.png)
You’re a UX researcher preparing a major product design and the work requires deep insights into users' interactions with the platform in real-world scenarios.
But from where to start?
Crafting the right questions, structuring observations, and the entire analysis process of contextual inquiry UX can be overwhelming and time-consuming.
This is where ChatGPT revolutionized the UX research process. In this blog we will zoom in on how ChatGPT for contextual inquiry UX saves the day (it sure comes with some challenges too). Find detailed process flow and best tips to use ChatGPT in contextual inquiry.
Let’s explore the possibilities!
What is contextual inquiry in UX?
Contextual inquiry is a user-centered research method based on a master-apprentice model, where researchers observe and interview users in their natural environment. Researchers learn by watching users perform their actual work while asking questions to understand their behavior, challenges, and needs. This method provides richer insights than traditional methods by capturing the full context of how users interact with products in real-world settings.
ChatGPT can be used innovatively to support this research method. Simulating conversations can help generate detailed, insightful questions and scenarios for user interviews, making it a valuable tool for conducting research.
How to make ChatGPT adopt a persona?
Creating a ChatGPT persona improves contextual inquiry in UX by simulating across realistic user scenarios for deeper insights while doing user research. Leveraging ChatGPT effectively defines the persona with demographics, challenges, behavior and goals relevant to the research. Set clear interaction context to ensure response aligns with user expectation. Play well with ChatGPT prompts, such as using task-based questions like, “How would you, as a tech-savvy user, find the settings menu on the app?”
Additionally, ask ChatGPT to generate contextual inquiry questions for real-world scenarios to uncover user challenges and improve product design.
ChatGPT has been increasingly used in UX research, from analyzing qualitative data to generating research questions. Here’s how it can support different UX research methods.
How do you use ChatGPT for contextual inquiry questions?
Here’s the step-by-step process of using ChatGPT for contextual inquiry questions in the UX research process:
1. Generating effective research questions
The first step in conducting contextual inquiry is designing research questions that generate meaningful responses from the user. Instead of asking vague questions, ask about the pain points.
Vague- “What do you think about this feature?”
Specific- “What challenges do you face when using the X feature?”
You should focus on understanding user behavior to gain detailed insight into their real-world interactions. For best results, ask storytelling questions like, “Can you recall the last time you struggled with this app? “What happened?”
2. Refine follow-up questions based on user responses.
Follow-up questions help us understand user responses more deeply.
If a user says, “I often get lost in the navigation,” a good follow-up should be: “Can you elaborate on the specific instance where this happened? What did you try to do next?”
Your follow-up questions should connect well with the current response and focus on giving a detailed view.
3. Ensure neutrality in phrasing
To get authentic feedback, ensure your research question is neutral and unbiased. ChatGPT can help you rephrase the question better.
Avoid asking leading questions; instead, ask, “How frustrating is the checkout process?” or “How would you describe your experience with the checkout process?”
Keep room for a balanced response rather than assuming the experience is negative.
If you're looking to maximize AI’s role in research, here’s a guide on how to use ChatGPT alongside UX research tools.
4. Prepare structural contextual inquiry sessions for better insights.
Beyond generating questions, let ChatGPT assist you in structuring a practical contextual inquiry session. Begin with general questions that state the broad perspective, like: “How do you use this application?” Based on the response, move to specific questions and let ChatGPT generate inquiries like: “Can you walk me through what happened the last time you faced a challenge using X feature?”
5. Automating the analysis
After gathering the responses, you need to extract key themes, summarize the user feedback, and generate insights for design improvement. Doing this manually can take hours—or even days. On the other hand, relying entirely on AI, like ChatGPT, can sometimes lead to skewed results. The best approach is a balance between automation and human judgment.
This is where modern UX research tools like Looppanel come in. Looppanel automates transcription, identifies key themes across multiple interviews, and generates AI-powered summaries—helping you uncover meaningful insights faster, while still keeping you in control.
By using Looppanel, you can save time, reduce manual effort, and ensure your analysis remains accurate and actionable. Book a demo to see for yourself.
How to use ChatGPT for contextual inquiry: Examples
Here are some examples on how can you use ChatGPT for contextual inquiry:
Example 1: Create a comprehensive user persona of shopping app user
Prompt: Create a detailed user persona for a shopping app user. Consider age, location, occasion, lifestyle, styling interest area, personality traits, shopping frequency, preferred product categories, online shopping expectations, and pain points.
Why does this prompt work?
User personas help set the foundation for any design project. Well-constructed ones will help the team align the project with user expectations and make it user-focused.
Example 2: User interview questions to evaluate music app
Prompt: Generate a set of user interview questions to understand a music app's user experience. Focus on elements like ease of navigation, recommendation, and ability to create a playlist.
Why does this prompt work?
This directly targets the key elements of the user experience that are essential for assessing the usability and satisfaction of the music app. Navigation, recommendation, and playlist creation focus on functional and experiential aspects, uncovering surface-level feedback and deeper emotions.
Example 3: Key behavioral pattern to observe contextual inquiry for airline website and app
Prompt: What behavioral patterns should I look for during a contextual inquiry to understand how users navigate an airline website and app in natural settings?
Why does this prompt work?
