Solved: Meta showing ads to the wrong age group

Hi there,

Thanks for reaching out!

Happy to give you some initial thoughts on the issue you're having with Meta Ads. It's a really common problem, so don't worry, you're not alone in this. I've seen this happen across quite a few accounts, from eCommerce stores to software businesses. The platform can be a bit of a law unto itself sometimes.

What you're describing, where Meta seems to ignore your age targeting and shows your ads to a much older demographic, is something we see a fair bit. It's frustrating, especially when you've clearly defined who you want to talk to. But before we get into the tricks and tactics, it’s important to understand why this is probably happening. It's rarely a simple glitch.

We'll need to look at why Meta is doing this...

The first thing to get your head around is Meta's algorithm. Its primary goal isn't to follow your instructions to the letter; its goal is to get you the results you asked for (e.g., clicks, conversions, video views) at the lowest possible cost to them. It's a machine built for efficiency, not obedience.

When you set up a campaign with a "Reach" or "Brand Awareness" objective, you're basically telling the algorithm: "Find me the largest number of eyeballs for the cheapest price." And who are the cheapest eyeballs? Often, it's users who aren't in high demand from other advertisers, who don't click on many things, and who are less likely to buy. You're effectively paying Meta to find you the worst possible audience. I've seen so many businesses burn cash this way, thinking they are building a brand when they are just talking to people who will never become customers.

Even with a conversion objective, the algorithm is constantly hunting for pockets of users within your targeting parameters that are most likely to take an action for the lowest cost. If women aged 45+ or 65+ are, for whatever reason, more likely to click on your ad or are simply cheaper to show ads to than an 18-25 year old, the algorithm will divert budget there. It sees a 'cheap win' and takes it, even if it's outside the core demographic you've set. It thinks it's helping you by getting a cheaper cost-per-result, but it's completely missing the point of your brand's strategy.

So, the problem isn't just a setting you've got wrong. It's a signal that there's a disconnect somewhere in your overall strategy. The algorithm is finding a path of least resistance to a surface-level goal, and that path leads to an older audience. Our job is to close that path and force it to find your actual customers. This usually means we need to look deeper than just the age settings in Ads Manager. It often comes down to the ad creative itself, your audience layering, and even your core offer.

I'd say you need to seriously critique your ads...

This is probably the most overlooked area. You say you're targeting women aged 18-44, but does your ad scream that it's for them? Or is it a bit generic? The algorithm is smart. It analyses the image, the video, the copy, and the reactions it gets. If your creative unintentionally resonates with an older demographic, the algorithm will notice that and lean into it, because it's getting positive signals (likes, clicks, shares) from that group.

Think about the messaging. An ad that works for a high-ticket product often uses a "Problem-Agitate-Solve" framework. You identify a pain point, you pour a bit of salt in the wound, and then you present your product as the solution. For instance, you don't sell "a nice dress"; you sell "the confidence to walk into a room and own it, instead of feeling invisible again."

Let's think about your audience. The problems of an 18-year-old are completly different from the problems of a 44-year-old.

• -> For the 18-25 group: Their pain might be about fitting in, expressing individuality on a budget, or finding something unique for a specific event like a festival or a uni social. The messaging should be about self-expression, trends, and community.
• -> For the 26-44 group: Their pain might be about finding quality that lasts, juggling a career and family life, wanting to feel stylish without looking like they're trying too hard, or finding clothes that are both comfortable and professional. The messaging here should be about quality, versatility, and sophisticated style.

If your ad copy is generic, like "Beautiful products for women," it could appeal to anyone. But if your copy is, "Tired of fast-fashion that falls apart? Our timeless pieces are designed for the modern woman who does it all," you're speaking more to that 26-44 demographic. Conversely, "Your festival fit just dropped," is clearly aimed at the younger end. Your creative—the models you use, the styling, the music in videos, the graphic design—all send powerful signals about who this product is for. If there's a mismatch, Meta will exploit it.

Here's a practical demonstration of how we might re-work copy. Imagine you sell unique, handmade jewellery.

You see the difference? The targeted versions are impossible to mistake. They speak a different language. You need to be doing this. Split your campaigns by age demographic like you have, but then give each one creative that is hyper-specific to them. It gives the algorithm much stronger signals about who to find.

You probably should rethink your audience strategy...

Just setting an age and gender is the most basic form of targeting. It's like using a sledgehammer when you need a scalpel. To force Meta to find the right people, you need to give it more constraints. This is where audience layering and building a proper funnel comes in.

I'd suggest you start by thinking about interests. What do women in your target age groups actually care about? Don't just target "Fashion" or "Shopping"—that's far too broad. You'll get everyone. Think more specifically.

• -> For the 18-25 group: Which brands do they follow (e.g., Glossier, Aritzia, Urban Outfitters)? Which influencers? Which musicians? Which university groups or publications? You can layer these interests, so you're targeting 'women 18-25 who like Brand X and Influencer Y'. This narrows the pool considerably.
• -> For the 26-44 group: What are their interests? Maybe it's specific magazines (e.g., The Gentlewoman, Vogue), high-end but accessible brands (e.g., & Other Stories, ME+EM), parenting blogs, or professional networks. Again, layering is your friend.

