What have we found to expand your email knowledge today?

Here are a few of our favourite links from across the email and business world, carefully curated just for you:

Find of the week ⭐

Having double opt-in on your emails is certainly encouraged, but often, it’s also something that could be holding back audience growth.

If a new subscriber misses that ONE email from you to confirm their subscription, you’ve lost them. Forever.

Our friend, Dylan Redekop, who runs the amazing Growth Currency newsletter, has an ingenious False Double Opt-In strategy that looks after your list and ensures you don’t rely on folks hitting that “confirm” button.

If you’re keen to see how he does it and receive his brilliant emails (we’re big fans), make sure you check that out

Grab your FDO walk-through guide here.

We’re also constantly on the lookout for new resources, news, tools and links, so hit us up if you’ve got something valuable to feature!

We've spoken about A/B testing before (and you see it as part of those “expert recommendations” all the time.)

But, there’s something most experts providing email advice get wrong:

The majority of A/B testing guidance is built for marketing emails.

Think about it. Often, this advice speaks about promos or product launches. It’s often testing those abandoned carts or discounts in flash sales.

And that's great if you're an e-commerce brand trying to squeeze an extra 0.3% out of a checkout flow.

But if you're a newsletter sender? Half of that advice doesn't apply to you.

As newsletter senders, we’re not optimising for a single conversion.

Everything we do is built around optimising for people to keep showing up, keep reading, and keep clicking.

That's a fundamentally different game.

So today, we're offering a little perspective and focusing on what actually makes sense to test when you're sending recurring content to an audience that's chosen to hear from you.

And the good news? Most of these apply to your marketing emails, too.

This is what trips most newsletter operators up before they begin testing.

They test because they've been told to test. They A/B their subject lines because some blog post said so. They try a new button colour or subject line because…that’s all they know.

But testing without intention is just guessing with extra steps.

Before any test, ask yourself: What decision will this help me make?

If you can't answer that, you're not ready to test. You're (honestly) just spinning wheels in the mud.

A/B testing works when it's tied to something specific you're trying to improve. For newsletters, that's almost always:

Everything below ties back to those three.

Not "best time to send" generically. Your audience's sweet spot. Pick two realistic windows and split-test with identical content.

What you're looking for isn't just opens.

We spoke about this last week, but you want to measure when your “North Star” metric performs best.

Someone might open at 7 am on their phone during a commute and skim right past. That same person at 12 pm on a laptop might click three links and actually engage.

The open tells you when they noticed. Your North Star metric (which, for us, remains clicks) determines when they act.

If you’re dipping your toes into the A/B testing and optimisation side of things ( you like our GIF this week? 😏), run this over 3 to 4 sends minimum, because you need enough data to make the right call on send timing.

If your newsletter has multiple sections (curated links, main article, community highlights, a meme…sound familiar?), the order matters more than you'd think.

Put your deep-dive first in Version A. Lead with curated links in Version B.

Then check: Which version gets more total clicks? Which gets clicks deeper into the email?

The answer will be specific to your audience, and that's the whole point.

Button vs text link. Some audiences prefer a visual button. Others click more on inline text links because they feel less "salesy."

Top vs bottom of section. Do readers click after the intro, or after the full explanation?

Specific vs generic copy. "Read more" vs "See the full teardown" vs "Grab the checklist." Specificity tends to win because it tells the reader exactly what's on the other side.

Test one variable at a time. (This is NB!) Change everything at once, and you'll learn nothing and blame the wrong thing.

Are your readers scanners or deep readers?

You probably think you know, but have you ACTUALLY tested it?

Send a concise edition against your standard length. Compare clicks, scroll depth and replies.

You might discover your audience reads more when you write less. Or your longer editions drive more clicks because the depth builds enough context to make links feel worth clicking.

Either way, you're making decisions based on evidence, not assumptions. Plus, there’s scope to having a TLDR segment of readers too, why the heck not?

The beauty of the newsletter is that it’s an expression of you, your style, and your voice.

The fact that each one has unique elements means that you can test things that are unique to your emails.

Here’s what we often wind up testing to enhance our experience for our readers:

Your newsletter is YOUR space, but you have a direct feedback mechanism from your audience, so use it.

Every A/B testing article starts here. We intentionally left it for last.

Subject lines still matter, but their importance is shifting. With AI inbox summaries becoming the norm (hey, Gmail), your subject line is increasingly competing with a machine's interpretation of your content, not just other subject lines.

If you do test them, test the type, not just individual words:

That gives you a reusable strategic insight, not just a one-off winner.

Test the things that shape the reading experience, not just the things that get the email opened.

Opens are the door. What happens inside is the house. Your readers decide whether to stay and come back based on what they find once they're through.

Pick one thing from today's list. Test it over your next 3-4 sends. Let your audience tell you what they want.

That's how newsletter growth actually works.

What are you testing ~ Let us into your brain here ~ 💌

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It’s the inevitable small-talk question: “So, what do you do?”

Let’s all just cut to the chase 🙃