The Myth of the Universal “Good” Open Rate: Why Averages Lie
Introduction – The Question Every Marketer Asks
I’ve been in rooms—boardrooms, Slack huddles, post-mortem calls—where this question comes up like clockwork. Usually, it’s a founder who just got their first Mailchimp report, or a marketing director staring at a dashboard wondering if they should be celebrating or panic-hiring. “What’s a good open rate?” they ask. And they want a number. They want to hear “22%” or “18%” so they can exhale and move on with their day.
Here’s what I’ve learned after managing email programs for SaaS companies with million-subscriber lists, tiny e-commerce brands just getting started, and nonprofit clients where every open literally translates to a meal served or a petition signed: the question itself is a trap.
Not because open rates don’t matter. They do. But because asking for a universal “good” open rate is like asking what a good salary is. For a software engineer in San Francisco? For a teacher in rural Mississippi? For a freelance artist in Berlin? The number is meaningless without context. And when you take that context-free number back to your team, you’re making decisions based on a ghost.
Why “What is a good open rate?” is a trick question
The email marketing industry has spent twenty years training marketers to ask the wrong question. Software platforms show you a number, color-code it green or red, and suddenly that number becomes a proxy for your entire competence. But open rates don’t exist in a vacuum. They are the result of a chain of events that started long before the send button was clicked.
I’ve consulted for a skincare brand that launched with a list of 500 friends, family, and early Kickstarter backers. Their first campaign opened at 68%. They thought they were geniuses. Six months later, after scaling to 15,000 subscribers through a pop-up discount, their open rate settled at 12%. The list hadn’t gotten worse. The audience had changed. The open rate was telling a story about who was on the list, not just about how good the subject lines were.
That’s the trick. Open rates are primarily a reflection of audience composition and deliverability infrastructure. Content matters—I’m not saying it doesn’t. But when someone asks me for a benchmark number, my first question back is always: “Tell me about your list. Where did it come from? How old is it? What’s your double opt-in rate?” If I don’t get answers to those questions, any number I give is just noise.
The danger of fixating on a single number
I’ve watched marketers do genuinely destructive things because they were chasing a number they read in a blog post.
They start buying lists—which is a fast track to spam folder purgatory—because they see their open rate dip below some mythical industry average and panic. They start sending clickbait subject lines that get the open but destroy trust with the audience. They stop emailing engaged segments because they’re afraid to annoy people, letting warm leads go cold while they obsess over a metric that was never meant to be a primary KPI in the first place.
Here’s what actually happens when you fixate on a single number: you optimize for the number, not the business outcome.
I worked with a B2B software company a few years back. Their open rate was hovering around 18%, which according to some benchmarks was “average.” The head of marketing was obsessed. We ran tests. We changed subject line structures, send times, preheader strategies. We got the open rate up to 24% in three months. Everyone was thrilled.
But revenue from email didn’t move. Not a dollar.
Why? Because we had optimized for opens, not conversions. We were writing subject lines that were curiosity-driven but disconnected from the offer. People opened, saw the email didn’t match the intrigue, and bounced. Click-through rates actually dropped during this period, even as opens went up.
The single-number fixation almost cost them a quarter of revenue growth because we were solving for the wrong variable. That’s the danger. You end up with a dashboard that looks good and a bank account that doesn’t.
The Problem with Averages: Apples vs. Oranges
I want to be clear about something: benchmarks exist for a reason. They give you a sense of the landscape. But they are descriptive, not prescriptive. Knowing that the average open rate for e-commerce is around 15% doesn’t tell you what your open rate should be. It tells you what everyone else’s is, across thousands of businesses with wildly different lists, products, and audiences.
Industry benchmarks: A starting point, not a finish line
Let’s look at the real data. I keep a running spreadsheet of benchmark reports from the major email service providers—Mailchimp’s annual report, Constant Contact’s benchmarks, HubSpot’s marketing statistics, and a few industry-specific reports from Klaviyo and Omnisend. The patterns are consistent, but the spread is enormous.
Nonprofit & religious organizations (The 45% club)
I’ve worked with two different nonprofits. One was a large international aid organization. The other was a regional food bank. Both had open rates that would make most marketers weep with envy—consistently in the 40-50% range.
Why? Because the audience wants to hear from them.
Nonprofit subscribers are self-selected. They signed up because they care about the mission. They’re not hunting for a discount code or entering a contest. They’re there because they want to be there. Add to that the fact that many nonprofit lists skew older, and older demographics still treat email as a primary communication channel, not a spam folder they occasionally glance at.
The food bank I worked with had a welcome email open rate of 73%. That’s not a typo. Seventy-three percent.
But here’s the catch: their click-through rate on fundraising emails was often under 2%. High opens, low action. Because people wanted to stay informed about the mission but weren’t always ready to donate. If I had benchmarked them against e-commerce and decided their 45% open rate was “good enough,” I would have missed the actual problem: they weren’t converting opens into donations.
E-commerce & retail (The 8-15% reality)
Now let’s talk about the other end of the spectrum.
E-commerce open rates are brutal. I’ve managed programs for D2C brands where a 12% open rate was considered healthy. Why? Because e-commerce lists are often built through discounts. Someone buys a $40 sweater, they get added to the list. They weren’t signing up because they wanted weekly emails about sweater trends. They signed up because they wanted 15% off their first order.
The email address becomes a transactional artifact, not a relationship signal.
Add to that the sheer volume of e-commerce email. The average consumer gets dozens of retail marketing emails a day. The competition for attention is fierce. And many of those subscribers are using promotional Gmail accounts where emails get buried in the “Promotions” tab faster than you can hit send.
I had a client in the outdoor gear space. Their abandoned cart emails opened at 28%—great. Their weekly newsletter opened at 7%. Same audience, same sender, vastly different open rates. Because the context of the email matters. A cart abandonment email is timely, transactional, expected. A newsletter is noise unless it’s exceptional.
B2B & SaaS (The 20-30% sweet spot)
B2B lands in the middle, but with its own complications.
SaaS open rates tend to hover in the 20-30% range, but the distribution is bimodal. You have the transactional emails—onboarding sequences, feature announcements, account updates—that often clear 40% or more. And then you have the nurture campaigns, the thought leadership content, the “we wrote a blog post” emails that struggle to break 15%.
The difference is intent. A new user who just signed up for a trial? They’re going to open your emails because they need to figure out how to use your product. A lead who downloaded a white paper six months ago? They’ve forgotten who you are.
I managed email for a project management SaaS. Their onboarding sequence consistently opened at 52%. Their weekly product update newsletter opened at 19%. Both were “good” for what they were. If I had averaged them together and said “our open rate is 35%,” I would have been lying to myself about the health of both programs.
Source credibility: Why Mailchimp data differs from HubSpot data
Here’s something most benchmark articles won’t tell you: the source of the data matters as much as the data itself.
Mailchimp’s benchmark report is massive—they analyze billions of emails. But Mailchimp’s user base skews heavily toward small businesses, solopreneurs, and early-stage companies. Their data reflects that. A small bakery using Mailchimp to send a weekly “today’s flavors” email is not the same as a mature B2B SaaS using Marketo.
