What is A/B testing? Three facts and three most common mistakes 

If you want to make your cash flow grow, enable A/B testing. Testing can tell you what works and what doesn’t - you don’t have to guess what your customers like and what elements on your website, for example, make them buy. Without testing your options, you’ll be running around blind, writing content for your website that doesn’t actually work, or choosing a Facebook ad that is quite uninteresting in the eyes of your target audience.

A/B testing means testing alternatives

As the name implies, A/B testing means testing alternatives. For example, these options are shown to website visitors or the target audience of the ad, after which decisions are made based on their behavior to see if Option A or Option B works better.

You can use a tool like Google Optimize to do your A/B testing. Whether it’s testing a website, a Facebook ad, or a newsletter, it’s a good idea to think carefully about what you want to test. You can test, for example, a button and its placement and color, title, body text or image.

A/B testing provides valuable insight into customer behavior. Do customers click more on the black or blue button? Is the bounce rate higher when the landing page image is a cat than when it is a dog? In all its simplicity, A/B testing gives an idea of ​​customer preferences and buying behavior.

A/B testing is not rocket science

Finally, a tool that makes it easy to make decisions and yet easy to use! You can compare the effectiveness of your advertising channels - is Facebook or Google bringing money more efficiently? At its simplest, A/B testing is a change in the color and placement of the Buy button found on a website or newsletter that is tested in two different versions for the same audience. Option A can be a powerful black button with white text placed at the top, while Option B can charm the audience with its bright blue color along with white text, this time placed at the bottom.

A/B testing is statistics

A/B testing is not rocket science, but statistics. The results must be interpretable in order for testing to be useful. The technical construction of the test is often painless, while analyzing the results can really be a headache. 

However, A/B testing is easy to measure - you just have to know what it does.

It is easily measurable

A/B testing is easily measurable. Choose one thing to measure instead of several. You can choose, for example, a purchase or a contact as a metric, not both. Analyzing just one metric is much easier than trying to analyze multiple metrics. 

When advertising directly, a smarter metric can be popularity or traffic. In this case, the metric used is which ad is the most popular among the target group, or which ad generates the most traffic. Thus, A/B testing measures the effectiveness of an ad or landing page, for example, and helps make decisions based on customer behavior, rather than purely guessing or hoping for the best results. When data drives decisions, there are often good ones for business.

3 of the most common A/B testing errors

You can learn from mistakes, but some of them can also be cleverly circumvented. Kubla has compiled the three most common mistakes that can easily happen during the first tests.

1. Target group too small

You don’t need a target group of thousands, but it needs to be big enough. If the set to be tested is too small, there may be more people in the group who have already made their buy decision beforehand. In this case, the test result is distorted, and incorrect decisions are made on the basis of it. The target group to be tested must therefore be a flat, random group and, above all, of a suitable size.

2. Too little change

If the change between options A and B is so small that it is not even apparent to the naked eye, the results should not be relied upon. The change should be clear and easy to detect so that decisions can be made based on testing. Testing A/B with too little change can make the success of the second option completely different from the achievement of the thing than the change itself.

3. You are doing your test at different times

You always need to test option A at the same time as Option B. If you perform the A/B test at a different time, the result of the other option may be affected by, for example, the day of the week or the weather. Therefore, it is always a good idea to test at the same time so that it makes sense to analyze and make use of the results.

Successful AB testing under professional guidance

Kubla marketing is a professional in marketing development and therefore also in A/B testing. You have to test different options. Don’t do this and you’ll be left behind in development. A/B testing plays an important role in growing your business - you will understand at the latest when you see the results of testing with your own eyes! Sounds interesting? Contact us today!

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