Conversion rate improvements need to be delivered faster these days, too fast to rely on yesterday's testing methodologies, "best practices" and guideline guesswork. One answer has been custom multivariate testing: that is of course, if you have high site traffic and a generous budget. Google's free, easy Web Site Optimizer (WO) made multivariate testing more popular. But most small to midsized companies lack sufficient site traffic to produce statistically significant results for many months with WO. So how can these smaller companies compete? WebSiteOptimization.com has the solution.
WSO's new adaptive multivariate testing methodology is able to boost conversion rates right from the start, even during the testing period. Our self-learning method adapts to visitor traffic in real time and after a very brief learning period starts to consistently test only those page impressions that are better than the control. This means that you can start making more money immediately.
If you're part of a small to mid-sized company with normal web traffic you probably spend good money each month on improved SEO (Search Engine Optimization). Great, you're getting more prospects "in the door." But what percentage are you closing? Without a proven way to turn those prospects into customers you're just throwing your SEO money away (not to mention all the other investments you've made in your Web presence). That's why you need WSO's Adaptive Conversion Rate Optimization: it's the only proven solution that can cost-effectively turn web leads into sales for small to mid-sized companies. The best part is: you're only a brief interview away from the higher profits you've been working so hard for. So don't wait a minute longer. Call us at (877)-SITEOPT (877.748.3678) or contact us and ask to speak to our Adaptive Conversion Rate Optimization team leader.
Multivariate testing pits different variations of your content against each other, to prove which combinations best convert prospects into buyers. Multivariate testings allows you to test different combinations of headlines, calls to action, layout, and color treatments to maximize the conversion rate of your landing pages.
The advantage of multivariate testing lies in is its ability to test large numbers of page versions while varying many elements at the same time. Before adaptive multivariate testing, there were only two main multivariate testing methods: full factorial, and fractional factorial. These older methods have an Achilles heel; they require large numbers of web visitors to suggest significant conversion rate improvements. Let's take a closer look at these older methods.
The full factorial method is a fancy name for 'test all combinations and find a winner.' This is a brute force approach used by Google's Web Site Optimizer and other approaches.
To compare the different optimization methods let's illustrate the number of visitors required for a full factorial testing of two variable elements. Each variable is represented by its own axis, and the total number of visitors needed to perform this test is represented by the cube below:
The full factorial method has its advantages and disadvantages:
A more sophisticated and more expensive method is the so-called fractional factorial method. Instead of testing all possible page combinations, only a subset is tested and mathematical modeling is used to predict the overall combination winner. This method is very sensitive to potential interactions between different elements. That is why several waves of testing are necessary before good results are achieved.
The picture below illustrates the reduced number of web visitors required by this methodology.
Clearly these older methods have too many drawbacks to make them practical for small to mid-sized companies without a huge amount site traffic. The best solution for them is the WSO solution: Adaptive Multivariate Testing.
The adaptive method moves multivariate testing to an entirely new level. The main advantage of this method is its ability to adapt to visitor behavior in real time while converging toward the winning page combination. Actual testing is initialized by presenting a few random page combinations to live visitors. Visitor reactions are then processed in real time creating statistical data that is used by the adaptive algorithm to generate a new page combination that will be shown to live visitors. During this iterative process, the adaptive algorithm is able to effectively detect elements that impact page conversion in positive way and to filter out elements that have a negative impact. The bottom line; a far quicker, less expensive path to web site success.
The picture below illustrates the adaptive method and its ability to effectively converge on the best page combination with a dramatic reduction in the required number of web visitors.
Adaptive multivariate testing embodies the best aspects of other two methods: the exactness of results achieved through full factorial testing and reduced number of web visitors produced by fractional factorial methods.
To quantify the difference in performance between the three methods above, we applied all three methods to the following real life multivariate test:
|Number of test combinations:||196|
|Current Conversion Rate:||30%|
|Method||Required Number of Website Visitors|
|Full Factorial (Google Website Optimizer)*||306,936|
|Fractional Factorial (estimated for 1-2 waves)||16,608-38,240|
*See Google calculator
The adaptive method required two orders of magnitude fewer page impressions than the full factorial method, and one order of magnitude fewer impressions that the fractional factorial method.
The software automatically favors the combinations that yield the highest conversion rates, quickly finding the optimum solution. You'll get results faster and be able to run more tests than with conventional conversion rate optimization methods.