How Do I Know Which App Store Changes Help Downloads?

Your app sits there in the store with barely any downloads coming in and you're wondering if changing that screenshot or rewriting the description would actually make a difference. I've seen this situation play out hundreds of times—developers and product managers making changes to their app store listing based on gut feeling or what they've seen competitors do, then sitting back and hoping something magical happens. Spoiler alert: it rarely does. The problem isn't that making changes is wrong; its that most people have no systematic way to know if those changes actually helped or hurt their download numbers. They're basically flying blind, and in an industry where user acquisition costs can reach £10 per install for competitive categories, that's an expensive way to operate.

I remember working on a fintech app where the client was convinced their conversion rate would skyrocket if we just made the app icon brighter. They'd seen a competitor do something similar and assumed that was the secret sauce. We tested it properly—ran a controlled experiment over three weeks with half the traffic seeing the new icon and half seeing the original. The result? The brighter icon actually decreased downloads by 8%. Turns out their target audience (people managing serious financial decisions) saw the bright icon as less trustworthy. Without testing, they would have rolled out that change to everyone and watched their acquisition costs climb without understanding why.

The difference between guessing and knowing what works in your app store listing can mean thousands of pounds in saved acquisition costs, but you need a proper framework to measure it.

This guide walks you through the entire process of ASO testing—from setting up your first experiment to reading the data without second-guessing every fluctuation. You'll learn which elements of your listing are worth testing (and which ones waste your time), how to measure results that actually matter to your business, and the common mistakes that even experienced developers make when running app store experiments. This isn't theoretical stuff; its what I've learned from years of testing across healthcare apps, e-commerce platforms, and everything in between.

Understanding What ASO Testing Actually Means

ASO testing—or App Store Optimisation testing if we're being formal about it—is basically the process of changing different bits of your app store listing to see what gets more people to download your app. Simple as that. But here's where it gets interesting; most people think they're doing ASO testing when really they're just making random changes and hoping something sticks. That's not testing, thats guessing with extra steps!

I've worked on dozens of app launches over the years and the difference between proper ASO testing and just fiddling with your listing is massive. Real ASO testing means you change one specific thing—like your app icon or your first screenshot—and then measure whether that change actually improved your conversion rate. Your conversion rate is the percentage of people who see your listing and then actually tap the download button. If 100 people look at your app page and 5 download it, you've got a 5% conversion rate. When we ran tests for a healthcare app a while back, we found that changing just the main screenshot from showing the app interface to showing an actual person using the app increased downloads by 23%. That's real money we're talking about.

The tricky bit is that you cant just change everything at once and call it a test. If you swap your icon, rewrite your description, and change all your screenshots in one go, you'll have no idea which change made the difference. Was it the icon? The description? Who knows! This is where most app owners mess up because they get impatient... they want results fast and end up learning nothing useful. Proper ASO testing takes time and discipline, but its the only way to know for certain what works for your specific app and audience.

Setting Up Your First App Store Experiment

Here's what I tell people who want to start testing their app store listing—pick one thing to test and stick with it. I mean, genuinely just one thing. I've seen too many clients get excited and try to test three different screenshots, two icon variants, and a new description all at once, and then they cant figure out which change actually made the difference. Its chaos basically.

The way I usually set this up for clients is dead simple; start with your app icon or your first screenshot because those are what people see first when they're scrolling through search results. You know what? I worked on an education app where we tested just the main screenshot—one version showed kids using tablets, the other showed learning outcomes with star ratings. The second one increased our conversion rate by 23% which was bloody mental really. But we only knew that because we tested one thing at a time.

Getting Your Baseline Numbers Right

Before you change anything, you need to know where you're starting from. Run your current listing for at least a week (two is better) and track these numbers:

• Daily impressions in search results
• Product page views
• Downloads from those views
• Your current conversion rate (downloads divided by page views)

Most people skip this step and jump straight into testing, but then they've got nothing to compare against. I learned this the hard way on a fintech project where we started testing too early and couldn't prove our changes actually worked—the client wasn't thrilled about that delay. Getting proper baseline data helps you understand your actual user behaviour patterns versus what you think is happening.

Choosing Your Test Duration

The length of your test depends on your traffic really. If you're getting 1,000+ page views per day, a week might be enough; if you're getting 100, you'll need three or four weeks to get meaningful data. Sure, its tempting to rush this, but statistical significance matters more than speed. You want enough data that you can be confident in your results... otherwise you're just guessing and wasting money on changes that might not actually help.

Start your first test on a Monday or Tuesday so you capture full weeks of data—weekend user behaviour is often different from weekdays, and you want your test periods to include the same mix of days for fair comparison.

Which Parts of Your Listing Should You Test

Right, so you've got your app in the store and you're ready to start testing. But where do you actually begin? I've run hundreds of these tests over the years and I can tell you the answer isn't as obvious as most people think. The temptation is to test everything at once, but that's a recipe for confusion and wasted budget.

Your app icon is hands down the most important element to test first. It's the first thing people see in search results and it massively influences whether someone even clicks to see your full listing. I worked on a fitness app where we tested five different icon variations—the winner improved our conversion rate by 34% just by itself. But here's the thing, you need to test icons that are genuinely different from each other. Changing the shade of blue slightly won't tell you much; you need to test different concepts entirely.

After icons, your screenshots are next. These tell your app's story and honestly, most apps get them completely wrong. People don't read the text on screenshots (even though we spend ages writing it!) so focus on showing actual app interfaces that look clean and understandable. For a healthcare app I worked on, we found that showing the results screen performed better than showing the onboarding flow, which surprised everyone on the team. If you want to dive deeper into this, there's a detailed guide on systematic screenshot testing methods that covers the technical setup.

Your app title and subtitle matter too, but here's something people don't realise: you can't test these as freely as visual elements because changes require app updates and review approval. So test these less frequently but more carefully. Understanding effective positioning frameworks becomes crucial when you're making changes that take weeks to implement.

Priority Order for Testing

• App icon (biggest impact on click-through rate, easiest to test)
• First three screenshots (most users never scroll past these)
• App preview video if you have one (but only 20-30% of users watch it)
• Feature text in later screenshots (lower priority, less visual impact)
• App title and subtitle (requires app submission, test sparingly)

One mistake I see constantly is testing your app description text. Sure, its technically possible to A/B test it, but barely anyone reads it anyway. The data shows that less than 5% of users expand and read your full description before downloading. Focus your energy on the visual elements that actually influence decisions, not on writing copy that nobody will see. When designing your competitive screenshot strategy, remember that visual impact trumps detailed explanations every time.

How to Measure Real Results That Matter

Right, so you've run your test and now you're staring at a spreadsheet full of numbers. Fun times. But here's what actually matters—conversion rate is your north star metric. Everything else is just noise if people aren't downloading your app. I've seen clients get excited about a 20% increase in impressions, but their conversion dropped by 3%. That's not a win, thats just more people seeing your app and deciding not to download it.

When we ran tests for a fitness app a while back, we tracked six different metrics but only three really mattered; conversion rate (obviously), first-day retention, and what we call "quality installs." You see, getting downloads from users who uninstall within 24 hours actually hurts your ranking. The app stores are smart enough to know when people regret downloading your app... and they will punish you for it. So we started measuring not just how many people downloaded but how many kept the app past day one. Changed everything about how we approached our tests. Understanding early deletion patterns helps you spot when your listing attracts the wrong audience.

The metric that looks impressive in a report isn't always the one that grows your business

Statistical significance is where most people mess this up completely. You need at least 350-400 conversions per variant before you can trust your results—and that's the bare minimum really. I've watched teams celebrate a winning variant after 50 downloads, make the change permanent, then watch their numbers tank because it was just random chance. Its a bit mad how often this happens. Also, run your tests for a full week minimum to account for weekday versus weekend behaviour; user behaviour changes massively depending on when they're browsing the store. This connects to broader testing environment variations that can skew results if you're not careful.

Track your cost per install if you're running paid campaigns alongside your ASO work. Sometimes a test variant gets more organic downloads but performs worse with paid traffic, which means you need to think carefully about which version to implement based on where most of your users actually come from. The relationship between organic appeal and paid performance often reveals whether your conversion optimisation efforts are attracting genuine intent or just curious browsers.

Common Mistakes That Waste Time and Money

I've seen clients burn through thousands of pounds testing the wrong things in their app store listings, and its honestly painful to watch. The biggest mistake? Testing multiple elements at once. A fitness app we worked with changed their icon, first screenshot, and headline simultaneously—then couldn't figure out which change actually improved their conversion rate by 12%. They basically wasted three weeks and had to start over, testing each element separately. One variable at a time, that's the rule.

Another common error is ending tests too early because you're excited about initial results. I mean, I get it—you see your downloads jump 20% after two days and want to declare victory. But here's the thing: you need statistical significance, which typically means running tests for at least a week (sometimes two) depending on your traffic volume. We had an e-commerce client who switched to a "winning" screenshot after just 48 hours, only to watch their conversion rate drop the following week when the novelty wore off.

People also test during unusual periods—launching experiments right before Christmas or during major OS updates when user behaviour is completely different. Your baseline data becomes meaningless. And don't even get me started on testing with tiny sample sizes; if you're only getting 100 impressions per day, you'll be waiting months for reliable data. Sometimes its better to focus on other growth channels first until you have enough traffic to make ASO testing worthwhile. The maths simply doesn't work otherwise, and you'll end up making decisions based on random noise rather than actual user preference. Getting better app store visibility might be a prerequisite before testing becomes viable.

Tools That Make Testing Easier

Right, so you've decided to start testing your app store listing—brilliant first step. But here's the thing; doing it manually is a bit mad really. I mean, you could sit there with spreadsheets tracking everything yourself, but honestly that's going to eat up time you don't have. Over the years I've used pretty much every ASO tool out there (some of them were absolutely rubbish) and there are a few that genuinely make life easier.

