What is A/B testing ?

Has your company’s marketing developed sufficiently in the last 12 months? Do you know if there are any barriers to sales growth in advertising or on websites? If you answered no even to the second question and the principles of A/B testing are strange, then you should read the text carefully.

The importance of testing and learning is constantly emphasized in marketing. Especially in the field of digital marketing, A/B testing is emphasized, because all digital marketing can provide clear figures on what works and what doesn’t. For this reason, a tour of the world of A/B tests in digital marketing is made.

A/B testing is a comparison

As the name suggests A/B testing it is a comparison that constantly looks for the alternative with better performance. From the comparison a statistical difference can be deduced and it can be seen which of the two options is more profitable in terms of the company’s objectives.

In digital marketing, digital footprints of people’s actions are left, from which clear figures are obtained. This can be used to determine which other marketing message or presentation is more effective.

A/B test example

Let’s say we’re doing A/B testing on Google Adwords advertising. We write two ads that are displayed when customers search for our products. Ad A has a conversion rate of 1 in this case, and Ad B has a conversion rate of 0.5. So Ad A is 100% more effective than Ad B.. When we find that Ad A is statistically significantly more profitable than Ad B, we can disable Ad B. However, this does not mean we are ready. But we are writing ad B instead of the new ad, which will be carried over to the next comparison.

When a new ad B is written, we can take advantage of the information we received from ad A and change some sections. In the new comparison, the new competitor Ad B beats the winning Ad A from the First Round, with a conversion rate of 1.2%.

In this case, two A/B testing comparisons have been obtained. much more effective advertising Other than that, we would have stuck to our luck and written just one ad without A/B testing.

The goal of A/B testing is to get better results

When we start A/B testing, we need to have a clear idea of what we are aiming for. Only with a clear objective can we begin to map the factors that affect it and compare what contributes to the emergence of a positive result.

For example, if the goal is to contact the company through a website, there are already many points along the way that can be improved through A/B testing.

The company can compare different channels like Facebook advertising, Google Adwords advertising, Banner advertising, etc. and see which channel gets the most value for the euro invested.

In-channel testing can also be done by running multiple ads at the same time. By comparing what people prefer to click on and the likelihood of a click converting to a website lead.

It is often forgotten to also test different landing pages, that is, different solutions on the company website for people to contact you on the page. It does not matter how many buying customers visit the website, but if the site does not support contact or purchase, the results may be limited.

Case: A/B Test Results

Test Meters A/B

There can be as many meters as possible, but you should always choose only one meter that is actively monitored. This makes measurement easy and A/B test results easy to express. Normally I prefer direct contacts or trade as a measure. There can be no clearer measure of this for the company and it can be used to calculate the direct effects on the company’s cash flow.

Sometimes direct marketing metrics are too far off or impossible to measure, so you need to choose different measurement techniques, such as which ads are the most popular and bring in the most traffic. You can also test which types of ads are clicked on by the people who enjoy your business website the most. These metrics can be used to measure the effectiveness of an advertising message and the relevance of the ad to the landing page, the page to which the user clicks.

There are countless metrics used in digital marketing. The most important thing is to choose the right metrics that support the objectives of the company and this will allow the marketing to develop statistically based on the accumulated data.

Testing must not stop

Too often I have heard that testing stops after one round and then we are happy with the result. It is thought that the best option was found and now the results have been maximized. Of course, continuous A/B testing required the right tools, as the amount of data grows exponentially after each round of testing. Machine learning is one of the most important tools for A/B testing.

This is a misconception that is causing marketing development to come to a halt. If you have done a test, for example, between two Adwords ads, you only know which of the two options works better. The idea of continuous A/B testing is that the loser is always stopped and a new competitor is written to the winner, with some sections of the winning ad and other sections changing. A new comparison will be made between these announcements. This way you can really find out what works, and with continuous improvement, the results will keep increasing.

If you stop doing A/B tests, you will also stop developing your marketing.

We are living in an age of statistical evidence.

All digital marketing can be tested and thus find the channels that bring effective marketing to the company. For many companies, this testing principle is still strange, but not for long. When you can develop the marketing and analyze the results in light of the figures, the comments of “black sensation” are left aside. If two people are arguing about the best way to market a message, stop the discussion and try it out. It is better to win and your further development will be tested.

As a result, digital marketing is growing rapidly and delivering results for businesses.

A/B Test Example of a Facebook Ad

We always carry out A/B tests on all our clients’ campaigns so that the results obtained with the marketing are in constant evolution.