{"blocks": [{"key": "a310ac28", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "c768b68b", "text": "Leadership wants to use the '% of users with contacts synced' metric to drive growth and evaluate experiments.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "5e44761b", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "ef95ad99", "text": "How would you position this percentage metric as a meaningful goal for stakeholders? Describe a framework to set a realistic 2025 target for this metric. During an A/B test the percentage increases but the true-north business metric does not—how would you investigate and respond? If an A/B test is infeasible, what causal-inference approach(es) would you use to estimate the impact of contact syncing?", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "77d2cd06", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "dfee5623", "text": "Think metric hierarchy, historical trends, benchmarking, guardrail checks, causal inference methods like DID or propensity matching.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}