Strategy question
Glean needs input from end users, workspace admins, security teams, Sales, and Success, and those groups often want different things. How would you run customer discovery for a new enterprise AI workflow so that interviews, support tickets, win/loss data, and usage logs turn into a prioritized roadmap instead of a list of anecdotes?
- Glean
- Strategy
- Medium
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What this question tests
Whether you can turn fragmented, multi-stakeholder discovery input into a prioritized roadmap using a repeatable method rather than anecdote collection.
How to approach it
- Set up parallel discovery tracks: structured interviews with end users and admins, a review of support ticket themes, win/loss interview notes from Sales and Success, and usage log analysis.
- Tag every input (interview quote, ticket, win/loss note, usage pattern) against a shared taxonomy of workflow problems, so disparate sources can be compared on the same axis.
- Weight each input by frequency across sources and by business impact (deal-blocking versus nice-to-have), not by how vividly it was described.
- Cross-validate: only promote a theme to the roadmap if it shows up in at least two independent sources, for example both usage logs and win/loss notes.
- Score the validated themes on a reach times impact times cost framework to produce a ranked list.
- Close the loop by sharing the synthesized roadmap and its evidence back to end users, admins, security, Sales, and Success so they see their input reflected.
What a strong answer includes
- Uses a shared taxonomy to make qualitative interview data comparable to ticket and usage data, rather than treating each source separately.
- Requires cross-source validation before a theme becomes a roadmap item, directly preventing anecdote-driven prioritization.
- Names the weighting factors explicitly, frequency and business impact, not just interview intensity.
- Closes the loop with stakeholders, which matters for a lean team relying on continued input from Sales and Success.
Common mistakes
- Treating every stakeholder group's input with equal weight regardless of frequency or business impact.
- No cross-validation step, so a single loud anecdote can end up on the roadmap.
- Not closing the loop with stakeholders, which erodes future willingness to share input.
Likely follow-up questions
- How would you handle a security concern that appears in only one source but is high severity?
- What would you do if usage data and interview feedback point in opposite directions?
- How often would you refresh this synthesis process?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop