Solved: Too Narrow Audience on New Meta Campaign?

Hi there,

Thanks for reaching out!

I'm happy to give you some initial thoughts on your Meta campaign setup. Your question about audience layering is a really common one, but I think the way most people approach it is actually the biggest reason their campaigns fail to deliver. You're right to be cautious, because stacking audiences like that can seriously hamstring the algorithm.

My short answer is you're thinking about targeting backwards. Instead of trying to manually build the "perfect" person with demographics, you should be focused on finding the perfect *problem* and letting Meta's algorithm find the people who have it. I'll walk you through what I mean.

We'll need to look at... why your current targeting is a trap

Alright, let's get straight into it. Your approach of layering 'Engaged Shoppers' + 'In a relationship' + 'Anniversary within 60 days' feels logical, I get it. You're trying to build a profile of someone who is not just likely to buy, but likely to buy *now* for a specific reason. Ten years ago, this was considered smart targeting. Today, it's like tying one of the algorithm's hands behind its back.

Here's the uncomfortable truth: when you constrain the ad platform with too many specific, layered rules, you're making a huge assumption. You're assuming you know better than a multi-billion dollar machine that processes trillions of data points every single day. The problem is, you don't. None of us do.

Think about it. What does 'In a relationship' even mean on Facebook? It's self-reported. Many people don't update it. Many people in long-term partnerships are listed as 'single'. The 'Anniversary' life event is notoriously unreliable. You're building your entire strategy on flimsy, often outdated data points. You might be excluding thousands of potential buyers who just haven't ticked the right boxes on their profile, while including people who ticked them years ago and forgot.

More importantly, you're preventing the system from doing what it does best: finding patterns. When you set your campaign objective to 'Conversions' (and you absolutely should, I'll get to that later), you're giving the algorithm one simple command: "Go find me more people who look and act like the people who are already buying from me". It then analyses thousands of signals – not just demographics, but what pages they've liked, what ads they've clicked, what articles they read, their purchasing behaviour across the web, and a hundred other things we can't even see. It finds the *real* patterns that lead to a purchase.

By pre-defining such a narrow box, you're telling it to ignore all those powerful signals and only look for people who fit your flawed, human-made stereotype. This leads to a few bad outcomes:

• Sky-High CPMs: You've created a tiny, hyper-specific audience that every other gift company is also targeting. You're now in a bidding war for a very small pool of people, which drives your cost to even show them an ad through the roof.
• Limited Delivery: The audience might be so small that Meta struggles to spend your budget, especially after the initial few days. It can't find enough people who meet all your criteria to serve the ad to.
• Failed Learning Phase: The algorithm needs a certain volume of conversions (typically ~50 per week) to exit the 'learning phase' and properly optimise. If your audience is too small and your costs are too high, you'll never get enough sales to feed it the data it needs. The campaign gets stuck in "Learning Limited" and never performs well.

This is related to a mistake I see all the time, which is choosing the wrong campaign objective. If you run a 'Brand Awareness' or 'Reach' campaign, you are literally paying Facebook to find you non-customers. You're telling it "Find me the cheapest eyeballs possible", and it does. It finds people who scroll endlessly but never click, and certainly never buy. Their attention is cheap for a reason. You must align your objective with your business goal. If you want sales, you have to choose 'Sales' as your objective and optimise for 'Purchase' events. This is non-negotiable.

I'd say you... need to define your customer by their nightmare

So if layering demographics is the wrong way, what's the right way? You need a fundamental shift in your thinking. Forget demographics. You must define your Ideal Customer Profile (ICP) by their pain. By their specific, urgent, emotionally-charged nightmare.

Your customer isn't "a man, 30-45, in a relationship, with an anniversary coming up". That's a sterile list of facts. Your real customer is "a person who is starting to panic because their anniversary is next month and they have absolutely no idea what to get their partner. They're terrified of buying another generic, thoughtless gift that leads to a forced smile and a tinge of disappointment. Their nightmare is the feeling of failure, of not showing their partner how much they truly care."

See the difference? The second one is a person. It has emotion. It has a problem you can solve. This "nightmare" is the blueprint for your entire advertising strategy.

When you understand their nightmare, a few things happen:

1. Your Ad Copy Writes Itself: You stop writing generic copy like "Shop our Anniversary Collection". Instead, you write ads that speak directly to the nightmare.
   
   Before: "Beautiful Handcrafted Jewellery. The Perfect Anniversary Gift."
   
   After (using Problem-Agitate-Solve): "Another anniversary, another panic-buy? You know the feeling – the desperate search for something that says 'I love you', not 'I bought this at the last minute'. Don't settle for a gift that gets a polite smile. Give them a piece of handcrafted jewellery that tells your story and watch their eyes light up. Find the gift that proves you've been listening."


