In A/B testing, when it comes to statistical significance, what is the minimum confidence level HubSpot suggests?
Explanation: The correct answer is 95%. Statistical significance is crucial in A/B testing as it determines whether the observed differences in performance between the variations of the test are due to actual differences in the variations or simply due to random chance. HubSpot suggests a minimum confidence level of 95%, which means that there is a 95% chance that the observed difference in performance between the variations is not due to random variation. This level of confidence is widely accepted in statistical analysis as it provides a strong indication that the results are reliable and meaningful. A confidence level of 95% indicates a relatively low probability of a Type I error, which occurs when a true difference between variations is wrongly interpreted as being due to chance. By aiming for a 95% confidence level, marketers can make more confident decisions based on the results of their A/B tests, ensuring that any changes implemented are likely to have a genuine impact on performance rather than being the result of random fluctuations. Therefore, adhering to a 95% confidence level helps to ensure the validity and reliability of A/B test results, providing marketers with actionable insights to optimize their email marketing strategies effectively.