{"blocks": [{"key": "7d92869b", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "9a381644", "text": "Online experimentation and causal analysis for a consumer app.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "57ada11b", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "2f3d3e98", "text": "An A/B test changed a call-to-action button from green (control) to red (treatment) and retention dropped. Describe the diagnostics you would run to decide whether uneven traffic allocation or other experiment-quality issues drove the result. You are asked to measure the causal impact of receiving negative reviews on a merchant’s coupon repurchase rate. Outline the data you need and the methodology you would use to obtain an unbiased estimate.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "afe86a10", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "185d2b5f", "text": "Think about sample-ratio mismatch checks, covariate balance, time windows, difference-in-differences, matching/propensity scores, or holdout experiments.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}