User research generates enormous amounts of qualitative data. AI transforms hours of analysis into minutes while surfacing insights humans might miss.

Interview Analysis

AI accelerates every stage:

• Transcription: Convert recorded interviews to text with speaker identification
• Thematic Analysis: Automatically identify recurring themes across interviews
• Sentiment Mapping: Track emotional responses throughout conversations
• Quote Extraction: Pull the most impactful quotes organized by theme
• Insight Synthesis: Generate research summaries with supporting evidence

Analyzing at Scale

Prompt Templates for Research

• "Analyze these 10 interview transcripts. Identify the top 5 themes, supporting quotes for each, and any contradictions between participants."
• "Categorize these 200 survey open-text responses into themes. For each theme, provide the percentage of respondents, sentiment, and representative quotes."
• "Analyze this set of app reviews. What are the top pain points, most-loved features, and feature requests?"

Best Practices

• Always validate AI insights against the raw data
• Use AI as an accelerator, not a replacement for human judgment
• Combine AI analysis with your domain expertise
• Keep research participants' privacy in mind when using AI tools
• Document your AI-assisted methodology for transparency