Solved: Stalled Meta Ads 'Purchase' Campaign for New Store

Hi there,

Thanks for reaching out!

Happy to give you some of my initial thoughts on your situation. Honestly, what you're seeing with your Meta ads is super common for new stores, so don't feel like you've done something massively wrong. It's a classic case of following what seems like good advice ('always optimise for purchase') without understanding the context of when that advice actually applies. The algorithm is a powerful tool, but you've basically sent it on a mission impossible with no map and no fuel.

The solution isn't just flicking a switch on your conversion event, though that's part of it. It's about thinking more strategically about how you feed the machine the data it needs to actually find you customers, especially when you're starting from absolute zero. Let's get into it.

We'll need to look at the 'always optimise for purchase' myth...

Right, let's tackle the biggest issue head-on. This idea that you should *always* set 'Purchase' as your conversion event is probably the most costly piece of well-intentioned but misguided advice in the paid ads world. It's repeated everywhere, but it completely misses the nuance of how the machine learning actually works.

Think of it like this: you've hired a new employee, the Meta algorithm. You tell them, "Your only job is to find me people who will buy this exact product." But you haven't given them a list of past customers, you haven't told them who your target market is, and you haven't even had a single sale yet. So the employee just sits there, confused. They have no idea what a "buyer" looks like. They don't know if your buyers are 18-year-old students or 65-year-old retirees. They have zero starting information. So, they show your ad to a few random people, get no response, and then basically give up to avoid wasting your money. That's what's happening to your campaign. It's getting "basically next to 0 reach" because the algorithm has concluded it has no chance of succeeding at its impossible task, so it stops spending your budget.

Meta's system needs data to function. Specifically, to get out of the dreaded "Learning Phase," a campaign ideally needs about 50 conversions per ad set, per week. Let's do some quick maths. Your budget is $20 a day, which is about £16. For a new eCommerce store, a good Cost Per Purchase (CPP) could be anywhere from £20 to £70, or even higher. With a £16 daily budget, you're not even funded to get *one* purchase a day, let alone 50 a week. The campaign is starved of both data and budget. It was doomed from the start, tbh.

This isn't your fault; it's the fault of guru advice that lacks context. Optimising for purchases is the end goal, the final destination. But when you're at the very beginning of the journey, you have to aim for the first milestone, not the finish line.

I'd say you need a 'data ladder' approach...

So, if not purchases, what should you be aiming for? You need to give the algorithm a simpler, more achievable task. You need to walk it up what I call the 'data ladder'. Instead of asking for the most difficult and infrequent action (a sale), you ask it to find people who take the next best step. For a new store, that's almost always 'Add to Cart'.

Why? Because you'll get far more 'Add to Cart' events than you will 'Purchase' events. Maybe for every 10 people who add to cart, only one will buy. By optimising for 'Add to Cart', you're giving the algorithm 10x more data points to learn from. It can start to build a picture of the kind of person who shows a high level of interest in your products. This gets the ball rolling. The ad starts getting reach, you get traffic, and the pixel on your website starts gathering valuable intel.

Once you're consistently getting a good number of Add to Carts (let's say 25-50 a week), your pixel is now a bit smarter. You can then think about the next rung on the ladder. You could create a new campaign that optimises for 'Initiate Checkout'. This is a higher-intent action than adding to cart, so the leads will be better, and because you've already 'warmed up' the pixel, the algorithm has a better starting point for finding these people.

Only after you've got a decent volume of purchases coming through—maybe 50 sales in total across your whole account—should you even consider testing a campaign that optimises directly for 'Purchase'. By then, your pixel will have a rich profile of what your actual buyers look like, and the algorithm will have a real chance of success.

Here's a simple visualisation of that progression. You have to earn the right to optimise for purchases.

You probably should fix the foundations first...

Now for some brutal honesty. Changing your campaign objective from 'Purchase' to 'Add to Cart' might get your ads running, but it won't magically make your store successful. If the core foundations are weak, you'll just be paying for more traffic that doesn't convert into sales. The number one reason paid ads fail isn't the targeting or the creative; it's the offer and the landing page (your website).

I haven't seen your website, but I've seen hundreds of new eCommerce stores, and they almost all make the same mistakes. I remember one client selling handcrafted products whose ads were getting clicks, but no one was buying. When we looked at the store, we saw why instantly.

Here's a checklist of things that kill conversions, based on our experience with that client and many others:

• Trust is Everything: A new store has zero reputation. Why should anyone give you their credit card details? Your website needs to scream "trustworthy". This means having a professional design, clear contact information (address, phone number), an 'About Us' page that tells your story, clear shipping and returns policies, and customer reviews. Even if you have no sales yet, you can get testimonials from friends or family you've given products to. No reviews is a massive red flag for a potential customer.
• Product Presentation: Are your product photos top-notch? For the client I mentioned, the photos were dark and didn't show the products on a model. We told them to get proper photography done, even just using a friend as a model in good natural light. It makes a world of difference. People can't touch or feel the product online, so your photos and videos have to do all the work.
• Compelling Product Descriptions: "Red T-shirt, 100% cotton" isn't a description; it's a label. You need copy that sells. What's the benefit of the product? How does it make the customer feel? Who is it for? You need to answer the question "Why should I buy this from *you*?"
• A Clear Offer: What's the deal? Is it free shipping? A first-time buyer discount? A bundle offer? You need a clear, compelling Call to Action. For a new store, an introductory offer like "15% off your first order" can be the little nudge people need to take a risk on a new brand.

