Demographic Targeting: Stop Guessing Who Your Customers Are

Demographic targeting is how you show ads to specific groups of people based on who they are.  It lets you show ads to people based on age, gender, income, and location instead of blasting everyone and hoping something sticks.

It is basic. But I keep seeing the same mistakes over and over. Someone sets up a Facebook campaign, picks “women 25-45” because that feels right, burns through $2,000, gets nothing. Then blames the platform. But the platform isn’t the problem.

What This Actually Means

You’re slicing up your potential customers into groups. Old people, young people, rich people, broke people, city people, rural people. Then you pick which groups see your ads.

That’s it. That’s demographic targeting.

A company selling hearing aids doesn’t need to reach 19 year olds. A brand selling skateboards probably shouldn’t waste money on retirees. Common sense stuff. But here’s where people get tripped up. They think picking the right demographics is the whole game. It’s not. It’s maybe 30% of the game. The other 70% is what you do after you pick them.

The Demographics That Actually Matter

Age

Age is the obvious one. But don’t just pick random ranges. A 22 year old and a 29 year old have almost nothing in common. One just graduated. The other might have two kids and a mortgage. Same “age bracket” on Facebook though.

Income

Income matters more than most people admit. I’ve seen luxury brands target everyone because they didn’t want to limit themselves. Then they wondered why their conversion rate was garbage. You’re not limiting yourself by excluding people who can’t afford your product. You’re being smart.

Location

Location is tricky. Someone in Miami has different problems than someone in Minnesota. Obvious for weather-related products. Less obvious for everything else. But it still matters. Regional cultures are real.

Gender

Gender used to be simpler. Men buy this, women buy that. Now it’s messier. Men’s skincare is huge. Women buy power tools. The old assumptions don’t hold up like they used to. Test before you assume.

Family status

Family status is underrated. Parents and non-parents might as well be different species when it comes to buying behavior. What they care about, when they’re online, how much disposable income they have. Completely different.

Where You Actually Set This Up

Google Ads lets you add demographics on top of keywords. So someone searching “best running shoes” who’s also female, 25-34, and has household income over $75K. That’s your target. You can get specific.

The “Unknown” category trips people up. Google can’t figure out everyone’s demographics. If you exclude Unknown, you might cut your audience in half. I usually leave it on and let the data tell me if it’s hurting performance.

Facebook has more options than you’ll ever use. Age, gender, location, education level, job title, relationship status, life events.

All targetable.

The weird thing about Facebook now though. Their algorithm has gotten aggressive about finding buyers. Sometimes you set up all this careful targeting and the algorithm basically ignores it. Goes broader. Finds people you never would have picked. And they convert better than your hand-selected audience.

I’ve tested this multiple times. Broad targeting with good creative versus narrow demographic targeting with the same creative. Broad wins more often than I expected. Not always. But enough that I don’t trust narrow targeting as much as I used to.

LinkedIn is different. B2B lives there. Job titles, company sizes, industries. If you’re selling software to HR directors at companies with 500+ employees, LinkedIn lets you find exactly those people. Expensive clicks though. Like $8-15 per click expensive. Worth it if your deal sizes are big enough.

The Difference between Demographic and Behavioral and Interest

People mix these up constantly.

Demographic is who someone IS. Their age, where they live, how much money they make. Static stuff that doesn’t change much.

Behavioral is what someone DOES. Did they visit your website? Did they abandon a cart? Did they search for your competitor? Actions they took.

Interest is what someone LIKES. They follow fitness accounts. They’re into photography. They watch cooking videos. Preferences and hobbies.

Here’s the thing. A 55 year old man might be interested in skateboarding. An 18 year old girl might be shopping for golf clubs for her dad. Demographics alone miss this stuff. Best approach is layering. Demographics as your foundation. Then add behavioral signals. Then add interests.  

Why People Still Mess This Up

Getting too specific. I watched someone target “women 28-32 with master’s degrees living within 10 miles of downtown Austin who are parents.” Audience size: 340 people. You can’t run a real campaign against 340 people. The algorithm needs room to work.

Trusting assumptions over data. You think your customers are young men. Cool. What does your actual purchase data say? I’ve seen plenty of businesses shocked when they finally look. Their real customers are nothing like who they imagined.

Forgetting the Unknown bucket. Especially on Google. You exclude Unknown because you want clean targeting. Now you’ve cut out maybe 40% of your potential reach. Those Unknown users might convert just fine. You’ll never know because you blocked them.

Ignoring platform changes. Facebook’s targeting got worse after iOS 14. Third-party cookies are dying. What worked in 2021 doesn’t work the same way now. Demographic targeting isn’t broken, but the data feeding it is getting thinner.

Treating demographics like strategy. Demographics are one input and not the strategy. If your creative sucks, perfect targeting won’t save you. If your offer is weak, reaching the exact right people won’t matter. Demographics help but don’t do the whole job.

How I Actually Set This Up For Clients

First thing I do is pull their customer data. Who’s actually buying? Not who they think should be buying. Who IS buying. CRM export, purchase history, whatever they have.

Usually there’s a surprise in there. The founder swears their customer is young urban professionals. Data shows it’s suburban moms 35-50. Happens more than you’d think.

Then I look at competitors. Not to copy them. Just to understand the landscape.

Run campaigns against each segment. Same offer, different creative angles. See what happens. The data tells you what to do next. Double down on winners. Cut losers and test new angles with the segment that’s working. This isn’t a one-time setup. What worked six months ago might not work now. Treat it like an ongoing thing, not a task you complete and forget.

Is This Even Going To Work In A Few Years?

Privacy stuff is getting serious. GDPR in Europe. CCPA in California. More states adding their own rules. The amount of demographic data platforms can collect is shrinking.

Apple’s changes already hurt Facebook’s targeting. The third-party cookie death keeps getting delayed but it’s coming. Google’s pushing their Privacy Sandbox thing.

So is demographic targeting dying?  The version that relied on tracking people across the internet is definitely dying. But understanding who your customers are and creating messages for them specifically? That’s not going anywhere.

Final Thought

Demographic targeting is one tool. Good tool. Not magic. The businesses that do this well aren’t doing anything complicated. They know who their actual customers are. They target those people. They test what works.  The businesses that fail at this are usually guessing. Picking demographics based on vibes instead of data. Setting it up once and never looking again.

FAQs

What demographics should I start with?

 Look at your existing customers first. No existing customers? Look at competitors. Still nothing? Make educated guesses and test fast.

Does this work with small budgets?

Actually works better. Big budgets can afford waste. Small budgets can’t. Targeting helps you not waste the little you have.

Which platform is best?

 Depends what you’re selling. B2B goes LinkedIn. B2C consumer products go Meta. Local services go Google.

Should I use narrow or broad targeting?

Test both. Seriously. I’ve been surprised too many times to have a strong opinion anymore. Platform algorithms are getting better at broad targeting than they used to be.

How do I know if my targeting is working?

 Cost per acquisition. If it’s going down while volume stays stable, targeting is helping. If CPA is high and you’re barely spending budget, you’re probably too narrow.