The key is to pick interests that your target audience is much more likely to have than the general population. Targeting "Amazon" is useless if you sell eCommerce software because everyone uses Amazon. But targeting "Shopify" and "Retail Page Admins" is much smarter. It's the same principle for your product.

Beyond this initial 'cold' targeting (ToFu - Top of Funnel), you need to build out the rest of your funnel. Right now, it sounds like all your budget is going on trying to find new people. The real money in eCommerce is made in the middle and bottom of the funnel (MoFu and BoFu).

This means setting up retargeting campaigns. These are your highest-value audiences because they already know who you are.

1. MoFu (Middle of Funnel): Retarget people who have visited your website in the last 30-60 days but haven't purchased. Show them ads featuring different products, testimonials, or your brand story.
2. BoFu (Bottom of Funnel): This is your goldmine. Retarget people who have added a product to their cart or initiated checkout in the last 7-14 days. These people were this close to buying. Hit them with an ad showing the exact product they left behind, maybe with a gentle nudge like "Still thinking about it?" or a small "free shipping" offer. We've seen huge returns here for clients, like the 691% return we got for a women's apparel brand, which was driven heavily by a rock-solid retargeting structure.

Once you get some sales from the correct demographic, you unlock Meta's most powerful tool: Lookalike Audiences. You can create an audience of your past purchasers and tell Meta, "Go and find me more people who look exactly like this." A Lookalike of your buyers is a thousand times more effective than just targeting an age range. It's based on thousands of data points and behaviours, not just a birthday.

A proper campaign structure might look like this:

• -> Campaign 1: Prospecting (ToFu) - Objective: Conversions (Sales). Ad sets targeting your different layered interest groups for each age bracket (18-25, 26-44). Exclude all past purchasers and recent website visitors.
• -> Campaign 2: Retargeting (MoFu/BoFu) - Objective: Conversions (Sales). One ad set for website visitors, another for cart abandoners. Exclude past purchasers.
• -> Campaign 3: Loyalty (Past Customers) - Objective: Conversions (Sales). Target past purchasers to announce new collections and drive repeat business.

This structure forces the algorithm to work smarter. It's no longer just chasing cheap clicks; it's working within a system designed to guide a customer from awareness to purchase and beyond.

You'll need an offer that speaks directly to their pain...

This might be the most difficult bit of advice, but it's the most important. If, after refining your creative and your targeting, you still find your ads aren't landing with the right people, the problem might be more fundamental. It might be your offer.

The number one reason advertising campaigns fail is a weak offer, or a lack of real demand for that offer from the target audience. You have to forget about your product's features for a moment and focus on the customer's nightmare. Your Ideal Customer Profile isn't a demographic ("women 18-44"); it's a problem state ("I have nothing to wear for this wedding and I feel awful about myself"). Your product is the solution to that nightmare.

You need to ask yourself some hard questions:

• What specific, urgent, expensive problem does my product solve for a 22-year-old?
• What specific, urgent, expensive problem does it solve for a 38-year-old?
• Are these problems truly urgent, or just 'nice to haves'? Ads work best on urgent problems.
• Is my brand's value proposition crystal clear on my website and in my ads? Why should they buy from me and not one of the thousand other brands competing for their attention?

I remember one client, a B2B software company, was struggling with their accounting system ads. While your product is different, the core issue they faced is highly relevant: their offer was misaligned with their market's real pain points. They were trying to sell on "privacy," but their customers cared more about reliability and features, and they weren't offering a free trial, which was standard in their industry. No amount of clever ad targeting could fix that. We had to help them reshape the offer first, focusing on a free trial and messaging that addressed the real-world accounting headaches their customers faced. Only then did the ads start to work.

For you, this means ensuring your entire funnel, from the ad to the landing page to the checkout, is a seamless experience that reinforces the value proposition for your specific target customer. If a 22-year-old clicks an ad that speaks her language but lands on a website that feels generic or aimed at her mum, she'll leave. The congruence has to be there every step of the way.

Let's bring it all together

As you can see, the issue of "Meta showing ads to the wrong age group" is often just the tip of the iceberg. It's a symptom of a deeper strategic misalignment. Fixing it isn't about finding one secret button in Ads Manager. It's about building a robust advertising system where the creative, targeting, funnel, and offer all work in harmony to attract your ideal customer.

This process takes time, testing, and a willingness to be brutally honest about what's not working. You have to be prepared to test different audiences, different ad copy, different images, and maybe even rethink how you present your products. It's a process of continuous optimisation.

I've detailed my main recommendations for you in a table below to make it a bit clearer.

I know this is a lot to take in. It's a shift from 'running ads' to 'building a customer acquisition machine'. This is where professional help can make a huge difference. An experienced eye can spot these misalignments quickly and implement a structure like the one above far faster than you could through trial and error, saving you a lot of time and wasted ad spend.

We've helped brands in similar positions turn things around—like an eCommerce store we worked with that saw a 1000% return on ad spend, or a software client where we significantly reduced their cost per acquisition from £100 down to just £7. This level of performance doesn't come from just tweaking age settings; it comes from implementing a comprehensive, strategic system.

If you'd like to go through your account in more detail, we offer a free, no-obligation 20-minute strategy session where we can audit your live campaigns and give you a concrete plan of action. It might be a good next step to get some clarity.

Hope this helps give you a new way to think about the problem.

Regards,

Team @ Lukas Holschuh