Before you spend another pound on ads, you need to look at your website with a brutally honest eye and ask, "If I'd never heard of this brand before, would I feel comfortable buying from here?" If the answer is anything less than a resounding "yes," that's where your real work lies.

You'll need to get your targeting right from the start...

When you have no sales data, your targeting is everything. You can't rely on powerful tools like Lookalike Audiences (which are built from your existing customer data) or advanced retargeting. You're starting with cold audiences, which means you're relying entirely on Meta's 'Detailed Targeting' (interests, behaviours, and demographics).

This is another area where new advertisers go wrong. They choose interests that are far too broad. Let's say you sell high-quality leather dog collars. A novice advertiser might target interests like "Dogs," "Pets," or "Dog Lovers." The problem? That's a massive audience of millions of people. It includes people with rescue mutts who buy cheap collars from the supermarket, people who just like watching dog videos on Instagram but don't own one, and everyone in between. Your ad spend gets diluted across a huge, mostly irrelevant audience.

You need to think like an expert. Who is your *ideal* customer? They probably own a specific breed of dog, they probably shop at high-end pet boutiques, they might follow specific luxury brands (for humans and pets), and they probably read certain magazines or follow specific influencers in the 'dapper dog' space. Your job is to find interests that act as a proxy for this ideal customer.

Here's how that thinking translates into a targeting strategy:

Your first few hundred pounds in ad spend shouldn't be thought of as a quest for profit. It's an investment in data. You're testing these different, highly specific audience hypotheses to see which one resonates. When you see an ad set with a high click-through rate and a low cost per 'Add to Cart', you've found a pocket of your ideal customers. That's when you can start to put more budget behind it. But if you start too broad, you'll never find those pockets; your budget will just evaporate.

You'll need to know your numbers, or you're just gambling...

This might be the most important part of this whole letter. Most business owners think about advertising cost. Experts think about advertising investment. The difference? Knowing how much a customer is truly worth to your business over their lifetime.

This is called Customer Lifetime Value (LTV). Once you know this number, it changes everything. A £50 cost to acquire a new customer might seem terrifyingly high. But what if you knew that, on average, each customer you acquire will spend £500 with you over the next two years? Suddenly, paying £50 to get them in the door looks like an incredible bargain. Without knowing your LTV, you're flying blind, making decisions based on fear rather than data.

Calculating a precise LTV can be complex, but we can use a simple, powerful formula to get a very good estimate. You need three pieces of information:

1. Average Revenue Per Account (ARPA): How much does a typical customer spend with you per month? For an eCommerce store, you can estimate this based on your average order value and how often you expect people to re-purchase.
2. Gross Margin %: What's your profit margin on each sale after accounting for the cost of the goods?
3. Monthly Churn Rate %: What percentage of your customers do you lose each month? For an eCommerce store that doesn't have a subscription, you can estimate this as the percentage of customers who don't make a repeat purchase within a certain timeframe (e.g., 90 days).

The formula is: LTV = (ARPA * Gross Margin %) / Monthly Churn Rate

I've built a simple calculator for you below. Play around with the sliders to see how small changes in your business metrics can drastically affect how much you can afford to spend on ads. A common rule of thumb is to aim for a 3:1 LTV to Customer Acquisition Cost (CAC) ratio. The calculator shows you what your target CAC should be based on this ratio.

Once you understand this math, it liberates your advertising strategy. You stop panicking about daily results and start focusing on the only metric that matters: are you acquiring profitable customers?

I've detailed my main recommendations for you below:

Alright, that was a lot of information. Let's boil it all down into a clear, actionable plan. This is what I would do if I were in your shoes, starting today. This isn't a list of vague suggestions; it's a step-by-step process to get your ads working and your business off the ground.

Navigating these early stages is, without a doubt, the hardest part. You're trying to get a flywheel spinning from a complete standstill, and it requires a very different approach than optimising a mature, successful ad account. It involves a lot of careful testing, data analysis, and an understanding of both the technical side of the ad platforms and the psychological side of what makes people buy.

This is where professional help can make a huge difference, not just in getting better results, but in avoiding the costly mistakes that cause so many new businesses to give up on paid advertising altogether. We spend all day, every day, inside ad accounts, building campaigns for businesses from the ground up and scaling them profitably.

If you'd like to have a more detailed chat where we could look at your actual website and ad account together, we offer a completely free, no-obligation initial consultation. It's a chance for you to get some expert eyes on your specific situation and for us to give you a more tailored plan of action.

Regards,

Team @ Lukas Holschuh