The Easy Guide To A/B Testing

The Easy Guide to A/B Testing

A/B testing is a fantastic testing method that should be a part of every business’s online marketing arsenal. It allows you to home in on exactly what your market responds positively to, giving you more clicks and opens on your marketing emails, increased site visits, and even improved conversion rates to help improve that ever-important bottom line. How can you use online A/B testing to sharpen your view of what the market wants? Lets take a dive and explore the wonderful world of this digital dream!

First, here is a simple, quick, and easy-to-understand definition: A/B testing is when you present two versions of the same thing – it could be a web page or a marketing email, for instance – and measure the results to see which one performs better. Its not a new concept; paper marketing materials used to use A/B testing to see which print advertisements performed best in order to hone their advertising outreach, television commercials showed different versions of a commercial for the same product and gauge results, and newspapers would use different headlines on their front pages to see which version sold better on newsstands. Its a basic yet tried-and-true method to determine the success of different campaigns in a variety of industries.

In todays digital world, A/B testing is used in various ways, but the majority of locations will be in web pages and email marketing. Before you consider implementing it into your digital armament, however, there’s one thing you need to make sure is up and running like a well-oiled machine: Analytics.

Analytics are essentially what make A/B testing possible in digital marketing. Without them, you wouldn’t be able to tell which version of your A/B test performed better and the entire endeavor would be pointless. Google Analytics is a great place to start for your tracking your website performance, and whatever email client you sent should also be equipped with stats that track opens, unique opens, clicks, unique clicks, and unsubscribes (at the very least).

Once you have ensured your analytics are correctly tracking your website and emails, it’s time to start thinking about the design of your A test and your B test. If youre starting from scratch, you can make your two versions markedly different from one another; as you continue to perform more A/B tests, you can get more subtle with the differences.

When using A/B testing on your web page, determine what you’d like to use as a measure of success. Are you tracking how many people convert to a sale? Are you trying to get visitors to stay on your site as long as possible? Or do you want to simply increase the number of clicks on a specific link on a web page? Whatever your goal, make sure it is clearly stated and benchmarked before you begin so that you can easily measure success after your test.

Youll use a similar idea with email marketing, but the initial results are a bit easier to track. After sending the two versions of your email, track the stats we mentioned above – opens, unique opens, clicks, unique clicks, and unsubscribes – as a starting point. The version that gets more opens will have a lot to do with the subject line, as well as with the preview text. Clicks will show you how your call to action performs: the more clicks you get, the more enticing your content was. There will be many more factors to explore once you delve into more in-depth A/B testing, but these are good indicators of what your audience responds more favorably to initially.

After conducting your A/B tests, compare the results and use the findings as you go forward. Did web pages or emails with more images perform better, or were text-focused versions the favorite? Was the call to action placed higher up in one of the versions, and did this affect how much your audience engaged? Whatever the differences between versions, take note of them and incorporate them into your next update. The more A/B tests you perform, the better youll come to know your audience; before you know it, youll soon be the one talking about A/B tests in your next meeting!

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