In this kind of test, commonly referred to in the high-tech industry as an A/B test, the choices are already laid out. In this Google pick-a-blue experiment, the result was always going to be one of those forty-one options. While the A/B test might be a good way to find the single most clickable shade of blue, the dynamic range between best and worst isn’t that much. More important, the opportunity cost of running all the trials meant there was less time available for everyone on the development team to dream up a design that people might like two, or three, or ten times more. A/B tests might
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