How can A/B testing help with conversion rate optimization? 

A/B testing is a method of running a trial where two variations of an item or page are shown to a randomly selected audience and the version that performs better is declared the winner. It’s a simple way to find out which changes affect a given metric or goal most effectively. 

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The first step to successful A/B testing is deciding what you want to test, Fung says. This could be the color of a call-to-action button, the size or placement of a particular CTA, or any other variable that affects conversion rates. Once you have this figured out, you can create a test and run it on your site. 

Another important part of an A/B test is letting it run its course. Fung recommends giving the test a minimum of a week, as that gives time for any changes in performance to become apparent. This is especially important for sites with low traffic, which can make it difficult to determine whether a change has been effective. 

A/B testing is often a valuable tool for conversion rate optimization, but it shouldn’t be used at all times. Ideally, a site should have a good handle on its customer base and enough traffic to make it worth the investment in A/B testing. 

One of the main reasons that A/B testing isn’t a good fit for small websites with low traffic volume is that it can be expensive. The cost of the software, a statistician who can interpret the results of an A/B test, and the time it takes to gather the data all add up to more than a few thousand dollars. 

The second mistake that many managers make when performing A/B tests is that they try to implement changes too quickly. As the result, they can end up with a lot of unsatisfactory variations that don’t provide reliable results. 

As a result, they don’t take the time necessary to learn from the data and figure out what works best for their specific situation. This can lead to wasted time and resources, which is why it’s essential to use a testing solution that provides intuitive tools for collecting, analyzing, and tracking your results. 

Once you have an A/B testing solution, it’s critical to build a testing calendar. This can help you schedule the different tests in advance, avoid duplicating efforts, and streamline the process. 

Having a well-built testing calendar can also ensure that you’re able to scale your A/B testing program, which means you’ll get more benefits with less effort. It also allows you to track multiple metrics and ensure that you’re maximizing the benefit of every single variation. 

It’s also a good idea to choose a test solution that uses multi-armed bandit algorithms, which are designed to automatically and gradually redirect your traffic toward the winning variation. This can be particularly helpful for reducing click-through rates and increasing conversions. It also helps reduce outliers, which can significantly impact the results of an A/B test.