Solved: Best Ad Attack Plan for Print on Demand Clothing

Hi there,

Thanks for reaching out!

That's a classic problem for anyone starting with print-on-demand or any clothing brand with a decent-sized catalogue. It feels like you're standing in front of a massive wall of options with a limited budget, and you're being asked to pick the one magic brick that holds the whole thing up. The temptation to just throw the whole catalogue at an algorithm and hope for the best is huge, I get it.

But tbh, letting a "full catalog campaign" run wild on a new store is one of the fastest ways to burn through your cash with very little to show for it. The algorithm needs data, and when it has none, it just finds the cheapest people to show your ads to, not the people most likely to buy. You have to feed the machine winners first. I'm happy to give you some initial thoughts on a much better way to approach this, a more deliberate 'attack plan' that will save you money and actually tell you what works.

Your Customer's Nightmare is Your Targeting Goldmine

Right, let's get this out of the way first because it's the bit everyone skips. You asked which products to build creatives for. The real question is, for *who*? You're not selling clothing. You're selling identity. You're selling a badge that says "I'm part of this tribe," or "I get this joke," or "I believe in this thing."

Forget demographics. "Males aged 25-34 who like streetwear" is useless. It tells you nothing. You need to get uncomfortably specific about their internal world. What is the 'nightmare' your brand solves? And I don't mean a life-or-death problem. I mean a nagging, persistent frustration or desire.

Let's imagine you sell t-shirts with sarcastic, witty designs about corporate office life.
-> The Demographic Profile (Useless): "Office workers, 30-45, living in major cities."
-> The Nightmare Profile (Gold): "A Senior Project Manager, let's call her Sarah. She's 38. She spends 6 hours a day in pointless meetings listening to buzzwords. Her secret nightmare is that her creativity is dying a slow death by PowerPoint. She feels like a cog in a machine. She desperately wants a way to subtly rebel, to connect with other people in her office who feel the same way without getting fired. Your t-shirt isn't a piece of clothing; it's her silent protest. It's the knowing glance she can share with a colleague over the coffee machine."

See the difference? Now you know exactly what your ads need to say. You know what kind of humour will land. You know what Facebook pages she follows (probably 'The Office' fan pages, satirical cartoonists who mock corporate life). You know what podcasts she might listen to on her commute. Your ICP isn't a person; it's a specific, emotionally-charged problem state. Until you've defined this for your brand, you have no business spending a single pound on ads, because you'll just be shouting into the void.

This work is not optional. It dictates every single decision you make from here on out. Your best-selling designs won't be the ones you think are coolest; they'll be the ones that connect most deeply with a specific person's 'nightmare'.

The Myth of the Magic Algorithm: Why Starting Broad is a Terrible Idea

Okay, let's tackle your main question directly. Is a full catalog campaign (what Meta calls an Advantage+ Shopping Campaign or what Google calls Performance Max) the best option? For a new store, absolutely not. It's probably the worst thing you could do.

Here's the uncomfortable truth about these campaigns: they are powerful, but they are not magic. They are scaling tools, not discovery tools. They work by taking existing conversion data – what products are selling, who is buying them, what ads they responded to – and then finding more people just like that, at scale.

When you start a new store, you have zero conversion data. You are giving the algorithm an empty map and telling it to find treasure. So what does it do? It does what you told it to do in the campaign settings: "find me purchases". But because it has no idea what a buyer looks like, it defaults to its secondary objective: "get the most clicks/impressions for the lowest possible cost within the budget".

This means the algorithm actively seeks out the people inside your audience who are cheapest to reach. These are often people who are chronically online, click on lots of things, but rarely ever buy anything. They are not in demand by other advertisers, so their attention is cheap. You are literally paying Facebook or Google to find you an audience of non-customers. I've seen so many accounts that have spent hundreds or thousands on an ASC campaign right out of the gate, got loads of clicks, maybe a few adds to cart, but almost no sales. This is why. You have to do the initial work yourself.

I'd say you need to build a Creative Testing Engine

So if a catalogue campaign is out, what's the alternative? You need to build a simple, repeatable system for testing. A 'Creative Testing Engine'. Your goal is not to get sales immediately (though that's a bonus). Your primary goal is to get *data*. You want to find out which of your 60+ designs actually resonates with real people enough for them to click and consider buying.

Here’s how I'd structure it:

Step 1: Pick Your Contenders

Don't test all 60 designs. That's madness. Based on your ICP 'Nightmare' work, make an educated guess. Pick the 3-5 designs you believe speak most directly to that core customer pain point. These are your 'hero' product contenders. Forget the rest for now. Let's say you pick 1 shirt, 2 sweatshirts, and 1 hat.

Step 2: Create Varied Creatives

For each of those 3-5 products, you need to create a few different ad creatives. Don't just use the standard POD mockup on a white background. That's what every other beginner does. You need to stand out.

• -> The Clean Mockup: Yes, you need one of these. It's your baseline. Simple, clear, shows the product.
• -> The Lifestyle Shot: This is huge. Get samples. Give them to friends who fit your ICP and take photos of them wearing the clothes in a relevant enviroment. If it's a shirt for hikers, get a picture of someone on a trail. If it's for coders, get a picture of someone at a cluttered desk with multiple monitors. People need to see themselves in the product. It feels much more real.
• -> The Simple Video: A 10-15 second video can outperform images by a mile. It doesn't need to be a Hollywood production. It could be a simple panning shot of the product, or a screen recording of you showing the design details on your store. Or even better, a friend wearing the shirt and turning around. It just needs to grab attention in the feed.

