How to apply split testing methodology to your mobile games 

A/B testing, also known as split testing, is a crucial tool for mobile game developers and marketers. It’s a methodical process that allows you to compare different variations of your game or marketing campaign to determine what works best. This guide will provide a comprehensive overview on split testing mobile games, including why it’s essential, how to conduct it effectively, and some best practices to follow. 

Table of Contents

What is split testing? 

Split testing is a method used to compare two versions of a mobile game to determine which one performs better. It involves creating two variations of the same game feature (Variant A and Variant B) and then exposing these to different segments of the game’s user base to see which variant drives better outcomes based on predefined metrics. 

Effectively, you are dividing your audience into different groups and exposing them to different versions of your game to see which performs better. You can then collect valuable data and make informed decisions to optimise user engagement, retention, and monetization. 

Why is split testing important for mobile games? 

Split testing allows mobile game developers and marketers to make data-driven decisions, reducing guesswork in mobile game design and development. It helps identify what keeps players engaged, what turns them away, and how to optimise the game for improved overall satisfaction. 

Moreover, A/B testing can help in:

  • Enhancing Player Experience: Understand what keeps players engaged and allows for optimizations that improve overall player satisfaction.
  • Increasing Monetization: Test different monetization strategies to find the most effective approach without disrupting the player experience.
  • Boosting Player Retention: Understand what keeps players returning and use this knowledge to increase long-term engagement.
  • Driving Informed Decisions: Make game development decisions based on concrete data rather than assumptions or industry trends. 

How do you properly conduct split testing for mobile games? 

Effective A/B testing involves several steps from planning to implementation and analysis. Here’s how you can conduct split testing on your mobile game. 

Planning for Mobile Game Testing 

Goal Setting: Identify specific objectives for each test. Whether it’s increasing session length, improving conversion rates, or enhancing user engagement, set clear, measurable goals. 

Hypothesis Formation: Based on the objectives, formulate hypotheses about what changes might lead to better game performance. 

Segmentation: Segment the game’s audience to ensure that test results are relevant and reliable. This involves selecting appropriate player groups based on behaviour, demographics, and game progression. 

 

Implementation for Mobile Game Testing 

Variant Development: Create the variants for each aspect being tested, ensuring they are distinct enough to measure but consistent with the overall game experience. 

Data Collection: Throughout the testing phase, collect data on player interactions, responses, and overall engagement with each variant. 

Analysis for Mobile Game Testing 

Data Analysis: Analyse the collected data, using the advanced analytical tools provided by T-Plan to discern patterns and outcomes. 

Results Interpretation: Interpret the results in the initial goals and hypotheses context. Look beyond numbers to understand the ‘why’ behind player behaviours.

Recommendations: Develop actionable recommendations for game improvements based on these insights.  

Iteration for Mobile Game Testing 

Implementation of Findings: Assist in implementing the successful elements from the test into the game. 

Continuous Improvement: A/B testing is an ongoing process. Use the learnings from each test to refine future tests, creating a cycle of continuous improvement. 

 

Key Areas for A/B Testing in Mobile Games 

A plethora of opportunities exist for A/B testing within mobile games, spanning various facets of the player experience. From optimising tutorials and onboarding processes to fine-tuning monetisation strategies, each area presents unique challenges and opportunities for experimentation. 

Tutorial and Onboarding Optimisation 

The initial moments of a player’s journey are crucial for setting the tone and laying the foundation for engagement. A/B testing enables developers to experiment with different tutorial formats and onboarding sequences to enhance the First-Time User Experience (FTUE), ultimately leading to improved retention and engagement rates. 

Enhancing User Progression and Gameplay Mechanics 

As players dive deeper into a game, the progression system and gameplay mechanics play a pivotal role in shaping their experience. A/B testing allows developers to iterate on these elements, testing different systems and mechanics to optimise player engagement and long-term retention. 

Monetisation Strategy Optimisation 

Balancing monetisation with player satisfaction is a delicate tightrope that developers must walk. A/B testing empowers developers to experiment with in-app purchases, ad placements, and pricing strategies, finding the optimal balance that maximises revenue without compromising the player experience. 

Social Features and Community Building 

In an increasingly interconnected gaming landscape, social features and community building initiatives can significantly impact player retention and engagement. A/B testing enables developers to gauge the effectiveness of features like leaderboards, guilds, and multiplayer modes, fostering a sense of community and belonging among players. 

