Solved: Ad Set Taking 90% of Daily Budget in One Hour

Hi there,

Thanks for reaching out. I saw your post and thought I'd give you some of my thoughts on the situation. It's a really common problem, especially when you're just starting out with Meta ads, so don't feel like you've done something massively wrong. The platform can be a bit of a beast to get your head around.

What you're describing with the CBO (Campaign Budget Optimisation) is something we see quite a bit. Your instinct to question it is spot on. The short answer is that CBO isn't really designed to split your budget evenly. It's designed to spend it where it thinks it will get the best results, and it makes those decisions incredibly quickly. But often, its initial guess is wrong.

I'm happy to give you some initial thoughts and guidance based on what you've shared. The goal here is to give you a more robust framework for thinking about your campaigns, so you can avoid this kind of thing in the future and start building something that's actually scalable and profitable. We'll go through the 'why' of what happened, and then dive into a much more effective way to structure things moving forward.

We'll need to look at why CBO is behaving this way...

Okay, so first things first, let's break down the CBO behaviour. When you turn on CBO, you're essentially handing the keys to Meta's algorythm and saying, "Here's €30, go find me customers." The algorithm’s one and only job is to get you the most conversions (or whatever your objective is) for that budget. It doesn't care about fairness between your ad sets.

What likely happened in your case is that in the first hour, one of your interest-based audiences showed a few early, promising signals. This could be anything:

• -> A Larger Audience Size: If one interest audience was significantly bigger than the others, the algorithm sees more room to 'play' and might start there by default.
• -> Lower Initial CPMs (Cost Per 1,000 Impressions): Sometimes, one audience is just cheaper to reach. The algorithm sees this low cost and thinks, "Great! I can get loads of eyeballs here for cheap," and it pours money in before it even knows if those eyeballs will convert.
• -> A Lucky Early Click: It's possible that someone in that ad set clicked your ad very early on. The algorithm sees this as a sign of huge potental and goes all-in, hoping to find more people just like that one person.

The problem is that these are very early, often misleading signals. An hour is nowhere near enough time for the campaign to get out of the 'learning phase' and make smart decisions. So it makes a quick, dumb decision and blows 90% of your money. It's a classic case of the algorithm being a bit too eager.

A short-term fix is to do what you've probably considered: switch back to ABO (Ad Set Budget Optimisation) or set manual spend limits on each ad set within the CBO. This gives you back control and forces Meta to give each of your audiences a fair shot. However, this is just a plaster on a bigger wound. The real issue, and the real opportunity for you, lies in completely rethinking your campaign structure from the ground up. This is how you go from being a "rookie" to running campaigns that actually deliver consistent results. I recall one instance where we restructured a campaign for a client in the outdoor equipment niche. They were facing a similar challenge with unbalanced CBO spending. By implementing a proper funnel structure, we managed to drive over 18,000 qualified website visitors to their site.

The core problem is that you have broad and interest-based audiences competing in the same campaign. This is a mix of different user temperatures, and it confuses the algorithm. A better approach is to seperate them out based on where the user is in their buying journey.

I'd say you need a proper funnel structure...

This might sound a bit like marketing jargon, but it's the single most important concept in paid advertising. You need to think in terms of a funnel: Top of Funnel (ToFu), Middle of Funnel (MoFu), and Bottom of Funnel (BoFu).

• -> ToFu (Top of Funnel): These are your cold audiences. People who have never heard of 'MyGamingSet' before. This is where your interest-based and broad audiences live. The goal here is prospecting – finding new potential customers.
• -> MoFu (Middle of Funnel): These are warm audiences. People who have shown some interest but haven't taken a key action yet. They might have watched one of your videos, visited your website, or engaged with your Facebook page. They know who you are.
• -> BoFu (Bottom of Funnel): These are your hot audiences. People who are on the verge of buying. They've added a product to their cart, initiated checkout, but for some reason, they didn't complete the purchase. These are the people you need to give a final nudge to.

Your current campaign is mixing ToFu audiences (broad and interests) all together. It's like trying to have a first date and a wedding proposal in the same conversation. It's awkward and inefficient. The algorithm doesn't know whether to prioritise cheap reach (for prospecting) or aggressive conversion tactics (for closing sales).

A propper structure would involve creating seperate campaigns for each stage of the funnel. For example:

Campaign 1: ToFu - Prospecting

• Objective: Conversions (e.g., Purchases)
• Budgeting: CBO (but only with ToFu audiences inside)
• Ad Sets: Each ad set would contain one specific interest group or a lookalike audience. E.g., Ad Set 1 targets interest 'Logitech G', Ad Set 2 targets interest 'Razer', Ad Set 3 targets a Lookalike of your past customers.

Campaign 2: MoFu/BoFu - Retargeting

• Objective: Conversions (e.g., Purchases)
• Budgeting: CBO or ABO
• Ad Sets: Ad Set 1 targets all website visitors from the last 30 days (excluding purchasers). Ad Set 2 targets people who Added to Cart in the last 14 days (excluding purchasers).

This seperation is vital. It allows you to tailor your messaging and your budget allocation logically. You speak to cold audiences differently than you speak to people who have already put your gear in their shopping cart. This structure brings clarity to your advertising and allows Meta's algorithm to do its job much more effectively within each campaign.

Here’s a simplified look at how you could structure your account to begin with, assuming you have a small budget. You can combine MoFu and BoFu at the start.

