Ezoic employs multivariate testing, which significantly differs from traditional A/B testing in its approach and outcomes. Traditional A/B testing involves comparing two versions of a web element, such as a webpage layout or call-to-action button, to determine which version performs better based on user responses. For instance, if version B receives 60% positive feedback while version A receives 40%, conventional wisdom dictates switching to version B for all users.
However, A/B testing has several limitations that need to be acknowledged. One of the primary issues is its inability to account for visitor behavior. For instance, if 60% of people prefer ad set A and 40% prefer ad set B, selecting ad set A leaves the preference of the 40% unaddressed. Moreover, metrics like CPM/CTR are averages that obscure the underlying data details and the pricing of impressions.
Another challenge with A/B testing is ensuring that test groups are random. Questions arise about segmenting traffic and assigning users to groups—whether by user, session, or pageview. The complexity extends to the mathematics involved: determining the run duration, understanding the data distribution, calculating the significance level, and controlling random bot traffic are not straightforward tasks.
A/B tests also lack responsiveness to real-time changes. A test run in June may yield significant results, but these may not hold true for December.
In contrast, Ezoic's multivariate testing runs thousands of tests simultaneously by leveraging artificial intelligence (A.I.) to gather, analyze, and implement the results. This adaptive approach ensures that users are served the version they prefer. If a subset of users shows a preference for version A, they will continue to see version A. Similarly, those who prefer version B will see version B. For users who do not have a clear preference, Ezoic's system will continue to test and offer different options until the most suitable version is identified.
This sophisticated testing capability is particularly beneficial for smaller, independent publishers who lack the resources to develop such advanced technology on their own. Ezoic democratizes access to powerful multivariate testing, making it available to all website owners, irrespective of their size, budget, or technical skills. Ultimately, the goal is to make design decisions based on objective user preferences rather than subjective tastes or individual inclinations, enhancing overall user satisfaction and engagement.
In short, while summary statistics are often uninformative, AI-driven approaches can unlock valuable insights and optimize ad revenue by delving deeper into the data.