{"blocks": [{"key": "8843deb6", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "a02447d8", "text": "A fintech app A/B-tested a new Spend-Tracker feature. Test and Control data are split into High-Income and Non-High-Income segments, with metrics such as average revenue, total revenue, profit, and acquisition cost.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "401a1b15", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "eea2f1bc", "text": "Given the T/C metrics for each segment, how would you decide whether to launch the Spend-Tracker? State the factors, calculations, and thresholds you’d use. Which two or three metrics would you prioritize and why? How would you interpret divergent results between High-Income and Non-High-Income users? What additional analyses or data would you request before final launch?", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "30e7a203", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "e410b6ba", "text": "Compare relative lift vs. cost, test for statistical significance, check segment interaction effects, and weigh long-term LTV against acquisition spend.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}