Think about analysis early

One of the most common mistakes in UX research is treating analysis as something you figure out after the data is collected. In practice, the best analyses start taking shape before a single session is run.

Your research goals and hypotheses act as a filter. They help you stay focused during analysis and avoid the trap of chasing every interesting detail in the data. If your research goal is to understand why users abandon a shopping cart, you already have assumptions going in. Maybe you suspect the checkout process is too long, or that users hit an unexpected cost at the final step. Those assumptions shape what you look for and how you interpret what you find.

One practical way to prepare is to define your codes before fieldwork begins. Codes are short labels you assign to observations or quotes that match your research goals. For example, if you're testing the usability of a landing page, you might set up codes like "navigation," "aesthetics," "critical errors," and "recommendations" in advance. When a participant struggles to find the sign-up button, you tag it immediately rather than sorting through raw notes later.

This approach doesn't mean you should ignore unexpected findings. Surprising patterns that fall outside your initial codes are often the most valuable. But having a structure in place makes it much easier to spot them.