Writing recently about landing parties I mentioned that A/B testing is an extremely important part of conversion optimization, or CRO for short. Where I can, I try to remind you of this with the hope that at least a small percentage of you will eventually start using them.
What are A/B tests
A/B testing In the simplest terms, it's two different versions of a page, two different versions of the headline, content, image, etc. that you run for a specific purpose. Let's assume that you have a hypothesis according to which you assume that a different colour of call to action button can be more effective and generate more conversions. So you create an experiment (A/B test) to confirm or refute this hypothesis.
This is the basic version of the test, where you have two versions to verify. However, there are more complex tests, the so-called A/B/n tests, where the versions of the page, headline, colour... can be any number. You can, as an experiment, prepare several colours of CTA buttons and see which one will be the most effective.
Just remember that tests with multiple versions as an experiment work well on sites with high traffic, where you are able to gather enough data for each version to be considered reliable.
This is a common mistake for beginners. The site has little traffic and they launch an experiment consisting of 10 versions. Eventually after a week each version has traffic of say 20 unique views which is far too small a sample size to draw any conclusions.
If instead of 10 different colours you were to run the experiment for 2 for now, note that each colour will have 100 unique visits. This is of course still a small sample, but already much more valuable. Therefore, if your traffic is low and you want to draw meaningful conclusions start with the basic version, i.e. A/B testing.
How to run an A/B test
This is probably one of the main reasons why testing is so rarely used by beginners. We do not know which tools to use, and if we do, they either prove difficult to implement and analyse or too expensive. Eventually we give up, explaining to ourselves that none of our friends runs tests. Crazy time.
In practice you lose a lot by refraining from A/B testing, and in extreme cases the lack of tests and thus of conversion optimisation may lead to closing the business. But then no one who closes such a business will even think about the fact that the scenario might have been different if he hadn't given up A/B testing and strived to optimise conversions.
A/B testing tools free of charge
In fact, I should probably use the singular, as the only sensible and free one I've worked with is Google Optimize. Using this tool, you can run any experiments in a relatively simple way and verify what on your site works and what doesn't.
As you can see in the above screenshot, setting up an experiment consists of several steps. In the first one you create different versions of what you want to test, the next step is targeting rules which means you can narrow down the group of test participants e.g. to people who come to you from a specific URL etc. The next step is to connect with Google Analytics, configure the goal and launch the experiment.
The goal could be, for example, a click on a call to action button or anything else, such as a purchase. This will allow you to verify which of the tested versions best achieves the goal, and this is invaluable information for any online business owner.
A/B testing tools paid
There are many more of them and they compete with each other mainly in the comfort of working and managing experiments and the readability of analytical data, so that it is as easy as possible for you to draw accurate conclusions and, consequently, to make good business decisions related to your website.
Personally, I use a Hungarian tool that used to be very popular in Poland, called Omniconvert. The workflow is very similar to Google Optimize. You can also create arbitrarily large experiments. You can even test multiple changes within a single experiment, although this is usually not the best idea as it is very easy to misinterpret.
The above experiment was basically about one change. The header itself was changed, nothing else. I wanted to check if it would influence the number of clicks on particular buttons of the tested subpage. With the number of UU views as you can see the results are not yet reliable so I have to wait, but if I were to draw conclusions based on them, you can see that the sign up button for free WordPress course is more readily clicked on in the version of the page with the changed header. Whether the coming days will strengthen or blur this result, I do not know, but for now I want you to understand the importance of such tests.
Why A/B tests are ignored
Most often it is due to lack of time. It's not enough that we often create our website ourselves, which can also be optimized if you use my courses, but Krzysiek writes me about conducting A/B tests. Where to find the time for this?
In fact, if you want to time will be found. If you sit down one evening, plan an experiment and implement it, you continue to let it run freely. You come back in a while to the results, analyse, draw conclusions and make changes to the site. All in all, that's two evenings, a lot? With each subsequent test this time will be shorter!
It is also often the case that we are simply afraid of analytics. You are afraid that you will misinterpret something and there will only be problems from it. But if you don't, you'll never learn it, and the consequences can then be even more unpleasant. Each time you run another experiment you will get smarter. Step by step you will come to perfection 🙂 .
A/B testing is also ignored for another reason. You have created a website, you are proud of it. You think it's perfect and you don't want to change anything about it. The fear is that when you run the tests, your vision of a perfect site will be shattered, and you don't let that happen. However, you need to answer the question: what is this page for? Is it there to boost your ego or to make money for you? The truth is that the website is not supposed to please you, because your client is not you. The website has to be effective and achieve the goal you set it.
If it turns out that the tests confirm that the website should look different, and that you don't like this different look at all, then you shouldn't worry about it at all. Write down somewhere on your desk that the website is to grow your business, not to please you or a bunch of your friends!
How often to perform A/B tests
It doesn't stop at one test, testing should be practically an integral part of your ongoing work with the site. You finish one experiment and start another, until you finally reach a level of conversion optimisation that satisfies you. But can you then be done with them? No. Because the world around us is constantly changing. Trends and tastes change. Something that worked yesterday may not bring any benefit tomorrow. That's why you should perform A/B tests regularly to keep the conversion optimisation you've developed as high as possible.
We all want to earn quality links leading to our sites that will improve rankings and increase traffic, so we can grow our business more efficiently.
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