Supercharge Your Tree Testing Efficiency with These Top AI Prompts
- Philip Burgess
- 3 days ago
- 3 min read
By Philip Burgess | UX Research Leader
Tree testing is a powerful method to evaluate the structure of a website or app by testing how easily users can find information. Yet, setting up effective tree tests and analyzing results can be time-consuming and complex. Over the past year, I’ve explored how AI can simplify this process, making tree testing faster and more insightful. In this post, I’ll share the best AI prompts that helped me improve my tree testing workflow, from designing tests to interpreting data.
Top AI Prompts: Designing Clear and Focused Tree Tests
Creating a tree test starts with defining the right tasks and organizing the content hierarchy. AI can help generate clear, user-friendly prompts that guide participants without confusion.
Here are some AI prompts I found effective for designing tree tests:
Generate simple task descriptions for testing a website’s navigation
Example prompt: “Write 5 clear and concise tasks for testing the navigation of an e-commerce website selling outdoor gear.”
Suggest improvements for ambiguous task wording
Example prompt: “Rewrite this tree test task to make it easier to understand: ‘Find where to update your payment method.’”
Create alternative task phrasings to test different user interpretations
Example prompt: “Provide three different ways to ask users to find the ‘return policy’ page.”
Using these prompts, I quickly developed tasks that matched real user goals and avoided jargon. This helped participants focus on navigation rather than decoding confusing instructions.
Generating Realistic User Scenarios
Tree testing works best when tasks reflect actual user needs. AI can simulate user personas and scenarios to enrich your test design.
Try prompts like these:
Create user personas with specific goals related to website navigation
Example prompt: “Describe a user persona who frequently shops for camping equipment and values quick access to product reviews.”
Write short scenarios that explain why a user would look for certain information
Example prompt: “Write a scenario where a user wants to find the customer support contact after receiving a damaged product.”
These prompts helped me build context around tasks, making tests feel more natural and relevant. When participants understand the “why” behind a task, their navigation choices become more authentic.
Analyzing Tree Test Results with the Top AI Prompts
After collecting data, interpreting it can be overwhelming. AI can assist by summarizing patterns and highlighting problem areas and help with the top AI prompts.
Useful prompts include:
Summarize common navigation paths and identify where users get stuck
Example prompt: “Analyze this tree test data and list the most frequent paths users took, noting where they abandoned the task.”
Suggest possible reasons for low success rates on specific tasks
Example prompt: “Explain why users might struggle to find the ‘shipping information’ page based on this tree structure.”
Recommend changes to improve navigation based on test results
Example prompt: “Propose three changes to the website’s menu structure to reduce confusion in the checkout process.”
Using AI to interpret results saved me hours of manual analysis. It also provided fresh perspectives on why users behaved a certain way, which helped me prioritize fixes.
Creating Reports and Sharing Insights
Communicating findings clearly is essential to get buy-in from stakeholders. AI can draft concise reports and highlight key insights.
Try these prompts:
Write a summary of tree testing findings for a non-technical audience
Example prompt: “Summarize the main results of a tree test on a retail website, focusing on user difficulties and suggested improvements.”
Generate bullet points of actionable recommendations based on test data
Example prompt: “List five clear recommendations to improve website navigation after analyzing tree test results.”
Create engaging presentation slides content for sharing with the team
Example prompt: “Draft slide content explaining the tree testing process and key findings in simple language.”
These prompts helped me produce polished reports quickly, making it easier to share insights and get support for changes.
Tips for Using AI Prompts Effectively in Tree Testing
Be specific with your prompts. The more detail you provide, the better the AI output matches your needs.
Iterate and refine. Don’t expect perfect results on the first try. Adjust prompts based on the AI’s responses.
Combine AI with your expertise. Use AI as a tool to speed up tasks, but apply your judgment to ensure quality.
Keep user focus. Always design prompts that prioritize real user behavior and goals.
Final Thoughts on AI and Tree Testing
Integrating AI prompts into tree testing transformed how I approach this research method. It made designing, analyzing, and reporting faster and more effective. If you want to improve your tree testing process, start experimenting with AI prompts tailored to your project’s needs.
Try crafting your own prompts based on the examples here and watch how AI can support your work. The key is to keep tasks clear, scenarios realistic, and analysis insightful. With these tools, you can build navigation structures that truly help users find what they need.
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