Solved: Google Ads App Campaign Pricing in Zurich (Data Inside)

Hi there,

Thanks for reaching out! Happy to give you some of my initial thoughts on this. It’s a common question, trying to nail down a specific cost for app installs, especially in a competitive market like Zurich. Tbh, you're asking a question that doesn't really have a simple answer, but that's a good thing. It means we can build a much smarter strategy than just trying to guess a number.

The truth is, focusing on a fixed "price" for an install is the wrong way to look at it and it's a trap many people fall into. We need to flip the problem on its head. Instead of asking "What will an install cost?", we need to ask, "What can I *afford* to pay for a high-quality user who will stick around?". Once we know that, the rest of the plan starts to fall into place. Let's get into it.

We'll need to look at why 'price' is the wrong question...

First things first, let's debunk this idea of a set price. There isn't a rate card for Google Ads where you can look up "app install, Zurich" and get a number. It's a live, real-time auction, happening millions of times a day. The price you pay is determined by a few key factors, and understanding them is far more valuable than knowing some generic industry average.

-> Competition: You've picked Zurich. That’s a global hub for finance, insurance, and tech. It's a high-income area, which means two things: users have more disposable income (good for you), but advertisers have bigger budgets and are willing to pay a lot to reach them (not so good for you). You're not just competing against other app developers; you're competing against banking giants, luxury brands, and high-growth SaaS companies all bidding for the same eyeballs on the same screen. Their huge budgets drive up the cost for everyone.

-> Audience Quality: This is the big one. Google’s algorithm is incredibly sophisticated. It knows which users are likely to just install an app and forget about it, and which ones are likely to open it, engage, and eventually make an in-app purchase or subscribe. The users who are more likely to take valuable actions are more expensive to reach. This is why the advice to "just run a brand awareness campaign" is often terrible. You're effectively telling Google, "Please find me the cheapest people who will never, ever become my customers." We've seen it time and time again. The goal isn't the cheapest install; it's the most *profitable* user, and they almost always cost a bit more to acquire.

-> Your Ads & App Store Page: The quality and relevance of your ad creative and your app store listing have a huge impact. A compelling video ad that speaks directly to a user's problem will get a higher click-through rate (CTR) and a better Quality Score from Google. A well-optimised App Store page with great screenshots, reviews, and a clear description will have a higher conversion rate from click to install. If your ads are poor or your store page is weak, Google will charge you more to show them because users are less likely to respond positively. It's their way of protecting the user experience.

Obsessing over getting the absolute lowest Cost Per Install (CPI) is a race to the bottom. I remember one software client who came to us fixated on their cost per trial on Meta. We had successfully generated over 5,000 trials for them at around $7 each, but the challenge became scaling with high-quality users. We've learned that focusing purely on the lowest cost can attract users who install the app but never convert. The real goal is to find the most profitable user, and they almost always cost a bit more to acquire. That’s the mindset shift we need to make here. So, let's forget the "price" and start thinking about the person.

I'd say you need to define your customer's nightmare, not their location...

Your target audience is not "people in Zurich." That tells me nothing. It's a demographic, and demographics don't buy products. People with problems buy solutions.

You need to get incredibly specific about the *pain* your app solves. What is the specific, urgent, expensive, or career-threatening nightmare that your ideal user is experiencing right now? This is your Ideal Customer Profile (ICP), and it has nothing to do with age or gender and everything to do with their problem state.

Let's imagine your app is for expense tracking. A bad ICP is: "Professionals aged 30-50 in Zurich." Who cares? That's everyone and no one.

A great ICP is: "A junior associate at a major bank in Bahnhofstrasse who is terrified of submitting their travel expenses late and being out of pocket for thousands of Francs because they lost a receipt. They are currently using a messy spreadsheet and a folder of crumpled paper, and they hate the last two days of every month."

See the difference? We've gone from a generic demographic to a person with a real, tangible problem. Now we can write ad copy that speaks directly to that nightmare. Instead of "Easy Expense Tracking," we can say, "Stop dreading month-end. Scan your receipts in seconds and get your expenses filed before you've even finished your coffee. Never lose a Franc again."

This deep understanding of the customer's pain is the foundation of your entire advertising strategy. It dictates your ad copy, your targeting, and even your app's features. When your ad is hyper-relevant to the user's problem, your click-through rates go up, your conversion rates improve, and Google rewards you with a lower cost to acquire that perfect customer. This is how you win in a competitive market like Zurich – not by outspending the competition, but by out-thinking them.

You probably should calculate what a user is actually worth to you...

Alright, this is the most important part of this whole letter. This is the maths that unlocks intelligent, scalable growth. Before you spend a single Franc on ads, you MUST know your Customer Lifetime Value (LTV). LTV tells you the total profit you can expect to make from a single user over the entire time they use your app.

The real question isn't "How low can my CPI go?" but "How high a CPI can I afford to acquire a fantastic customer?" LTV gives you the answer.

Here are the components you need:

-> Average Revenue Per Account (ARPA): What do you make from a user, per month? This could be their subscription fee or average in-app purchase value.

-> Gross Margin %: What's your profit margin on that revenue? After app store fees, server costs, etc., what percentage is left as profit?

-> Monthly Churn Rate: What percentage of your paying users do you lose each month? This is critical. A lower churn rate dramatically increases LTV.

