Solved: Facebook Ads Slowdown with Same Audience

Hi there,

Thanks for reaching out! I had a look at your situation with the Meta ads, and it's a really common problem to run into, so don't worry. When results start to slow down like that, it's almost always a sign that something's off with the campaign structure or the way you're telling the algorithm who to go after. It's not about random 'tweaks'; it's about fixing the foundation.

Your instinct that the issue is with having multiple campaigns hitting the same audience is spot on. You're basically making your own ads fight each other for attention, and Facebook is more than happy to take your money while they do. We need to stop that and get your budget working smarter. I'll walk you through how I'd approach this.

The first thing we need to fix is your campaign structure...

Alright, let's get straight to the heart of the problem. When you run multiple campaigns or ad sets that are all aimed at the same, or a very similar, audience, you create something called 'audience overlap'. In simple terms, you are entering the same auction with different ads and forcing them to bid against each other. Meta's system sees your ads from Campaign A, Campaign B, and Campaign C all trying to reach 'Broad Audience X'. It doesn't see them as a team; it sees them as competitors. The result? Your auction costs (CPMs) go up, and your overall peformance goes down. It's one of the fastest ways to burn through a budget with diminishing returns, which sounds exactly like the slowdown you're experiencing.

A lot of people make this mistake. They think "new product, new campaign". It seems logical, but it's not how the algorithm works best. The algorithm needs a clear goal and enough data and budget to achieve it efficiently. By splitting everything up, you're starving it of the data it needs to properly optimise and forcing it to make inefficient decisions. You're paying a premium for the algorithm to get confused.

We need to move away from this fragmented approach and towards a consolidated, strategic one. Think of it less like running three seperate market stalls next to each other all shouting at the same crowd, and more like having one big, well-organised department store with different sections for people at different stages of their buying journey.

I'd say you need a funnel, not just more campaigns...

So, how do we build that well-organised department store? We use a marketing funnel. This just means we structure our campaigns based on the customer's awareness of our brand, not by the products we're selling. For Meta ads, I typically break this down into two, maybe three, core campaigns:

1. Prospecting (or Top of Funnel - ToFu): This is where you find new people who've never heard of you. Your broad targeting ad sets live here. The goal is to introduce your brand and products to a cold audience and drive initial interest.
2. Retargeting (or Middle/Bottom of Funnel - MoFu/BoFu): This is where you talk to people who have already shown some interest. They've visited your website, watched a video, or engaged with a post. The goal here is to nurture that interest and guide them towards a purchase.

By seperating them, you can tailor your message. You wouldn't speak to a total stranger the same way you'd speak to someone who's already put an item in their shopping cart, would you? Your ads shouldn't either. A ToFu ad might highlight a problem your product solves, while a BoFu ad for someone who abandoned their cart might offer a small discount to encourage them to complete the purchase.

Within your Prospecting campaign, you can still test your different products. You could set it up using Campaign Budget Optimisation (CBO) and have three different ad sets, one for each product, all targeting that same broad audience. CBO will then automatically shift your budget towards the product and ad set that's performing the best. The algorithm does the heavy lifting for you, finding the most efficient way to spend your money. This is a much better way to test than creating three totally seperate campaigns.

Here's a breakdown of how I'd prioritise the audiences within this new structure. You'll see that the "hottest" audiences—those closest to buying—are the ones you should focus on first in your retargeting efforts.

You probably should focus on audience quality, not just size...

When you start building this new structure, it’s tempting to just pour all the money into the big, broad 'ToFu' campaign because the audience size is massive. But often, the real money is made in the smaller, higher-quality retargeting audiences. A person who has already visited your site and added a product to their cart is infinitely more valuable than a random person in a broad audience who fits a vague interest profile. Your ad spend should reflect that.

This is why prioritisation is so important. We always build out the BoFu audiences first (Add to Cart, Initiate Checkout), then MoFu (Website Visitors), and only then do we focus heavily on scaling the ToFu prospecting. The performance difference is usually massive. Your cost per purchase from a 'cart abandoner' audience will almost always be lower than from a cold interest-based audience. For instance, we've run campaigns for eCommerce clients, from apparel to subscription boxes, that generated overall returns of over 600%, with some even reaching a 1000% return on ad spend. A huge driver of that profitability is always the efficiency of retargeting warm audiences who are already close to buying.

Even within prospecting, quality matters. When you get enough data (at least 100 purchases, ideally more), you can create Lookalike audiences. A Lookalike of your past customers is going to be far more effective than just targeting a broad interest like "shopping". Meta's system is incredibly good at finding patterns in your customer data and locating new people who share those same characteristics. This is how you scale intelligently, by feeding the algorithm high-quality data about who you want to find.

You'll need to consolidate your budget to escape the learning phase...

This is probably the most critical technical reason why your results have slowed down. Every time you launch a new ad set, Meta puts it into a 'learning phase'. During this time, the algorithm is actively exploring your audience to figure out who is most likely to convert. To get out of this phase and achieve stable, predictable performance, an ad set needs to get roughly 50 conversions (purchases, leads, whatever your objective is) within a 7-day window.

Now, look at your setup. You have a €2000 budget split across three campaigns. Let's assume you're running them for about four weeks. That's roughly €167 per campaign per week (€2000 / 3 campaigns / 4 weeks). If your cost per purchase is, say, €20, you're only getting about 8 purchases per week in each campaign. That's nowhere near the 50 needed to exit the learning phase. Your ad sets are perpetually 'stuck' in learning, meaning the delivery is unstable, costs fluctuate wildly, and performance will definitly suffer. This is almost certainly what's causing your slowdown.

By consolidating your budget into one prospecting campaign, you'd have €500 per week to work with. At a €20 cost per purchase, that's 25 conversions. Still not 50, but much closer and more likely to give the algorithm enough data to start optimising properly. If you can get your cost per purchase down to €10, you hit the magic number. Consolidation gives you a fighting chance to achieve the data volume needed for stable performance.

Use the calculator below to see this in action. Play with the sliders to see how splitting your budget across too many campaigns prevents any of them from getting the conversions they need to perform well.

This is the main advice I have for you:

So, to bring it all together, you need to pause your current campaigns and rebuild with a focus on consolidation and the user journey. It's a bit of work up front, but it'll save you a lot of money and headache in the long run and should fix the performance issues you're seeing.

Here’s a table outlining the exact structure I'd recommend you implement with your €2000 budget. This is a solid foundation that will stop audience overlap, give the algorithm the data it needs, and set you up for stable, scalable results.

I know this can seem like a lot to take in, especially when you're just trying to get your ads to work. Moving from a simple setup to a more strategic one involves a learning curve. It's not just about setting it up correctly, but also about knowing how to read the data, when to turn off losing ads, and how to scale the winners without breaking the system.

Getting it right can be the difference between a campaign that struggles to break even and one that becomes a reliable engine for growth. If you feel like you could use an expert eye to help implement this, or just want to talk through your specific situation in more detail, we offer a completely free, no-obligation initial consultation. We can have a look at your account together and make sure you're set up for success.

Regards,

Team @ Lukas Holschuh