Latest / Marketing Automation with Fexingo: HubSpot, Marketo, and Automated Customer Journeys / How Marketing Automation Benchmarks Mislead Your Strategy
Transcript
- Lucas: So you're reading a marketing automation report in early 2026, and it says the average email open rate for your industry is twenty-two percent. Your last campaign hit eighteen percent. You think, 'We're underperforming.' But what if that benchmark is actually misleading you? Luna: I've been there. And I think a lot of marketers are, especially when they're trying to justify budget or set targets. But you're saying the benchmark itself is flawed? Lucas: Exactly. The problem is aggregation. A single average number like twenty-two percent lumps together everything from a one-person real estate agent's weekly newsletter to a Fortune 500 B2B SaaS company's transactional triggers. Those are fundamentally different email programs. The average is meaningless unless you're comparing apples to apples. Luna: And even then, the platforms themselves distort the data. Apple's Mail Privacy Protection, for instance, inflates open rates because it pre-loads pixels. So a benchmark from a report that doesn't account for that is already off. Lucas: Right. Let's take a concrete example. A HubSpot benchmark report from late 2025 showed that the median open rate for marketing emails across all industries was about twenty-three percent. But if you segmented by company size, companies with fewer than fifty employees averaged around twenty-seven percent, while enterprises with over a thousand employees averaged nineteen percent. So if you're a small business looking at that twenty-three percent, you might think you're average, but actually you should be aiming higher. Luna: And that's just company size. What about industry? I remember a Marketo study that broke down open rates by vertical. Healthcare was around twenty-eight percent, while retail was closer to eighteen percent. But the overall average was still twenty-two. So if you're in retail, you're comparing yourself to a number that includes healthcare, and that's not fair. Lucas: Exactly. And it gets worse when you look at click-through rates. The global average click-through rate for marketing emails is somewhere around two and a half percent. But that's across all industries and all campaign types. A triggered welcome email might have a click-through rate of ten to fifteen percent, while a promotional blast might be under one percent. So if your welcome email is at eight percent, you might think it's underperforming against the two-point-five average, but actually it's doing great. Luna: So the real question is: what should marketers use instead? Because we can't just throw out benchmarks entirely. They're useful for context. Lucas: The answer is internal benchmarks. Your own historical data is the most relevant comparison you have. If your October newsletter had a twenty percent open rate and your November one hit twenty-two percent, that's improvement. That's actionable. Comparing your October newsletter to a random industry average doesn't tell you anything about your audience or your content quality. Luna: And internal benchmarks also account for your specific list hygiene, your sending frequency, your time zone. All those variables that an industry report can't possibly control for. Lucas: Right. So the framework I recommend is this: first, establish your own twelve-month rolling average for each key metric by campaign type. Second, segment that by audience, like leads versus customers versus inactive. Third, track outliers—if a campaign outperforms your internal average by twenty percent, study why. If it underperforms, study that too. That's how you learn, not by chasing a number from a report. Luna: I had a client last year—a B2B SaaS company—who was obsessed with beating the industry average open rate. They were at around fifteen percent, and the benchmark they saw was twenty-two percent. So they started using more clickbaity subject lines, more urgent language. Their open rate went up to eighteen percent, but their unsubscribe rate tripled and their click-through rate actually dropped. They were optimizing for the wrong metric. Lucas: That's the classic benchmark trap. You optimize for the metric that's being compared, not the metric that drives business value. In marketing automation, the ultimate metric isn't open rate—it's revenue attributed or at least conversion rate. But those are harder to benchmark externally because they're so specific to each company's product and pricing. Luna: So what about the platforms themselves? I've noticed that HubSpot and Marketo both have their own benchmark dashboards now. Are those any better? Lucas: They're better because they can segment by industry and company size and sometimes by campaign type. But they still have the aggregation problem. HubSpot's benchmark tool, for example, shows you how your email performance compares to 'similar businesses,' but that's based on self-reported data from HubSpot customers. Self-reported data is always noisy. Plus, it's biased toward HubSpot's user base, which tends to be smaller companies and more marketing-savvy. So if you're using Marketo and comparing yourself to HubSpot benchmarks, you're comparing two different user populations. Luna: And there's also the issue of how different email clients handle tracking. Gmail and Outlook have their own algorithms for filtering and pre-loading images. So open rates on Gmail can be inflated compared to Outlook. If your audience is mostly Gmail users and the benchmark is based on a mix, you're going to look better or worse depending. Lucas: Exactly. Some reports try to adjust for Apple's Mail Privacy Protection by excluding opens that happen within a second of send or something like that. But those adjustments are imperfect and vary by vendor. So the raw numbers from different platforms are not directly comparable. Luna: Let's talk about conversion rate specifically. That's the one metric that really matters for revenue, but it's rarely benchmarked well. Why is that? Lucas: Because conversion rate depends on so many things outside the email itself: your landing page, your offer, your pricing, your market conditions. A benchmark for conversion rate would have to control for all those variables, which is basically impossible. So most reports don't even try. They just give you open and click rates and maybe bounce rates. But those are proxies, not outcomes. Luna: So if I'm a marketer listening to this, what's my takeaway? Should I ignore industry benchmarks entirely? Lucas: Not entirely. They can be a useful sanity check, but you have to understand their limitations. Use them as a rough directional guide, not a target. If your open rate is five percent and the industry average is twenty-two, something is probably wrong. But if you're at eighteen and the average is twenty-two, that difference could be