Multi-variate testing makes things much simpler for people in the advertising industry to be able to target their ads to prospective customers better. That happens to be the biggest promise of AI, which is being able to target ads appropriately. Targeting appropriately with AI helps to eliminate or reduce the impact of mistakes, which can be very costly to the advertiser when considering how a campaign should be targeted.
Multi-variate testing is designed to identify the combination of factors which lead to a better ad performance overall. Because ads/websites are combinations of different elements, multi-variate tests are designed to modify or alter the ad or website in order to test new variations for better performance.
This is different from the traditional A/B split testing which only alters one variable to track for better performance. Nearly every variable can be altered in a multi-variate test to determine which combination of variables produces the best result. The challenge with a multi-variate test is that these types of tests require for the site to be receiving a large amount of traffic. The traditional A/B test works better for a site which receives less traffic.
This type of testing is a very powerful method of being able to gather information on website visitors. The reason is that it provides a lot of insight into how customers normally behave. Doubt, as well as uncertainty, are removed from the picture when testing occurs on a continual basis to produce more conversions.
A report from the consulting firm Accenture says that 50% of customers want to see ads that are tailored to their desires. The common mistake that is made is for ads to not be targeted properly, so a comprehensive approach would be to work with a proven method for correcting these issues!