It identifies specific behaviors that users exhibit while interacting with the application or website, which is the essence of a contextual inquiry. By asking about behavioral shifts, the prompt helps explore deeper how users naturally navigate, not just whether they can use the feature but how they do so. This reveals pain points and areas for improvement.
If you're curious about how ChatGPT can be used for different types of UX research, this breakdown covers it all.
Challenges of using ChatGPT for contextual inquiry
ChatGPT for contextual inquiry in UX streamlines the user research but isn’t sufficient alone. It presents several challenges researchers must address while conducting the UX research process.
1. Difficulty in capturing emotions
Human responses carry emotions, tone, and personal intent, significantly impacting UX research. While ChatGPT analyzes responses to contextual inquiry questions, it cannot interpret nonverbal cues such as hesitation, excitement, happiness, frustration, and similar ones.
2. Biases based on datasets
AI models are trained on vast datasets covering biases from the training data. This can cause biased or irrelevant suggestions when researchers explore how to use ChatGPT for contextual inquiry questions. If researchers rely on biased responses, it will skew the research insights and affect overall decision-making.
3. Linear conversation
Traditional contextual inquiry involves researchers adapting questions based on user responses. However, using ChatGPT for contextual inquiry becomes more challenging because it follows a linear conversation flow and cannot dynamically adjust its questioning strategy based on subtle behavioral shifts, like a human researcher.
4. Lack of real-environment context
ChatGPT is famous for its inability to observe user behavior in their natural environment. For example, the platform cannot perceive subtle cues when used for contextual inquiry. Contextual inquiry relies heavily on real-world interactions, body language, and emotions, which ChatGPT cannot provide.
Tips and best practices for using ChatGPT for contextual inquiry in UX
To maximize results from ChatGPT for contextual UX inquiry, you must put into practice the following tips while remembering ChatGPT limitations:
1. Use ChatGPT to draft and refine contextual inquiry questions
You must ask the right questions to achieve the correct score in contextual inquiry. Poor structure or misleading questions can result in biased or incomplete information. Instead of asking ChatGPT to generate contextual inquiry questions, feed them with background information, user personas, and specific scenarios for your study.
2. Cross-validate the data
ChatGPT prepares responses based on existing data, which differs significantly from real-time user behavior data. If UX researchers rely on this data, there is a high chance of misinterpreting user needs. Always cross-check ChatGPT-generated insights with direct user feedback from interviews, surveys, or usability tests.
You can use ChatGPT to generate an initial idea, not to validate insights. Here, user research tools like Looppanel provide excellent support through AI thematic tagging, which helps UX researchers analyze large volumes of data in a few minutes and with the highest accuracy level.
ChatGPT should work as a complementary tool in contextual inquiry rather than the primary one.
3. Provide specific prompts
You must provide clear, specific, and well-structured prompts to get relevant information from ChatGPT. The answer from ChatGPT will depend on how deep your context is in the way of prompts.
4. Refine user personas
User persona helps researchers understand and empathize with the target audience. You can extract key patterns and pain points by entering qualitative data like interview feedback, surveys, or usability tests into ChatGPT.
For example, ChatGPT can analyze phrases like “I get frustrated when the app takes time to load.”
This AI process helps identify the underlying factors, yet theme tagging is something it’s not excel at. That’s where Looppanel thematic tagging will be of your help.
While ChatGPT distills the insights, Looppanel’s thematic tagging adds precision and clarity by categorizing these traits into relevant themes.
Conclusion
ChatGPT can be a powerful tool for UX researchers who are conducting contextual inquiries. It helps in streamlining the process of generating research questions, structuring sessions and analyzing user responses. While the results offer efficiency and scalability, yet it should be used as a supplementary tool rather than a replacement for direct user observations.
The key to maximizing ChatGPT’s potential lies in crafting precise prompts, validating AI-generated responses with real-world and combining it with other UX research tools like Looppanel for best results.
By integrating AI-driven insights with human expertise, UX researchers can get deeper insights for creating intuitive, user-friendly products.
Request a Demo to learn more about Looppanel.
FAQs
1. How to do user research with ChatGPT?
User research using ChatGPT is not rocket science. Leverage the platform’s ability to generate ideas and text based on user personas. Draft interview questions, design user flows, identify potential pain points, and develop user stories, remembering to validate the outputs with actual user data.
ChatGPT is mainly used as a brainstorming tool to supplement your primary research efforts.
2. How do I ask contextual questions?
When using ChatGPT for contextual inquiry UX, prepare questions encouraging users to share their experience in detail. While asking the contextual questions, your focus should be on open-ended inquiries, be specific, and include background information to set the stage for your question.
3. How to ask better questions to ChatGPT?
While asking questions to ChatGPT, ensure to put detailed prompts. It improves the quality of the responses and bypasses general answers. Refine your question and specify minute details as and where possible. For example:
Generic: “How can I improve my UX research process?”
Well-structured: “How do I use ChatGPT for contextual inquiry UX in mobile app development?”
4. How many participants for contextual inquiry?
One participant per session is sufficient for contextual inquiry, as the method focuses mainly on profound observation and individual interaction with users in their natural environment. However, depending on the project size and complexity, the overall number of contextual inquiry participants can range from 4 to 12.
.svg)
