IT & Software

To identify patterns and trends

Identify Patterns and Trends in User Interviews with This ChatGPT Prompt

What This Prompt Does

Synthesizes qualitative interview data into actionable insights by identifying recurring themes across multiple user responses.

Surfaces user expectations, frustrations, and workarounds related to specific product features.

Provides a table summarizing each interviewee’s response per question for easy comparison and alignment.

Reveals emotional tone and behavioral patterns, helping teams validate assumptions or uncover hidden issues.

Reduces manual synthesis time for researchers and stakeholders reviewing transcripts.

Tips

Pre-clean the transcripts to remove filler words, unrelated digressions, and interviewer commentary. Condensed transcripts work best.
Use this prompt after conducting 5–10 user interviews to spot repeatable patterns and saturation points.
Ensure each interview includes consistent, well-phrased questions so that tabular output is cleanly structured.
Ask ChatGPT to cluster feedback by sentiment (positive/neutral/negative) or theme (usability, trust, onboarding, etc.) for deeper insight.
If multiple user types are involved, group the analysis per persona or segment to compare experience differences.

Prompt

Read the 5 condensed interview transcripts pasted below and identify the common patterns and trends in user experiences based on them. The product X does [list the features] and is designed for [describe the users]. Summarize the patterns and trends into bullet points. Also, share summaries of user responses to each question as a tabular column.

How To Use The Prompt

Replace the placeholders with details about your product, feature, and user type:

[list the features]: What the product enables users to do.
[describe the users]: User roles, needs, and context (e.g., remote developers, college students managing finances, etc.).

Example Prompt
"Read the 5 condensed interview transcripts pasted below and identify the common patterns and trends in user experiences based on them. The product X is a digital journaling app with features like voice notes, emotion tagging, calendar integration, and AI summaries. It is designed for busy professionals who want to maintain a mindfulness practice. Summarize the patterns and trends into bullet points. Also, share summaries of user responses to each question as a tabular column."

Example Input

#PRODUCT CONTEXT

Product: Reflectly AI — a journaling app
Features: Daily mood check-ins, AI-powered reflections, voice-to-text entries, insights dashboard
Target users: Professionals aged 25–40 aiming to reduce stress and track emotional patterns

#INTERVIEW QUESTIONS

What made you start using Reflectly AI?
How do you usually interact with the app in your day-to-day life?
What features do you use most often, and why?
Have you experienced any frustrations or challenges while using the app?
If you could change or improve one thing, what would it be?

#TRANSCRIPTS (5 users, condensed)
(Example summaries pasted below in real use)

Example Output

Common Patterns and Trends (Bulleted Summary)

Most users started journaling to manage anxiety or build daily mindfulness habits.
Voice-to-text is favored during busy moments but struggles with accuracy in noisy environments.
Users love mood-tracking visualizations but feel AI-generated summaries are sometimes too generic.
Several noted difficulty locating past journal entries—suggesting need for better search/tags.
Everyone appreciated reminders but wanted customization based on time of day and work rhythm.
Privacy concerns came up around syncing data to the cloud; users wanted offline options.

User Response Summary Table

Question	User 1	User 2	User 3	User 4	User 5
Why did you start using Reflectly AI?	To manage anxiety after work	Suggested by therapist	Daily mood tracking goal	For digital self-reflection	Wanted a healthier nighttime routine
How do you interact with the app daily?	Mornings during commute	Before bed	Randomly throughout the day	2× daily (morning/evening)	Mostly in the evening after dinner
Most used features & why	Voice notes—hands-free convenience	Mood check-ins—helps notice patterns	Voice + AI summary—time-saving	Dashboard view—motivating visual insights	Tags & reminders—helps stay consistent
Challenges or frustrations	AI summaries feel generic	Hard to search old entries	Voice not accurate when noisy	Can’t edit moods once logged	Entry reminders not adjustable
Desired improvements	More personalized insights	Smarter search with filters	Better voice transcription	Undo mood logging	More flexible reminder options

Additional Information

This prompt is a go-to tool for UX researchers, product managers, or founders who want to mine qualitative interviews for insights without hours of manual synthesis.

Ideal post-research prompt for usability tests, generative interviews, or customer discovery calls.
Can be paired with transcription tools like Otter.ai or Descript for seamless workflows.
Use follow-up prompts like “Cluster these themes into usability, emotional, and value-based insights” for deeper framing.

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