How to use NotebookLM to do real product research (with the prompts)

NotebookLM can do in an afternoon what used to take a research team a week, if you know how to prompt it.

In this episode of Human × Intelligent, we walk through a complete 8-step AI-assisted research workflow using a real Spotify UX interview study as our working example. Eight participants, 60-minute sessions and a set of raw transcripts, turned into personas, empathy maps, Jobs to Be Done analysis, How Might We questions, an opportunity matrix and a full synthesis report.

Every step includes the exact prompt to paste into NotebookLM. No vague instructions. No, just ask AI to help you. Real prompts, real frameworks, real output.

What you'll learn:

How to orient NotebookLM before any analysis begins (and why this matters)
How to build 3 grounded user personas, including a tension map that shows where their needs conflict
How to create empathy maps per persona using actual participant language
How to identify functional, emotional and social Jobs to Be Done and rank those that are most underserved
How to generate and prioritise How Might We questions that open up real solution space
How to build a feature opportunity matrix and effort vs impact quadrant
How to affinity cluster raw insights into a 3-level observation → insight → opportunity hierarchy
How to generate an executive summary, full research report and stakeholder presentation outline

All 16 prompts are included in the show notes as a ready-to-use guide.

This workflow applies to any qualitative research: user interviews, usability test notes, support tickets, survey responses. If you can put it in a document, NotebookLM can help you make sense of it.

Show Notes:

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Hosted by Madalena Costa · Senior product designer and AI systems strategist

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