retention

Separate new-user and new-item problems, design a useful first session, and test whether early relevance survives beyond onboarding.

Repeat items are predictable; meal plans are a nice demo. Start with replenishment, expose ordering to outside assistants with one confirmation, and keep household preferences inside your own app.

Benchmark gains do not cover what users built around the old model. Measure the behaviour that changed, give people a bridge and decide in advance when the old model goes.

Matching free is tempting and often ruinous when every use costs money. The interviewer wants a segmented response that protects the customers you can keep, the margin you need, and the value only you deliver.

Figma reported exactly this drop, driven by AI hosting costs, and moved to enforce credit limits. Find which features and customers cost the margin, meter heavy use, and keep margin only where AI does not buy retention.

AI features are unusually good at producing engagement that is actually friction. The question tests whether you can tell the two apart in the data.

Messages sent and time spent reward an assistant that wastes users' time. Choose a metric tied to tasks users come back to finish, and pair it with quality and cost.

Enterprise deals stall on this question. 'The provider doesn't train on our data' answers one of five different questions. The interviewer wants the full set and a clear answer to each.