2. Your Targeting Becomes Smarter: Instead of targeting the 'anniversary' life event, you start thinking about where someone in this "nightmare state" would be looking for solutions. What are their interests? Maybe they are interested in 'gift ideas', 'romantic getaways', or specific high-end brands that their partner likes. Maybe they follow relationship advice influencers or read publications about modern romance. These interest-based audiences are much broader and give the algorithm more room to work its magic. You target the *problem state*, not the demographic.

This approach allows you to create ads that resonate on a deep, emotional level. The prospect sees your ad and thinks, "Wow, they get it. They understand my exact problem." That connection is infinitely more powerful than simply matching a demographic checkbox. It builds trust and positions your product not as just another item for sale, but as the perfect solution to their specific anxiety.

You probably should... build your audiences around the funnel

Now we have a better way to think about cold audiences (people who've never heard of you). But honestly, the real money in Meta ads, especially for e-commerce, is made from people who already know who you are. This is where structuring your account by funnel stage becomes absolutly critical.

Instead of one campaign with one layered audience, you should have separate campaigns (or ad sets, if your budget is smaller) targeting people at different stages of their buying journey. The further down the funnel someone is, the more likely they are to convert, and the more you should be willing to spend to reach them again.

Here's a simplified structure I use for pretty much every e-commerce client. I remember one women's apparel brand we worked with where implementing this structure was the main driver behind achieving a 691% Return on Ad Spend. It works.

Your budget should be allocated based on performance, but a good starting point is something like 60% ToFu, 20% MoFu, and 20% BoFu. The BoFu audiences are small but they convert at a much higher rate. Your 'Add to Cart' audience will likely have the best Return On Ad Spend (ROAS) in your entire account. Don't neglect them.

With this structure, you let people self-segment. You use broader, interest-based targeting at the top of the funnel to bring people to your site. Then, your retargeting campaigns (MoFu and BoFu) pick them up and guide them towards a purchase based on the actions they've already taken. It's a much more elegant and effective system than trying to guess who might be interested based on flawed demographic data.

You'll need... to understand the maths behind scaling

This all leads to a much bigger, more important question that most advertisers never ask. They get obsessed with low Cost Per Click (CPC) or cheap leads. The real question isn't "How low can my Cost Per Acquisition (CPA) go?" but rather, "How high a CPA can I afford to acquire a great customer?"

To answer that, you need to know your numbers. Specifically, your Customer Lifetime Value (LTV). LTV tells you how much profit a customer is worth to you over their entire relationship with your business. When you know this number, you stop making decisions based on fear and start making them based on data.

Let's break down the calculation. You need three pieces of information:

1. Average Revenue Per Account (ARPA): For e-commerce, this is your average order value (AOV). If you have repeat customers, you'd calculate the average amount a customer spends per year.
2. Gross Margin %: What's your profit margin on each sale after accounting for the cost of goods sold?
3. Monthly Churn Rate %: What percentage of customers do you lose each month? For e-commerce, this is a bit trickier. A simpler metric might be your repeat purchase rate. For this example, let's stick with churn for a subscription-style model, as the principle is the same. If 5% of your customers don't come back each month, your churn is 5%.

Here's the formula: LTV = (ARPA * Gross Margin %) / Monthly Churn Rate

It's much easier to see with an interactive tool. Use the calculator below to get a rough idea of your own LTV.

So, in the example above, each customer is worth £1,400 in gross margin profit to the business. A healthy benchmark for a business is a 3:1 LTV to Customer Acquisition Cost (CAC) ratio. This means for every £1 you spend to get a customer, you should get at least £3 back in lifetime profit. With a £1,400 LTV, you can afford to spend up to £467 to acquire a single new customer and still have a fantastic business model.

Suddenly, that £50 Cost Per Purchase from your Meta ad doesn't seem so expensive, does it? It looks like an absolute bargain. This is the maths that unlocks aggressive, intelligent scaling. You're no longer scared of high CPAs; you understand what a customer is actually worth and can invest confidently to acquire more of them. It's probably the single biggest mindset shift needed to succeed with paid ads in the long run.

I've detailed my main recommendations for you below:

To pull all of this together, your entire strategy needs a rethink – moving away from restrictive, outdated tactics and towards a more modern, algorithm-friendly approach that focuses on your customer's real problems and your business's real numbers. The good news is that none of this is overly complicated to implement once you understand the principles.

This is the main advice I have for you:

I know this is a lot to take in, and it represents a significant change from how you've been thinking about your campaign. It can feel a bit daunting, especialy when you're trying to manage every other aspect of your business. Getting this stuff right – the strategy, the technical setup, the creative testing, the data analysis – is a full-time job. We've worked with numerous e-commerce clients, from subscription boxes where we achieved a 1000% ROAS to apparel brands, and the common thread is always moving from guesswork to a data-driven, systematic process like the one I've outlined.

The difference between a campaign that breaks even and one that profitably scales a business often comes down to this kind of expert-level strategy and relentless optimisation. If you feel like you could use a second pair of expert eyes on your account to make sure you're set up for success, we offer a completely free, no-obligation initial consultation where we can review your strategy together.

Hope this helps!

Regards,

Team @ Lukas Holschuh