noise. The real question is: are you improving against your own baseline? And are your campaigns driving the business outcomes you care about? Luna: I think a lot of marketers also forget that benchmarks change over time. What was average in 2023 is different in 2026. Email fatigue, algorithm changes, privacy regulations—they all shift the baseline. So a benchmark from two years ago is probably worthless. Lucas: Great point. And that's another reason to rely on your own rolling data. It automatically adjusts for those macro trends because your audience is experiencing them too. Your open rate might drop from twenty percent to eighteen percent over a year, but if your competitors are also dropping, then your relative position might be fine. An industry benchmark from a report might not capture that shift quickly enough. Luna: Okay, so I want to dig into a specific example. Say I'm a B2B company sending a monthly newsletter. My open rate has been steady at twenty-two percent for six months. My click-through rate is two percent. Should I be worried? Lucas: It depends on your goals. If your newsletter is primarily for brand awareness, then open rate matters more. If it's for lead generation, then click-through rate matters more. But a two percent click-through rate is actually pretty typical for a B2B newsletter. The global average is around two to three percent. So you're right in the middle. But again, the better question is: are those clicks converting? If they're not, then you might need to revisit your call to action or your landing page. Luna: And what about the size of the list? A lot of benchmarks don't account for list size. A company with a hundred thousand subscribers will naturally have lower engagement than one with a thousand, because it's harder to maintain relevance at scale. Lucas: Absolutely. List size correlates negatively with engagement metrics. That's a well-known fact in email marketing. So if you're a small company, you should expect higher open and click rates than a large enterprise. But most benchmarks don't segment by list size. They just give you one number. Luna: I think one of the most dangerous uses of benchmarks is in setting bonus targets. I've seen marketing teams get penalized because they didn't hit an industry average that was unrealistic for their specific situation. Lucas: That's a great point. If your boss says 'I want you to achieve a twenty-two percent open rate because that's the industry average,' and you're a small B2B company with a cold list, that's a recipe for gaming the system. You'll end up sending to a smaller, more engaged segment to hit the number, which might actually hurt your overall pipeline. Luna: So what's the solution? How do you convince stakeholders to move away from external benchmarks? Lucas: You show them the variance. Pull a report from your own platform that shows open rates by campaign type, by list segment, by time of day. Then compare that to the industry average. If the variance is huge, explain why. Say, 'Our transactional emails have a forty percent open rate, but our promotional emails have ten percent. The industry average of twenty-two percent doesn't represent either of those. Let's set targets based on our historical performance for each type.' Luna: And if they still push back? 'But the CEO read this report...' Lucas: Then you educate. Explain the methodology behind the report. Most marketers don't realize that many benchmark reports are based on opt-in panels or self-reported data, not a random sample. Some reports are even produced by platforms that have a vested interest in making email marketing look effective or ineffective. The Mailchimp benchmark report, for example, is based on their own user data, which is a specific population. Luna: Right. And if you're using a different platform, that benchmark might not even apply. I think the key takeaway is: benchmarks are a starting point, not a destination. Lucas: Exactly. Use them to get a rough sense of where you stand, but dig into your own data for real insights. And if you're going to compare, make sure you're comparing to the right segment. That's where the real value is. Luna: I want to pivot slightly to something you mentioned earlier—the idea of building your own internal benchmarks. That's something we've talked about with listeners before, and I think it's one of the most valuable things you can do for your marketing automation program. Lucas: It really is. And if these conversations have sparked something you've actually used in your own work—maybe you've set up your own internal benchmark dashboard or started questioning the numbers in those reports—then that's exactly the kind of practical takeaway we hope you get from this show. Luna: Yeah. And we deliberately keep this show free of ads because we want to focus on content that's actually useful, not on promoting products. So if you find value in what we're doing, and you want to support that choice, you can buy us a coffee at buy me a coffee dot com slash fexingo. Lucas: No pressure, honestly. But if it helps you keep getting episodes like this one, it's a nice way to say thanks. And now, back to benchmarks. I want to talk about one more thing: the future of benchmarking in an ai driven marketing world. Luna: Oh, that's interesting. Because AI is changing how emails are written and personalized. So benchmarks might shift even more. Lucas: Exactly. AI tools like ChatGPT are being used to generate subject lines and body copy. That means more emails are being sent, and they might be more similar in tone. That could compress open rates because everyone is using the same optimization tricks. On the other hand, ai driven personalization could lift engagement for those who do it well. So the benchmark landscape is going to get even more noisy. Luna: So the advice to rely on your own historical data becomes even more important. Because the external averages might be shifting in unpredictable ways. Lucas: Right. And I'd add one more thing: start tracking what I call 'composite benchmarks'—metrics that combine multiple data points, like click to open rate or revenue per email. Those are less commonly reported externally, so you won't be tempted to compare. And they're more closely tied to business outcomes. Luna: click to open rate is a great one. It measures the quality of your content, not just the subject line. And it's less susceptible to open rate inflation from Apple's privacy changes. Lucas: Exactly. So if you take nothing else from this episode, remember: the best benchmark is your own past performance. Everything else is just context, not a target. Luna: And if you're looking for a place to start, try pulling your last twelve months of data and calculate your own averages by campaign type. You might be surprised at what you learn. Lucas: That's a great action item. Alright, that's our show for today. Thanks for listening, and we'll see you next time.