Now you have, say, 4 products x 3 creative types = 12 different ads to test.

Step 3: Structure Your Testing Campaign (on Meta)

This is where the structure is vital. I'd set it up like this on Facebook/Instagram, as they are usually best for clothing.

• -> Create one new Campaign. Set the objective to 'Sales'. Turn on Campaign Budget Optimisation (CBO). Start with a small daily budget you're comfortable losing, maybe £20-£50 per day. The budget is for learning, not for profit at this stage.
• -> Create 3-4 Ad Sets inside this campaign. Each ad set will target a *different* audience based on your ICP research.
  • Ad Set 1: Interest targeting around the *niche*. E.g., for our 'corporate rebel' Sarah, this would be interests like "The Office (US TV series)", "Dilbert", pages of satirical business writers.
  • Ad Set 2: Interest targeting around *competitors or similar brands*. What other clothing brands does your ICP buy from? Target people who like their pages.
  • Ad Set 3: A broader interest. E.g., "Project Management" as an interest, layered with an age and location filter. This is a bit of a wider test.
• -> Load ALL 12 ads into EACH ad set. This is important. You want to give every creative a chance to be shown to every audience. CBO will automatically start spending more on the ad sets that are getting better results, and within each ad set, the algorithm will favour the ads that are performing best.

Step 4: Read the Data, Not Your Gut

Let this campaign run for 3-5 days. Don't touch it. Your job is to watch the numbers. You are looking for a few specific things:

• -> Outbound Click-Through Rate (CTR): What percentage of people are actually clicking the ad to go to your site? Anything over 1% is okay to start. Anything over 2% is good. This tells you if your creative is grabbing attention.
• -> Cost Per Add to Cart: This is a much better early indicator than purchases. Are people interested enough to actually add the product to their basket? You're looking for the ads that get the lowest Cost Per ATC.
• -> Purchases / ROAS (Return on Ad Spend): Of course, if you get sales, that's the ultimate signal. An ad with a 2x ROAS (you make £2 for every £1 spent) is a clear winner.

After a few days, you will start to see clear patterns. One of your sweatshirt designs might be getting all the clicks. The lifestyle photos might be completely outperforming the mockups. The 'niche interest' audience might be where all your adds to cart are coming from. This is the data you were looking for. You've now identified your first 'hero' product, your winning creative style, and a promising audience. You kill all the losing ads and ad sets, and you move the budget to the winners. THAT is your foundation for scaling.

You'll need to understand your numbers or you'll go broke

Before you even think about scaling up the winners, you need to answer a brutally honest question: how much can you actually afford to pay to get a customer? So many store owners have no idea. They see a £20 Cost Per Purchase and panic, without realising that their average customer is actually worth £80 to them over time. This is where calculating your Customer Lifetime Value (LTV) becomes non-negotiable.

For a POD or clothing business, a simple LTV calculation looks like this:

LTV = (Average Order Value x Gross Margin %) x Average Number of Purchases Per Year

Let's break it down:
-> Average Order Value (AOV): Simple. Total revenue / number of orders.
-> Gross Margin %: Crucial for POD. If a shirt sells for £25 and the POD base cost + shipping is £15, your gross profit is £10. Your margin is (£10 / £25) = 40%.
-> Average Purchases Per Year: How many times does a typical customer come back to buy from you in a 12-month period? For a new store, you might have to estimate this as 1.2 or 1.5 to start with.

Let's say your AOV is £40, your margin is 40%, and you hope customers buy 1.5 times a year on average.
LTV = (£40 * 0.40) * 1.5 = £16 * 1.5 = £24.

This £24 is your gross profit per customer. A healthy business model aims for a 3:1 LTV to Customer Acquisition Cost (CAC) ratio. This means you can afford to spend up to £8 (£24 / 3) to acquire a new customer and still have a sustainable business. Suddenly, that £8 CPA doesn't seem so impossible, does it? And if you can increase your AOV by encouraging bundles, or get people to buy more often, your affordable CAC goes up, allowing you to spend more on ads and grow faster.

I've detailed my main recommendations for you below:

This might seem like a lot, but it's a logical progression. You start hyper-focused and only broaden out once you have concrete data telling you where to go next. This approach prevents you from just throwing money at the wall and hoping something sticks. I've worked with numerous eCommerce clients, from apparel to subscription boxes, and the ones who succeed are always the most disciplined testers. I remember one campaign for a women's apparel brand, for instance, that achieved a 691% return on ad spend, but that success only came after rigorously testing to find the exact combination of product, creative, and audience that clicked.

This is a marathon, not a sprint. The process I've outlined above isn't a quick fix, it's a system for building a sustainable advertising model for your brand. It takes patience and a willingness to be led by data rather than your own assumptions about which designs are best.

Trying to manage this yourself can be incredibly time-consuming and it's easy to make costly mistakes, like turning off an ad too early or misinterpreting the data. This is often where getting some expert help can make a massive difference. An experienced eye can spot patterns faster, structure tests more efficiently, and knows the benchmarks for what 'good' actually looks like, which can save you thousands in wasted ad spend and months of frustration.

If you'd like to go through your specific products and brand in more detail, we offer a free, no-obligation initial consultation where we can take a look at your store and give you some more tailored advice. It's often the quickest way to get some clarity on the right path forward.

Regards,

Team @ Lukas Holschuh