Solved: Facebook Ads Budget Allocation Issue on Low Budget

Hi there,

Thanks for reaching out!

I had a look over the situation you described with your t-shirt store's Facebook ads. It's a really common frustration, especially when you're working with a tight budget, so I'm happy to give you some of my thoughts. It sounds like you're fighting the platform a bit, and honestly, the solution might be the opposite of what you think it is.

I'll walk you through my take on it. The short answer is you need to stop trying to force the budget to spread evenly and instead focus on why the algorithm is making that choice in the first place. It's giving you a massive clue about what's actually working.

We'll need to look at that budget... but it's not the real villain

Okay, let's get the big one out of the way first. That budget of about $8 a day. I've got to be honest with you, that's incredibly low. It's not impossible to work with, but it makes everything ten times harder and a hundred times slower. When you give Meta's algorithm a budget that small, it's like asking someone to learn to cook a gourmet meal with only a salt shaker and a microwave. It just doesn't have enough ingredients (data) to learn properly.

The "learning phase" you see in your ad manager isn't just some annoying notification; it's the algorithm actively spending your money to figure out who is most likely to buy your t-shirts. It needs about 50 conversions (purchases, in your case) per ad set per week to get a good idea. On $8 a day, if your t-shirts cost $25, you'd need a ROAS of over 4.4x just to get those 50 conversions in a week, and that's assuming every penny goes to a conversion which it never does. So, you're pretty much stuck in a permanent learning phase. This means your results will be unstable and your costs will be higher than they should be.

Your idea to split that tiny budget across multiple ad sets is, frankly, the worst thing you could do. You'd be taking an already starved algorithm and splitting its tiny food ration into even smaller crumbs. Each ad set would have maybe $2-$3 a day. They will never exit the learning phase, you'll get no meaningful data, and you'll just burn through cash with nothing to show for it. It's a guaranteed way to fail.

But here's the contrarian bit: the budget isn't your real problem. It's just a symptom that exposes the deeper issues much, much faster. If your offer, your creative, and your targeting were absolutely perfect, even $8 a day could start to show a tiny flicker of life. But because it's so small, there is zero room for error. So, let's stop worrying about the budget for a minute and focus on the things that will make that budget work harder.

I'd say you should stop fighting the algorithm... it's trying to help you

You mentioned that Meta is pushing most of the budget into the one ad that got the first conversion. You're right, that's exactly what happens. And you should be thanking the algorithm for it, not trying to fight it.

You're using an Advantage+ Shopping Campaign (A+SC), which is designed to do exactly this. You give it a budget, a country, and a bunch of creatives (ads), and its entire job is to find the cheapest conversions possible. When one ad gets a conversion, the algorithm thinks, "Aha! This one seems to be working. Let's show this ad to more people like the person who just bought something." It's taking your tiny budget and putting it on what it thinks is your best horse. This isn't a flaw; it's the entire point of automated campaigns.

Trying to force an equal spend across all your ads is like having a football team where one striker scores all the goals, and you tell the manager to give the ball to the defenders more often just to be 'fair'. It makes no sense. Your job isn't to ensure every ad gets a turn; your job is to make a profit. Meta is telling you, loud and clear, "This one ad is working better than the others." Your response should be to figure out why and make more ads like that one, not to strangle it and give its budget to the failing ads.

This is a major mindset shift. Stop seeing your ads as a creative contest where each one deserves a participation trophy. Start seeing them as a brutal competition where only the strongest survive. The algorithm is your ally in finding the winner. Let it do its job.

You probably should fix your offer before you fix your ads

So if the algorithm is favouring one ad, that means the other ads are failing. Why? The number one reason I see campaigns fail, especially for ecom stores, isn't the ad setup. It's the offer. People think an offer is just the product and the price. It's not. It's the entire package: the design of the t-shirt, who it's for, the story behind it, and the message you use to sell it.

T-shirts are one of the most saturated markets on the planet. You can't just sell "a t-shirt with a cool graphic." Nobody is looking for that. You have to sell a solution to a problem or an identity. Your ICP (Ideal Customer Profile) isn't "people who wear t-shirts." That's everyone. You need to get way, way more specific.

Your ICP isn't a demographic. It's a problem state. What nightmare are you solving? For a t-shirt brand, it's not a life-or-death nightmare, but it's an emotional one.

• Is it the nightmare of a boring wardrobe?
• Is it the frustration of a software developer who can't find clever, niche coding jokes on a shirt?
• Is it the desire of a new mum to wear something that's both comfortable and makes her feel like her old self?
• Is it the passion of a vintage car enthusiast who would love a shirt with a schematic of their favourite engine?

You have to pick one. You can't be for everyone. When you try to sell to everyone, you sell to no one. Once you know who you're for, and what their specific 'problem' or passion is, you can craft a message that they can't ignore.

Let's take an example. Say you decide to target people who love 80s sci-fi films.

A bad, generic ad message: "High-quality t-shirts. Unique designs. Shop now!"
A good, specific ad message: "Still quoting films no one else gets? Your people are here. We make the t-shirts with the deep-cut 80s sci-fi references you've been looking for. The kind that gets you a knowing nod from a fellow fan in the wild."

