Solved: Same People Seeing Ads Across Products

Hi there,

Thanks for reaching out!

It sounds like you're dealing with a really common but proper frustrating issue. Seeing the same faces pop up for completely unrelated products is a classic sign that something's off with the targeting strategy. It's a massive waste of budget and tells you the ad platform is just lumping people together.

Happy to give you some initial thoughts and guidance. The good news is this is almost always fixable. The problem isn't usually with the platform itself, but in how you're defining and segmenting your audiences from the get-go. We'll need to get a lot more specific and strategic about who you're talking to for each product.

We'll need to look at your fundamental approach to targeting...

Right, let's get straight to it. The reason the same people keep seeing your ads for two different products is almost certainly because your targeting is too vague. You're probably using broad interest categories like "shopping" or "business" or something similar for both. Meta's algorithm sees this, finds the cheapest people within those massive pools who tend to click on things, and shows them everything you run. It's doing its job, but its job isn't to find your actual customers unless you give it much, much better instructions.

Here's the first contrarian truth you need to embrace: your ideal customer is a nightmare, not a demographic. Forget "males, 35-55, living in London". That tells you nothing useful. It leads to generic ads that speak to no one and get shown to everyone. To stop burning cash, you have to define each customer by their specific, urgent, and expensive problem. The 'nightmare' that keeps them up at night.

What is the career-threatening, peace-of-mind-destroying problem that Product A solves? And what is the completely different, equally painful problem that Product B solves? These two nightmares are the foundations of your two separate advertising worlds. Until you can articulate these with absolute clarity, you'll continue to fish in the same muddy pond and catch the same uninterested fish.

Think of it like this. Broad interests are like a giant, overlapping Venn diagram. Your two customer types might be in there somewhere, but so are millions of other people who are completely irrelevant. Your job is to find the small, distinct circles that contain only your ideal buyers. These circles aren't defined by 'interests', they're defined by 'intent' and 'pain'.

I'd say you need to define two completely separate customer nightmares...

So, let's make this practical. You need to sit down and create two completely separate Ideal Customer Profile (ICP) documents. Not based on what they look like, but on what they're struggling with. Let's imagine for a moment that Product A is a B2B SaaS tool for managing project workflows, and Product B is a high-end, handcrafted leather wallet for consumers.

The buyer for Product A isn't just a 'Project Manager'. Her nightmare is her best developers threatening to quit because of chaotic workflows and constant interruptions. She's terrified of missing a critical launch deadline, which could damage her reputation and cost the company millions. She's desperately searching for a way to bring order to the chaos. Her pain is professional, urgent, and has significant financial consequences.

The buyer for Product B isn't just a 'man who needs a wallet'. His nightmare is feeling disorganised and unprofessional every time he pulls out his bulky, falling-apart wallet. He values craftsmanship, durability, and a sense of personal style. He's frustrated by mass-produced junk that doesn't last. His pain is personal, emotional, and tied to his self-image.

See the difference? One is trying to avoid a career disaster, the other is seeking a feeling of personal pride and organisation. They live in different worlds. They read different things, follow different people, and use different language to describe their problems. Your ads, your targeting, everything must reflect this separation. You're not running ads for two products; you're running two completely different businesses from a markeiting perspective.

Here’s a simplified breakdown of what these two ICPs might look like:

Once you have this level of clarity, your ad copy writes itself. You use the "Before-After-Bridge" framework. You describe their current "nightmare" (the Before), paint a picture of their "dream" (the After), and position your product as the thing that gets them there (the Bridge). This is how you create ads that resonate so strongly with one group that they're almost invisible to the other. You stop talking about features and start talking about solving their pain.

You probably should structure your account like a proper funnel...

Okay, so you've defined your two separate nightmares. Now you need to build two separate houses for them to live in. In paid ads, this means building two completely separate funnels, one for each ICP. Tbh, this is where most people go wrong. They lump everything into one or two campaigns and hope for the best. A proper structure will give you control and stop the audience overlap dead in its tracks.

A funnel has three basic stages:

• -> Top of Funnel (ToFu): This is your cold traffic. People who have never heard of you. Here, you're targeting those pain-based interests we just talked about. Your goal is to get their attention and make them problem-aware.
• -> Middle of Funnel (MoFu): These are people who have shown some interest. They've watched your video, visited your website, or engaged with your ad. You retarget them with a different message, perhaps showing testimonials or a different angle of the product.
• -> Bottom of Funnel (BoFu): These people are close to buying. They've added to cart or visited the checkout page. You retarget them with an urgent offer to get them over the line, like a small discount or a reminder.

You need to build this entire three-stage structure for Product A. And then you need to build a completely separate one for Product B. They should never cross paths. This is achieved through careful campaign structure and, most importantly, exclusions, which we'll get to next.

Here’s a visual representation of how these two parallel funnels should be structured in your ad account. This seperation is not optional, it's the only way to ensure your budget for Product A isn't being wasted on potential customers for Product B, and vice-versa.

You'll need to get serious about exclusions...

This is the part that ties everything together. Building two funnels is great, but they'll still leak into each other if you don't build walls between them. These walls are your audience exclusions. It's a simple concept but it's amazing how many advertisers ignore it.

