In the SaaS industry, your most lucrative opportunities will be within your existing client base. The reason for this is that it takes a lot of time and effort to develop trust and brand loyalty. Once a client is familiar with your company and products, they will be more likely to purchase products and services […]
What is Statistical Significance?
Statistical significance is the likelihood that a relationship between two or more variables is caused by something more than just random chance. In other words, it is the likelihood that the difference in conversion rates between any variation and the baseline is not a random occurrence.
When testing a hypothesis, the result of an experiment is thought to have statistical significance or to be statistically significant, meaning results are likely not caused by chance for any given level of statistical significance. When you’ve found the statistical significance level, it reflects the risk tolerance and confidence level of your hypothesis.
For example, say you run a split-testing experiment and find a significance level of 95%. This means that if you determine a winner within the split test, you can be 95% confident that the results you have observed are actually real and not an error caused by random chance.
A 95% confidence level means there is a 5% chance you could be wrong about your results. Thus, statistical significance allows you space to make better-informed decisions about marketing practices for your business.