Live Operations and Content Updates 

The journey of a mobile game doesn’t end at launch; it’s an ongoing evolution fuelled by live operations and content updates. A/B testing plays a vital role in this ongoing process, allowing developers to measure the impact of events, updates, and limited-time offers on player activity, ensuring that each iteration enhances the overall player experience. 

Once A/B tests are conducted, it’s crucial to analyse the results effectively to inform decision-making. Understanding statistical significance and interpreting test data are essential skills for developers, enabling them to glean valuable insights and refine their strategies through iterative testing. 

 

Advanced A/B Testing Strategies and Best Practices 

Here are some best practices to follow for successful A/B testing in mobile games:

1. Clear Objective and Hypothesis: Start with a clear and specific objective for what you want to achieve with each A/B test. Your hypothesis should be based on data or observations and clearly state the test’s expected outcome.

2. Rigorous Test Design: Ensure that the only difference between the control and test groups is the variable being tested. Choose a statistically significant sample size and run the test for a sufficient duration to collect meaningful data.

3. Focused Segmentation: Segment your audience effectively to ensure the test results apply to the relevant player base. Be careful not to introduce bias through your segmentation or test design.

4. Data-Driven Decision Making: Use robust analytics tools to measure and analyse test results accurately. Look beyond the surface-level numbers and understand the ‘why’ behind the data.

5. Continuous Testing and Learning: A/B testing is not a one-off exercise. Continuously test, learn, and iterate based on previous test outcomes. Embrace failures as learning opportunities.

6. Avoiding Common Pitfalls: Avoid testing too many variables at once or ignoring external factors that could impact your test results. Ensure your results are statistically significant to make reliable conclusions. Do not underestimate the impact of changes. 

 

Why Choose T-Plan for split testing mobile games? 

 

Choosing T-Plan for your mobile game’s A/B testing needs offers several unique advantages. Our platform provides: 

1. Advanced Analytics Platforms: We employ robust analytics platforms that aggregate data from various sources, providing a comprehensive view of player behaviour and game performance. 

2. Customised A/B Testing Frameworks: Our frameworks are designed to be highly flexible, enabling testing a wide range of game elements and scenarios. 

3. Machine Learning Algorithms: By leveraging machine learning algorithms, we can predict player behaviour and preferences, enhancing the accuracy of our A/B tests. 

4. User Experience (UX) Tools: We use UX tools to track how players interact with the game, providing insights into user experience and identifying areas for improvement. 

5. Performance Monitoring: Our monitoring systems provide real-time alerts for any significant changes or anomalies in-game performance during the testing phase. 

 
 

Conclusion: The Future of A/B Testing in Mobile Game Development

Implementing a split testing methodology for mobile games can seem daunting if you’ve never done it before, but with the right approach and tools, it can be a game-changer. It allows developers and marketers to make informed, data-driven decisions that can significantly enhance the player experience and drive success. So, start leveraging the power of A/B testing today and let your mobile game soar to new heights. 

 

Frequently asked questions about split testing in mobile games 

How can split testing be used to evaluate the impact of game narrative or storytelling elements on player engagement? 

Split testing can evaluate narrative impact by presenting different storylines or dialogue variations to player segments. By comparing player engagement metrics between variations, developers can discern which narrative elements resonate most with players, informing future storytelling decisions. 

 

Is there a recommended minimum sample size or duration for conducting split tests in mobile game development? 

There’s no one-size-fits-all answer to this, but too small a sample size won’t reveal statistically significant results. A minimum sample size ensures the reliability of findings, and factors like the variability of metrics, expected effect sizes, and desired confidence levels influence sample size determination. In terms of an ideal duration, tests should run long enough to capture sufficient data across different user segments and game conditions. Tests should last at least several days to account for daily variations in player behaviour and ensure robustness of results.

 

How can split testing be integrated into the iterative development process of live mobile games with ongoing updates and content releases? 

Integrating split testing into live mobile game development requires a structured approach: plan tests aligned with update schedules, segment players effectively, use real-time analytics, adopt agile practices, integrate player feedback, and foster cross-functional collaboration. This ensures ongoing optimization of the player experience and success of updates. 

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