A Brief Intro to eCommerce A/B Testing
A/B testing, also known as split testing, is an effective way to investigate and determine which design, functionality and content on your page is deemed the most successful to optimize your business. Using this, you can test variations of your page, or elements on your page, to see what works best for your customers. An example of A/B testing would be creating two different page layouts for your product and then analyzing which layout is more successful at generating sales. It’s an excellent way to test and improve aspects of your online shop to increase conversions.
Why it’s Important to Conduct A/B Tests on Your Webshop
A/B testing can have numerous benefits to your eCommerce business. It’s important to constantly adapt and fix your webpage to keep your business going strong. Of course, to be able to achieve this you need to be aware of what needs fixing in order to implement effective improvements.
The content on your website can have a large effect on your eCommerce conversion rates, you want to turn as many visitors to buyers as you can. Running an A/B test is a great way to help you figure out what works and what doesn’t work when it comes to converting customers. Doing this takes a little longer, but taking that extra time to create quality content for your customers will give you much better results.
Bounce rates are one of the most important aspects to analyse from your business. Having a high bounce rate indicates something on your website isn’t appealing to visitors. Creating different variations of your website’s layout and content then testing which version gives you a lower bounce rate is an easy and effective way to gain insight into what works better for your site to get you more customers. Having a high abandoned cart rate is also a crucial issue to fix in order to increase sales. Losing your customers at the last minute can be for many reasons but it could be an easy fix. Conducting an A/B test could identify where you are losing your customers and how to reduce your abandoned cart rate.
Knowing what your ideal customer likes and dislikes about your website is difficult to figure out without analysing and testing. With A/B testing you can test pretty much any aspect of your website to evaluate what your ideal customer prefers to see. Tweaking even small things, such as the location of your menu, the images you use or the description of your products could make a significant difference in achieving the all important customer conversions and successful sales.
Choosing the Correct Method: Know Your Multivariate From Your Redirect
There’s a few different split testing methods you can use to optimise your site. Consider which type would be best for your website before you conduct your test in order to get the most out of the results.
A/B testing, changing one element at a time
One way to conduct an A/B test is by changing one element at a time. With this, you test two pages that are almost identical however there is one element on the page that is different. For example, you might want to test an element of your home page such as the colour or the image for your background. One of the testing pages might have a light blue background and the other a dark blue background. You can then evaluate the results to see which background appealed better to visitors. This is a fairly limited test however still useful for making a few simple tweaks to your site.
Multivariate, testing multiple sections at the same time
Multivariate testing works the same way however it allows you to test multiple sections on one page. Multivariate testing is more useful when there are several problems that need addressing and testing. This way of testing gives more insight into how effective elements on the page in a section work as a combination. Giving far more potential combinations for elements to be changed in order to improve the site for your visitors. This does make it more complicated than straightforward A/B testing but does allow for more options when making decisions to change.
Redirect test, test two different pages
A redirect test involves testing two different active sites with different designs,layout or content. This is a simple way to evaluate the best design for your overall website that gets the most traction and conversions. Ease of analysis is an excellent advantage of A/B testing, as the results will reveal a clear winner and loser between the two sites. From there, the better page can influence other pages in order to optimize your website.
For example, these two different product pages could be A/B tested to evaluate which design converts more customers. The two pages have a slightly different design and layout for the same product, using A/B testing the company can identify which design won over the most customers and use that as an indication for what visitors want to see on their site.
Getting to Grips with Google Optimise
Google Optimise is a platform that allows you to test variations of your sites, as well as examine analytics and conduct surveys. It’s easy to use and to get the basics of an analysis it’s completely free. To run an A/B test using this platform is fairly simple.
The first step is to identify a problem and create a hypothesis (basically what you think will happen e.g. Making the add to cart button a contrasting colour on the page will increase conversions). Once you have a hypothesis, create an experiment and enter the url of the page you’re testing. Click create and you are able to monitor the test and evaluate the results.
With A/B testing you can gain insight into what works best at converting customers and what you need to implement to achieve these conversions. As A/B testing is one of the key components in conversion rate optimization, it’s important to be aware of ways you can improve your site. Having your website optimized for visitors to attract high quality traffic to your website is a crucial way to increase conversions. As a free and simple test, I encourage you to conduct some tests and get your eCommerce site optimized.
If you are still confused or just want some guidance around A/B testing, feel free to speak to us!