10 things I stopped doing with email that most marketers still do

I have been doing email professionally for a long time (nearly 13 years!). Long enough to have done it the wrong way, worked out why it was wrong, and changed how I do it.

Long enough to have watched the same patterns show up across hundreds of programmes and to recognise which ones are genuinely useful and which ones are habits that nobody has stopped to question.

This blog tells you ten things I stopped doing, not because I read a study that said I should, but because I kept watching them fail in practice, and eventually I found approaches that worked better.

Some of these will be uncomfortable if your programme is built around them. That is okay. Discomfort is usually where the useful stuff starts!!

1. Reporting on open rates as a performance metric

Most people still: Put the open rate in every campaign report and present it as evidence the email worked.

The open rate is the most widely reported email metric in the world, and it is one of the least reliable indicators of whether your email programme is actually performing.

Apple Mail Privacy Protection inflates open rates by preloading tracking pixels before the email is opened. Outlook's reading pane suppresses opens by allowing emails to be read without triggering tracking. Humans open emails to delete them, to clear the unread notification, or because a clickbait subject line tricked them into it. A high open rate can mean the content is great, or it can mean the subject line overpromised and the body underdelivered. The number alone tells you almost nothing about the difference.

I stopped putting open rate in reporting as a primary performance metric years ago. I still look at it — as one signal among many, used to spot unusual changes, not to declare success. "We had a 40% open rate" is not a result. "Our email subscribers took 2,400 meaningful actions this month" is a result.

The question I replaced it with is: what is email contributing to across the whole journey? That is a completely different question, and it produces completely different answers about what the programme is actually worth.

2. Using industry benchmarks to measure emails 

Most people still: Compare their open rates, click rates, and unsubscribe rates against industry averages and worry when they are below them.

Industry benchmarks are averages of everyone else's programmes, built in different contexts, with different audiences, at different lifecycle stages, with different content strategies. When you measure your programme against them, you are measuring it against people who have nothing in common with you except that they also send email.

A 20% open rate in an industry report might be the average for a sector that sends monthly, to highly intentional subscribers, with very specific educational content. Comparing that to a retail programme sending twice weekly to a mixed list of intentional and consequential opt-ins is meaningless. The numbers are not describing the same thing.

Your benchmark is your own historical data. Is this month better than last month? Is this quarter better than last quarter? Is per-send engagement holding steady or declining? Those comparisons tell you something real about your programme's direction, because they control for all the variables that make external benchmarks useless.

3. Using double opt-in

Most people still: Keep double opt-in on as a default, citing deliverability protection and compliance.

Double opt-in was invented in 1993 by LISTSERV, when there were no email address validation tools and the only way to verify an address was real was to make someone reply to confirm it. We are now in 2026. Real-time validation tools can check whether an address is valid, active, and not a known spam trap at the point of form submission, before you ever send anything at all.

The deliverability argument for double opt-in does not hold up. A bounced confirmation email damages your sender reputation exactly as much as a bounced welcome email. You are not preventing the bounce — you are just changing which email triggers it. The protection you actually need is validation at entry, not a second confirmation step.

The experience argument is worse. You ask someone to take an action — sign up, purchase, download something — and then you send them an email asking if they really meant to. On top of which, many ESPs suppress automated emails, including the thing the person actually signed up to receive until they complete the confirmation, so the lead magnet or the welcome content or the promo code never arrives. You broke the promise you made at the point of sign-up.

Double opt-in is not required by GDPR, CAN-SPAM, or CASL. It is only a legal requirement in a handful of specific markets including Germany and Austria. Everywhere else, it is a choice and it is usually the wrong one! 

4. Building email journeys based on time elapsed

Most people still: Set up automation sequences triggered by days: email one on day one, email two on day three, email five on day fourteen.

Time-based sequencing is the automation equivalent of sending the same email to everyone and hoping some of them happen to be in the right mindset to engage. It is the default because it is easy to build, not because it works well.

The problem is that a subscriber who signed up and immediately activated a key feature of your product, invited a colleague, and visited your pricing page is in a completely different place from one who signed up, visited for twenty seconds, and has not been back. By day five, the first person needs a conversion conversation. The second person needs help understanding what they found confusing. A time-based sequence sends them both email five, because it is day five.

