Avoid the pitfalls of a/b testing : make syure your experiments recognize customers' varying needs / Iavor Bojinov, Guillaume Saint-Jacques, Martin Tingley

Online experiments measuring whether “A,” usually the current approach, is inferior to “B,” a proposed improvement, have become integral to the product-development cycle, especially at digital enterprises. But often firms make serious mistakes in conducting these tests: They focus on the average, instead of looking at how a change impacts different customer segments. They forget that customers are connected and that their interactions can affect test outcomes. And they run tests for too short a period, failing to recognize that customers’ reactions can change over time. This article describes how to avoid all those traps by applying techniques that LinkedIn and Netflix have used to produce better insights.

Business.