As companies seek new ways to boost online conversion rates and improve their visitors' site experience, interest in multivariate testing is on a feverish rise. But those unfamiliar with the techniques are often unclear about where to start, or how to ensure success.

What is Multivariate testing?

Common methods for running controlled experiments on Web sites range from simple A/B testing to sophisticated multivariate testing, also known as multivariable testing.

In A/B testing, one or more new versions of a page or single site element competes against an existing control version. For example, two versions of a headline might compete against an existing headline.

Multivariate testing, on the other hand, is like running many A/B tests concurrently, where there are multiple elements being tested at the same time. For example, two alternate product images, plus two alternate headlines, plus two alternate product copy text, for a total of 27 possible combinations (including the original control versions).

What's important to understand about multivariate testing is that it not only shows you which combination of elements generate more sales or pull more leads but also reveals which individual elements influence visitor behavioral vs. those that do not. For example, did variations in product image influence visitor behavior more, less, or the same as the copy?

Understanding how each site element causes visitors to interact with your site is the essence of a test-learn-repeat process that marketers can use to synthesize new ideas and continually improve their site's ability to achieve—and exceed—their marketing goals.

Multivariate testing can yield some spectacular results in enhancing online effectiveness.

If you are looking optimize your online performance, multivariate testing should be part of your arsenal of analytics and optimization tools. It may seem like a fantastic revolution in site testing, and it is. There are however some things you should be aware off. First, the sample size required to reach statistical certainty can be large. Second, if you run several multivariate tests across the site at one given time, you exponentially increase the number of variations and the sample size needed for statistical accuracy.

Grid14 helps you to avoid yielding uncertain results and inexplicable outcomes. Should you consider A/B testing or is multivariate the way forward? How to set up a campaign and what are the current software solutions? Our consultants have experience in anything from Google Optimiser to Omniture Test&Target or Memetrics and have the numbers to prove it.