Synthesize AI research by coding evidence before naming themes
Turn qualitative AI-user research into defensible themes by moving from evidence to codes to themes.
The move: code what happened before you summarize what it means. Thematic analysis creates rigor by slowing down the leap from raw conversation to strategic conclusion. A code is a short label for something important in the data. A theme is a broader pattern that organizes multiple codes. That difference keeps product teams from turning one vivid quote into an entire roadmap. For AI research, the distinction is critical because complaints are often overloaded. “It was wrong” might actually mean wrong data, missing context, weak prompting, poor copy, or a confidence cue that misled the user. Coding specific observations lets…
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