A/B tests in advertising are one of the most common ways to find out which ad headlines, body copy, images, call-to-action, or a combination of the above work best for your target audience. Also known as “split test,” they are essential to determine where you have to invest your budget.
In an A/B test, you show two identical audiences different versions of something at the same time to find out which version drives better results.
Recently, with new Artificial Intelligence tools finally available on the market, you can use AI to run your A/B tests in a much more efficient way.
Results? A higher ROI for your digital marketing campaigns and several working hours and money saved. Follow us to discover why and how you should use AI to run your ads A/B test!
Split testing, or A/B testing, is one of the most diffused marketing techniques. Hubspot defines it as “a marketing experiment wherein you “split” your audience to test a number of variations of a campaign and determine which performs better”.
When you are going to create or send a new marketing element – landing pages, newsletters, or CTA – it may be useful to create two, or even more, versions. In this way, you clearly understand which kind of people are more likely to appreciate the message that you want to transfer.
You may have two landing pages that are identical, except for a detail. It might be the color of the CTA button or the main image. Both versions, however, have the same purpose – the customer has to click on the CTA button and convert.
Once you crafted the two versions of the page, you send them to two different target groups, track their actions, and see what happens. If one of the two versions collects more conversions than the other, you may be pretty sure that the reason lies in that little, different detail. You only have to check which versions people liked the most.
Naturally, it might take a few attempts before you find the best combo, but it is worth trying.
Thanks to A/B testing you can optimize your conversion rate. Not all audiences fancy the same advertising.
You can play with many different elements until you find the perfect formula.
However, even if this technique has been in fashion for years, it is not flawless. To create the different versions will take quite a long time, and it could not even be as useful as you thought.
First of all, it might take a significant amount of time and resources before the A/B tests provide a sufficient amount of data to analyze. This also means that you have to burn a small part of your budget to run campaigns or start activities that will be stopped soon because of their poor results.
Nearly 80% of A/B test variations fail to provide positive results. You can only detect a limited number of variables at the same time, and you can not cross all the data you would need.
Is anyway possible to decrease the number of unsuccessful pilots and point in a quick way to the winning direction? Lucky for all the marketers around the world, this technique exists. Let’s discover together how Artificial Intelligence can make A/B tests for advertising campaigns more reliable, precise, and broad-minded.
How To Optimize A/B Test With AI
It is here that AI and machine learning enter the game. Artificial Intelligence can make the entire test processing more complete and useful for marketers. It is a better choice for many reasons; let’s see some of them.
- Data analysis is faster and more accurate. As we said, one of the worst flaws of A/B tests is that they take a long time for satisfactory results. This time is even longer if you are working on more than one element. AI can work on many fronts, adjusting the parameters by itself – thanks to machine learning – and frees a lot of your time.
- AI can test more variables at once. If you have to confront more than one variable, or if you have to match them with each other, the risk of failure is quite high. You may not understand the real importance of an element or forget a meaningful match. Thanks to AI, you can experiment with a virtually infinite number of variables and see what is different when they change. The structure can handle a complex system. You can match variables with core metrics and select thousands of combinations. In this way, you can spot even minuscule changes.
- Luck is overrated. Thanks to AI, you can conduct a test to analyze more pieces of information. You can allow yourself to experiment more in a low-risk situation with extensive frameworks and wilder hypothesis. Logic and data take the place of guessing.
- The whole funnel can benefit from AI. You can apply the benefits of AI and A/B testing to many elements of your marketing strategy. As we said at the beginning of this article, AI and A/B testing can be useful in email marketing, advertising, and more. Moreover, it allows you to follow almost client by client in their acquisition path.
Have you already implemented the A/B test and AI in your marketing strategies? How is it going?
- A/B tests can help you to make better decisions, and AI can improve their efficacy.
- A/B testing is an inexpensive and useful test, but it’s not infallible. AI can improve its accuracy and analysis power.
- AI can make the entire process more complete. It can also work on many aspects of the marketing strategy.