Product design question

Consider you are assigned to find the best Sort option for product list pages. How would you solve this problem?

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 and experimentation thinking for a seemingly simple but high-impact ranking feature.

Clarify the goal, is the current default sort suboptimal for conversion, relevance, or both, and for which product categories.
Identify sort options users need, price, customer rating, relevance or best match, and newest arrivals, since different shopping intents need different defaults.
Analyze current behavior, which sort options users manually switch to most often, signaling the default may be wrong for many.
Propose a smarter default, a relevance-based 'Best Match' blending rating, price competitiveness, and past conversion data, rather than a single static field.
Test the hypothesis, an A/B test comparing the new default sort against the current one on conversion rate and bounce rate.
Define success metrics, click-through rate on the first page of results and overall category conversion rate.

Uses actual user behavior data, which sort option users manually switch to, as the starting signal rather than guessing.
Proposes a blended relevance algorithm instead of assuming a single field, like price, is universally best.
Designs a proper A/B test to validate the hypothesis rather than shipping a new default sort untested.
Sets metrics tied to the real business goal, conversion rate, not just engagement with the sort control itself.

How would you personalize sort order per user.
What would you do if the new sort improves conversion but hurts diversity of results shown.
How would you test this without hurting revenue during the experiment.