{"blocks": [{"key": "b1431555", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "5e147959", "text": "Deciding whether to launch and how to evaluate a new Group Call feature for a communication app.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "deed3bdb", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "63fc8d46", "text": "Using only the existing usage table, how would you decide if the product needs a Group Call feature? If additional resources were available, what extra data or research would you request and why? How would you set an upper limit on the number of participants in a group call? Define and justify a threshold. Design an A/B test for the Group Call feature. Detail hypothesis, metrics, experiment setup, sample-size and runtime calculations, guardrails, and potential pitfalls. Nine months after launch, what metrics and analyses would you use to measure the feature’s success? If there is no measurable impact on overall company metrics, is that good or bad? Should the feature be kept? Explain. Discuss trade-offs between optimizing ecosystem-level metrics versus focusing on users with poor call experiences. Identify likely post-launch drop-off points in the Group Call funnel and propose mitigations.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "c36da284", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "e0c68431", "text": "Think metric definitions, leading vs. lagging indicators, experiment design best practices, and user-level diagnostic analyses.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}