Improve the open rates of your emails, the conversion rates of your landing page or the click-through rate of your CTA? It is time to use A/B testing. Through my experience, I explain how to set it up to get better results.
4 tips for successful A/B testing
The tools for doing A/B testing
The basics of A/B testing;
A/B testing, or split testing, is a common strategy in digital marketing. About 59% of companies use it to optimize their email campaigns. It involves comparing two versions of content, such as an email, a landing page or an SMS.
Definition
A/B testing aims to send two versions of the same content to similar audiences in order to compare the results. In practical terms, it is a method that allows you to act on a variable on a landing page, an email, a call-to-action, etc. in order to influence your performance indicators. This helps you understand which elements affect your database and thus improve the results of your marketing campaigns.
A/B Testing, is it dynamic content?
Good question! Both influence content, but the way they do it is different
- A/B testing mainly consists of changing the appearance of a variable in your content to optimize the results obtained
- Dynamic content adjusts the appearance or content according to your recipient’s profile and behavior.
What are the differences between A/B testing and multivariate testing
If you have done some research on A/B testing, you have probably come across the term multivariate testing. It allows you to test several elements at once, such as different layouts, images or CTAs. Unlike A/B testing, which compares two versions of a single element. Multivariate testing takes more time because there are more variables to analyze. It is also a strategy that requires more traffic.
⚠️ Be careful with multivariate testing not to modify an entire page or email. If there are major differences between the two pieces of content, it greatly distorts the analysis and feedback.
4 tips for successful A/B testing
Test all variables… But one at a time!
You can test many parameters: colors, subject lines, layout, timing, font size, content, frequency. These are all factors that can help increase your conversion, click-through or open rates. Result: the combinations are endless. The more parameters you test, the more you optimize your content. However, you must test the variables one by one so as not to distort the test.
Test all channels
A/B testing works on emails, landing pages, social networks or SMS, for example. As with variables, the more tests you run, the more you will be able to increase your results. For example, a color that works in an email will not necessarily have the same result on social networks!
Which channels can be tested
All communication channels can be tested, and we will explain three of our favorites:
Landing pages?
Several elements can be tested on landing pages. For example, images and CTAs (layout, shape, text).
Emails?
For your emails, it is possible to set up tests on the text, images, CTAs, design, subject line, tone used, time and day of sending. A/B tests on emails help optimize your open rates, your conversion rates, etc.
SMS?
You can run tests on SMS messages. The elements you can test include calls to action, the tone used to address contacts, the text, as well as the time and day the SMS is sent.
Draw conclusions from all the results obtained
You now know which variables to test, how to test them and how to interpret the results of your A/B testing. And each result has an impact: the color of your CTA does not change the click-through rate? Very well, this is a place where you can display your brand guidelines. Is your click-through rate significantly higher when you ask a question? Keep this parameter in your next tests!
You now know everything you need to set up A/B testing and optimize your results.
Bonus tip?
Think about sampling?
Sample size is key for a successful A/B test. The larger your sample, the more statistically significant your results will be. There are tools to calculate the ideal size according to your project, although you can estimate the size yourself. We recommend testing your A/B test on 10% of your sample over a period of 24 hours?
The tools for doing A/B testing
Many tools can help you set up A/B testing easily. Nevertheless, I am going to tell you about Webmecanik Automation, where AB tests can be configured in just a few clicks on the platform. It is even possible to use artificial intelligence to simplify the process.
Optimize your campaigns with AB testing! Set your goals, choose the right key performance indicators (KPIs) and let Webmecanik Automation guide you. By analyzing the detailed results of your tests, you will identify the elements that work best and adjust your strategies accordingly. Result: more qualified leads and a better return on investment.
Also read: how to do A/B testing in your emails with Webmecanik Automation.
