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Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments
2017
Marketing science (Providence, R.I.)
Firms using online advertising regularly run experiments with multiple versions of their ads since they are uncertain about which ones are most effective. Within a campaign, firms try to adapt to intermediate results of their tests, optimizing what they earn while learning about their ads. But how should they decide what percentage of impressions to allocate to each ad? This paper answers that question, resolving the well-known "learn-and-earn" trade-off using multi-armed bandit (MAB) methods.
doi:10.1287/mksc.2016.1023
fatcat:oxkaeege6zeo3oopaxf7bvb5oy