Focus on the long-term: It's better for users and business
Hohnhold, O'Brien and Tang describe a problem with A/B testing at scale. Short-term results from experiments are easy to measure but often fail to predict what happens in the long run, after a change ships and users adjust their behaviour. The central problem is estimating long-term user impact while still deciding quickly enough to be useful.
Hohnhold, O'Brien and Tang describe a problem with A/B testing at scale. Short-term results from experiments are easy to measure but often fail to predict what happens in the long run, after a change ships and users adjust their behaviour. The central problem is estimating long-term user impact while still deciding quickly enough to be useful.
Written from the abstract read 2026-10-26 via OpenAlex.
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Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Sydney. https://research.google/pubs/pub43887/