This might be one of the most obvious things to test on a cart page. Designers sometimes think that using a particular color for the “proceed to checkout” button, such as red, is bad. That is not necessarily the case. What doesn’t work for one website might work for another. So, test different designs to find the one that increases your conversion rates. Different designs of the “proceed to checkout” button will impact your conversion rates; however, it is rare that these designs will result in huge uplifts in conversion.

Conventional wisdom is that the fewer steps you have in the checkout process, the fewer chances your visitors have to exit. As a result, there is a growing trend toward using a single page for the checkout process. That is not always a good option. Yahoo! offers its ecommerce customers a single-page checkout. Checkout abandonment rates for these stores is comparable to industry rates (45% to 80%), and the single-page checkout does not show any considerable improvement. There is no magic number for how many steps you should have in the checkout process. A good rule of thumb is to limit checkout steps to fewer than five. Combine different steps in the checkout and examine how they impact your conversion rate.

If visitors place orders on an infrequent basis, allowing them to check out without creating an account can help increase conversions. You should still capture visitors’ email addresses to notify them of their order status and to conduct any future marketing; you just do not need to require them to store all their information on your website. Figure 9-18 shows how BestBuy.com allows visitors to check out as guests without creating an account on the site. Although the functionality of the page is excellent, the design could use significant improvements based on some of the concepts we discussed earlier in this chapter.

BestBuy.com’s checkout options
Figure 9-18. BestBuy.com’s checkout options

A well-designed checkout process moves visitors in a single direction. Take a close look at your checkout funnel and examine how visitors move through it. Do you notice that a percentage of visitors are going back and forth between different steps of the process? We call this the checkout bounce-around effect. Checkout bounce requires that you tweak the design of some of your checkout pages. For example, if you notice that a high percentage of visitors keep going back from the last step of the checkout to a previous step, this indicates that you need to move some information or design elements from the previous step to the last step.

A Case Against Multivariate Testing

Conversion optimization approaches let you get instant feedback on a marketing initiative, adjust it accordingly, and receive even more accurate feedback. The more companies we talk to, the more we are reminded that multivariate testing is one of the main factors that reduces the quality of optimization work.

When I (Khalid) was at the University of Texas at Austin, I attended lectures by some of the great modern-day minds in computer science. Among the intellects I had the pleasure of meeting was Dr. Edsger Dijkstra, who had contributed some of the most influential algorithms in modern computing. He was also known for his low opinion of the GO TO statement in computer programming. This led to his writing an important paper in 1965, which was culminated in the 1968 article “A Case against the GO TO Statements.”

Dijkstra argued that programmers relied heavily on compilers to discover bugs in their code rather than investing time upfront to verify the accuracy of their programs and ensure the preciseness of their algorithms. This reliance of software on compilers is one of the main reasons we have ended up with lower-quality programs. The compiler should play a supporting role. It is not meant to replace the intellectual activities of humans ensuring the quality of software.

This brings me to the topic at hand: multivariate testing plays a major role in conversion optimization, and no one can argue the benefits of using this method in testing. Our average client who uses any form of testing reports a 65% increase in conversion rates. When multivariate testing becomes the main activity of optimization, though, it does a disservice to conversion optimization efforts. Too many clients rely on multivariate testing software to tell them which combination of elements on a page converts better. To do so, many elements on a page must be tested with different combinations.

Let’s do some simple math. Say you want to test six different elements on a page (headers, benefit list, hero shots, etc.). For each element, you will choose four different options. This means you will have a total of 46 = 4,096 possible scenarios that you will have to test. Google’s Website Optimizer allows a maximum of 10,000 combinations.

As a general rule of thumb, you will need around 100 conversions per scenario to make sure the data you are collecting is statistically significant. This translates into 4,096 * 100 = 409,600 conversions. If your website converts around 1%, you will need 409,600 * 100 = 40,960,000 visitors before you start gaining some confidence in your testing results. If testing 4,096 variations sounds difficult, imagine how complicated matters will get by adding variation in campaigns, offers, products, and keywords.

Running this many test scenarios is not unheard of for many larger websites. But why deal with this headache in the first place? Why spend hundreds of thousands of dollars on pay-per-click (PPC) because you need to test whether the variation works? And there is no guarantee you’ll get the accurate results you are looking for. This only happens because an activity designed to take place at the very end of the optimization effort becomes the centerpiece of that effort. Optimization that relies heavily on testing assumes that websites have an endless number of resources to test all possible combinations. This is simply not the case.

The science of marketing is about studying human behavior and how to influence it. When relying heavily on multivariate testing software, I find that marketers are not doing what marketers traditionally do; instead, they are taking a back seat to software programs. Yes, software is important, but human power and intellect should be what guides that software.

Optimization done correctly starts with a full analysis of the target client and gaining a deeper understanding of their business goals. This should lead to developing site personas as a first real step in conversion optimization efforts. These personas guide how pages are designed, how copy is created, and how site navigations are laid out. Only after you have employed all of these methods should you use multivariate testing software.