If you’re in the process of buying a website optimization solution, you know there are many different options available to you. Each solution touts its own set of capabilities and pros and cons, and it’s important to understand how different platforms can help you optimize your website and achieve your marketing goals.
Let’s take a look at 4 common website optimization approaches and see how they compare.
A/B testing has long been marketers’ default method to optimize their websites. This approach compares the conversion rate of a new version of a page (sometimes called the challenger) with the conversion rate of the original page by showing each variation to a random 50% of your audience. Whichever version performs best is declared the winner, baked into the website, and shown to all future website visitors.
While A/B testing creates the opportunity for a more data-driven marketing approach, it is really only ideal when you can have one—and just one—version of your site shown to all of your visitors. Also, you’re limited to testing one idea at a time and must wait weeks or months for that test to reach statistical significance before being able to declare a “winner”. Finally, the result of your A/B test is only representative of the winner at a single point in time, so once it’s baked into your site, it’s there forever and won’t adjust for inevitable changes in visitor behavior.
Multivariate testing (MVT) is like running multiple A/B tests in parallel. This approach uses many of the same principles as A/B testing but instead of testing one element at a time, MVT tests multiple elements simultaneously (e.g. headline, image, and CTA). Similar to an A/B test, MVT will allocate traffic evenly among every possible combination of your ideas. For example, if you were testing 2 headlines, 2 images, and 2 CTAs, MVT would allocate traffic evenly among all 8 (2 x 2 x 2) possible combinations. In other words, each combination of headline, image, and CTA would receive 1/8th (one-eighth) of the traffic.
MVT is best used when you want to find the single best version of a page and understand how different elements interact with one another. However, because you are testing many combinations, you typically need exponentially more traffic than with A/B testing and, therefore, exponentially more time to find a winner. When you do find a winner and bake it into your site, keep in mind that you’re ultimately still serving up a one-size-fits-all experience to your website visitors.
With rules-based personalization, you set up one or more rules to define what a segment of visitors will see on your website. Each rule is like an “if this, then that” statement. For example, “If the visitor is from a B2B SaaS company, then show them case studies from other B2B SaaS companies.” It makes the most sense to use rules-based personalization when it’s inappropriate or brand unsafe to show particular content or a specific experience to an audience (e.g. showing content about the Boston Red Sox to a New Yorker).
Unlike A/B testing and MVT, rules-based personalization enables you to show a different experience to each segment of site visitors, so you’re not treating every last visitor the same, which is great. However, there is a ton of manual effort required in order to determine the right rules for the right segments, set those up, and regularly maintain and iterate on them as visitor behaviors change. Most marketers tap out at maintaining a few 10s of rules (if that).
Continuous Conversion uses machine learning to automatically test a virtually unlimited number of variations simultaneously on the same page and decide which combination of these variations to show each unique visitor in order to maximize conversions. Continuous Conversion also automatically adjusts the page experience over time as visitor mix or visitor behavior changes (i.e. when you run a promotion or change ad targeting). This approach is best used when you want to deliver the most relevant, personalized page experience to each unique site visitor in real time and are okay with each visitor having their own experience.
Continuous Conversion starts optimizing in minutes and hours so you see exponentially faster results, and marketers don’t need to constantly check for statistical significance. Continuous Conversion automatically amplifies winning ideas by showing them more often, and protects you from your losing ideas by starving them of traffic.
We’re just scratching the surface on these 4 optimization approaches. To take an even deeper dive into the optimization methods, their pros and cons, and questions to ask yourself and prospective vendors in the buying process, download The Buyer’s Guide to Website Conversion Optimization Solutions.