn't open emails but is still paying. Luna: Paid subscribers are a different beast entirely. You obviously don't want to delete them. Lucas: No. But you might still segment them — maybe they get a separate 'paid-only' content stream. The point is, segmentation works for every type of newsletter, whether free or paid. Luna: Let's talk about a real example. There's a newsletter called 'The Hustle' — actually, they were acquired by HubSpot, but before that, they were famous for their segmentation. They'd send different versions of their daily email based on whether you subscribed via a referral link or a landing page. Lucas: Yeah. And they tracked not just opens and clicks, but also which specific article topics you clicked on. If you consistently clicked on crypto articles, you'd start getting more crypto-oriented subject lines. That's the next level. Luna: Is that overkill for a smaller newsletter? Lucas: It can be. I'd say start with just two segments: engaged and disengaged. Once you have that down, you can add more granularity. The risk is analysis paralysis. Luna: Makes sense. So the playbook is: pick one behavior, set up one automation, and measure the impact on open rate and click rate. Lucas: Exactly. And that's a strategy that actually works. A lot of newsletter growth advice is vague — 'write better' or 'build your list' — but this is a specific, measurable action you can take today. Luna: And it's refreshingly low-cost. Which, speaking of which — if these marketing conversations have sparked something you've actually used in your own newsletter, a couple of dollars a month is genuinely what keeps these episodes coming. You can find us at buy me a coffee dot com slash fexingo. Lucas: Yeah. No pressure, no perks — just a small way to keep this show ad-free and independent. Luna: Alright, back to segmentation. One thing I want to dig into: how do you actually set up these automations in Beehiiv? Lucas: Sure. In Beehiiv, you go to the 'Automations' tab, create a new workflow, and choose a trigger. The trigger could be 'subscriber opens an email' or 'subscriber clicks a link.' Then you add a condition: 'if they clicked, add to segment A; if not, add to segment B.' Then you define the action — send a specific email to that segment. It's all drag and drop. Luna: And you can also use tags. So if someone clicks a link about a specific topic, you can tag them with that topic and later send them targeted content. Lucas: Exactly. That's the next level. But even the basic 'clicked vs. not clicked' split is powerful. I've seen newsletters double their revenue from sponsorships just by showing advertisers a higher engaged subscriber count. Luna: Sponsors care about engagement, not raw numbers. A list of ten thousand engaged subscribers is worth more than fifty thousand dead ones. Lucas: A hundred percent. And segmentation is how you prove that engagement. So if you're a newsletter operator listening, I'd say pick one metric — clicks — and set up two segments this week. See what happens to your open rate over the next month. Luna: And if you need a tool, Beehiiv is the easiest for this, but Mailchimp's free tier can handle a basic split too. Lucas: Right. The key is just starting. Most newsletters never segment at all, so even a simple split puts you ahead of the majority. Luna: I think that's a good place to wrap. Next episode, we'll look at something a bit different: how newsletters are using AI to generate personalized content for each subscriber. Lucas: Looking forward to that. For now — go segment your list. Luna: See you next time.