  Comparison Lift is an experimentation-as-a-service (EaaS) application for
testing online advertising audiences and creatives at JD.com. Unlike many other
EaaS tools that focus primarily on fixed sample A/B testing, Comparison Lift
deploys a custom bandit-based experimentation algorithm. The advantages of the
bandit-based approach are two-fold. First, it aligns the randomization induced
in the test with the advertiser's goals from testing. Second, by adapting
experimental design to information acquired during the test, it reduces
substantially the cost of experimentation to the advertiser. Since launch in
May 2019, Comparison Lift has been utilized in over 1,500 experiments. We
estimate that utilization of the product has helped increase click-through
rates of participating advertising campaigns by 46% on average. We estimate
that the adaptive design in the product has generated 27% more clicks on
average during testing compared to a fixed sample A/B design. Both suggest
significant value generation and cost savings to advertisers from the product.
