A/B testing, also known as bucket testing or split testing, is a valuable tool in advertising. It involves creating at least two variations of ad creatives that run against each other to see which your audience responds better to. A/B testing isn’t a new idea, it comes from the well-known idea of trial and error, trying out different ideas and variations to see which one is the most effective.
We mainly use A/B testing to test ad creatives and copy to see which version has the highest results to inform future campaigns in order to achieve the best results within the campaign budget. (You can learn more about what we do here Our Work) But this type of testing can be used for several different aspects of your brand and business, not just improving your advertising.
A/B testing can also be used for market research, by advertising different aspects of your brand or business you can see which is the most grippy and relevant to your audience and therefore focus on developing that feature. You may even realise a feature that you were spending time and money on has no relevance to your audience and you can move your resources to a more relevant feature. You can then focus on advertising the features that you know your audience finds valuable and respond to ensuring that your campaigns are relevant and will gain better results.
A/B testing can also be useful in the development stages of new products or brands, you can test your ideas as you go to get live feedback from potential consumers which can inform the direction of your project. For example, you can run a campaign testing landing pages or whole websites/customer journeys. By creating ads where the only variation is the link they click. You can then see which version of your website is driving people through the funnel. A/B testing is an invaluable tool when used properly, learn how to A/B test below:
The first and most important step is deciding what the goal of your A/B test will be. Your goal for the A/B test needs to be clearly defined, there can’t be any confusion as to what your testing or the test won’t work. If the goal is too complex or broad the test can be inaccurate as you won’t know which element being tested is having an impact or causing the results.
A successful A/B test involves keeping the differences small and simple so that they are the only things affecting the actions of the audience. For example, if you want to increase website traffic you may create an A/B test with different images or different texts but not both. If you want to test both the images and the text you can do separate rounds of A/B testing. First by testing the images and after that campaign ends you can then move on to test the text.
Once you understand what you are testing for you now need to determine how you will measure the success of the variants. You will need to determine which ad was the most successful by choosing which KPIs (Key Performance Indexes) are most important to you. If you want to create ads that will be seen by the most amount of people, Reach will be your most important metric. If you want to drive website traffic, then Click-Throughs would be a better measure of success. If you want to start a conversation around your brand then Engagement is what you should be focusing on measuring.
Once you have fully understood your goals for the campaign it’s time for the fun part, you get to create your campaign. You should already have an idea of what your campaign will look like from the earlier stages as you know which elements you are testing. If you’re looking to test the imagery within the campaign find 2-4 impactful images and keep the text fairly simple. Make the important decisions about how long to run the test and what your budget will be. It’s important to put a decent amount behind your campaign and allow the test to run for a few weeks so you have the chance to reach as many people as possible so that it is a big enough audience and data collected is more likely to be accurate.
When the campaign ends you’ll need to record all the data and compare it. These results should now be able to inform future campaigns. You can also create a second A/B test with the strongest of the last test and change a different aspect this time. For example, if you just found out which type of image was the strongest this time you can test the text to see which has the biggest result.
The text on the image and the caption remained the same across all four variants; the only thing that changed was the imagery. Out of those four images, which one would encourage you to click onto the website?
The best-performing ad had over 300% more clicks than the next best-performing ad. The best-performing ad also received over 250% more impressions than the next-performing ad.
And the winner is…. Ad number 4 with 2,107 clicks. Ad number 3 was second best with 629 clicks, ad number 2 received 475 clicks and ad number 1 only received 11 clicks. What do these results tell us? The targeted audience prefers ads that contain food images that are more gourmet while still being simple. The best-performing image was also the only one that was shot at an angle (not directly over the food). The results can now be used to influence the creative for the next campaign by choosing a similar image to the one used in ad 4.
The results of an A/B test are extremely valuable but it is important to consider the limitations of A/B testing. A/B testing can only show you the best of what you’re testing, the best solution may lay outside of what you have considered, and there is no way for an A/B test to create a solution outside of the options you are testing.
A/B testing also heavily relies on what you decide is the most valuable aspect to test. If you are looking to increase sales you need to decide what step of the sales process is the current issue. Is it the ad creative, the customer journey on your website or maybe the issue is something smaller and harder to identify like an unclear process on your cart page? You have to make the decision on what aspect to test and if it is the wrong one the answers might not fix the issue.
A/B testing can inform many decisions within your brand or business once it is done correctly and is well thought out and planned so that you are aware of the potential limitations of your test and other factors that could influence your results.
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Written by Emma Kate Rowlette