Ever wonder how to choose between two different website designs? Do you have a hard time figuring out the best content or layout for your site? Are you a perfectionist when it comes to making sure your online business is the most successful it can be?
Multivariate and A/B testing offers a convenient way to compare the quality of two or more different designs.
What is A/B Testing?

A/B testing lets you compare a baseline page with a page that has a single change made to it. For instance, if you are wondering whether placing a banner ad in a particular location results in greater click-through rates, A/B testing will let you try it out.
How it works is, you (the designer) provide two pages for the A/B testing program – the baseline and the changed page. When viewers go to that page, the A/B testing program randomly feeds them one or the other page. You can then use an analytic program to determine which page receives the better result over a period of time. You can read more on AB testing here.
What is Multivariate Testing?
Multivariate testing is a lot like A/B testing, except you can change many variables and compare many different pages. This lets you compare many different design elements at the same time. For instance, if you are trying to choose between two banner ad placements, two forms of written content, two sidebar layouts and two shopping cart locations, you can test them all at the same time with multivariate testing.
The only downside to multivariate testing is that it isn’t as effective for sites that don’t get a lot of visitors. In order to get adequate web analytics data, you need to have a statistically significant number of visitors to the site. Depending on the complexity of your multivariate testing regimen, this may number in the tens or hundreds of thousands. You can find a more detailed description here of multivariate testing and how exactly how it works.
Why Use A/B and Multivariate Testing?
The point of these tests is to make your website better than your competitors’ sites. These are scientific, empirical, statistically-based tools that help you determine the most popular design for your site’s pages. If you want to make sure that your design captures the most visitors, gets the most advertising revenue or converts the most visitors into paying customers, A/B and multivariate testing are essential.
Tips to Take Advantage of A/B and Multivariate Testing
* Always test everything simultaneously, and always split traffic evenly between each test.
* Don’t conclude your testing too early. Make sure you get a statistically significant number of hits. Your testing program can help you determine when you have enough hits.
* Don’t let your sense of aesthetics overrule test results. A/B testing is not about creativity; it is about what works for your website. If an “ugly” element happens to convert more sales, then you need to keep the ugly.
* Show repeat visitors the same variations that they saw before. Your testing program can help you configure this. The point is that you are testing two different website experiences. You want visitors to have the same experience from visit to visit.
How to Do It?
Google’s free website optimizer, located here- is a good place to start. This free analytics tool lets you upload different versions of the same page, then provides analysis of user data to determine the most effective page designs. While there are other pay-to-play testing programs, Google’s free program remains one of the most user-friendly, effective A/B and multivariate testing programs out there today.
A/B and multivariate testing are just two additional things that any web developer should understand. They should be used in conjunction with SEO techniques in order to build the most effective websites. While these techniques are powerful methods for maximizing profit potentials, they are no substitute for good design principles and modern web protocols. Implement them alongside your other web-based tools – not instead of them!
Happy optimizing!

















Nice information you have here. I never know that there is something called ab testing and multivariate testing. Thanks for sharing