A product team wants to add more options to an existing user flow. Design an experiment to determine whether the change improves the product, and explain how you would interpret the result if engagement with the new options rises but completion of the overall flow falls. ### Constraints & Assumptions - The exact product surface and option types are intentionally unspecified. - Randomization is feasible at the user level, but users may return to the flow more than once. - The team wants a launch recommendation, not merely a statistical-significance calculation. ### Clarifying Questions to Ask - What user problem is the additional choice intended to solve? - What is the current flow, and where can extra options introduce friction or confusion? - Is the desired outcome immediate completion, downstream quality, retention, revenue, or another decision metric? - Can users switch devices, see both variants, or affect one another? - How long does the relevant outcome take to mature? ### What a Strong Answer Covers - A testable hypothesis, one primary decision metric, and guardrails for friction, quality, reliability, and longer-term outcomes. - User-level randomization, stable assignment, exposure logging, eligibility rules, and analysis based on assigned treatment. - Sample-size and duration reasoning tied to a meaningful detectable effect and the outcome's observation window. - Checks for sample-ratio mismatch, instrumentation errors, novelty, repeated exposure, and heterogeneous treatment effects. - Interpretation of the engagement/completion trade-off in terms of the original product objective rather than metric movement alone. - A launch, iterate, or stop recommendation with explicit uncertainty and follow-up evidence. ### Follow-up Questions 1. How would you handle users who never reach the part of the flow where the options appear? 2. When would session-level randomization be preferable or dangerous? 3. How would you investigate a positive effect for new users and a negative effect for returning users? 4. What would you do if completion falls immediately but downstream outcome quality improves?