HubSpot’s benchmarks, by contrast, pull primarily from their B2B customer base. Their numbers tend to be lower on opens but higher on click-through rates, because B2B audiences are more selective about what they open but more likely to engage once they do.
Klaviyo’s data is e-commerce first. Their open rates are often lower than Mailchimp’s overall averages, but their revenue-per-email numbers are higher, because they’re measuring different things.
If you pull a number from one report and treat it as gospel, you’re comparing your business to a cohort that might not look anything like your business. It’s like looking up the average height of humans and asking why your NBA player nephew doesn’t fit the number.
The Three Variables That Render Averages Useless
If I’m brought in to look at an email program, I ignore the open rate entirely for the first hour. I want to know three things: where the list came from, how old it is, and what the sender reputation looks like. These three variables predict open rate more accurately than any subject line test ever will.
Audience source: The warm lead vs. cold lead gap
The single biggest determinant of open rate is whether the person on the other end actually wants to hear from you.
Past customers vs. cold traffic
I’ve run the numbers across dozens of accounts. Past customers open at 2-3x the rate of cold leads. Sometimes more. It’s not even close.
Why? Because they already trust you. They’ve given you money. They know what to expect. When a past customer sees your name in their inbox, it’s a known quantity. When a cold lead sees it, it’s one of fifty promotional emails they’ll get today.
One of my clients in the supplement space had a list of 80,000 people. About 15,000 were past customers. The past customers opened at 32%. The cold leads opened at 9%. Same sender, same campaigns, vastly different results.
If I had looked at the blended average of 14% and called it a day, I would have missed the fact that their cold acquisition funnel was broken. The problem wasn’t email strategy. The problem was that they were driving traffic to a lead magnet that attracted low-intent users.
Double opt-in vs. single opt-in lists
This one’s controversial, but the data is clear: double opt-in lists outperform single opt-in lists on open rates by 20-40%.
Double opt-in means someone gives you their email address, then clicks a confirmation link to verify they actually want it. The friction is real—you lose about 15-20% of signups in that confirmation step. But the ones who make it through are genuinely interested.
Single opt-in lists are bigger. Double opt-in lists are better.
I had a client who switched from single to double opt-in. Their list growth slowed by about 18%. Their open rate on the first campaign after the switch jumped 27%. The people who stayed wanted to be there.
This isn’t a moral argument about consent. It’s a practical one about engagement. If you’re optimizing for list size, you’re optimizing for lower open rates. Those two goals are in direct tension.
List age: The decay factor
Email lists rot.
It’s not a metaphor. Every month, about 2-3% of your list decays—people change jobs, abandon email addresses, or simply stop checking that account. After a year, 20-30% of your list is effectively dead.
I’ve seen it happen over and over. A brand builds a list aggressively for two years. They hit 100,000 subscribers. They’re thrilled. But they never cleaned the list. By year three, their open rate has dropped from 25% to 12%. They panic. They blame the subject lines. They blame the content. The real problem is that half their list is comprised of addresses that haven’t engaged in 18 months.
The math is unforgiving. If you’re adding 5,000 subscribers a month but losing 3,000 to natural decay and disengagement, your list is only marginally healthier. Most brands don’t track this. They track total subscribers. Then they wonder why open rates keep falling.
Sender reputation: The invisible hand
This is the variable nobody wants to talk about because it’s technical and boring, but it’s also the one that can kill you overnight.
Sender reputation is how email providers like Gmail, Outlook, and Yahoo score your domain and IP address. It’s based on engagement rates, spam complaints, bounce rates, and whether you’re sending to known spam traps. If your reputation drops, your emails go to spam. It’s that simple.
I worked with a brand that had a pristine reputation. Their emails always landed in the primary inbox. Open rates were consistently in the high 20s. Then they hired a growth consultant who convinced them to buy a list of 50,000 “targeted” leads. They sent one campaign to that list. Bounce rates spiked to 15%. Spam complaints flooded in. Gmail flagged them.
Their open rate on the next campaign dropped to 4%. It took six months of careful list cleaning and engagement campaigns to recover.
That’s the invisible hand. You don’t see it until it slaps you. And once it does, all the clever subject lines in the world won’t matter because your emails aren’t reaching inboxes.
Redefining “Good” for Your Business
If you’ve made it this far, you’ve probably realized that the question “What is a good open rate?” is starting to feel like a trick. Good. That’s the point.
Your only true benchmark: Your own historical data
I tell every client the same thing: your benchmark is you. Not some aggregate report. Not what your competitor claims their open rate is. You.
Track your open rate month over month, segment by segment. Understand the patterns. Your welcome email opens will be higher than your newsletter opens. Your abandoned cart opens will be higher than your post-purchase follow-ups. That’s not a problem to solve. That’s just how email works.
What you’re looking for is trend lines. Is your open rate trending up or down within each segment? Are new subscribers engaging at the same rate they were six months ago? Are your re-engagement campaigns performing better or worse than last quarter?
Those are the questions that lead to action. A static number compared to an irrelevant benchmark leads to anxiety.
Setting realistic KPIs based on your funnel stage
Your open rate expectations should shift depending on where the subscriber is in the funnel.
For a brand new lead who just opted in through a content download? I’m happy with 20-25% opens. That tells me they’re interested enough to see what happens next.
For a recent purchaser? I expect 40-50% opens on post-purchase emails. If it’s lower than that, something’s wrong with the timing or the offer.
For a subscriber who’s been on the list for two years and opens sporadically? I’m not expecting miracles. But I am watching to see if they ever engage with a re-engagement campaign.
Setting one KPI for your entire email program is like setting one KPI for your entire business—revenue. It’s technically accurate and completely useless for decision-making.
Focus on trend lines, not isolated numbers
Here’s the mindset shift I try to instill in every marketing team I work with: stop looking at the number. Start looking at the direction.
An open rate of 18% sounds average. But if that 18% is up from 14% six months ago, you’re doing something right. If it’s down from 22%, you’re doing something wrong. The direction tells you more than the number ever will.
I worked with a skincare brand whose open rate dropped from 24% to 19% over the course of a year. They were panicked. When I dug into the data, I found that their list had grown 300% in that same period, and the new subscribers were from lower-intent sources—contest entries, discount seekers, social media followers who wanted a freebie. The existing subscribers were still opening at the same rate. The blended number dropped because the composition of the list changed.
Was that a problem? Maybe. It meant they were building a list of lower-quality subscribers, which would eventually impact deliverability if left unchecked. But it wasn’t a crisis. It was a signal to revisit their acquisition strategy, not their email content.
If they had fixated on the isolated number—19% “good” or “bad”?—they would have missed the actual business decision they needed to make.
This is how you treat open rates like a professional. Not as a report card. Not as a vanity metric to post on LinkedIn. As a diagnostic tool that tells you something about your audience, your infrastructure, and your acquisition channels.
The next time someone asks you what a good open rate is, don’t give them a number. Ask them about their list. Ask them about their double opt-in rate. Ask them about their last deliverability audit. Ask them about the trend over the last six months.
If they can answer those questions, they don’t need a number. If they can’t, the number won’t help them anyway.
Decoding Apple’s Mail Privacy Protection (MPP): How the 2021 Update Changed Everything
Introduction – The Day the Metric Broke
A brief history of the open rate (pre-2021)
Before September 2021, the open rate was something we trusted. Not blindly—anyone who’d been in email for more than five minutes knew about image-blocking and the fact that opens were technically just a tracking pixel loading. But for the most part, if someone opened your email, the pixel fired, and you knew. It was as close to a reliable signal as email marketing had.
I remember building dashboards in the mid-2010s where open rate was the north star. We’d run A/B tests on subject lines with sample sizes calculated to hit statistical significance based on opens. We’d segment lists by “active opens” and “inactive opens” and build re-engagement campaigns around those definitions. We’d report to leadership with confidence: “Our open rate this quarter is 22.4%, up from 21.8% last quarter.”
It wasn’t perfect. There were always the image-blocking holdouts—Outlook users, mostly, and people who’d configured their email clients to not load images by default. We knew those opens weren’t being tracked. But it was a consistent blind spot. The same percentage of people across campaigns and senders had images blocked, so we could compare apples to apples, more or less.
The system worked well enough that we stopped questioning it. Open rates became embedded in every email marketing playbook, every benchmark report, every agency pitch deck. They were the metric.
Then Apple lit a match.
The announcement that shook the email marketing world
I was on a client call when the news broke. June 2021, Apple’s Worldwide Developers Conference. They announced Mail Privacy Protection as part of iOS 15 and macOS Monterey. I remember reading the feature description and feeling my stomach drop.
Here’s what Apple said: when a user enables Mail Privacy Protection, their email client will pre-load all email content—including tracking pixels—in the background, regardless of whether the user actually opens the email. The pixel fires whether the email is read, glanced at, or never touched.
I sat there doing the math in my head. If Apple Mail users—which accounted for somewhere between 35% and 50% of most consumer-facing lists—started pre-loading pixels, then every email sent to them would register as an open. Even if the email went straight to the trash. Even if they never looked at it. Even if they deleted it without a glance.
The client asked if I was okay. I said yes. I was not okay.
Over the next few months, as iOS 15 rolled out to users, the reality set in. Open rates across the industry started climbing. Not because people were suddenly more engaged, but because Apple had fundamentally broken the metric. The one number we’d been using to measure attention, to segment audiences, to report performance—it was now, for a huge chunk of our lists, completely fictional.
I had clients calling me in October and November of 2021 asking why their open rates had jumped 20 percentage points overnight. “We’re crushing it,” one founder told me. “What did we change?” Nothing, I said. Apple changed it for you.
That was the day the metric broke.
How MPP Works: The Technical Breakdown
The pre-load proxy: Why “opens” are no longer intentional
Let me explain what’s actually happening under the hood, because understanding the mechanism helps you understand why the old rules no longer apply.
Every marketing email contains a tiny, invisible image—usually a 1×1 pixel GIF—hosted on the sender’s server. When an email client loads that image, the server logs a request. That request is what we call an “open.” Pre-MPP, that request only happened when the user actually opened the email and allowed images to load.
With Mail Privacy Protection, Apple’s mail client does something different. When an email lands in an MPP-enabled inbox, Apple’s servers—not the user’s device—fetch all the content of that email, including the tracking pixel, and cache it. The pixel fires on Apple’s servers, not on the user’s phone or computer.
So here’s what happens: You send an email to a subscriber with MPP enabled. Apple’s servers immediately load the email, fire the tracking pixel, and cache the content. Later, if the user actually opens the email, they’re loading it from Apple’s cache, not from your server. The pixel never fires again.
The result? You get an “open” for every single email sent to that subscriber, regardless of whether they ever looked at it.
This isn’t a bug. It’s a feature Apple deliberately built. They told us exactly what they were doing. Their stated goal was privacy—preventing senders from knowing when and where users open emails. And they accomplished it brilliantly, from a privacy standpoint. From a marketer’s standpoint, they pulled the floor out from under us.
I’ve had marketers ask me if there’s a way to detect MPP opens and filter them out. The short answer is no. You can identify which opens likely came from MPP based on user agent and behavior patterns, but you can’t know with certainty. The pixel fired. The server logged it. That’s an open, as far as your ESP is concerned.
Identifying the affected audience
Not everyone on your list is affected by MPP. Knowing who is—and who isn’t—is the first step to making sense of your data again.
Apple Mail users (iOS & macOS)
MPP affects users who meet two conditions. First, they need to be using the Apple Mail app—the default email client on iPhones, iPads, and Macs. Not Gmail’s app. Not Outlook’s app. Not Spark or Superhuman or any other third-party client. Apple Mail.
Second, they need to have Mail Privacy Protection enabled. When iOS 15 first launched, Apple presented users with a prompt asking if they wanted to enable it. Most users clicked yes, because it was presented as a privacy feature and required zero effort. In my experience, the opt-in rate is somewhere between 70% and 90% of Apple Mail users. That’s not official Apple data—they don’t release it—but it’s consistent across the accounts I’ve managed.
So the affected audience is: people who use Apple Mail and who said yes to the privacy prompt.
That’s not everyone. Gmail app users aren’t affected. Outlook app users aren’t affected. People who use Apple Mail but clicked “no” aren’t affected. But the segment is significant enough that you can’t ignore it.
Estimating your list impact (The 35-50% rule)
Here’s the rule of thumb I use across accounts: if your audience is primarily consumer-facing, expect 35-50% of your list to be MPP-affected. If you’re B2B, that number drops—sometimes significantly—because business users are more likely to use Outlook or Gmail for work accounts.
I managed a D2C apparel brand where MPP-affected subscribers accounted for 48% of the list. A B2B SaaS client came in at 22%. A nonprofit with a donor base that skewed older? 54%, because older demographics are more likely to use whatever came default on their iPhone.
The variation matters. If you’re looking at your overall open rate without segmenting by email client, you’re looking at a number that combines MPP-inflated opens from one segment with real opens from another. It’s like averaging the temperature in a freezer and a furnace and wondering why your food won’t cook.
I pull a client’s email client breakdown in every audit now. If I don’t see a clear segmentation between Apple Mail and other clients, I know they’re flying blind.
The Fallout: What MPP Did to Your Data
The artificial inflation of open rates
The most immediate and obvious impact was the inflation. Open rates went up across the board, but not evenly. Lists with high Apple Mail penetration saw dramatic spikes. Lists with low penetration saw barely any movement.
I had a client in the outdoor gear space whose open rate jumped from 19% to 34% over a three-month period. They’d changed nothing about their email program. The 34% was a fiction. The real open rate among non-MPP users was actually slightly down during that period—something we only discovered after segmenting.
The inflation creates a weird dynamic where your reported open rate becomes a function of your list composition rather than your email quality. Add more Apple Mail users? Your open rate goes up. Lose them to churn? Your open rate goes down. You can be doing everything right with your subject lines and content and see your open rate drop because your audience shifted toward Android users.
