Solved: Low App Installs with Facebook AEM SDK

Hi there,

Thanks for reaching out! Happy to give you some initial thoughts and guidance on your situation with the app install ads. It’s a really common problem to see lots of cheap clicks but no actual installs, and tbh, it's usually a sign that the campaign's foundations are a bit wobbly. The good news is it's almost always fixable.

Let's get into it.

We'll need to look at why 'clicks' are a trap...

Right, first thing we need to get straight is this idea of cheap clicks being a good thing. They’re not. In fact, they’re often a sign that you’re actively damaging your campaign performance. It sounds completely backwards, I know, but stick with me.

When you tell Meta you want 'Link Clicks' or 'Traffic', you give its incredibly powerful algorithm a very simple, very specific instruction: "Go and find me the largest number of people, for the lowest possible price, who have a history of clicking on ads."

And the algorithm, being the ruthlessly efficient machine it is, does exactly what you asked. It scours its user base and identifies a specific segment of people. These people are the "Clickers". They click on everything. They’re curious, maybe a bit bored, and their attention is dirt cheap because advertisers who want actual *results* (like sales, leads, or installs) have learned to avoid them. You're paying Facebook to find you the digital equivalent of window shoppers who have no intention of ever coming inside the store. You are paying the world's most powerful advertising machine to find you the worst possible audience for your app.

The user you actually want is the "Installer". This person is completely different. They're more selective. They don't click on ads for fun. They install apps to solve a problem they have. They might cost more to reach because they are in higher demand, but they're the only ones who matter to you. Your current strategy is actively avoiding them.

This is probably one of the biggest myths in paid ads. That more clicks for less money is always better. It's just not true. You'd rather have 10 clicks at £2 each that result in 2 installs, than 100 clicks at £0.20 each that result in zero installs. The first scenario costs you £20 for two valuable actions. The second costs you £20 for absolutely nothing. I remember one app client of ours is getting over 45,000 signups, and their cost per signup is under £2. I can promise you their cost per click is a lot higher than £0.19, but it doesn't matter, because they're paying for the result, not the click.

I'd say your campaign objective is the root of the problem...

So, how do we fix this? We change the instruction we give to Facebook. This brings us to the most fundamental part of any campaign setup: the objective. Right now, you're using a 'Traffic' objective. You need to switch to an 'App Installs' objective immediately. This isn't a small tweak; it's a complete change in strategy.

When you select 'App Installs', you're telling Meta's algorithm something completely different. You're saying: "I don't care about clicks. I only care about people who actually install my app. Use all the data you have from my SDK and the Facebook AEM to find people who look and act like other people who have installed my app, or similar apps, in the past."

This is where your SDK setup becomes incredibly powerful. Every time someone installs your app via an ad, the SDK sends that data back to Meta. The algorithm learns. It gets smarter. It starts to build a profile of your ideal user and gets better and better at finding more of them. By running a Traffic campaign, you're starving the algorithm of the very data it needs to help you succeed. You have this powerful tool (the SDK) but you've essentially left it unplugged.

The entire system is designed to follow your lead. If you tell it the wrong destination, it will dutifully and efficiently drive you off a cliff. If you give it the right destination (installs), it will move heaven and earth to get you there. It's a fundamental shift from buying *attention* to buying *action*.

Here’s a simplified look at how the algorithm makes its decisions. Notice how the initial objective dictates every subsequent step. You've been stuck in the red path, and we need to get you onto the green one.

You probably should redefine who you're actually targeting...

Fixing the objective is the biggest technical step, but it won't work if you're pointing the ads at the wrong people. This is where most advertising advice falls flat. They talk about demographics and interests in a really sterile way. "Men aged 25-40 who like 'technology'." That's useless. It tells you nothing of value and leads to generic ads that speak to no one.

To stop burning cash, you have to define your customer by their *pain*. Your Ideal Customer Profile (ICP) isn't a demographic; it's a problem state. It's a nightmare. You need to become an expert in their specific, urgent, expensive problem that your app is built to solve.

Let's make this practical. Forget who your user *is* for a moment and focus on what they're *struggling with*.

• If you have a project management app, the nightmare isn't 'needing to organise tasks'. It's the gut-wrenching fear of a project manager realizing a critical deadline is about to be missed, costing the company a huge client and damaging their own reputation.
• If you have a meditation app, the nightmare isn't 'wanting to relax'. It's the Sunday evening dread of a high-achiever lying awake at 3 AM, heart pounding, utterly overwhelmed by the week ahead and terrified of burnout.
• If you have a language learning app, the nightmare isn't 'learning Spanish'. It's the embarrassment of being on a business trip in Madrid, unable to order a coffee, feeling isolated and unprofessional.

Once you've isolated that nightmare, everything changes. Your ad copy changes. Your targeting changes. You stop targeting broad interests like "Productivity" and start targeting people who follow specific productivity gurus, use competitor software, or are members of groups for stressed-out professionals. This intelligence isn't just data; it's the blueprint for your entire strategy. If you haven't done this work, you have no business spending another pound on ads.

Let's try and map this out for your app. Take some time to really think about these questions. The more specific you are, the better.

You'll need a better way to qualify your audience...

Once you know who you’re talking to and what their problem is, we can think about *how* to best reach them. Even with an App Install objective, sending cold traffic directly to the App Store can be inefficient. The App Store page gives you very little control over the message, and it's a big commitment for a user to press 'Install' based on a single ad.

