User Experience Research Techniques for Game Development

User experience surveys are often underestimated. Too many teams reduce them to a checkbox exercise - a few questions thrown in post-launch, a quick look at average scores, and then back to development. But that approach leaves immense value on the table. A UX survey is not just a feedback form; it’s a structured method for learning what users think, feel, and need at scale- a design artifact in its own right. Designing an effective UX survey starts with a deeper commitment to methodology. Every question must serve a specific purpose aligned with research and product objectives. This means writing questions with cognitive clarity and neutrality, minimizing effort while maximizing insight. Whether you’re measuring satisfaction, engagement, feature prioritization, or behavioral intent, the wording, order, and format of your questions matter. Even small design choices, like using semantic differential scales instead of Likert items, can significantly reduce bias and enhance the authenticity of user responses. When we ask users, "How satisfied are you with this feature?" we might assume we're getting a clear answer. But subtle framing, mode of delivery, and even time of day can skew responses. Research shows that midweek deployment, especially on Wednesdays and Thursdays, significantly boosts both response rate and data quality. In-app micro-surveys work best for contextual feedback after specific actions, while email campaigns are better for longer, reflective questions-if properly timed and personalized. Sampling and segmentation are not just statistical details-they’re strategy. Voluntary surveys often over-represent highly engaged users, so proactively reaching less vocal segments is crucial. Carefully designed incentive structures (that don't distort motivation) and multi-modal distribution (like combining in-product, email, and social channels) offer more balanced and complete data. Survey analysis should also go beyond averages. Tracking distributions over time, comparing segments, and integrating open-ended insights lets you uncover both patterns and outliers that drive deeper understanding. One-off surveys are helpful, but longitudinal tracking and transactional pulse surveys provide trend data that allows teams to act on real user sentiment changes over time. The richest insights emerge when we synthesize qualitative and quantitative data. An open comment field that surfaces friction points, layered with behavioral analytics and sentiment analysis, can highlight not just what users feel, but why. Done well, UX surveys are not a support function - they are core to user-centered design. They can help prioritize features, flag usability breakdowns, and measure engagement in a way that's scalable and repeatable. But this only works when we elevate surveys from a technical task to a strategic discipline.

Your research findings are useless if they don't drive decisions. After watching countless brilliant insights disappear into the void, I developed 5 practical templates I use to transform research into action: 1. Decision-Driven Journey Map Standard journey maps look nice but often collect dust. My Decision-Driven Journey Map directly connects user pain points to specific product decisions with clear ownership. Key components: - User journey stages with actions - Pain points with severity ratings (1-5) - Required product decisions for each pain - Decision owner assignment - Implementation timeline This structure creates immediate accountability and turns abstract user problems into concrete action items. 2. Stakeholder Belief Audit Workshop Many product decisions happen based on untested assumptions. This workshop template helps you document and systematically test stakeholder beliefs about users. The four-step process: - Document stakeholder beliefs + confidence level - Prioritize which beliefs to test (impact vs. confidence) - Select appropriate testing methods - Create an action plan with owners and timelines When stakeholders participate in this process, they're far more likely to act on the results. 3. Insight-Action Workshop Guide Research without decisions is just expensive trivia. This workshop template provides a structured 90-minute framework to turn insights into product decisions. Workshop flow: - Research recap (15min) - Insight mapping (15min) - Decision matrix (15min) - Action planning (30min) - Wrap-up and commitments (15min) The decision matrix helps prioritize actions based on user value and implementation effort, ensuring resources are allocated effectively. 4. Five-Minute Video Insights Stakeholders rarely read full research reports. These bite-sized video templates drive decisions better than documents by making insights impossible to ignore. Video structure: - 30 sec: Key finding - 3 min: Supporting user clips - 1 min: Implications - 30 sec: Recommended next steps Pro tip: Create a library of these videos organized by product area for easy reference during planning sessions. 5. Progressive Disclosure Testing Protocol Standard usability testing tries to cover too much. This protocol focuses on how users process information over time to reveal deeper UX issues. Testing phases: - First 5-second impression - Initial scanning behavior - First meaningful action - Information discovery pattern - Task completion approach This approach reveals how users actually build mental models of your product, leading to more impactful interface decisions. Stop letting your hard-earned research insights collect dust. I’m dropping the first 3 templates below, & I’d love to hear which decision-making hurdle is currently blocking your research from making an impact! (The data in the templates is just an example, let me know in the comments or message me if you’d like the blank versions).

People often say what they think they should say. I had a great exchange with 👋 Brandon Spencer, who highlighted the challenges of using qualitative user research. He suggested that qual responses are helpful, but you have to read between the lines more than you do when watching what they do. People often say what they think they should be saying and do what they naturally would. I agree. Based on my digital experiences, there are several reasons for this behavior. People start with what they know or feel, filtered by their long-term memory. Social bias ↳ People often say what they think they should be saying because they want to present themselves positively, especially in social or evaluative situations. Jakob's Law ↳ Users spend most of their time on other sites, meaning they speak to your site/app like the sites they already know. Resolving these issues in UX research requires a multi-faceted approach that considers what users say (user wants) and what they do (user needs) while accounting for biases and user expectations. Here’s how we tackle these issues: 1. Combine qualitative and quantitative research We use Helio to pull qualitative insights to understand the "why" behind user behavior but validate these insights with quantitative data (e.g., structured behavioral questions). This helps to balance what users say with what they do. 2. Test baselines with your competitors Compare your design with common patterns with which users are familiar. Knowing this information reduces cognitive load and makes it easier for users to interact naturally with your site on common tasks. 3. Allow anonymity  Allow users to provide feedback anonymously to reduce the pressure to present themselves positively. Helio automatically does this while still creating targeted audiences. We also don’t do video. This can lead to more honest and authentic responses. 4. Neutral questioning We frame questions to reduce the likelihood of leading or socially desirable answers. For example, ask open-ended questions that don’t imply a “right” answer. 5. Natural settings Engage with users in their natural environment and devices to observe their real behavior and reduce the influence of social bias. Helio is a remote platform, so people can respond wherever they want. The last thing we have found is that by asking more in-depth questions and increasing participants, you can gain stronger insights by cross-referencing data. → Deeper: When users give expected or socially desirable answers, ask follow-up questions to explore their true thoughts and behaviors. → Wider: Expand your sample size (we test with 100 participants) and keep testing regularly. We gather 10,000 customer answers each month, which helps create a broader and more reliable data set. Achieving a more accurate and complete understanding of user behavior is possible, leading to better design decisions. #productdesign #productdiscovery #userresearch #uxresearch