Optimizing with A/B testing is simply the process of testing two variants (in other words an A and a B variant) of some element of your marketing activities. By comparing their performance we can draw conclusions and apply the results to optimize for success. Although the A/B testing method can be used with all types of content, it is generally most popular when it comes to designing and launching emailing and landing pages campaigns.
The Optimization Do’s and Don’ts of A/B Testing
The Do’s: to ensure optimum results, we recommend you consider the following best A/B test practices:
Change only one component at a time
When you start testing, ensure not to get carried away diving into testing all our assumptions at once. If we test more than one component at a time, although we think we’re optimizing and testing everything, in reality we’re testing for nothing. Creating totally different variants with the maximum amount of changes is an error, since you will not know what has worked in each scenario. So it is better to focus your tests. Check and optimize for a single element on each test, such as, button size, copy, color … etc.
Look at your KPIs
It is useless to measure clicks if what we really want is to increase the sales of a certain product, for example. A/B testing should always be in line with your marketing objectives, your KPIs, or in other words your key performance indicators. To ensure your incorporating your KPIs in your tests, compare your metrics that are most related to the tests. For example if we’re optimizing for sales, the conversion of new visitors or repeat purchases is key.
Convert test results to actionable changes
After you’ve gained insights on how to optimize performance through your A/B tests, it’s time to take action! The objective of A/B tests should always be to find actionable changes that you can apply directly and continuously from now on. So apply the high performing changes and continue testing the next variable until you get the perfectly optimized landing (or email, or ad … etc.).
The Don’ts: successful optimization of your A/B tests comes from the strategic combination of following best practices (the Do’s mentioned above) and avoiding the following fundamental mistakes (the Don’ts):
Comparing apples and pears
The user groups on which the A/B test is carried out have to be as homogeneous as possible, or the results will not be reliable. It is not representative to direct each test variant to visitors who come from a different channel or who have some other important difference.
Let yourself be carried away by impatience
For the results of an A/B test to be statistically relevant, they must be done on a group as large as possible. If your website does not have a lot of traffic, that means you should leave both test variants (A and B) active for days or even weeks to really get reliable data and in turn successfully optimize.
Indulge in safety
A/B tests are the perfect place to take a risk, unleash your creativity and experiment. Dare to try your craziest ideas, you never know what can surprise you in the results!
Get Maximum Return Through A/B Optimization with Social Ads Image Testing
Putting theory into practice, let’s explore a case in point. We used A/B testing to publish more effective social ad campaigns.
Given the immense amount of content that is published on social networks every day, getting users to click on ads can be quite a challenge. For this, it is essential to stand out with an image that attracts user attention.
For our experiment, we launched a series of Social Ads in which their images corresponded to two variants: one followed the style guide of the brand, while the other was created with a 100% performance optimization approach. The purely performance optimized images fulfilled the following characteristics:
- Use strong contrasts and striking colors
- Do not ‘abuse’ filters
- Image quality
The result: images with a performance approach obtained a 35% higher CTR and more than twice the ROI in terms of sales and revenue. Optimize your approach to digital ads by getting to know the digital advertising formats available to you. Through the science of A/B testing, and striping all underlying assumptions and ‘given guidelines’ we can optimize for success.
About the Author:
Journalist, content creator, community manager and social strategist. Laia studied Journalism and Audiovisual production. Innovative ways with words and communication are Laia’s passion