Introduction

As we established in our article about the impact of mobile app stability on user retention, performance is an important part of any mobile app's success. It's also a part that gets easily ignored which could spill future disaster. But let's suppose you are now convinced that your app could run faster and smoother and you see a realistic promise of a return on the (fixes') investment. What to do next? Can you expect positive results soon?

Well, if you are committed to giving the green light on good, old maintenance work it's only step one of a potentially long project. After all, if performance was neglected until now, you literally have a patient who can only say "It hurts" ("app runs poorly"). You and your dedicated team are the doctors who need to guide the efforts to diagnose and alleviate this pain. So, where to begin? Let us help!

In this article, we'll explore just that. We'll look at the most common ways to diagnose and/or pinpoint your app's performance bottlenecks. You will learn about the tools and methods of finding those, learn the most common issues you can find, and generally how to build a process and culture where caring for the app's speed and response time is baked into any work done by the team. Let's begin!

Why should you care?

Performance bottlenecks, crashes, slowdowns, and other performance issues significantly impact user retention, engagement, and, thus, business growth. Various research shows that 90% of users abandon an app due to performance issues, and those who experience two or more crashes within 30 days are 6.9 times more likely to churn. Crashes also lead to secondary costs, such as increased customer support volume (each crash generates an average of 2.3 support tickets) and slower user acquisition (apps with >2% crash rates grow 40% slower than more stable competitors). On the psychological side, neuroscientific studies indicate that crashes trigger 300% stronger frustration responses than planned downtime, severely harming brand perception.

In a typical SaaS (Software as Service) company, even a 5% increase in monthly churn can reduce company valuation by 30-50%. This is not even the only way stability investments yield high returns: reducing churn by 15% through stability improvements boosts customer lifetime value by 19.6%, and companies ranking in the top 10% for stability enjoy 2.3x more organic installs and 17% pricing power.

Additional Data on Software Instability:

74% of users uninstall an app after three consecutive crashes.
Gaming apps tolerate up to 2.3% crash rates, while FinTech must stay below 0.2%
Production crashes cost 15-30x more to fix than pre-release issues
Apps ranking in the top 10% for stability achieve 38% faster enterprise sales cycles

So, when we boil the numbers down, it's clear that improving performance has so many, sometimes not visible to the naked eye, consequences to the product and the whole company that it can be ignored. But is this performance issue always a case of looking at the numbers on your product dashboard?

The Perception of Mobile Performance

One of the critical aspects of mobile performance is how your users perceive speed. Sometimes, a minor slow-down can cause massive frustration if the interface gives no visual feedback. On the other hand, a lengthy process can feel acceptable if the app communicates a sense of progress or partial results along the way. This concept underscores the importance of investigating not just absolute load times, but also the user experience around loading states. While raw metrics matter, user satisfaction can be influenced by the right UX behaviors. It is thus fair to say, that not all slowness can and should be addressed on the backend level. A lot of AI applications will require time to provide output (say "Generate 50 professional business pictures of me") and users understand this process takes time. A surprising conclusion here is that your app's performance audit needs to start with a UX-level audit of what constitutes an actual backend bottleneck and what can be addressed with a simple animation or the right text copy.

With this out of the way, let's focus on proper, poor-tech fundamentals originating slowness. While the sources of performance issues vary, they typically fall into one of these categories:

CPU Overload: This often comes from expensive operations such as image processing, encryption, or large data manipulations executed on the main thread. It can also come from developing with high-end machines while your user base uses mostly low and medium-tier Android phones.
Memory Leaks: This happens when some piece of the code needlessly and constantly writes data to RAM memory until there is no more RAM to use and the app crashes.
Network Latency: This not entirely code-dependent issue results from low or frequent requests, minimal caching, or large payloads that cause your app to freeze while waiting for data. Fixing this involves mostly preparing the code for such eventualities and handling them on a UX level.

Of course, those are only the main culprits. You can also face poorly written code, old and inefficient dependencies (i.e. external plugins or frameworks), and poorly optimized database performance. Regardless, the general approach to diagnosing performance concerns remains the same: measure, hypothesize, and fix. Let us walk you through those four.

Measure

Before choosing your best direction for achieving better performance, you need to be able to identify the worst offending bottlenecks. Fixing them is no thing, but you will also need to be able to observe the improvement and see if it doesn't degrade again in time. So how to do that?

Use The Right Tools

iOS: Xcode Instruments

Here, your team needs to consider using the following build-in options:

Time Profiler: Identifies CPU bottlenecks by showing which methods consume the most processing time.
Allocations & Leaks: Monitors your memory usage in real-time and flags suspicious patterns that might indicate a leak.

Android: Android Studio Profiler

Similar on the Android part:

CPU Profiler: Records method traces so you can see exactly which functions hog the CPU.
Memory Profiler: Charts memory allocations and helps you capture heap dumps to pinpoint leftover objects that never get garbage-collected.
Network Profiler: Visualizes every request, response size, and throughput, making it obvious if you're making too many calls or fetching oversized data.

Cross-Platform

You may not be developing your app in native form but using a more platform-agnostic version. In that case, consider:

React Native/Flipper or Flutter DevTools: Those offer performance overlays, timeline events, and memory usage graphs that help you track where your code might be doing unnecessary heavy lifting.

