Strategy question
Would you build a travel product on Instagram?
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
Start a mock interview on this question · Mock interview from a job description
What this question tests
Whether you can judge a market entry decision on mission fit, competitive reality and resourcing, not just enthusiasm for the idea.
How to approach it
- Clarify what travel product means here: trip inspiration, itinerary planning or booking, since each implies a different build.
- State Instagram's core strength, visual discovery through Reels and Explore, and check how much travel content already exists organically.
- Map the competitive field: Google Travel, TripAdvisor and Airbnb already own planning and booking.
- Weigh build versus partner versus stay out, given Meta's mixed record on vertical bets like Marketplace.
- Recommend a narrow wedge, travel inspiration and creator monetization, that extends what Instagram already does well.
- Define a success metric such as saves and shares on travel content or creator earnings from travel posts.
What a strong answer includes
- Separates inspiration, Instagram's real strength, from transaction, where OTAs already win, and commits only to the former.
- Uses a believable signal, for example travel-tagged Reels already earning high saves, to justify doubling down instead of building a new surface.
- Flags cannibalization risk if users leave the app to book elsewhere, hurting Meta's ad revenue.
Common mistakes
- Jumping to a full booking flow without checking fit with Instagram's ad-supported, high-frequency engagement model.
- Ignoring that travel bookings are low-frequency, which clashes with a feed business built on daily visits.
Likely follow-up questions
- How would you measure whether this cannibalizes ad revenue?
- What would make you kill this feature six months after launch?
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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