With more apps to choose from than ever before, user expectations are higher than ever.
We all know the headline: users are quick to abandon slow, unresponsive apps, or prone to crashing. Most mobile app users (around 70%) will abandon an app if it takes too long to load. A one-second delay in response can result in a 7% loss in conversion, and nearly one in every two apps are uninstalled within the first month of download.
As a developer, performance is not just a technical consideration but a crucial element of the user experience. A well-optimised app can lead to higher user retention, better reviews, and ultimately, more success. Below, the Monedata team explores the best practices for maximising app performance, ensuring your app is functional but also fast and efficient.
Why’s performance important?
Before diving into optimisation techniques, it’s important to understand what we mean by app performance. Broadly, it encompasses three key aspects:
- Speed: How quickly the app responds to user actions and loads content.
- Efficiency: How well the app utilises resources such as memory and battery.
- Stability: The app's ability to run without crashes or errors.
Improving performance requires a holistic approach, focusing on all these aspects throughout the development lifecycle.
Optimising your code
It’s common for developers to over-engineer when creating their software, writing overly complex code for simple tasks. While it's tempting to add more features and clever solutions, this can lead to bloated, hard-to-maintain code that slows down your app. Stick to the simplest solution that works effectively. Frequent object creation and garbage collection can lead to performance issues, especially in memory-constrained environments. Use object pooling where applicable, and consider using primitive data types to reduce memory usage.
Inefficient loops and algorithms can dramatically impact app performance.
Always strive for O(n) complexity or better. When working with large data sets, consider using more efficient data structures and algorithms to reduce processing time.
Reducing launch times
The first impression is critical; a slow app launch can deter users from engaging further.
Load only what's necessary at launch and defer non-essential tasks like analytics tracking, feature setup, and data synchronisation until after the main UI is visible to the user.
A splash screen provides visual feedback while your app loads, but it shouldn't be a crutch for slow load times. Use lightweight splash screens and keep their duration short. For apps that rely on network data, preload critical information asynchronously in the background. This ensures that data is ready when the user needs it, without blocking the main thread.
User interface responsiveness
A sluggish UI can ruin the user experience, no matter how robust the backend is. To keep your UI snappy, keep the main UI thread free from heavy processing. Use background threads for tasks like network requests, image processing, and data parsing.
Many frameworks offer built-in tools for this purpose, like Android’s AsyncTask or iOS’s Grand Central Dispatch. Complex view hierarchies can slow down rendering times. Flatten your view hierarchies where possible, and use tools like Android's ConstraintLayout or SwiftUI's VStack and HStack to simplify your layouts. Load data or resources as they are needed rather than all at once. For example, use RecyclerViews or ListViews with pagination in Android, and UITableView with dynamic cell loading in iOS.
Reduce memory usage
Memory leaks and high memory usage can lead to app crashes and sluggish performance, especially on devices with limited RAM. Memory leaks occur when objects are no longer needed but cannot be garbage collected because they are still referenced. Use tools like Android Studio's Memory Profiler or Xcode's Leaks instrument to identify and fix leaks.
Choose the most appropriate data structure for your needs. For example, use SparseArray instead of HashMap in Android when keys are integers, and prefer value types over reference types in Swift. Large resources like images and bitmaps should be managed carefully. Recycle bitmaps in Android once they are no longer needed, and use image caching libraries like Glide or Picasso.
Networking
Network calls are often the most time-consuming operations in an app. Compress data before sending it over the network. Many REST APIs support gzip compression. This can reduce the size of data transferred, speeding up load times. Minimise the number of network requests by batching them together when possible. For example, instead of sending multiple small requests, aggregate them into a single larger request. Implement caching mechanisms to store data locally, reducing the need for repeated network calls. Use HTTP caching headers, and consider tools like Room in Android or Core Data in iOS for local data storage.
Optimising
App performance is not a one-time task but an ongoing process. Regular monitoring and optimisation are essential. Leverage tools like Firebase Performance Monitoring for Android and iOS, and Xcode Instruments for detailed performance insights. These tools can help you track app performance in real-time and identify bottlenecks. Regularly profile your app using tools like Android Profiler or Xcode’s Instruments. Look for trends in memory usage, CPU consumption, and network activity, and address any anomalies. Pay attention to user feedback and analytics data. Slow load times, unresponsive UI elements, and crashes are often reported by users. Use this feedback to guide your optimisation efforts.
Wrapping up
Maximising app performance is essential for creating a seamless and enjoyable user experience. By focusing on efficient code, reducing load times, improving UI responsiveness, managing memory effectively, optimising networking, and continuously monitoring performance, you can ensure that your app not only meets but exceeds user expectations. Click here to find out more about Monedata and our performance-enhancing monetisation strategies.
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