Live Monitoring

Other than the ones listed above, tools like Firebase Performance Monitoring, Sentry, or AppDynamics will help you track performance in production environments, where true user behavior reveals the real bottlenecks. Logs from these tools often give you raw data on slow API calls, frequent crashes, or out-of-memory errors. You will also be able to spot any crashes that appear in numbers you can't ignore and other issues worth addressing. However, do also note that fixing crashes in production costs 15-30 times more than identifying issues during testing. Thus, if you find yourself finding too many issues once a product update is live, perhaps it's also worth to re-examine your testing and release pipeline to see if future "production issues" can be avoided.

Hypothesize

With performance data in hand, the next step is to draw informed hypotheses about what's causing the slowness. Much like a doctor analyzing lab results, you and your team look for anomalies or suspicious patterns and propose possible causes. To extract the actual issues bogging your app follow these steps:

Ask the Right Questions

Can you connect slowness to a specific action?
Does it occur for all users or only specific devices/OS versions/others?
Is it an anomaly or expected behavior?
Can you tie the issue to a specific release?
Is it connected to your own code or external API/service?
Can you replicate the issue easily?
Does it happen universally or only under certain conditions? What are those?

with those answered, you can move on to the next step:

Assess and prioritize

You can't chase every lead at once. Pick the most critical or highest-impact suspicion first. For instance, a frequent memory spike that hits 70% of your user base is more urgent than a mild CPU inefficiency that only surfaces on older phones. By prioritizing your theories, you prevent your team from scattering its efforts without finishing any meaningful fix.

To get the most out of your maintenance investment make sure to work with the team to estimate the effort needed to implement the specific fix and the level of certainty you have that the issue and the fix were chosen correctly. The obtained in the previous steps will be essential. You will want to address the issues that you know cause the most slowness, can be easily replicated, and can be addressed relatively quickly. Those will be your "low-hanging apples".

At the same time, you need to remember not to fall into the mistake that often gives maintenance the bad name: overcommitting. Once you clear all those obvious fixes you may find yourself chasing issues that are hard to replicate, the fix is not clear cut or it will simply take a lot of time to implement. This is the moment where you can no longer prioritize inside only this "maintenance" bucket, but also confront the fixes with potential new features or UI improvements. You are chasing the most value for the development time you can get. If you can't get those values from the fixes easily, you need to look further for the best opportunities for your product. After all, we started in a hypothetical scenario where the product was slow enough that it started to cause issues for user retention. However, once that risk is elevated, further chasing an issue-less app is simply fools' gold.

So, let's suppose you fixed those low-hanging fruit, and you decide to leave some issues be. What next? Well, just like with diet: you need to make this care for performance your ongoing focus. If you return to old habits, the "yoyo" effect will surely kick in and the slowness will come back sooner than you expect. Thus, before we conclude this entry, let us share one final paragraph:

Achieving Scalable Performance

Quick fixes can patch immediate performance hurdles, but only when true scalability emerges can performance become an everyday habit rather than an emergency, and temporary, focus. Here's how to embed that mindset in your workflow:

Make Performance Part of Your Monitoring Dashboard

Don't just run tests occasionally. You already collected data; now, use this experience to create a performance dashboard as granular as you need. You can collect real-world metrics using tools like Firebase Performance Monitoring, Sentry, or Datadog. Additionally, schedule regular check-ins to spot creeping memory usage or response-time spikes. By catching trends early, you can fix minor slumps before they blow up into full-blown crises. If Thus, if you automated alerts on top of that, you can sleep peacefully knowing your app is performing at least as well as you set your quality standards.

Set Performance Budgets and Goals

Define clear targets (e.g., "each screen must load within 500ms on mid-tier devices") and make sure they are executed. This way the team will formally be expected to put performance in the forefront. However, this comes with a clear consideration of the specific amount of time dedicated to working on performance and maintenance. It would be silly to set quality standards and then ignore them to fully focus on new features, right?

Consider Performance on the Design Stage

As we mentioned, not all delays are preventable. Thus, when designing any new functionality, ensure you cover things like long load times (if they are expected) or slow networks. This way you can cover both the actual and perceived drops in performance for an all-in-all great user experience.

Refactor on the Fly

Instead of bundling all your code cleanups into massive maintenance sprints, consider tackling them one by one when you touch a certain area of code for any reason. Of course, this is more of a technical team area, but if they have the founder's blessing to take a tad longer on a project to optimize existing code around it, they will surely spend the time well to ensure long-term, scalable, peak performance of the whole app.

Conclusion

As you can see, giving the performance the time of day is barely the first step to tackling any slowness that builds up over the months and years. As long as you don't lose too many clients, it is never too late to turn your attention to improving performance. Fortunately, the process of getting there is not that difficult and the main cost of it is delaying any new work for a chosen period of time. At the same time, the return on this investment might be far greater than most of the new app's improvements you had lined up.

That being said, there is a way to have your cake and eat it: let us help! AppUnite can come in, diagnose, prioritize, and fix selected performance bottlenecks while your in-house team continues their regular work. If you find this appealing, be sure to contact us today and let us see what we can do for you and your app. Looking forward to speaking with you.

How to Diagnose Performance Bottlenecks in Mobile Apps