A/B Testing – A Simple Method for Increasing Online Sales

Every website can be improved in some way to provide a better user experience and increase conversion rates and sales, but to do that effectively you have to test what works best. That’s the only way to know how users behave on a website and which pages or page sections they prefer.

Testing is a crucial step when implementing website changes and the simplest form of testing is A/B testing – simply running a live trial between 2 different options. However, it’s important that tests run for long enough to reach a meaningful number of web visitors with the right buying intent.

Getting started with an A/B test
The first step is to identify a page on a website that could be improved to achieve a specific goal. The page should already be generating visits so that the test has enough data with which to draw a conclusion. For websites with few visitors this might mean running the test for a month or more, but for others a few days might suffice.

Then, create a second variation of the existing page so you have an “A” version and a “B” version with a simple difference between the two. This difference can be a different colour or position for a call-to-action button, or it could be a new image, or different wording. Keep the difference simple to start with so that each test and subsequent test are only comparing one change.
Then show each of the two variations to 50% of site visitors simultaneously – this ensures the test is not impacted by the time of day or the day of the week. Half the visitors will see variation “A” and half will see variation “B”.

Tools such as HotJar, CrazyEgg or Optimizely (and plenty of others) can help here, with easy-to-use visual editors and simple setup procedures. Google Analytics 4 also has A/B testing features which are free to use.

Testing further variants
Once you have enough data to make a choice between which A/B variant produces the highest conversion rate then you can take that test and create another variant to test against it. Then repeat the process for as long as it takes to determine the best variant of the page.

It’s perfectly possible to continuously run simple A/B tests in this way, comparing two variants against each other at a time. However, that process can be refined by using split testing, which is similar to A/B testing but uses more than two variants allowing multiple ideas to be tested at the same time.

For example, when one company wanted to increase the number of people requesting a quote for their services they started by testing variations of a call-to-action button in multiple combinations of their three brand colours: dark blue (hex code #02224e), mid-blue (hex code #2974ac) and orange (hex code #f28500). What they actually found was that a different colour altogether had by far the highest click rate (green #149414) because it stood out from the page amongst their other brand-coloured items 

The impact of implementing a green button was to increase conversion rates by 28.4% over the original orange button on a mid-blue background.

What else to test
A/B testing or split testing doesn’t have to be restricted to clicking buttons or other elements on a web page. It can also, for example, be used to test the impact of different wording, fonts and layouts on Engagement Rate i.e. how long people stay on the page and read the content. This can contribute to increasing brand awareness for business that provide expert information and want to build up their online authority.

Simply increasing Engagement Rate (which is a standard metric in Google Analytics 4) will also have a positive impact on search ranking positions so testing a range of changes to a page is definitely worthwhile. And, remember, what works in one industry may not work in another, and what works for one website may not work for another. The popular green with hex code #149414 that worked in the example above would be unlikely to work for a website which already had green as a brand colour (although worth testing).

A/B tests are a valuable technique to help businesses understand more about web visitors’ behaviour on a page; and use that knowledge to change pages to more effectively convert those visitors into customers.
Of course, a single image, button colour or button position is just one element in a whole website and the user’s journey through, and experience with, the website will also contribute to a buyer’s decision.


This site uses cookies to offer you a better browsing experience. By browsing this website, you agree to our use of cookies.