Post by huangshi715 on Feb 15, 2024 9:52:45 GMT
A Type I error, also known as a “False Positive,” indicates whether the change between variations was due to alterations to the page or due to other noise. The confidence level does not indicate the percent of effectiveness of the test or the element’s percent contribution to the total lift. Yes, I’ve heard it explained this way by so-called “experts” more than I’d care to admit. Currently, the industry standard is a 95% confidence level, which leaves a 5% chance that the change in conversion wasn’t due to the tested element. BONUS TIP: Two other confidence level related items worth noting: . Stop reporting that way. It’s wrong.
Even at a 95% confidence level, errors can occur. Essentially, 1 in every 20 tests will Switzerland Email List commit a false positive. If you have the time and resources, verify results before making changes your landing page. Re-testing is a great way to verify results, but is only necessary (in my opinion) for large-scale changes or when you question your results. If you don’t have time to re-test, keep an eye on your numbers and make sure you have a large sample size as well as ample conversions (the rule of thumb is >100 per variation). Scary fact: 1 in 20 A/B tests will return a false positive.
CRO CLICK TO TWEET 3. If you change a feature on your homepage and see a drop in returning visitor conversions, what may your page be suffering from? changed-homepage1 47% of people got this wrong. Knowing the effects that can taint your data is extremely important, so pay close attention to this one! The correct answer Whenever you change a long-standing design element or feature on your site, be prepared for a drop-off caused by the “Primacy Effect.” The Primacy Effect occurs when you make major layout changes that require experienced visitors to “re-learn” how to use your site.
Even at a 95% confidence level, errors can occur. Essentially, 1 in every 20 tests will Switzerland Email List commit a false positive. If you have the time and resources, verify results before making changes your landing page. Re-testing is a great way to verify results, but is only necessary (in my opinion) for large-scale changes or when you question your results. If you don’t have time to re-test, keep an eye on your numbers and make sure you have a large sample size as well as ample conversions (the rule of thumb is >100 per variation). Scary fact: 1 in 20 A/B tests will return a false positive.
CRO CLICK TO TWEET 3. If you change a feature on your homepage and see a drop in returning visitor conversions, what may your page be suffering from? changed-homepage1 47% of people got this wrong. Knowing the effects that can taint your data is extremely important, so pay close attention to this one! The correct answer Whenever you change a long-standing design element or feature on your site, be prepared for a drop-off caused by the “Primacy Effect.” The Primacy Effect occurs when you make major layout changes that require experienced visitors to “re-learn” how to use your site.