By splitting things up like this, your prospecting campaign's CBO can focus on finding the cheapest new customers from the cold audiences you give it. Your retargeting CBO can then focus on efficiently converting the warm traffic you've already generated. It's a much cleaner, more logical system.

You probably should rethink your audience targetting...

Now that we've covered structure, let's talk about the actual audiences you're putting inside those ad sets. This is where most people go wrong. With a name like "MyGamingSet," you're in the eCommerce space, which is great, but also very competitive. Your targetting needs to be sharp.

Your current approach of '1 broad' and '2 interests' is a start, but it's not specific enough.

On 'Broad' Targeting: Going 'broad' (targeting no interests at all) can work brilliantly, but only when your Meta Pixel has thousands of conversion events (e.g., purchases) under its belt. It needs a huge amount of data to understand who your ideal customer is. As a "rookie" account, your Pixel is new and doesn't have this data. Going broad right now is like telling a new taxi driver to "just drive" without giving them a destination. You'll just burn fuel (and your budget). Park the broad audience for now and come back to it in 6-12 months when you have a lot more data.

On 'Interest' Targeting: This is where you should be focusing your ToFu budget. But you need to be smart about it. The key is to find interests that your target audience is much more likely to have than the general population. For a gaming setup store, this is crucial.

Let's say you sell high-end mechanical keyboards. A bad interest to target would be "Gaming". Why? Because millions of people, from kids playing on a console to mobile gamers, will fall into this bucket. Most of them will never buy a premium keyboard. It's far too general.

A better approach is to get specifc and layer your thinking. What are the niche interests that a PC gaming enthusiast would have?

• -> Brands: Target competing or complementary brands. Not huge ones like 'PlayStation', but more niche ones like 'SteelSeries', 'Razer', 'Corsair', 'Ducky' (for keyboards), 'Glorious PC Gaming Race'.
• -> Media & Influencers: Who do they watch? Target followers of specific tech review YouTube channels like 'Linus Tech Tips', 'Gamers Nexus', or specific Twitch streamers known for their pro setups.
• -> Software & Communities: Interests like 'Discord', 'PC Building Simulator', or specific subreddits (though Reddit targeting is done on Reddit itself, the mindset is what matters).

Here’s a demonstration of how to think about this:

You need to create multiple ad sets, each testing a different one of these 'Excellent' quality audience ideas. Once you start getting data, you can then move on to building Lookalike audiences (LLAs). These are audiences Meta builds for you based on a source. You could create an LLA of your past purchasers, or people who've added to cart. These are often the best-performing cold audiences, but you need at least 100 people in your source audience before you can even think about creating them.

You'll need to watch your metrics closely...

Once you have the right structure and the right audiences, the job becomes about optimisation. You need to become a detective and use Meta's data to figure out what's working and what's not. Don't just look at sales. Look at the whole journey.

• -> Is your Click-Through Rate (CTR) low (e.g., below 1%)? This means your ads aren't grabbing attention. The problem is your creative (the image/video) or your ad copy. People are seeing it, but they're not interested enough to click. Test new images, new headlines.
• -> Is your CTR high, but you're getting very few Add to Carts? People are clicking, so the ad is working. But they're dropping off on your product page. The problem is likely your product photos, your product descripion, or your pricing. Does your landing page deliver on the promise of the ad? Is it trustworthy?
• -> Are you getting lots of Adds to Cart, but few Purchases? This is a classic. People want the product, but something in your checkout proccess is stopping them. Is it unexpected shipping costs? Do you require them to create an account? Is the checkout page slow or confusing? This is 'money left on the table' and your BoFu retargeting campaign is designed to fix this by reminding them to complete their order.

Understanding this lets you diagnose problems accurately instead of just guessing. Now, you’re probably wondering what kind of costs to expect. This is a question we get all the time, and the honest answer is "it depends". But based on our experience, we can give you some realistic ballpark figures.

For an eCommerce store selling in developed countries (like most of Europe), here's what the maths typically looks like for driving sales:

As you can see, your Cost Per Purchase can vary wildly. Your job is to push your CPC down (with better ads and targeting) and your CVR up (with a better website and offer). This is the game. I remember we worked with a women's apparel brand where we focused relentlessly on creative testing and audience refinement. This disciplined approach led to a 691% Return On Ad Spend. It's not about magic; it's about a methodical process of testing and optimisation based on what the data tells you.

This is the main advice I have for you:

I know this is a lot to take in, so I've put together a table that summarises my main recommendations. This is your actionable plan to move forward and take control of your ad account.

This framework is your starting point. It moves you from reacting to problems (like your CBO issue) to proactively building a system designed for success. It takes the guesswork out of it and replaces it with a logical, testable structure.

Executing all of this correctly, creating compelling ads, writing persuasive copy, and constantly analysing the data to make the right optimisations takes a huge amount of time, effort, and experience. That's where getting some professional advice can make a huge differance. Having a team that has navigated these challenges for hundreds of clients, from small eCommerce stores to major SaaS companies, can be the difference between a campaign that breaks even and one that transforms your business.

We have seen clients reduce their cost per lead by 84% using similar principles, as well as clients in the eCommerce space achieve returns of over 600% on their ad spend. If you'd like to have a more in-depth chat about your specific situation, we offer a free, no-obligation initial consultation where we can review your account and strategy together.

Hope this helps!

Regards,

Team @ Lukas Holschuh