In this edition:

→ Guide to Email Marketing Metrics & Reporting

→ The Science of Sending the Right Email at the Right Time (scroll to blogs)

→ Why FAQ emails always win (scroll to videos)

→ Your data is already telling you what to send, you're just not listening to it (scroll to end)

Hiya 👋

Hope life is treating you well, or at least tolerably. It's been a busy one over here, but I'm not complaining.

Right, before we get into the good stuff, a couple of things from last edition you might have missed:

→ Deliverability Certification Programme: coming soon, you get first dibs at £48 before the price goes up 

→ Email Copy & Psychology Guide: 70+ pages of principles, knowledge & strategies

→ Email Strategy Workshops:

I mentioned email strategy workshops last time. A few of you replied (love that) - but let me actually explain what they are, because "workshop" can mean anything.

In-person or online, fully bespoke and built around you.

Before anything, I review what you've got, and we align on what success looks like.

Then we map your full email ecosystem - strategy, segmentation, messaging, automation, measurement, and whatever specific challenge you're dealing with.

Interested? Just reply. My inbox is always open✌️

Guide to Email Marketing Metrics & Reporting

The first ever marketing email got $13 million in sales 

In 1978, Gary Thuerk sent the first ever marketing email to 400 people and reportedly generated $13 million in sales. And the belief that followed, send an email, get results, has never really left the building.

The problem? The inbox is not 1978 anymore.

Yet most businesses are still measuring email like it is.

Opens. Clicks. "Revenue attributed."

Tidy little numbers on a dashboard that feel like answers, but are often lying to you.

Your quick link to read the guide →

Here's what's actually going on:

Opens aren't what you think & are not reality - they are not a positive or negative metrics and are pretty useless tbh

Clicks are better - but still broken. Security tools in B2B environments automatically follow links to check for threats. In one client audit, their reported click rate was 1.5%. Their real human click rate was 0.8%. Decisions had been made on completely made-up numbers for months.

Email creates impact before anyone even opens it. Every delivered email is a micro-branding moment. Your sender name, your subject line, your preheader - they all land in someone's environment, even if they scroll straight past.

I call it the billboard effect.

Email is an impact channel. Not a conversion channel and that's actually a more powerful position - if you know how to measure it properly.

In this piece, I break down the full measurement framework for D2C, B2C, and B2B, covering what to actually track, how to report it to leadership, and how to prove email's value without arguing theory.

From the Vault

A blog a day keeps the spam filter away 

⌚ 11 min read:

→ The Science of Sending the Right Email at the Right Time

⌚ 8 min read:

→ List Churn: Here's How to Measure It, Manage It, and Stop Panicking About It

⌚ 6 min read:

→ The Psychology Behind Email Copy

List churn: What you need to know

It's normal but it's also a important signal 

Most marketers panic when their list shrinks. Or like a dagger in the hear when someone unsubscribes. 

This piece will change how you think about unsubscribes, list health, and who actually belongs on your list.

From the Queen’s Court

Voiceover video verdicts 

Why FAQ emails always win

Your key message matters

The Inbox Drop

Your data is already telling you what to send, you're just not listening to it

We ALL guess sometimes, or we follow the generic advice on the internet on when to send, how often and how many emails

But the REAL answers are already in your stack, you just haven't modelled them yet.

Here's how to start using data to make email actually perform:

Step 1:

Know the difference between what people tell you and what they show you

You have two types of data:

• Explicit (what someone fills in)

• Implicit (what they actually do). Both matter.

Neither is enough on its own.

One tells you intent, the other confirms it.

Step 2:
Stop treating all subscribers the same

There are two types of subscribers and they need completely different treatment:

Consequential opt-ins: they signed up as a by-product of something else (a purchase, a download, a form). They didn't come for ongoing emails. You have to earn the right to keep emailing them.

Intentional opt-ins: they actively asked to hear from you. They're warmer, more patient, more forgiving.

If you treat both groups identically, your metrics will lie to you and your deliverability will suffer.

Step 3:

Only collect data that changes what you send

Before you add any field to any form, ask one question: will this change who gets what, when?

If yes, collect it and automate the change.
If no, don't bother. 

The most underrated question you can ask at sign-up? "What's the main thing you're trying to fix right now?" One answer. Completely different journey.

Step 4:
Build data over time, not all at once

Don't interrogate people on day one.

Progressive profiling is how you build a full picture without scaring anyone off.

→ At sign-up: ask the minimum needed to send the right first email
→ After first engagement: ask one more thing
→ After a purchase or action: go deeper
→ Use behaviour to fill in the rest

A conversation, not a form.

Step 5:
Use data to exclude, not just include

This is the bit most teams skip entirely, and it's one of the biggest levers you have.
New subscriber? Protect them from promos for the first two weeks.

Active sales conversation? Stop the marketing emails.
Open support ticket? Send helpful content, not a campaign.

Exclusions protect deliverability, protect relationships, and make every email you do send land better.

Step 6:

Score engagement properly
Opens alone tell you almost nothing. Build a simple composite score that weights real signals:

→ Replied to an email: high value
→ Visited pricing or demo page: high value
→ Clicked two or more meaningful links: medium value
→ Attended a webinar or event: medium value
→ Just opened: low value

Use that score to decide cadence, content type, and CTA strength. High intent gets a strong CTA. 

The full playbook, field schemas, scoring models, exclusion rules, advanced plays and copy-paste quick starts - is all in the link below.

Quick win for you

Do you actually have all your exclusions in place?

Most teams have one or two. Most teams need ten.

Grab a piece of paper (or open a doc) and map every situation in your business where someone should NOT be receiving a standard marketing email.

Here's a starter list:

B2C / D2C:
→ Subscribed in the last 14 days
→ Open customer service ticket
→ Active complaint
→ In-progress return or refund
→ Just purchased (protect from immediate promo)
→ High value customer (needs different messaging, not the same blast)
→ Subscriber showing intent but not buying (needs different strategy) 

B2B:
→ Active deal in pipeline
→ In onboarding
→ Open complaint or escalation
→ Recently churned
→ In a re-engagement sequence
→ Contacted by sales in the last X days
→ Active support ticket
→ Wrong lifecycle stage for this message

Now cross-check that list against your current campaigns.

How many of those situations have an exclusion rule built in?

Every gap is a relationship at risk and a deliverability signal you don't want to be sending.

Plug of the week 

Training and workshops 

I run workshops and training sessions on email strategy, deliverability, design, copy, and more - for individuals and teams, in person or online.

May your list be healthy, your data be useful, and your emails actually go to the inbox,

Beth ✌️

I have ADHD (IFYKYK) so please excuse any typos and spelling errors in this email.

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