What does Split testing mean in marketing terminology?

Split testing

Split testing (also known as A/B testing) is a popular and effective marketing technique used to test content and design changes, with the aim of increasing conversions and optimising the user experience. By comparing two versions of a web page or email, digital marketers can determine which works best in terms of visuals, wording, and call-to-action (CTA) buttons.

Split testing allows you to experiment with two (or more) versions of a page or email, in order to compare results and determine which version achieves a greater success in terms of click-through rate, time-on-site, and other metrics. With testing, you can see which version performs better and make informed decisions about whether to keep the design, substitute elements, or move on to something new.

It is important to note that the data split testing provides is only valid if the versions of the page or email that you’re testing are closely controlled. If too many variables are changed between the versions (for example, substituting one image for another, or drastically altering the wording) then the result will be invalid and misleading.

When creating two versions of your page or email, you must ensure they’re as closely matched as possible to ensure valid results. Start by selecting a specific element that you want to test; views, colours, headings, images and wording are all suitable candidates. Then create two versions of the page which differ only in that one particular element; everything else should remain identical.

Before applying split tests, it’s important to consider your existing website analytics and think carefully about which element you want to test. Sometimes, the obvious and popular design choices won’t be the most effective for conversions. Common elements for testing include:

- Headlines and titles: Do short, direct headlines work best? Or does one that is longer, descriptive and engaging have better results

- Images: Test images and visuals to see which ones have the greatest impact

- Buttons: Test colour, shape, size and position of the buttons to create a call to action (CTA)

- Layout: Which page design works better for your target audience? Are there any spacing, colour, or font issues?

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- Content: You may want to test different versions of content that vary in length or style

- Offers: Test different offer types, such as discount codes, free shipping or buy one get one free deals

- People: Experiment with different levels of customer service and support

- Wording: Test different wording, since it can have a major impact on how your message is interpreted

Once you’ve identified an element to test, create two versions of the page or email that differ only in the chosen element. A/B testing software can automate the process of redirecting visitors to different versions of the page, depending on the visitor’s characteristics.

To make sure the test results are as accurate as possible, it is important to factor in a wide range of variables, including platform, device, and location. You should also run the test for long enough that any seasonal or random variation in the data is reflected and accounted for.

It’s important to keep a close watch on the test and make sure that the conversion rate, pageviews, click-through rate and time-on-site metrics are being tracked accurately. It is only when these metrics are watched carefully that you can identify the winning variant.

Once a clear winner is obtained, the final version should be tested against further changes to further optimise the page or email. With each test, the variations to the element should be small so that it is easy to identify the outcome. Then, if the results are not satisfactory, it is important to identify what went wrong, learn from your mistakes, and move on.

Split testing is a key component of any digital marketing strategy. By testing different variations, you will be able to determine what works best for maximum optimisation. With each test, it is essential to keep a close watch on the metrics and make sure the correct variables are being tested. By doing so, you can ensure that the version you’ve ended up with is the one that’s most effective for conversions.