10 Essential AI Prompt Frameworks for UX Researchers to Master

By Philip Burgess | UX Research Leader

User experience (UX) researchers face growing challenges as AI tools become part of their daily workflow. Crafting effective AI prompts can unlock powerful insights, speed up analysis, and improve design decisions. Yet, many UX researchers struggle to write prompts that deliver clear, relevant, and actionable results. Mastering the right AI prompt frameworks can transform how you gather and interpret user data.

This post explores 10 essential AI prompt frameworks every UX researcher should know. These frameworks help you structure prompts to get precise answers, generate ideas, analyze feedback, and simulate user behavior. Whether you are new to AI or want to sharpen your prompt skills, these frameworks will boost your research quality and efficiency.

1. AI Prompt: Context-Setting Framework

Start your prompt by clearly defining the context. This framework ensures the AI understands the background and scope of the task.

Example:

"Imagine you are a UX researcher analyzing a mobile app for fitness tracking. Users report difficulty finding workout history. Suggest three ways to improve navigation."

This framework helps the AI focus on relevant details and avoid generic responses.

2. Role-Playing Framework

Assign a role to the AI to simulate expert perspectives or user personas. This approach generates insights from specific viewpoints.

Example:

"Act as a first-time user of an e-commerce website. Describe your experience checking out and identify any pain points."

Role-playing prompts reveal user emotions and expectations that might be missed in traditional surveys.

3. Step-by-Step Reasoning Framework

Break down complex questions into smaller steps. This framework guides the AI to provide detailed, logical answers.

Example:

"List the steps a user takes to complete a purchase on a website. For each step, identify potential usability issues."

This method uncovers problems at each stage of the user journey.

4. Comparative Analysis Framework

Ask the AI to compare two or more options, designs, or features. This framework supports decision-making by highlighting pros and cons.

Example:

"Compare the checkout process of Website A and Website B. Which one offers a smoother experience and why?"

Comparisons help prioritize design improvements based on user impact.

5. Data Summarization Framework

Use this framework to condense large volumes of user feedback or research data into key themes.

Example:

"Summarize the main complaints from 100 user reviews about a travel app."

Summaries save time and reveal common patterns quickly.

6. Hypothesis Generation Framework

Encourage the AI to propose hypotheses based on user data or observed behaviors.

Example:

"Based on low engagement rates in the app, suggest possible reasons why users drop off after the onboarding screen."

Hypotheses guide further testing and validation.

7. Scenario Simulation Framework

Create hypothetical user scenarios to explore how users might interact with a product under different conditions.

Example:

"Simulate a user trying to book a flight on a website during a high-traffic sale event. Identify potential usability challenges."

Simulations help anticipate issues before real users encounter them.

8. Sentiment Analysis Framework

Ask the AI to analyze the tone and sentiment behind user comments or reviews.

Example:

"Analyze the sentiment of these 50 customer feedback entries and categorize them as positive, neutral, or negative."

Sentiment insights inform emotional responses and satisfaction levels.

9. Question Refinement Framework

Use this framework to improve the clarity and focus of your research questions or survey prompts.

Example:

"Rewrite this survey question to make it clearer and less biased: 'Do you find the app difficult to use?'"

Clear questions lead to more reliable data.

10. Idea Generation Framework

Leverage AI to brainstorm new features, design elements, or research methods.

Example:

"Suggest five innovative features that could enhance user engagement in a meditation app."

Idea generation sparks creativity and expands possibilities.