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Experiments: Now it's time to test these hypotheses under real conditions. what ten UX designers think is the best idea in a brainstorming session, but what the user does. Therefore, in the next step, designers, developers and data analysts develop a series of experiments to see which idea works best in reality.

For example, for a week, the question about shoe size is only asked for some users at the very end of the purchase process, and not at the beginning. Or in some cases, an auxiliary tool appears in uk rcs data the online shop that helps customers determine their shoe size with the help of a photo. But it's important to note that experimentation is not the Wild West, but an extremely methodical way of working: an experiment extends from the planning, design, development and execution of an experiment to validation, gaining knowledge and deriving the next actions. It is a statistically reliable test of validations or permutations against control groups in a controlled environment.

Outcome: Once an experiment has run long enough to collect a sufficient amount of data, it is time to determine what the data is telling us. This will tell us whether the control group or a variation of it (our hypotheses) performed better. These results tell us what our next steps should be. We ask ourselves questions like: What have we learned? How should we apply what we have learned? What should we do next?