What do you do when user research data contradicts your assumptions?

1 Acknowledge your biases

The first step is to recognize that you are not a neutral observer, but a human being with your own perspectives, preferences, and preconceptions. These can affect how you frame your research questions, interpret your data, and validate your solutions. You may also have a tendency to confirm your existing beliefs and ignore or dismiss evidence that contradicts them. This is called confirmation bias, and it can lead to poor decisions and outcomes. To avoid this trap, you need to be aware of your own biases and challenge them with data and feedback from diverse sources.

2 Revisit your problem statement

The next step is to revisit your problem statement and make sure it is clear, specific, and aligned with your user research goals. A problem statement is a concise description of the issue you are trying to solve, the context in which it occurs, and the impact it has on your users. It helps you define the scope and direction of your research and design process. If your problem statement is vague, broad, or based on assumptions, you may end up with data that is irrelevant, misleading, or conflicting. To refine your problem statement, you need to ask yourself: Who are your users? What are their needs, goals, and pain points? How does your product address them? How do you measure success?

3 Analyze your data critically

The third step is to analyze your data critically and objectively, without jumping to conclusions or cherry-picking the results that support your assumptions. You need to look at the data from different angles, identify patterns and outliers, and compare and contrast different sources and methods. You also need to consider the quality, reliability, and validity of your data, and account for any limitations, biases, or errors that may have affected your collection or interpretation. To analyze your data critically, you need to ask yourself: What does the data tell you? What does it not tell you? How confident are you in the data? How does it relate to your problem statement and research questions?

4 Embrace uncertainty and learning

The fourth step is to embrace uncertainty and learning as part of your user research process. You need to accept that user research data is not a definitive answer, but a source of insight and inspiration that can help you explore and test different solutions. You also need to acknowledge that user research data is dynamic and evolving, and that you may need to revisit or revise your assumptions, hypotheses, or ideas as you learn more about your users and their context. To embrace uncertainty and learning, you need to ask yourself: What are the assumptions or hypotheses that you are testing? How do you validate or invalidate them with data? What are the new questions or opportunities that emerge from the data?

5 Communicate your findings effectively

The fifth step is to communicate your findings effectively to your stakeholders, team members, and clients. You need to present your data in a clear, concise, and compelling way that highlights the key insights, implications, and recommendations for your product. You also need to provide context, evidence, and rationale for your findings, and address any questions, doubts, or objections that may arise. To communicate your findings effectively, you need to ask yourself: Who are you communicating to? What are their expectations, interests, and concerns? How do you tailor your message and format to suit them? How do you invite feedback and collaboration?

6 Iterate and improve your product

The final step is to iterate and improve your product based on your user research data and feedback. You need to use your data to inform your design decisions, prioritize your features, and evaluate your outcomes. You also need to keep testing and refining your product with your users, and measure its impact and value. To iterate and improve your product, you need to ask yourself: How do you translate your data into actionable steps? How do you prioritize and implement your changes? How do you measure and report your progress and results?

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?