Creating a website, marketing email, or internet advertisement can be challenging. Many factors need to be taken into consideration. That list only continues to grow as the internet becomes more advanced and users become more sophisticated with their preferences and needs. Naturally, this means you need to curate your webpage or media to suit your particular visitors.
There are two main reasons why tailoring online media can be difficult. First, you need to understand your users’ perspectives and behavior. Second, you need to use that information to choose the best of your creations or designs. If you perform these actions sequentially, it can be a long and drawn-out process. Of course, this is not ideal when you wish to launch your webpage or campaign. It is also frustrating when you simply want to perform a small change. Fortunately, there is a way to speed up and optimize this process: A/B testing. Follow along to learn more about what A/B testing is, how it can help you, and how to get started with A/B testing.
What Is A/B Testing?
A/B testing (split testing) is an excellent way to test different options for webpages, website elements, advertisements, and advertisement elements. It allows developers and marketers to test two or more variations of their creations. These variants (A being the original and B being the variant) will be shown to different groups of users at random. Certain variables will be tracked, determining the performance of each option. After the A/B test finishes, developers can easily and quickly view up-to-date, accurate results. From here, they can choose which version impacts their viewers or visitors best.
Depending on what developers or designers plan to test, they may wish to track different variables. They can track clicks, click-through rates, time spent on a page, sales, cart abandonment rates, bounce rates, response rates, subscriptions, and lead generations, amongst other measurements. The collected data will indicate which variant has better outcomes for behavior and engagement. Likewise, this method can help you determine solutions for concerns, issues, or pain points.
How Can A/B Testing Help You?
A/B testing can help you with many goals concerning development and optimization. A few of the main objectives are:
- Increasing user engagement or driving visitor traffic to a website or specific parts of a website.
- Reducing the number of viewers or visitors to a webpage who do not stay on the page.
- Increasing conversion rates, lead generations, or sales.
- Creating designs or content that appeals to the target audience.
- Encouraging viewers to navigate to or click a certain button or link.
- Performing modifications without affecting current statistics negatively.
How Do You Perform A/B Testing?
A/B testing provides you with concrete, accurate data so you can make informed decisions about designs and content. Accordingly, it will save you time, effort, and money in the long run. Ready to try it out? Find out the best way to get started below.
First, you will need two or more variations of your media. If you are starting from scratch, these can both be new designs. However, if you already have an original in place, use that as your control (A). You can do this with something as significant as a webpage or as small as a design detail. Popular choices include:
- Landing pages
- Service pages
- eCommerce shops and carts
- Click-through links
- Forms for requests or subscriptions
- Headers and sub headers
- Length of content
- Preview content
- Keywords, search intent, or hashtags
- Background colors or patterns
- Font types, sizes, colors
- Images or videos
- Navigation bars
- Lengths of advertisement videos or click-throughs
- Marketing or campaign emails
- Calls to action
- Social media proof or customer reviews
It is important that you only test one element at a time to ensure accurate results. However, with certain A/B testing tools, you can test how specific changes perform together on one webpage. For instance, you may wish to see how a different website layout with different navigation bars affects visitor engagement. You may not need to independently test background color, content placements, font sizes, and button sizes.
Second, you should choose an A/B testing tool that meets your specific needs. Some platforms will provide different types of A/B testing, elements for various media, customized testing, multiple tracking templates, calculators, and intuitive tracking and reporting.
Next, you must determine certain variables for the test itself. Some tools will help you optimize these factors, such as how many users are in each group or how long the tests run. It may also be helpful to figure out which metrics are the most important for your test before running it, although many tools configure this for you.
After the test is complete, you can generate comprehensive reports and analyze the data. Some software will specify which variant won the test and which metrics indicate that success. In other cases, you may wish to poll or survey your users to determine exactly why they enjoyed or engaged more with a certain element. In this way, you will be able to develop a deeper understanding of your users or visitors.
Naturally, the remainder of A/B testing is straightforward. In some cases, the results of a test will be distinct. One variant will win out over by a long shot in terms of engagement or satisfaction. Here, it is a green flag to implement that variant. In other situations, the differences may be slim. You may wish to go back to the drawing board or optimise another element within the design or content.
Finally, after implementing the change, you may run a test to reveal the significance of the change amongst all users or visitors. Ideally, the difference will be significant and measurable.