A/B testing is the process of comparing two versions of a digital asset to see which one performs better. The two versions are given to two same-sized groups of users, and the impact of the variation is measured through a particular set of metrics. You can run A/B tests on emails, webpages, product placements, pricing, and more.
A/B testing is also called split testing or bucket testing.
Benefits of A/B Testing
This is a conversion optimization strategy that can help you to:
- understand consumer behavior,
- determine which modifications will produce the best results,
- increase your revenue,
- improve the overall customer experience.
How Does It Work?
To run an A/B test, you start by creating two versions (or more) of a digital asset, with the second sample bearing minor modifications. Half of your audience, or the control group, sees the original version, while the other half sees the modified version. (Note: It is possible to test more than one variable in the process.) You then collect and measure the audience engagement, and pick the best option based on the results of the metrics.
In eCommerce, for example, you can run A/B testing experiments on your homepage’s merchandise ranking and placement, search results, or lists of recommended products to learn which items resonate best with your customers. When you’re planning to buy a digital solution to add to your tech stack, you can also dedicate a period for A/B testing to gauge your audience’s reception.
Pro-tip: Changes can be applied gradually instead of doing a complete overhaul. Doing so prevents a drastic impact on conversion rates. However, you can also do a test more than once to determine which techniques work best and then combine the most successful options to create a winning digital asset, campaign, or strategy.
Why is A/B Testing Important?
Through A/B testing, you can clearly identify the incremental changes you should make to reach your eCommerce goals. This can include attempting to boost average order value, increasing basket size, and everything in between. Test results can also help you deduce why certain variations work better than others and which modifications have the most impact — all based on tangible results rather than assumptions.
For example, in terms of your site performance, A/B testing allows you to better understand your customers’ and visitors’ browsing habits and intent. It can explain why users bounce or stay longer on your website.
Remember, even minor modifications can create behavioral changes that have a huge impact on the results.
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