What actually matters is not how many days have elapsed since someone joined your list — it is what they have done since then. A behavioural trigger fires when something happens, or when something that should have happened has not. That is the signal worth responding to. Day five is not a signal! 

5. Sending to the whole list because the list feels too small to segment or adding more to the list because segment is too small

Most people still: Worry that segmenting will make the numbers look too small, and send to everyone instead.

This is one of the most expensive beliefs in email marketing, and it is rooted in a fundamental misunderstanding of what list size is for. A large list is not an asset if the majority of it is the wrong people receiving the wrong email at the wrong time — it is a deliverability liability.

The belief that more recipients equals more results is mathematically plausible but practically wrong. What you actually get from sending to a large, unsegmented list is diluted engagement rates, higher complaint risk from people receiving irrelevant emails, and deteriorating sender reputation as the inbox providers' engagement prediction models learn that a significant portion of your audience does not want what you are sending.

A smaller, well-segmented send to people for whom the email is genuinely relevant will almost always produce better per-send results and better deliverability outcomes than a larger send to everyone. The number at the top of the segment is not the goal. The outcome at the bottom of the journey is.

I also tell clients: getting the list smaller through better exclusions and tighter segmentation is a feature, not a failure. The mindset shift from "how do I reach more people?" to "how do I reach the right people?" is the most commercially valuable change you can make to your email strategy.

6. Trying to capture attention in the inbox

Most people still: Write subject lines and email content designed to "capture" or "grab" attention as though attention is something you have to wrestle from the subscriber.

This framing fundamentally misunderstands what the inbox is and how people use it.

You cannot capture attention in the inbox. You already have it!! The moment your email appears in someone's inbox, their brain processes your sender name, your subject line, and your preheader, passively, automatically, in under two seconds. The attention is not something to be fought for; it is already happening. What you are competing for is a positive response to that automatic processing, and the way you earn that is through relevance and familiarity, not through trying to interrupt or hijack.

People do not enter their inbox looking to be surprised or entertained. They enter in a mode — task, utility, reward-seeking, avoidance, or learning. Your email lands into whatever mode they are in and is assessed against it instantly. The emails that win are the ones that feel immediately consistent with what that subscriber already associates with you, and relevant to where they are right now.

The five things the brain does the moment the inbox opens are:

• Assess cognitive load (is this too hard to find the point of?)

• Triage (does this fit my current mode and priority?)

• Predictive coding (does this match what I expect from this sender?)

• Check emotional association (how do I feel about this sender based on history?)

• Test for pattern interruption (is anything here unexpected enough to spike my attention?).

Understanding those five things is more useful than any subject line hack.

7. Calling it (and treating it like) a welcome flow

Most people still: Build a welcome sequence and consider the new subscriber relationship properly established.

A welcome flow welcomes someone! That is all it does.

It acknowledges their arrival, sends them the thing they signed up for if there is one, and maybe gives them some information about the brand/business/person. It is transactional, and it is passive.

An orientation flow does something different. It deliberately establishes what the subscriber relationship is, what they can expect from it, what makes it worth their time, and what to do next. It is built around the subscriber's context, why they arrived, what they are trying to do, what they are thinking and feeling at this stage, rather than around what the brand wants to tell them. And it varies based on how they arrived, because someone who signed up intentionally for a newsletter has completely different needs from someone who ended up on the list as a consequence of making a purchase.

The first email a subscriber receives is the highest-engagement moment in the entire relationship. That is the moment when the association with your brand is being set, when the expectation for every subsequent email is being established, when the pattern the subscriber's brain will use to assess your emails for the next two years is being built. Using that moment to send a generic "welcome, here's what we do" email is one of the most consistent wastes of the most valuable real estate in email marketing.

8. Treating email as a performance channel measured per campaign

Most people still: Report on email by looking at what each individual campaign generated in revenue, clicks, or conversions, and judge the programme's health from those individual numbers.