One strategy we've used with software clients is to create a pre-qualification step: a simple landing page. Instead of the ad's call-to-action being "Install Now," it's "Learn More." The user is taken to a dedicated page you control completely. Here, you can show off all the features, use persuasive copy that speaks directly to their 'nightmare', show video demos, and display social proof like testimonials. The only goal of this page is to get them so excited about the solution that downloading the app becomes the obvious next step.

The downsides? This approach will almost certainly increase your cost per click. You're adding an extra step to the funnel. But the upside is that the quality of person who clicks from your landing page to the app store is dramatically higher. They are pre-sold. They understand the value. Their intent to install is massive compared to a cold clicker. You might pay more per click, but your final cost per install could actually go down because the conversion rate from click-to-install will be so much better.

It's a trade-off between volume and quality. This interactive calculator below can help you visualise the maths. Play around with the numbers. See how a higher landing page conversion rate can make up for a higher CPC, leading to a more efficient overall cost per install (CPI).

We should talk about what a realistic install cost looks like...

This leads to the big question: what *should* an app install cost? Your £0.19 clicks have probably skewed your perception of what's "expensive". The reality is, a B2C app install in a developed, English-speaking country usually costs somewhere between £1 and £5. It can be more, it can be less, but that's a realistic ballpark.

I looked back at a campaign we ran for an events and sports app. We were managing ads across Meta, TikTok, Apple and Google, and we ultimately drove over 45,000 signups at a cost of under £2 per signup. This was for a fairly broad audience. For more niche apps, or B2B apps, the cost can be significantly higher. I've seen B2B software trials from Meta ads cost $7, and leads from LinkedIn ads cost $22. It all depends on the value of the user you're acquiring.

The cost will also vary massively by country. Targeting the US, UK, Canada, Australia will always be more expensive than targeting developing countries. You might be able to get installs for £0.50 in some regions, but the quality and monetisation potential of those users will likely be much lower. It's not about getting the cheapest install; it's about getting the most *profitable* install.

Here’s a general idea of what you might expect, based on typical ranges we see. Your own results will vary, of course, but this gives you a much healthier benchmark to aim for than £0.19 clicks.

I'd say you need to test your way to a lower CPI...

So, you've fixed your objective, defined your ICP, and set realistic expectations. Now the real work begins: optimisation. The goal is to systematically test different variables to find the combinations that bring your CPI down while maintaining user quality. This isn't about random guesswork; it's a structured process.

You want to isolate variables and test them against each other. The two big levers you have are your **Audience** (who you show the ads to) and your **Creative** (what you show them).

Audience Testing:
Start with your ICP research. Create different ad sets targeting different audience 'themes'.

• Ad Set 1 (Interest Stack): Group together interests based on the tools, publications, and influencers your ICP follows. For example, for a project management app, you might target interests like "Asana", "Trello", "Scrum", and followers of "Scott Belsky".
• Ad Set 2 (Lookalikes): Once you get your first 100+ installs, create a Lookalike Audience. This tells Facebook to find people who are statistically similar to your existing installers. This is often the most powerful audience type. Start with a 1% Lookalike in your target countries.
• Ad Set 3 (Broad): This might sound counter-intuitive, but once your pixel has thousands of install events, you can test an ad set with very open targeting (e.g., just age and location). The algorithm can sometimes be smart enough to find installers on its own, but only do this once you have significant data.

Creative Testing:
Inside each ad set, test different types of ads. People respond to different things.

• Ad 1 (Problem-Agitate-Solve Video): A short video (15-30 seconds) that starts by calling out the 'nightmare', shows how it feels, and then presents your app as the solution. User-generated style content often works very well here.
• Ad 2 (Feature-Benefit Image): A clean, simple image or carousel ad that highlights one key feature and clearly states its main benefit. E.g., "Automated Reporting" (feature) -> "Save 5 Hours a Week" (benefit).
• Ad 3 (Social Proof Ad): A simple ad that uses a direct quote from a happy user. "This app changed the way I manage my team. We've not missed a deadline since." This builds trust and credibility.

The structure is key. Don't test different audiences and different creatives in the same ad set. Keep it clean. Let each ad set run for a few days until it has enough data (e.g., has spent at least 2-3x your target CPI), then turn off the losers and give more budget to the winners.

This is the main advice I have for you:

I know this is a lot of information to take in. Paid advertising seems simple on the surface, but there are a lot of layers to getting it right. The difference between burning money and getting a profitable return often comes down to these foundational strategy decisions. Here's a summary of the most important steps for you to take.

Getting this stuff right takes time, expertise, and a lot of testing. It's not just about setting up an ad and hoping for the best. It's about building a system for growth, understanding your audience on a deep level, and making data-driven decisions to optimise your spending.

That's where professional help can make a huge difference. An expert can help you avoid common pitfalls, accelerate your learning curve, and implement advanced strategies from day one. We do this stuff all day, every day, and have seen what works (and what doesn't) across dozens of software and app campaigns.

If you'd like to chat through this in more detail and have us take a proper look at your specific situation, we offer a free, no-obligation initial consultation. We can review your strategy together and give you a clear roadmap for what to do next. Feel free to book a time that works for you if you're interested.

Hope this helps!

Regards,

Team @ Lukas Holschuh