I’ve had to walk founders off ledges multiple times since 2021. They see a drop and panic. Then we pull the segment data and realize the drop is just a shift in list composition, not a failure of strategy. But if you’re not segmenting, you don’t know that. You just see a number moving and assume you’re the cause.
The distortion of A/B testing results
This one’s more subtle but just as destructive.
Pre-MPP, A/B testing subject lines was straightforward. You’d split your audience, send two versions, and measure which had a higher open rate. The winner was the one that got more people to click.
Post-MPP, if you’re still measuring A/B tests by open rate, you’re testing something entirely different. You’re testing which subject line gets pre-loaded by Apple’s servers at a higher rate? No, that’s not how it works. The open rate for MPP users is 100% regardless of subject line. So your test results are now being diluted by a segment that will open every email no matter what.
I saw this happen with a client who ran a subject line test. Version A had a 28% open rate. Version B had a 31% open rate. The marketing manager declared Version B the winner and rolled it out to the whole list.
When I segmented the data, the non-MPP open rates were 18% for Version A and 17% for Version B—Version A had actually performed better among real opens. The overall numbers were flipped because the MPP segment (which opened everything) was larger in the Version B group due to random variation in the split.
The client had been optimizing for a metric that no longer meant what they thought it meant.
If you’re running A/B tests post-MPP, you have two options. First, you can test on click-through rate instead of open rate. That’s what I recommend for most clients. Second, you can filter out MPP users from your test and only measure non-Apple clients. Most ESPs allow this if you know how to set up the segments.
But if you’re still running subject line tests and declaring winners based on open rate without accounting for MPP, you’re making decisions on bad data.
Why location data is now mostly useless
This is the fallout that doesn’t get talked about enough.
Pre-MPP, we could see roughly where opens were happening. City, state, country. It was useful for timing sends, localizing content, understanding geographic engagement patterns.
Now, with MPP, the location data you get is the location of Apple’s proxy servers. Not your subscriber. Those servers are scattered across data centers—many of them in Northern Virginia, where AWS has a massive presence, or in other major data hub locations.
I’ve looked at location reports where 40% of “opens” were showing from Ashburn, Virginia. Unless I’m running a business that inexplicably appeals to residents of suburban DC data centers, those aren’t real opens. They’re MPP.
For B2B companies with sales territories, this is a genuine problem. If you’re using open location data to identify which accounts are engaging, you’re now seeing a massive cluster of “engagement” from Virginia that means nothing. It’s noise.
I’ve stopped using open location data entirely for most clients. If a client asks about geographic engagement, I look at click data instead. Clicks still come from the actual user’s device. That data is still reliable.
How to Navigate the Post-MPP Landscape
Segmenting Apple users vs. non-Apple users for accurate analysis
If you take nothing else from this, take this: segment your data.
I set up a segment in every ESP I work with that isolates non-Apple Mail users. Sometimes it’s “email client is not Apple Mail.” Sometimes it’s more specific—”email client is Gmail, Outlook, Yahoo, or Other.” The goal is to create a view of your data that excludes the MPP noise.
When I report to leadership now, I show two numbers. The overall open rate, with a caveat: this number is inflated by Apple’s privacy protections and should be considered directional only. And the non-Apple open rate, which is the closest thing we have to a true engagement signal.
The difference between these two numbers tells you something. If they’re close, your list is mostly non-Apple or mostly opted out of MPP. If they’re far apart, you have a high MPP penetration and your overall open rate is largely a fiction.
I also build segments for automation triggers. If I’m setting up a re-engagement campaign based on open inactivity, I cannot use open data from Apple Mail users. They’ll never be inactive by that definition. I either use non-Apple users for that automation or use click data instead.
This adds complexity to setup. There’s no way around it. The old days of a simple “if not opened in 90 days” trigger are over. That trigger will now keep Apple users in your active flow forever, regardless of whether they’ve ever looked at an email.
The metric hierarchy shift: Introducing CTOR and Click Rates
If open rates are now broken, what do we use instead? This is where the real work of post-MPP email strategy happens.
Why Click-Through Rate (CTR) is now the king
CTR hasn’t been affected by MPP. A click still requires the user to actually engage with the email, to move their cursor or thumb, to take action. Apple’s servers aren’t clicking links on your behalf. Not yet, anyway.
I’ve shifted nearly all of my reporting and optimization to focus on CTR. When I’m evaluating a campaign’s performance, the first number I look at is click rate, not open rate. When I’m running A/B tests, I test on clicks. When I’m segmenting audiences for engagement, I use clicks as the primary signal.
This takes some adjustment, especially for stakeholders who’ve been trained to look at opens. I’ve had to re-educate multiple leadership teams on why we’re “ignoring” opens. The explanation is always the same: we’re not ignoring them, we’re using them appropriately. They’re a directional signal. Clicks are what actually drive revenue.
Introducing Click-to-Open Rate (CTOR) as the quality check
CTOR is clicks divided by unique opens. It tells you, of the people who opened your email, what percentage clicked.
Here’s why CTOR matters post-MPP: it gives you a quality check on your opens.
If your open rate is inflated by MPP, your CTOR will drop—because you have a bunch of fake opens that will never click. A declining CTOR is often the first sign that MPP is distorting your numbers. It’s also a useful way to compare campaigns across time. If your open rate is up but your CTOR is down, you’re probably seeing MPP inflation, not real improvement.
I use CTOR to evaluate content quality. Subject lines and preheaders drive opens. Content drives clicks. CTOR bridges the two. If CTOR is high, your content is resonating with the people who actually opened. If CTOR is low, you have a mismatch between what your subject line promised and what your email delivered.
Pre-MPP, I could infer that from open rate and click rate. Post-MPP, CTOR is essential because open rate alone no longer tells you how many real people are actually reading.
Accepting the open rate as a directional signal, not a truth
This is the mindset shift that separates the marketers who’ve adapted from the ones who are still stuck in 2020.
Open rates are not gone. They’re just different. They’re no longer a precise measurement of engagement. They’re a rough indicator of deliverability and subject line effectiveness, filtered through the lens of your list composition.
I still look at open rates. I just don’t trust them like I used to.
When I see a campaign with a 40% open rate, I don’t celebrate. I check the non-Apple segment. If that’s also 40%, I celebrate. If it’s 15%, I know the 40% is mostly MPP noise and I need to look at CTR to understand what actually happened.
When I see a declining open rate over time, I don’t panic. I look at list composition first. Are we adding more non-Apple users? Are we losing Apple users to churn? The trend might be real, or it might be a demographic shift.
The professional approach post-MPP is not to throw open rates out entirely. It’s to treat them with the skepticism they deserve. They’re one data point among many. They’re directional. They’re contextual. They’re no longer the center of the universe.
I’ve had clients ask if they should just stop reporting open rates. I don’t recommend that. Leadership still wants to see them. Investors still ask. But I do recommend showing them alongside click rates, CTOR, and non-Apple segments. Give the number context. Explain what it means and what it doesn’t.