Apple and Google both offer their own built-in testing platforms now. Apple's Product Page Optimisation lets you test up to three variations of your screenshots, preview videos and app previews—its completely free and runs directly through App Store Connect. Google's experiments work similarly through the Play Console. I always tell clients to start here because the data comes straight from the source and you don't need to pay for third-party tools. The downside? They're a bit limited in what you can test, and Google's experiments can take ages to reach statistical significance if your download numbers are low.

For more detailed testing I've had good results with tools like StoreMaven and SplitMetrics. StoreMaven's particularly useful because it shows you exactly where users drop off in your screenshots—we used it for a fintech app and discovered that 60% of people stopped scrolling after the second image, which completely changed our approach. SplitMetrics is solid for running tests outside the app stores themselves, which means you can iterate faster before committing to a live experiment. Understanding these drop-off points becomes especially important when you're trying to create personalised app experiences that resonate with specific user segments.

Don't overlook App Radar and Sensor Tower for competitive analysis—knowing what your competitors are testing helps you avoid wasting time on experiments they've already validated or disproven.

What Each Tool Actually Does Well

Here's what I reach for depending on the situation. Not every tool suits every project and budget matters more than people admit:

• Apple Product Page Optimisation: Free, reliable data but limited to three variants maximum—best for basic screenshot testing
• Google Play Experiments: Free but slow to reach significance—you'll need decent traffic volumes or patience
• StoreMaven: Shows user behaviour on your listing with heat maps and scroll depth—expensive but worth it for high-stakes launches
• SplitMetrics: Lets you test before going live in stores—good middle ground on pricing
• App Radar: Keyword tracking and competitor monitoring—helps inform what to test next

One thing I've learned the hard way is that tools won't tell you what to test; they just make running the tests easier. You still need to understand your users and form hypotheses based on real insights, not just gut feelings. We ran experiments for an e-commerce app using three different tools simultaneously and got slightly different results from each—turns out the audience demographics varied between testing methods. So pick one tool, stick with it for consistency, and remember that the platform data (Apple and Google's own tools) should always be your source of truth when making final decisions.

Reading Your Data Without Getting Confused

I'll be honest—when I first started running app store tests years ago, the data completely baffled me. You've got conversion rates, download counts, impression numbers, all changing constantly... its easy to look at a graph and convince yourself you've found something meaningful when actually you're just seeing normal fluctuations. The biggest mistake I see people make? They look at their data too early and make decisions before the test has actually reached significance.

Here's what I do now after running dozens of these tests: I wait until I've got at least 350-400 conversions per variant before I even think about drawing conclusions. Sure, you might see a 15% lift after the first day, but that could easily flip the other way by day three. I learned this the hard way when we tested a new icon for a fitness app—looked like a winner after 48 hours but by the end of week one it was performing 8% worse than the original. Bloody frustrating but that's why we test properly. This connects to the broader challenge of creating memorable app positioning that works consistently across different time periods.

What Numbers Actually Matter

Focus on these metrics and ignore the rest for now:

• Conversion rate (impressions to downloads)—this is your primary metric
• Sample size—you need enough data to trust your results
• Statistical confidence—aim for 95% minimum before making changes
• Time period—run tests for at least 7 days to account for weekly patterns

The Reality Check

Look, sometimes your test will show no significant difference. That's fine. It doesn't mean you failed; it means you learned something. I've run tests where variant A looked 20% better but once we factored in the confidence intervals, there was actually no meaningful difference. When that happens, stick with what you've got and test something else. The data's there to help you make smarter decisions, not to tell you what you want to hear. Remember that successful testing often reveals how user engagement patterns differ from what we assume during the design process.

Conclusion

Look, ASO testing isn't magic and its definitely not something you set up once and forget about. I've worked with fintech apps where we tested icon variations for months before seeing meaningful patterns, and I've had e-commerce clients who saw massive download lifts within weeks of their first experiment. The difference? They stuck with it and they actually acted on what the data told them.

The biggest mistake I see people make after learning about testing is they go quiet. They run one experiment, get some results, then never test again because they think theyve "figured it out". But here's what actually happens—user behaviour changes, competitors update their listings, and seasonal trends shift how people search for apps. What worked brilliantly in January might perform terribly by June; I've seen this happen with healthcare apps where summer searches completely changed user intent compared to winter months.

Start small if you need to. Test your first screenshot. See what happens. Learn how your specific audience responds to changes. Then test your description, then maybe your icon if you're feeling brave (icon tests take longer to show significance, just so you know). Build this into your regular workflow rather than treating it as a one-off project. The apps that consistently rank well in their categories? They're testing something most of the time, not because they're obsessed with perfection but because they understand user preferences evolve and staying still means falling behind. Your app store listing is never truly finished—it's just your best understanding of what works right now, based on actual evidence rather than guesswork.