Product design question

How will you build a travel recommendation product for an online travel giant?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Product design for a personalization-heavy recommendation product, requiring clear signals, ranking logic, and trust-building.

Define the target user and moment: a traveler in the early research phase deciding where and what to do, not someone already booked.
Identify the input signals available: past bookings, searches, saved items, and stated preferences like budget or travel style.
Design the recommendation logic: rank destinations and activities by similarity to past behavior plus trending signals from similar traveler segments.
Address trust and transparency: show why a recommendation appeared, e.g. 'because you saved beach destinations,' since opaque recommendations get ignored.
Define success as click-through and save rate on recommended items, and downstream booking conversion, with a diversity guardrail so recommendations don't get stuck in a narrow loop.

Grounds recommendations in concrete signals, past bookings and saves, rather than a vague 'personalized for you' claim.
Explains the recommendation reasoning to the user, a known driver of trust and engagement in recommendation products.
Names a diversity or filter-bubble guardrail, since travel recommendations that never surface anything new lose value over time.

Designing the recommendation logic with no mention of cold-start users who have no history yet.
No guardrail against a narrow feedback loop, where recommendations converge on the same few destinations.

How would you handle a brand-new user with no booking history?
How would you balance personalization against surfacing genuinely new destinations?