If you’re still reporting a single open rate number in a dashboard and treating it as the primary indicator of email health, you’re not doing post-MPP email marketing. You’re doing pre-2021 email marketing with a broken metric.
Apple changed the rules in 2021. The professionals adapted. The rest are still wondering why their open rates look great but their revenue isn’t moving.
The Anatomy of a High-Converting Subject Line: Psychology Over Clicks
Introduction – The Gatekeeper of the Inbox
The 3-second window to capture attention
I’ve sat next to enough people watching their inboxes to know how this actually works. They’re not reading. They’re scanning. Thumb on the screen, scrolling through a list of senders and subject lines at a pace that would make a speed-reader dizzy. Stop. Delete. Stop. Open. Stop. Archive. It takes about three seconds from the moment they glance at your name to the moment they decide whether you live or die.
Three seconds.
That’s less time than it takes to tie a shoe. Less time than it takes to register what you’re looking at and make a judgment call. In that window, your subject line has to do something remarkable. It has to interrupt the pattern. It has to make a brain that’s already processing forty other emails today stop and say, “Wait. What’s this?”
I learned this lesson the hard way about ten years ago. I was running email for a SaaS company and we’d spent weeks crafting what we thought was the perfect newsletter. Great content. Strong design. Clear CTA. We sent it to a list of 50,000 with the subject line “October Product Updates.” The open rate was 7%. Seven. We might as well have not sent it.
The next month, I changed the subject line to “We fixed the thing you hated.” Same list. Same content. Same day of week. Open rate hit 24%. The content hadn’t changed. The offer hadn’t changed. The only thing that changed was whether people bothered to look.
That was the moment I stopped treating subject lines as metadata and started treating them as the primary creative challenge of email marketing. Because they are. The rest of the email doesn’t matter if no one opens it. And no one opens it if the subject line doesn’t earn their attention in the time it takes to blink.
The cost of a bad subject line (lower deliverability)
Here’s what most people don’t understand about subject lines. The cost of a bad one isn’t just a low open rate. It’s a slow death by reputation damage.
Email providers like Gmail and Outlook watch what people do with your emails. When someone gets an email from you and deletes it without opening, that’s a signal. When they mark it as spam, that’s a louder signal. When enough people ignore your emails, the algorithm learns. It starts routing you to the Promotions tab if you’re lucky, or the spam folder if you’re not.
I managed a list once where the previous marketer had a habit of writing subject lines that were basically lies. “Your account has been suspended” when the account was fine. “Urgent: Action required” when the email was just a feature announcement. The open rates were actually decent because the subject lines were manipulative. But the spam complaints were through the roof. People opened, felt tricked, and marked the email as spam out of annoyance.
By the time I took over, the domain reputation was shot. We were hitting spam folders at Gmail and Outlook at a rate of about 40%. No amount of great content was going to fix that. We had to rebuild reputation from scratch, which took six months of meticulously clean sending, high engagement rates, and absolutely zero gimmicks.
A bad subject line doesn’t just cost you that send. It costs you the ability to reach the inbox on future sends. The algorithm remembers.
The Psychology of the Click
Curiosity gap: The Zeigarnik effect
There’s a psychological principle called the Zeigarnik effect. Named after a Russian psychologist who noticed that waiters could remember complex orders from customers who hadn’t paid yet, but forgot them immediately after the bill was settled. The brain holds onto unfinished business. Open loops create tension. Tension demands resolution.
The curiosity gap is just this principle applied to subject lines. You create a gap between what the reader knows and what they want to know. Then you offer to close that gap if they open the email.
I’ve used this a thousand times. The formula is simple: make a statement that implies information the reader doesn’t have, without giving it away.
Examples of incomplete narratives
Here are subject lines I’ve written that worked because they left something out:
“What happened when we stopped running Facebook ads” — the implication is a story with a lesson. The reader wants to know the outcome. Did revenue crash? Did it stay the same? Did they discover something unexpected? They have to open to find out.
“The one metric we don’t report to the board” — this one works because it implies insider knowledge, a peek behind the curtain. There’s a secret here. If you open, you’ll be in on it.
“I’m about to do something stupid” — from a founder I worked with. It was a subject line for a fundraising email. The gap was obvious: what stupid thing? Is this a joke? Is it serious? The open rate was 47%.
The key is that the gap has to be compelling. “I have a question for you” creates a gap, but it’s vague and generic. “I have a question about your hiring plans” creates a gap that’s specific enough to matter to someone who’s hiring. The more specific the gap, the more likely the reader feels it applies to them.
The mistake I see marketers make is trying to close the gap in the subject line. They want to be clever and complete. But if you answer the question in the subject line, there’s no reason to open the email. The curiosity gap only works if you leave it open.
Personalization: Beyond just {First Name}
First name personalization is table stakes. It’s been table stakes for fifteen years. It doesn’t impress anyone. It doesn’t even register with most people anymore. If your idea of personalization is “Hey {{first_name}},” you’re not doing personalization. You’re doing mail merge.
Real personalization is behavioral. It’s using what you know about what someone has done to make the subject line relevant to them.
Behavioral personalization (“We noticed you left this behind”)
Abandoned cart subject lines are the classic example here, and they work for a reason. “You left something behind” isn’t generic. It’s specific to the person receiving it. They know they were looking at that product. The subject line reminds them of an unfinished action.
But you can take this further.
I worked with a B2B software company that sent a subject line that said “You’ve logged in 47 times this month.” The email was a simple check-in asking if they needed help with anything. The open rate was 58%. Because the subject line referenced actual behavior. The person receiving it knew it was true. They’d been using the product heavily. The subject line felt like it was written for them, because it was.
Another client in the education space sent “You started the course but didn’t finish Module 3.” Simple. Specific. Behavioral. The open rate was three times their average.
The principle is this: use data you have about the subscriber to make the subject line true for them. Not true in a generic way. True in a way that they know is true. That’s what cuts through the noise. When someone reads a subject line that references their actual behavior, they don’t think “marketing email.” They think “this is about me.”
Urgency & Scarcity: Fear of missing out (FOMO)
Urgency works. I wish it didn’t, because it’s been so overused that people are starting to develop immunity. But the data doesn’t lie. Subject lines that imply limited time or limited availability consistently outperform neutral subject lines.
The reason is evolutionary. Humans are wired to avoid loss more than they’re wired to seek gain. Losing something hurts more than gaining something feels good. Urgency triggers that loss aversion. The reader perceives that if they don’t act, they’ll lose something—a discount, an opportunity, access to something valuable.
I’ve run enough tests to know that urgency subject lines almost always win against non-urgency versions. The trick is making the urgency credible.
“Sale ends tonight” works if the sale actually ends tonight. If the sale ends tonight and then there’s another sale next week with the same discount, you’ve burned trust. I’ve seen brands do this repeatedly—a “24-hour flash sale” that appears every three days. Eventually, the audience learns. The urgency stops working because it’s never real.
The subject lines that work long-term are the ones where the scarcity is genuine. “Only 3 spots left for the workshop.” “Early bird pricing expires in 6 hours.” “Your trial ends tomorrow.” These work because they’re true, and the reader knows they’re true.
I had a client who ran a membership site. They sent a subject line that said “We’re closing doors for 30 days.” The email explained they were pausing new signups to focus on existing members. The urgency wasn’t manufactured. It was a real window closing. That subject line did a 62% open rate.
Problem-Agitation-Solution (PAS): The pain point opener
This is a copywriting framework that translates beautifully to subject lines. Problem. Agitate. Solution. You name a problem the reader has. You agitate it—make them feel why it’s a problem. Then you offer the solution in the email.
In a subject line, you usually only have room for the problem or the agitation. But if you pick the right problem, it’s enough.
“Struggling to hit your revenue targets?” — that’s a problem subject line. If the reader is struggling, they’ll open. If they’re not, they won’t. That’s fine. Targeting matters.
“Why your team keeps missing deadlines” — this is agitation. It implies there’s a reason for a known problem, and the email will explain it.
“Tired of losing candidates to competitors” — problem subject line for a recruiting email. It worked because the audience was recruiting managers who were, in fact, losing candidates to competitors.
The key to PAS subject lines is specificity. “Having problems with your business?” is too vague. “Having problems with cash flow?” is better. “Why your cash flow problems are getting worse” is better still. The more specific the problem, the more the reader feels seen.
The Technical Craft of Subject Lines
Mobile-first optimization (The 30-40 character limit)
I don’t care what your subject line looks like on desktop. Neither does your audience. The majority of email opens happen on mobile. I’ve seen numbers ranging from 60% to 80% depending on the industry and audience. If your subject line is optimized for a 27-inch monitor, you’re optimizing for the minority.
On an iPhone, the subject line gets cut off after about 30-40 characters, depending on the iOS version and whether there’s an emoji. Everything after that lives in the ellipsis. People don’t tap to expand. They make their decision based on the first 30 characters.
This changes how I write subject lines. The most important words go first. Not the clever twist at the end. Not the punchline. The hook.
If I’m writing “You won’t believe what happened when we stopped running ads,” that’s 50 characters. On mobile, it becomes “You won’t believe what happened when we…” The reader doesn’t see the specific context. They see a generic curiosity line.
If I write “We stopped running ads. Here’s what happened,” that’s 40 characters. On mobile, it shows “We stopped running ads. Here’s what…” The hook lands. The context is clear.
I write subject lines in a text file on my phone now. If I can’t read the full thing in the preview without tapping, I rewrite it. This isn’t optional. It’s the reality of where and how people read email.
The emoji debate: When to use them (and when to avoid them)
I’ve run tests on emojis across probably fifty different accounts at this point. The results are inconclusive in the way that makes marketers uncomfortable. Sometimes emojis lift open rates. Sometimes they hurt them. It depends entirely on the audience and the context.
What I can tell you is what I’ve observed.
Emojis work in B2C consumer brands, especially in lifestyle, fashion, food, and entertainment. They add personality. They break up the monotony of text-only subject lines. They signal that the brand is approachable, human.
Emojis tend not to work in B2B, especially in finance, legal, healthcare, or any industry where professionalism is paramount. A subject line with a rocket emoji from a SaaS company? That’s fine. A subject line with a money bag emoji from a wealth management firm? That looks amateur.
I also think emojis work best when they reinforce the message rather than replacing it. “🚨 24 hours left 🚨” is fine but it’s also a crutch. “Your cart is expiring 🛒” uses the emoji to add visual context, not to carry the meaning.
The worst use of emojis I’ve seen is when they’re completely unrelated to the content. A random smiley face. A party popper for a serious announcement. It creates a mismatch that makes the brand look like it doesn’t know what it’s doing.
My rule is this: test emojis if your brand voice allows them. But if you’re not sure, leave them out. A good subject line without an emoji outperforms a mediocre subject line with one.
The power of “you” and possessive pronouns
This is subtle but I’ve seen it move the needle consistently. Subject lines that use “you,” “your,” and “yours” outperform those that use “we,” “our,” and “us.”
The reason is simple. People care about themselves more than they care about your company. A subject line that’s about them gets their attention. A subject line that’s about you gets ignored.
“We’ve launched a new feature” is about the company. The reader thinks: that’s nice for you.
“You can now save 3 hours a week with this new feature” is about the reader. The reader thinks: tell me how.
I’ve rewritten subject lines for clients to flip the pronoun and seen open rates increase by 10-20% with no other changes. It’s not magic. It’s just aligning your message with what the reader actually cares about.
Implementing a Winning Subject Line Strategy
How to set up a proper A/B test (Statistical significance)
Most A/B testing I see is not actually A/B testing. It’s guessing with extra steps.
People will send a subject line to 10% of their list, see which one has a higher open rate, declare a winner, and send it to the remaining 90%. That’s not testing. That’s rolling dice. The sample sizes are too small, the test is underpowered, and the result is usually not statistically significant.
I have a rule for subject line tests. You need at least 1,000 recipients per variation to get meaningful data. That’s the floor. If your list is smaller than that, you don’t have enough volume to test. You’re better off using best practices and waiting until you have scale.
When I run a test, I do it the same way every time. I select a segment that’s large enough—usually 20-30% of the list. I split it evenly. I send two variations, varying only one element. Not subject line and preheader. Not subject line and send time. One variable. Subject line only.
Then I wait 24 hours. I check the open rates and I run a statistical significance calculator. If one variation is winning with 95% confidence, I declare a winner and send it to the rest of the list. If the test is inconclusive, I send the control to the rest of the list and run another test next time.
I’ve seen people declare winners based on a 1% difference with 200 recipients per variation. That’s not data. That’s noise.
The other mistake I see is testing too many variables at once. A/B/C/D/E tests with five different subject lines. Now you’re splitting your sample five ways. None of the groups have enough volume to reach significance. You’ve wasted a send and learned nothing.
Test one thing. Test it properly. Learn something. Move on.
Creating a “swipe file” for ongoing inspiration
I have a folder in my notes app called “Subject Lines.” It has hundreds of entries. Every time I see a subject line that makes me stop—whether it’s in my own inbox, a competitor’s email, a friend’s newsletter—I save it. I don’t save it to copy it. I save it to understand why it worked.
Some of them are curiosity gaps. Some are urgency plays. Some are just beautifully simple. The point is to build a library of patterns, not to steal specific lines.
I review this file before every major send. Not to find the perfect subject line, but to remind myself what’s possible. When you write subject lines every day, you fall into patterns. You start writing the same three or four structures over and over. The swipe file breaks that pattern. It shows you a structure you haven’t used in a while, a format you’d forgotten about.
I recommend anyone who writes email regularly do the same. Set up a folder. Every time you see a subject line that makes you open an email, save it. Every time you see one that makes you laugh or think or feel something, save it. Over time, you’ll build a collection that’s specific to your taste and your industry.
Then use it. Not to copy, but to learn. Ask yourself: why did this work? What pattern is it using? How could I apply that pattern to my audience and my offer?
Testing is the only universal truth
I’ve given you frameworks. Curiosity gaps. Behavioral personalization. Urgency. Problem-agitation-solution. Mobile optimization. Pronouns. Emojis. All of these are patterns I’ve seen work across hundreds of accounts and thousands of sends.
