{"blocks": [{"key": "a1e7fbda", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "1d58057c", "text": "Product team plans to launch a redesigned onboarding flow and needs evidence it increases activation.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "f887e26e", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "d0938b30", "text": "Design an A/B test for the new onboarding. State hypothesis, unit of randomization, key metrics, guardrail metrics, and runtime calculation. If early results show uplift but increased support tickets, how would you decide whether to launch?", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "4e588aef", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "af74d4be", "text": "Address sample size, power, sequential checks, and balancing primary vs. secondary metrics.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}