If you ever read one of those articles that declares "Baby Boomers are impossible to reach via email marketing" — you've probably rolled your eyes. 

And rightly so.

Age, we're told, is the magic metric. Segment your subscribers into Baby Boomers, Gen X, Millennials, and Gen Z, and the marketing puzzle solves itself. 

Except — it doesn't.

In fact, age is one of the weakest data points in your email marketing toolkit.

Let's figure out why.

The Problem With Generational Buckets

It feels neat to categorise people by year of birth:

• Gen Alpha: born since 2013
• Gen Z: born since 2000
• Gen Y (Millennials): 1980 – 1999
• Gen X: 1965 – 1979
• Baby Boomers: 1946 – 1964

Useful, right? Not really.

The assumption is that someone born in December 164 (a Baby Boomer) is fundamentally different from someone born in January 1965 (a Gen Xer). Well, that's like suggesting the difference between a cup of tea made at 3:59 and one at 4:01 is dramatic enough to change the taste entirely. It's arbitrary and doesn't hold up in the real world of email marketing.

Data Without Precision Is Just Guesswork

People love classifications because they feel like shortcuts. And clearly put people in buckets. If we can put someone in a neat box, we can decide:

• What time of the day is best to send emails?
• Which products to promote?
• What language to use?
• Even, which design will resonate?

But here's the catch: age-based segmentation isn't precise enough to drive meaningful email marketing results. At best, it's a general guide. At worst, it's misleading.

Take this example: you'll often read that Baby Boomers are "less likely to use mobile phones". That's true in aggregate. But what does that mean for your specific email marketing list? Unless you're running an enormous campaign with millions of subscribers, those averages might not reflect your audience at all.

If 52% of subscribers open emails on mobile overall, what if your list sits at 68%? Or 31%? The truth is: you won't know until you test.

Why Testing Beats Assumptions

Email marketing's biggest advantage is its measurability.

Unlike traditional advertising, you don't have to guess — you can track, segment, and adapt in real time.

Instead of relying on "Baby Boomers don't click mobile emails" research, run your own tests:

• Device tracking: see how your subscribers open emails (mobile, desktop, tablet).
• A/B testing: experiment with subject lines, copy length, and visuals across demographics.
• Behavioural data: look at clicks, conversions, and purchase history — metrics far more revealing than age.

Think of age as a blunt instrument. Behavioural data, by contrast, is a scalpel. It lets you slice precisely, uncovering insights that actually change how you write, design, and send.

So, Should You Ignore Age Completely?

Not necessarily.

Age can provide context, especially when paired with other subscriber data — purchase history, engagement rates, or browsing behaviour. 

But on its own, it's not enough.

Your subscribers aren't defined by when they were born. They're defined by how they interact with your brand, what motivates them, and the trust they place in you.

In email marketing, trust and behaviour matter far more than generational labels.

The Takeaway

Relying on age as your main data point in email marketing is like building a house on sand.

It might look solid at first, but it won't hold.

If you want email campaigns that actually connect:

• Treat generational research as a broad context, not gospel.
• Test, test, and test again — your subscribers will tell you who they are through behaviour, not birth year.
• Use age as seasoning, not the whole recipe.

Because in the end, whether your subscriber is 25 or 65, the question isn't "What generation are they in?". The question is: "Does this email solve their problem, earn their attention, and win their trust?"