None of them are guarantees.
I’ve had curiosity gap subject lines fail. I’ve had urgency subject lines fall flat. I’ve had tests where “you” lost to “we” for reasons I still don’t fully understand. Every audience is different. Every offer is different. Every context is different.
The professionals understand this. The amateurs want a formula.
If someone tells you they know the perfect subject line formula for your business, walk away. They’re selling certainty they don’t have. The only universal truth in subject line strategy is that you have to test. Not once. Not quarterly. Constantly. Every send is an opportunity to learn something about what your audience responds to.
I test subject lines on every single broadcast I send. Every one. Even when I’m confident. Especially when I’m confident. Because I’ve been humbled enough times to know that my instincts are wrong about as often as they’re right.
The best subject line strategy isn’t about being clever. It’s about being disciplined. Set up the tests. Measure the results. Let the data tell you what works. Then test again.
The Preheader Text: Your Second Subject Line (That Most People Ignore)
Introduction – The Most Valuable Real Estate You’re Wasting
Defining the preheader (snippet text)
The preheader is that line of text you see next to or below the subject line when an email lands in your inbox. Sometimes it’s the first few words of the email body. Sometimes it’s a custom snippet. Sometimes it’s a garbage string of code that someone forgot to delete. But it’s always there, and it’s always visible, and most marketers treat it like an afterthought.
I’ve sat in strategy meetings where we spent forty-five minutes debating a single word in a subject line. The same meetings where the preheader was whatever the email template defaulted to. The disconnect never stops surprising me. You’ll have a team obsessing over the first thirty characters of the subject line while ignoring the eighty characters directly below it that also appear in the inbox preview. It’s like spending hours polishing the front door while leaving the windows boarded up.
The preheader serves two functions, whether you intend it to or not. First, it gives the email client something to display in the preview pane. Second, it gives the reader additional context before they decide to open. If you don’t tell it what to say, the email client will grab whatever it finds first in the email body. Usually that’s a “View in Browser” link or a line of footer text. Neither of those is going to convince anyone to open your email.
I learned to respect the preheader about eight years ago when I was running a campaign for a B2B software company. We had a subject line that tested well: “The feature you’ve been asking for.” Open rate came in at 12%. Disappointing. I pulled up the inbox view and saw that the preheader was pulling from the footer: “You are receiving this email because you signed up for…” That’s what people saw below the subject line. Not a helpful second pitch. Just legal boilerplate.
The next send, we customized the preheader to say: “It’s finally here. See how it works inside.” Open rate jumped to 24%. Same subject line. Same audience. Same offer. The only thing that changed was we stopped letting the email client decide what to show people.
That’s when I started treating preheaders as second subject lines. Because that’s exactly what they are.
Visualizing the inbox: Mobile vs. Desktop layouts
The way preheaders display depends entirely on where your email is being read. And most of your emails are being read on mobile.
On an iPhone, using the default Mail app, the preheader appears directly below the subject line in a smaller, lighter font. The subject line shows first. The preheader shows second. Both are visible without the user tapping anything. The same is true for Gmail’s mobile app, though the formatting is slightly different—subject line on top, preheader in a smaller font below.
On desktop, it varies. Gmail shows the subject line in bold with the preheader text in a normal weight, gray font, directly to the right. Outlook shows the subject line with the preheader text in a smaller font below or to the side depending on the version. Apple Mail on Mac shows the subject line and then the first line of the email body, which is usually your preheader if you’ve set one.
The key takeaway is that the preheader is visible in every major email client, on every device, without the user doing anything. It’s not hidden. It’s not secondary. It’s right there, in the preview, alongside the subject line, competing for the same three seconds of attention.
I’ve seen the data on this. Inbox previews show between 80 and 120 characters total, depending on the device and client. The subject line takes up the first 30-50 of those characters. The preheader takes up the rest. That means the preheader is responsible for anywhere from 40% to 70% of the preview real estate. If you’re not customizing it, you’re giving up more than half of your prime inbox real estate to whatever garbage your email template coughs up.
Strategic Functions of the Preheader
The complement strategy: Extending the subject line
The most straightforward way to use a preheader is to let it finish the thought your subject line started. The subject line hooks. The preheader gives the context that makes the hook land.
I use this constantly. The subject line is short, punchy, optimized for mobile truncation. The preheader carries the explanatory weight. Together, they form a complete sentence or thought that the reader can process in one glance.
Subject: “Black Friday Starts Now” | Preheader: “Extra 20% off for first 100 customers”
Here’s what’s happening in this pairing. The subject line announces an event. It’s broad. It tells you that something is happening, but not why you should care specifically. The preheader adds the urgency and the exclusivity. Now the reader knows: not only is the sale happening, but there’s a limited window and a limited quantity. The hook is extended into a full value proposition.
Another example from a SaaS client. Subject: “Your trial ends in 3 days.” Preheader: “Here’s what you’ll lose access to—and how to keep it.” The subject line creates urgency. The preheader adds a curiosity gap and a solution path. Together, they tell the reader: there’s a problem coming, and this email contains the answer.
I’ve found that the complement strategy works best when the subject line is the headline and the preheader is the subheadline. The subject line grabs attention. The preheader tells the reader why that attention is justified. They work as a system, not as two separate elements.
The mistake I see with complement strategy is redundancy. If the preheader just repeats what the subject line said, you’ve wasted the space. “Black Friday Starts Now” as the subject and “Our biggest sale of the year is here” as the preheader tells the reader the same thing twice. It doesn’t add information. It doesn’t deepen the hook. It just takes up space.
The contrast strategy: Adding missing context
Sometimes the subject line is a hook that needs context that doesn’t naturally extend from it. The contrast strategy uses the preheader to add a layer of information that changes how the subject line is interpreted.
I used this for a client in the financial space. The subject line was “You’re losing money.” That’s a strong hook. It’s also potentially alarming. The preheader we paired with it was “Not in the way you think—read this before you panic.” The preheader changed the tone from alarm to curiosity. The reader knew this wasn’t a fraud alert or a collections notice. It was marketing content framed around a financial insight.
Another example from a nonprofit client. Subject: “We need to talk.” Preheader: “It’s not bad news, we promise. But it is important.” The subject line alone could signal a crisis. The preheader defused that while maintaining curiosity. The open rate on that campaign was 52%.
The contrast strategy is useful when your subject line is provocative enough to create interest but potentially ambiguous enough to create the wrong expectation. The preheader guides the interpretation. It tells the reader what kind of email this is going to be, which reduces the friction of opening. People don’t open emails they’re uncertain about. The contrast preheader removes that uncertainty while preserving the hook.
The call-to-action (CTA) preheader: Telling them what to do
This is the most direct approach. The preheader tells the reader exactly what you want them to do, and why they should do it.
I’ve seen this work exceptionally well in transactional and promotional emails. The subject line announces the offer. The preheader tells the reader what action to take.
