Analyzing the data from your longitudinal playtest

Longitudinal playtesting generates invaluable insights into player behavior, engagement patterns, and game design effectiveness over time. However, the volume of data – which could include survey responses, in addition to audio data from players and many hours of gameplay footage – requires a structured approach to analysis.

Before diving into the data, establish clear research objectives and key performance indicators (KPIs). These might include metrics like player retention rates, engagement with specific game mechanics, progression speed, or difficulty curves. To optimize viewing time, consider using accelerated playback speeds (1.5x or 2x) for sections with routine gameplay while maintaining normal speed for critical moments or new feature interactions.

Implement a mixed-methods approach to data analysis:

• Quantitative metrics: Track completion rates of predetermined checkpoints, time spent on specific features, and progression patterns

• Qualitative observations: Document player emotions, verbalized thoughts, and behavioral patterns

• Look for trends across sessions and between different players

• Examine how player behavior evolves over multiple sessions

Analyzing longitudinal data can be quite time-intensive and tricky. If you face any challenges, we’re happy to help. Our experienced research operations team can assist you at every stage from analyzing the videos to identifying trends within the data, culminating in actionable insights that can drive meaningful improvements in your game design. Book a session with us today!

Understanding player drop-offs in longitudinal studies

In longitudinal playtesting, player attrition is a natural and expected part of the research process. Playtest participants may not complete all scheduled sessions for various reasons. This phenomenon is particularly visible in longitudinal studies where results are typically published daily after the second day of gameplay.

Common reasons for participant dropout include:

• Schedule conflicts or time constraints

• Forgetting to complete scheduled sessions

• Technical issues or game bugs affecting player motivation

• Natural decline in engagement or interest

Understanding player churn in playtesting can actually provide valuable insights into potential retention issues in your game. By analyzing when and why players drop out during the testing phase, you can identify potential engagement barriers and address them before launch. This makes player churn an opportunity to strengthen your game's retention mechanics and overall player experience. For this reason, we recommend paying close attention to patterns in player dropout – they often highlight important areas for improvement in game design and player experience.