You need to be ruthless with your exclusions. Here’s a basic set of rules you should implement immediately:

• -> Exclude All Existing Customers: In your ToFu (cold traffic) campaigns for both products, you should always exclude everyone who has ever purchased from you. You've already acquired them, so stop paying to acquire them again. (The exception is if you're selling them something else, but that's a separate customer campaign, not a prospecting one).
• -> Exclude Funnel Traffic from Each Other: In your Product A ToFu campaign, you must exclude everyone in your Product A MoFu and BoFu audiences (e.g., website visitors, people who've added to cart). This ensures people move smoothly down the funnel and don't keep seeing your introductory ad.
• -> Cross-Exclude Product Audiences: This is the most important one for your specific problem. In your *entire* Product A funnel (ToFu, MoFu, BoFu), you should exclude everyone who has purchased Product B. And in your *entire* Product B funnel, you must exclude everyone who has purchased Product A.
• -> Cross-Exclude Website Visitors: To be even safer, in your Product A ToFu campaigns, you could exclude people who have visited product pages for Product B in the last 30 days, and vice versa. This keeps the initial prospecting super clean.

Implementing these exclusions transforms your ad account from a chaotic mess into a clean, efficient machine. It forces the platform to find genuinely new people for each product, rather than just serving ads to the same pool of low-cost, easily reachable users.

This table shows a simplified set of exclusion rules. A robust strategy involves many more layers to ensure minimal audience overlap.

We'll need to look at how you're actually selecting audiences on Meta...

Once you've got your funnels and exclusions sorted, the next step is actually choosing what to put in your ToFu campaigns. You know you need to be specific, but how specific? And what do you test first? I see so many clients wasting money on lookalikes that are too broad or interests that are completely irrelavent.

Here's the priority order I'd usually recommend testing audiences in, especially for a new or restructured account:

1. Detailed Targeting (Interests, Behaviours): Start here. This is your foundation. Use the 'nightmare' profile you built to brainstorm hyper-specific interests. If you're selling the SaaS tool, don't just target 'Project Management'. Target users of competitor tools like Asana or Trello. Target followers of industry influencers. Get granular. If your interest contains millions of peopel who don't fit your ICP, it's a bad interest.
2. Lookalike Audiences: Once you have enough data (at least 100 conversions, but ideally 1,000+), you can create lookalikes. But be strategic. A lookalike of 'all website visitors' is rubbish. You want a lookalike of your *best* customers. Start with a lookalike of purchasers, then work your way up the funnel (lookalike of checkouts, adds to cart, etc.). Always start with a tight 1% lookalike before testing broader ranges.
3. Broad Targeting: Only, and I mean *only*, test broad targeting (where you just set age/gender/location and nothing else) once your pixel has thousands of conversion events. You need to have 'taught' the algorithm exactly who your customer is before you can let it run free. Doing this too early is just throwing money away.

A big mistake is targeting an interest that's too broad. "Amazon" is a terrible interest if you want to target eCommerce store owners, because millions of shoppers also have that interest. You need to find interests that have a high concentration of your ICP. To help with this, you can use a simple scoring system to sanity-check your choices.

Use the calculator below to think about your audience choices. An interest like 'Jira' for a SaaS workflow tool is highly specific and relevant. An interest like 'Technology' is terrible. You want to live in the high-score zone.

I'd recommend you get a handle on what good performance actually looks like...

One last thing. Once you start running these new, structured campaigns, you need to know what to aim for. The cost of a conversion isn't a random number; it depends hugely on what you're selling, who you're selling to, and where in the world they are. A lead for a B2B SaaS product will cost a lot more than an email signup for a newsletter.

Based on our experience running hundreds of campaigns, here are some very rough ballpark figures. In developed countries (like the UK, US, Canada), a click (CPC) might cost you between £0.50 and £1.50. A good landing page might convert 10-30% of that traffic into a simple lead or signup. That gives you a Cost Per Lead (CPL) of anywhere from £1.60 to £15.00.

However, if your goal is an actual sale (a much harder conversion), your conversion rates will be much lower, maybe 2-5% for a typical eCommerce store. Suddenly, your Cost Per Purchase could be between £10 and £75. For high-ticket B2B, these numbers can be far, far higher, and that's perfectly normal. I remember one B2B software campaign we worked on where a qualified lead cost $22, but because the lifetime value of that customer was in the thousands, it was incredibly profitable.

The point is not to panic if your costs seem high initially. The real question is not "How low can my CPL go?" but "How high a CPL can I afford to acquire a profitable customer?" Understanding these benchmarks helps you test audiences intelligently. If one audience is costing you £100 per lead and another is £20, you know where to focus your budget. But if you don't have these reference points, you're just flying blind.

This is the main advice I have for you:

This is a lot to take in, I know. But fixing your audience overlap problem requires a strategic overhaul, not just a quick tweak. If you just change a few interests, you'll be back here in a month with the same problem. You need to build a proper foundation. I've detailed my main recomendations for you below in a more actionable format.

I hope this detailed breakdown gives you a much clearer path forward. It's about being deliberate and strategic, not just opening more advertisements and hoping for a different result. The reality is that getting this level of strategy, implementation, and ongoing optimisation right is a full-time job. It requires deep expertise not just in how the ad platforms work, but in marketin psychology, copywriting, and data analysis.

You can absolutely make progress on your own with the framework I've laid out here. But if you want to accelerate your results and be confident that your ad spend is working as hard as it possibly can, you might want to consider getting expert help.

We offer a completely free, no-obligation consultation where we can take a look at your ad account together. We can dive into your specific situation, review your current campaigns, and provide tailored advice on how to implement this kind of strategy effectively. It’s often incredibly helpful for business owners to get a second pair of expert eyes on their setup.

If that sounds useful, feel free to get in touch to schedule a time that works for you.

Regards,

Team @ Lukas Holschuh