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A few weeks ago, a Fortune 500 company asked that I review their A/B testing strategy.

The results were good, the hypotheses strong, everything seemed to be in order… until I looked at the log of changes in their testing tool.

I noticed several blunders: in some experiments, they had adjusted the traffic allocation for the variations mid-experiment; some variations had been paused for a few days, then resumed; and experiments were stopped as soon as statistical significance was reached.

When it comes to testing, too many companies worry about the “what”, or the design of their variations, and not enough worry about the “how”, the execution of their experiments.

Don’t get me wrong, variation design is important: you need solid hypotheses supported by strong evidence. However, if you believe your work is finished once you have come up with variations for an experiment and pressed the launch button, you’re wrong.

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