They want to solve the problem

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To stay with the example: Will I sell more sneakers in my online store if I don't ask customers about their shoe size first? Or is the zoom setting on the product images the problem I should focus my efforts on?

Hypotheses: Now comes the most exciting part uk rcs data of the whole process: the ideas. But we don't call our ideas ideas, we call them hypotheses. Because this is exactly where many people fall into the trap: instead of getting to the bottom of the cause, immediately. Often the next best idea has to do; the main thing is to find a quick "solution". But in this phase it is precisely about critically questioning ourselves and not being led astray by ideas - hence again: hypotheses, not ideas. We ask ourselves questions like: Will the hypothesis solve the basic problem? Will it create more problems than it solves? Is it specific enough that a designer, developer and data analyst can experiment on its basis alone?

Back to the sneakers: If the problem is located in the choice of shoe size, for example, hypotheses could be: Is the representation of the shoe size on the page too complicated? Do customers prefer to compare the different models before checking whether the shoe is available in their size? Or are many people simply unsure what their correct size is?