Email is an impact channel, not a performance channel. The difference matters enormously, for how you build the programme, how you report on it, and how you defend its commercial value to stakeholders who want to see the number from the last send.

Last-click attribution on email captures the visible, traceable, immediate portion of what email does. It misses the brand awareness built through inbox impressions across subscribers who never open a single email. It misses the pipeline velocity created by nurture sequences that move leads towards readiness over weeks or months. It misses the customer retention generated by post-purchase flows that make customers successful with what they bought. It misses the direct search traffic that spikes when email is consistent and present, because the billboard effect is real and it does not show up in campaign reporting.

The question "did this email generate sales directly?" is the wrong question.

The question is "what is email contributing to across the whole journey?"

Those are different questions and they produce different answers. One of them produces a number that undersells email every time. The other produces a picture of what email is actually doing for the business.

We did not measure what mattered. We made what we could measure, matter. That is the summary of thirty years of email reporting, and it is time for it to change.

9. Setting best practice as the standard

Most people still: Implement the recommended frequency, the recommended subject line length, the recommended send time, and the recommended re-engagement threshold without questioning whether any of it applies.

Best practice in email is largely BS and I will be direct about this! 

Best practice is an average of what works across a wide range of programmes, audiences, and contexts. It is designed to be safe advice for the broadest possible audience, which means it is optimised for nobody in particular. The recommendation to send on Tuesday at 10am, to keep subject lines under 50 characters, to suppress anyone who has not opened in 90 days, to always use double opt-in — these are generalisations that may or may not apply to your specific programme with your specific audience and your specific commercial context.

What best practice does not tell you is whether it fits your strategy. Should we? Can we? Does it fit what we are trying to do? Those are the questions. Best practice can prompt the thinking, but it cannot substitute for it. A principle tells you what to think about. Best practice tells you what to do. The principle is more useful.

The most expensive version of this I see regularly: suppressing subscribers at 90 days of email inactivity because "that is best practice," without checking whether they have website visits, recent purchases, event attendance, or any other brand interaction that signals they are not actually disengaged from the brand — just not engaging via email as a specific channel. Disengaged from email and disengaged from the brand are completely different things, and the 90-day rule does not know the difference.

10. Writing subject lines designed to maximise opens

Most people still: Test subject lines against each other to find the one that produces the highest open rate, and treat that as the measure of subject line quality.

This is the logical conclusion of the whole opens-as-success-metric problem, and it produces a specific and consistent failure mode: subject lines that are optimised for curiosity and withholding rather than for relevance and clarity.

The inbox brain is not looking to be intrigued. It is triaging. The question it is asking in under two seconds is: does this belong in my current mode and priority? A subject line that creates mystery without signalling relevance — "you won't believe this," "something important," "have you seen this?" — fails that test for most subscribers, most of the time, because it asks for the open before earning it.

The better question is not "which subject line will get the most opens?" but "which subject line most accurately represents what this email delivers, for this specific subscriber, right now?" Because an email opened on the back of a misleading or curiosity-baiting subject line and then abandoned when the content does not match the expectation is a negative brand experience. It builds the wrong association. It trains the subscriber's brain to distrust the pre-open promise from this sender. And it shows up in your engagement data as an open — which is why open-optimised subject line strategies consistently produce decent open rates and poor downstream performance.

A/B testing subject lines on small samples and calling the winner the right subject line is another version of this. With standard sample sizes, the confidence intervals on A/B subject line tests are so wide that the results are statistically meaningless, you are measuring noise and calling it signal.

The end

None of these are things I stopped doing because I read an article that said they were wrong.

I stopped doing them because I watched them fail across enough programmes, with enough different audiences, in enough different contexts, to be confident that better approaches exist.

The through-line across all ten is the same: email works best when it is built around the real human in their real inbox at their real moment of encounter, measured by what it actually contributes to the business over time, and governed by principles rather than rules.

The hard part is that most of the things on this list are the defaults! They are what ESPs suggest, what industry guides recommend, what your predecessor probably did, what the last marketing team normalised. Stopping them requires actively deciding to do something different, which requires both conviction and the ability to explain the decision to stakeholders who are used to seeing the old metrics.