Have you ever wondered how to optimize your mobile app to captivate users and drive success?
In today's competitive mobile app development landscape, learning how to optimize your app is paramount to success.
Constantly optimizing your app for an increased user experience is necessary to attract new users and keep current ones. If you want your users to enjoy the products & recommend them, then you need to identify potential customer issues and fix them.
Sometimes, the problem they are facing may look visually appealing, but for some reason, users don’t click a particular element or don’t complete the full action. In this case, A/B testing is vital in helping you find the reason and solution. This is also called split testing.
Even a small change in your app's user interface can impact the conversion rate. In this MarsDevs guide, we’ll show the importance of A/B testing. So, let’s get started!
A/B testing is a powerful tool for improving the app's marketing strategy. This helps you succeed with your app by improving user retention and conversion rates. It evaluates two variations of an element or two distinct images.
It can expose every segment to a different version of the variable & examine the impact of the variable on user behavior. For example, think you're running an e-commerce app and want to increase conversions for a specific product category.
You decide to target users aged 25–35 who have previously shown interest in athletic wear. Instead of blindly investing in ads, you consider testing two versions of your product page, one with high-resolution images as A & another with detailed product descriptions as B.
After conducting an A/B test, you discover that the version with detailed descriptions leads to a 25% increase in add-to-cart actions. B had a higher conversion rate compared to A, so it makes sense to expose a larger audience to the video with larger text.
What are the benefits of A/B testing?
Historically, A/B testing for mobile apps has been viewed as challenging due to technical difficulties and the necessity of tests across Android and iOS platforms. However, it remains a vital component of app marketing strategies.
The outcomes of A/B tests enable marketers to identify the optimal user experience, enhance app engagement, and deliver better campaign results. It includes,
Two different types of A/B testing are relevant to app marketers and developers. While both operate on the same principle of comparing one variable across a segmented audience, they serve distinct purposes.
In-app A/B testing
In-app A/B testing involves developers assessing the effects of alterations to an app's user experience (UX) and user interface (UI) on metrics such as session duration, user engagement, stickiness, retention rate & lifetime value (LTV).
Additionally, developers will evaluate the impact of specific metrics tailored to the app's functionality.
A/B testing for marketing campaigns
For app marketers, A/B testing serves as a means to enhance the efficiency of marketing initiatives. Through testing, marketers can identify the most impactful ad creatives for user acquisition campaigns, determine the most efficient advertising channels, and craft messaging that can encourage earlier churned users to return.
A/B testing campaigns can elevate app-based installations, optimize conversion rates & effectively retarget the user base.
A/B testing that can be used to optimize both app marketers and campaigns. Before getting started, ask yourself:
A/B testing helps remove speculation and assumptions from app marketing, allowing marketers to concentrate on proven strategies that have been shown to work and avoid wasting resources on tactics that don't yield the desired results.
In mobile applications, you can conduct tests on:
Focusing on a single functionality and showcasing it across multiple versions (not limited to two) is crucial. This approach ensures clear tracking of user preferences. Experiment with diverse keyword combinations and search queries.
For instance, if you're promoting a fitness app, you might experiment with different variations of the keyword "exercise," such as "cardio workouts" or "strength training." This approach allows you to target specific interests within your audience and attract users seeking particular types of fitness activities.
Thorough preparation is key to successful A/B testing, representing nearly half the solution to the problem. Well-executed tests aid in identifying issues, and the more precisely you identify them, the less resources you'll expend on rectifying them.
The following outlines the primary steps for preparing and executing A/B tests for mobile games and applications:
For instance, the ratio of men to women and the number of users with varying iPhone versions should be roughly equal. Allowing substantial differences can lead to highly skewed test results. Also, it's vital to know that a small audience size in A/B testing can offer inaccurate outcomes & hamper your app optimization efforts.
Let’s list the common mistakes in A/B testing:
Disregard external influences on user behavior: User actions frequently shift based on external circumstances, with seasonality serving as a prime example:
Therefore, it's advisable to compare samples from at least one seasonal period. Additionally, prioritize utilizing time frames that align with your primary audience's behavior patterns.
Complete your A/B tests, even if early results are inconclusive—don’t settle for ambiguity: Ensuring accuracy and establishing a high confidence level in your findings requires perseverance and running tests for an adequate duration. Terminating tests prematurely could lead to misleading outcomes, impeding the effectiveness and success of your marketing strategies.
Stick to using the standard A/B test approach: In classic A/B tests, users are evenly divided into each group. However, if you're a tech giant with abundant data, conducting A/B tests incurs testing costs. Throughout the experiment, economically disadvantageous product options may need to be displayed.
Nevertheless, algorithms can allow for adjusting the traffic distribution among options during the experiment. One such algorithm is the Thompson algorithm, which utilizes Bayesian statistics in the context of multi-armed bandits problems.
This algorithm recalculates the winning probabilities for each option at each experiment phase and directs traffic to the highest probability of winning.
As depicted in the illustration, if option A emerges as the winner, we gradually increase the proportion of users assigned to it on the subsequent day. If option A continues to outperform on the third day, its share is further increased.
Eventually, the winning option becomes fully deployed to 100% of users. The Bayesian bandit algorithm adjusts to temporal variations, resulting in time & cost savings.
Remember that A/B testing can be invaluable during mobile app development, especially when crafting your Minimum Viable Product (MVP). It offers a deliberate approach to selecting one version of a specific feature or component within the app.
Upon completing the A/B testing phase, beyond simply analyzing the results, it's essential to leverage other actionable insights by users. This approach yields valuable ideas for subsequent tests and optimizations.
To ensure continued profitability, mobile apps must evolve alongside advancements in mobile device technologies. A/B testing serves as a vital mechanism for achieving this goal. Want help? Contact us at MarsDevs & we will help you with your A/B testing!
FAQ
A/B testing benefits any mobile app seeking to optimize user engagement, conversions, and overall performance. If you're looking to make data-driven decisions, improve user experience & maximize your app's success, A/B testing is a suitable strategy for you.
The key metrics you should focus on during A/B testing include conversion rates, click-through rates, session duration & retention rates. Ultimately, the impact on your app's overall success metrics such as downloads, purchases, or subscriptions.
Examples of successful A/B testing strategies in the industry include testing different app features, UI/UX elements, promotional messaging, pricing strategies, and onboarding processes. For instance, apps have tested variations in app icons, color schemes, button placements, and wording to determine the most effective design for maximizing user engagement and conversions.
