What are the most common conversion optimization mistakes?

Common mistakes include testing too many variables at once, not having enough traffic for statistical significance, ignoring mobile users, focusing on minor changes instead of major friction points, and not understanding user intent. Other mistakes include removing trust signals, making assumptions without data, copying competitors blindly, and not following up on test results. Many teams also forget to test the checkout process, assume desktop is most important, or change too many things between tests making it impossible to know what worked. The key is systematic testing with clear hypotheses and sufficient sample sizes.