Example from an e-commerce client. Subject: “Your cart is waiting.” Preheader: “Click here to complete your purchase before these items sell out.” The preheader isn’t subtle. It’s not clever. It’s a direct instruction with a scarcity motivator attached.
Another from a webinar promotion. Subject: “How to scale your agency.” Preheader: “Save your seat now—space is limited to 100 attendees.” The subject line promises value. The preheader creates urgency and tells the reader how to claim that value.
The CTA preheader works because it removes ambiguity. The reader knows exactly what will happen when they open the email. There’s no mystery. There’s no fear of being sold to in a way they don’t want. The transaction is clear: open this email to take the action you already know you want to take.
Common Preheader Mistakes That Kill Opens
The default “View in Browser” or “If you cannot see this…”
I still see this constantly. Emails go out with the preheader set to whatever the email service provider automatically populated. Usually that’s a “View in Browser” link or the first line of the email body, which is often an “If you cannot see this email, click here” message.
Here’s what that looks like in the inbox. Subject line: “20% off your next order.” Preheader: “View this email in your browser.” The reader sees that and thinks: this is a generic marketing email. Nothing in that preheader tells them why they should open. It’s a utility message that adds zero value to the decision-making process.
I had a client whose preheader was defaulting to “Click here to add us to your address book” for six months. Six months. They were sending to a list of 80,000 people twice a week. Every single one of those sends had a preheader that said nothing about the content, the offer, or the value. That’s hundreds of thousands of wasted opportunities to add context and increase opens.
The fix is simple. You go into your email template and you add a custom preheader variable. Then you write a unique preheader for every send. It takes thirty seconds. There’s no excuse for default text.
Leaving it blank (a massive missed opportunity)
Some marketers know enough to avoid the default text but then make the opposite mistake. They leave the preheader field blank, assuming the email client will figure something out.
When you leave the preheader blank, the email client pulls the first text it finds in the HTML of the email body. Sometimes that’s a headline. Sometimes it’s a navigation link. Sometimes it’s a paragraph of body copy that makes no sense out of context. You’re leaving the decision to the algorithm, and the algorithm doesn’t care about your open rates.
I’ve seen preheaders that were pulled from navigation menus: “Shop Women Men Kids Sale About Us.” That’s what appeared below the subject line. The reader sees that and has no idea what the email is actually about. They’re not going to open to find out.
A blank preheader is a missed opportunity to control the narrative. You have the chance to put your message in front of the reader twice—once in the subject line, once in the preheader. If you leave the preheader blank, you’re choosing to only use one of those opportunities.
Repetition: Simply copying the subject line
This one makes me crazy. A marketer will write a subject line, then write the exact same thing in the preheader field. Subject: “Our biggest sale of the year.” Preheader: “Our biggest sale of the year.” That’s not a strategy. That’s a placeholder.
The preheader should add something. If it’s just repeating what the subject line already said, you’ve created redundancy without value. The reader gets the same information twice. Nothing new compels them to open.
I had a client argue that repeating the subject line in the preheader reinforced the message. I ran a test. The repeated preheader versus a complementary preheader that added context. The complementary preheader won by 18%. People didn’t need the message reinforced. They needed a reason to act.
Technical Implementation & Best Practices
How to code custom preheaders in major ESPs (Klaviyo, Mailchimp)
The technical implementation varies by platform, but the principle is the same across all of them. You need to add a hidden piece of HTML at the very top of your email body that contains your custom preheader text. This text is invisible in the email itself but appears in the inbox preview.
In Klaviyo, there’s a dedicated field in the email builder for preheader text. You find it in the campaign settings. Type your text, save it, and Klaviyo handles the HTML. It’s the easiest implementation of any major platform.
In Mailchimp, it’s slightly more involved. You need to use the “Settings” section of the campaign builder and look for the “Tracking” or “Options” tab. There’s a field labeled “Preheader” or “Snippet Text.” Enter your text there. Mailchimp will inject it into the email HTML.
In HubSpot, you’ll find preheader settings in the email editor under “Advanced Options.” In ActiveCampaign, it’s in the campaign settings under “Email Options.”
For any platform that doesn’t have a dedicated field, you need to add the HTML manually. The code looks like this:
<div style="display:none;font-size:1px;color:#ffffff;line-height:1px;max-height:0px;max-width:0px;opacity:0;overflow:hidden;"> Your preheader text goes here. </div>
You put this at the very top of the email body, before any visible content. The text is hidden from the reader inside the email but visible to the email client in the preview pane.
I’ve had developers argue that this is hacky. It’s not. It’s the industry standard. Every major brand using email marketing does this. It’s how you control what appears in the preview without affecting the design of the email.
Character limits: The 40-90 character sweet spot
How long should a preheader be? The answer depends on where it’s being read, but I’ve settled on a range based on testing across hundreds of campaigns.
On mobile, the typical inbox preview shows between 40 and 90 characters for the preheader, depending on the device and the email client. That’s your effective range. Less than 40 characters and you’re leaving preview space unused. More than 90 and you risk truncation, which means the last part of your message gets cut off.
I aim for 60-80 characters on most sends. That’s enough room for a complete thought without running the risk of truncation in most clients. If I need more space, I’ll push to 90, but I test the preview in multiple clients to make sure the full message displays.
The one exception is when I’m using the complement strategy with a short subject line. If the subject line is 20 characters, I’ll sometimes let the preheader run to 100 or more because the combined preview length is longer than the individual elements. But I still check truncation.
The technical implementation matters here too. The hidden div method ensures that the preheader text doesn’t wrap or break in unexpected ways. If you’re just letting the email client pull from the visible body text, you have no control over where the truncation happens.
Treat the preheader as a headline, not an afterthought
The shift I’ve seen in the best email programs I’ve worked with is treating the subject line and preheader as a unified creative unit. They’re written together. They’re tested together. They’re optimized together.
I write subject lines and preheaders in pairs now. I don’t write one without the other. I’ll open a document and sketch out ten pairs, then whittle down to the strongest combinations. The subject line might be the hook. The preheader might be the context. Or the subject line might be the curiosity and the preheader the payoff. But they’re designed to work together.
This changes how you think about the creative process. You’re not writing a subject line and then finding some text to fill the preheader field. You’re writing two lines of copy that appear together in the inbox, that will be read together, that will be judged together. They need to feel like they belong together.
I’ve tested subject lines with and without complementary preheaders. The ones with complementary preheaders almost always win. Not because the preheader itself is compelling, but because the combined unit gives the reader more information and more confidence in opening.
The marketers who ignore preheaders are leaving money on the table. Not metaphorically. Literally. Every email you send without a customized preheader is an email that’s underperforming its potential. The work to fix it is minimal. The upside is measurable.
I had a client who started customizing preheaders after years of leaving them blank. Their overall open rate across all campaigns increased by 11% in the first month. No other changes. Same subject line strategies. Same send times. Same audiences. Just adding preheaders that complemented the subject lines.
Eleven percent. That’s not a small lift. That’s a significant improvement from thirty seconds of work per email.
The preheader is not a technical detail. It’s not a box to check. It’s the second line of your headline, and it deserves the same attention you give the first.