The calculation is straightforward:

LTV = (ARPA * Gross Margin %) / Monthly Churn Rate

Let's run an example. Say your app has a subscription of CHF 20/month. Your gross margin is 70% after Apple/Google's cut and other costs. And you've observed that you lose about 5% of your subscribers each month.

LTV = (CHF 20 * 0.70) / 0.05

LTV = CHF 14 / 0.05 = CHF 280

This means, on average, each new paying subscriber is worth CHF 280 in gross profit to your business. Now we have a real number to work with!

A healthy, sustainable business model often aims for a 3:1 LTV to Customer Acquisition Cost (CAC) ratio. This means you have enough margin to cover other business costs and make a profit. So, with an LTV of CHF 280, you can afford to spend up to CHF 93 (280 / 3) to acquire a single paying customer. This is your target CAC.

Now, let's say you know from your data that 1 in every 10 people who install the app and complete onboarding become a paying subscriber (a 10% conversion rate). Your maximum affordable Cost Per Install (CPI) is therefore CHF 9.30 (CHF 93 / 10).

Suddenly, seeing a CPI of CHF 8 in your Google Ads dashboard doesn't look expensive anymore. It looks profitable. This calculation frees you from the tyranny of cheap installs and allows you to bid confidently for the high-quality users who will actually grow your business.

Use the calculator below to play with your own numbers. See how a small improvement in churn or a slight increase in your monthly price can dramatically change what you can afford to spend on ads.

You'll need a smarter way to find your first users...

Now that we know what we can afford to pay, how do we find these valuable users without breaking the bank? My advice is almost always the same for a new app launch: do NOT start with a broad Google App Campaign (sometimes called UAC). It might seem like the obvious choice, but it's a mistake.

A broad app campaign is designed for scale. You give Google your app, a budget, and a target CPI, and its machine learning goes out to find installs at that price. The problem, as we've discussed, is that it often optimises for the cheapest, lowest-quality users first. You'll burn through your initial budget getting installs from people who will never convert, and you won't get any good data.

Instead, you need to start where the *intent* is highest. That means **Google Search Ads** and **Apple Search Ads**.

Think about it. Someone going to the App Store or Google and physically typing in "best app for tracking business expenses switzerland" or "invoice generator app for freelancers" is not just browsing. They have a problem, and they are actively looking for a solution *right now*. They are pre-qualified. They are your best possible first customers. One campaign we managed for an app grew to over 45,000 signups at under £2 per signup by combining smart Search campaigns with other channels, but Search was where we found our initial, most valuable user cohorts.

Your strategy should be:

1. **Identify High-Intent Keywords:** Brainstorm all the terms your "nightmare-defined" ICP would search for. Think about problems, solutions, competitors, and job-related queries.

2. **Launch Search Campaigns:** Run ads on both Google Search (leading to your website or app store page) and Apple Search Ads (directly within the App Store). These will be more expensive per click than a display ad, but the conversion rate from click-to-install and install-to-paying-user will be vastly superior.

3. **Gather Data:** These initial campaigns are your intelligence-gathering operation. You'll learn which keywords drive the most valuable users, what ad copy resonates, and you'll start to build a real-world baseline for your profitable CPI and CAC. This data is gold.

4. **Scale Later:** Once you have a steady stream of profitable users from Search and your pixel/SDK has collected a few hundred conversion events (e.g., subscriptions started), *then* you can start experimenting with broader channels like Google App Campaigns or Meta Ads. You can use the data from your Search campaigns to build much more effective Lookalike audiences and inform the algorithm, telling it "go find me more people who look like my best customers from Search."

This approach is more methodical and might feel slower, but it's how you build a sustainable, profitable user acquisition engine instead of just setting your budget on fire.

This is the main advice I have for you:

So, to bring this all together, forecasting your budget and ROI isn't about finding a magic CPI number for Zurich. It's about building a system. It's about understanding your customer's value, finding them where their intent is highest, and then scaling intelligently based on real data. You're not buying installs; you're investing in acquiring profitable customers.

I've detailed my main recommendations for you in a table below. This is the step-by-step process I would follow if I were launching your app. It’s a framework that prioritises learning and profitability over vanity metrics like cheap installs.

To help with the forecasting part of your question, I've also built you a simple ROI calculator. Once you have your Target CAC from the LTV calculator and a rough idea of your install-to-paying-user conversion rate (a good starting estimate is anywhere from 2-5% if you dont have data yet), you can plug those numbers in and see how different ad spend levels might play out. This will help you set a realistic initial budget.

As you can see, it's a lot more involved than just setting up a campaign and hoping for the best. It's a process of building a growth engine piece by piece. This is where expert help can make a huge difference. We've built these kinds of systems for numerous software and app clients, helping them find their most profitable users and scale their ad spend without sacrificing their return.

This process of testing, data analysis, and strategic scaling can take months to get right if you're doing it for the first time. An experienced hand can often cut that time down significantly and help you avoid costly mistakes along the way.

Hope this has given you a much clearer framework for thinking about your launch. If you'd like to chat through your specific app and get a second pair of eyes on your strategy, we offer a free initial consultation. We can review your plans together and give you some more tailored advice.

Regards,

Team @ Lukas Holschuh