See the difference? The second one speaks directly to a person's identity. It makes them feel seen. That's what makes people click and buy. Before you spend another dollar, you need to be brutally honest with yourself: who are my t-shirts really for, and what am I really selling them? If you can't answer that in one sentence, your ads will continue to struggle.

We've run campaigns for a women's apparel brand and saw a 691% return on ad spend. That didn't happen because we were technical wizards with the ad settings; it happened because the brand knew exactly who their customer was and what she wanted to feel when she wore their clothes. The ads just delivered that message.

You'll need to know your numbers to scale

This might seem a bit advanced when you're on $8 a day, but understanding this now will change how you think about your business. You're worried about the cost of ads, but you should be focused on the value of a customer. The question isn't "how cheap can I get a sale?" but "how much can I afford to pay for a sale and still be profitable?" The answer is in your Customer Lifetime Value (LTV).

Let's do some rough, back-of-the-envelope maths for a hypothetical t-shirt store. This is just an example, you'll need to use your own numbers.

• Average Order Value (AOV): Someone buys one t-shirt for £30.
• Gross Margin: After the cost of the blank shirt, printing, etc., you make 60% profit. So, £30 * 0.60 = £18 gross margin per order.
• Repeat Purchase Rate: Let's say 1 in 4 customers comes back to buy another shirt within a year. So your average customer buys 1.25 times.

Simple LTV = (Gross Margin per Order) * (Average Number of Purchases)
LTV = £18 * 1.25 = £22.50

This means, on average, every new customer you acquire is worth £22.50 in gross profit to your business. A common rule of thumb is to have a 3:1 LTV to Customer Acquisition Cost (CAC) ratio. This means you can afford to spend up to £22.50 / 3 = £7.50 to acquire a new customer.

Suddenly, you have a target. Your target CPA (Cost Per Acquisition) is £7.50. Now when you look at your ad campaigns, you have a clear benchmark. If an ad is getting you sales for £5, it's a winner. If it's costing you £15 per sale, you're losing money on every order and you need to kill that ad immediatly. This maths is what separates amateur shop owners from professional ecom businesses. It frees you from just looking for cheap leads and allows you to make intelligent decisions about your ad spend.

With this knowledge, your whole perspective on that $8/day budget changes. The goal is now to get at least one sale for under £7.50 every day. It's a clear, simple target.

We'll need to build a campaign that actually works on a low budget

Alright, now that we've sorted out the strategy, let's talk tactics. How should you actually set up your campaign with all this in mind?

1. Simplify Everything:

Forget multiple campaigns and dozens of ad sets. You don't have the budget for it. You need one, maybe two campaigns at most.

2. The Prospecting Campaign:

This is for finding new customers.

• Use one single Advantage+ Shopping Campaign.
• Put your entire prospecting budget into it. Don't split it. If your total budget is $8, maybe put $6 into this.
• Inside this campaign, load it up with your best ads. I'm talking 5-10 different creatives. Use different images, different videos, and different copy based on the specific ICP you defined earlier. Let them all run inside the single A+SC ad set.
• Let Meta do its job. It will find the winning ad and put the budget behind it. Your job is to watch the results. When you see one ad pulling away and getting sales at or below your target CPA, pause the others. Then, create new ads that are variations of the winning one. This is how you iterate and improve.

3. The Retargeting Campaign:

This is for bringing back people who visited your site but didn't buy.

• Create one standard (manual) Conversions campaign with Campaign Budget Optimisation (CBO) turned on.
• Give it the rest of your budget, so maybe $2 a day.
• Inside, have one ad set. The audience for this ad set should be "Website Visitors in the last 30 days" EXCLUDING "Purchasers in the last 180 days." You can also target people who have "Added to Cart" or "Initiated Checkout." In the beginning, you might need to group them all together to have a big enough audience.
• The ads in here should be different. They should acknowledge that the person has already visited. Offer a small discount, show customer testimonials, or highlight your free shipping. Remind them what they were looking at.

I remember one of our clients, an outdoor equipment brand, wanted to test loads of different audiences. We convinced them to consolidate their structure into a similar simplified setup and it was what eventually allowed us to scale and drive over 18,000 website visitors. It works because it gives the algorithm clear instructions and enough data to work with. Your structure is much less important than the quality of your offer and your creative.

I've detailed my main recommendations for you below:

Look, this stuff can be a lot to take in, and it's difficult to get right. It's not just about pushing buttons in Ads Manager; it's about understanding business strategy, customer psychology, and financial modeling, and then translating all of that into a campaign that works.

This is why businesses hire experts. Not just for the technical setup, but for the strategic insight that stops them from burning money on things that were never going to work in the first place. We've helped numerous ecom businesses, from apparel to cleaning products, turn their ad spend into significant returns by applying these very principles.

If you'd like to go over your specific situation in more detail, we offer a free, no-obligation initial consultation where we can look at your store and your ads together and give you some more tailored advice. It might be helpful to have a second pair of expert eyes on it.

Hope this helps!

Regards,

Team @ Lukas Holschuh