A/B testing in web analytics

Online marketers are constantly on the lookout for innovative techniques and concepts that will help them take their marketing campaigns to the next level. The ultimate goal is to increase the company’s revenue through improved conversion rates. To achieve this, marketers must learn to understand their target audience and find out what really appeals to visitors. To achieve repeatable success, it is important not to rely on gut instinct. Instead, you should create a detailed marketing strategy that includes meaningful analytics and reports as well as statistics to minimise your risks. One method that has become a real darling in digital marketing is A/B testing. But what are A/B tests and how do you best use this testing method?

What does A/B testing entail?

A/B testing is a testing method that is used  in the performance marketing and web design. The concept is also known as split testing. Two different versions of a mobile app or website are directly compared with each other. The different versions are called A and B and are randomly displayed to the visitors. The aim is to find out which version of the website or mobile app performs better throughout the test. The test data is usually recorded using one or more tools. The subsequent evaluation and analysis of the data is in turn based on predefined metrics and reports, which ideally have already been determined in the marketing strategy. Depending on the purpose and goal of the test, it is possible, for example, to check which variant achieved the most clicks, purchases or registrations.

Where is split testing used?

While split testing was predominantly used in software engineering just a few years ago, it is now an important part of performance marketing and digital analytics. As a rule, not the entire website or mobile app is tested, but only a single element. Popular test objects are for example:

  • Color schemes and designs
  • Slogans
  • Newsletters
  • Call to action
  • Advertisements and banners
  • Landing pages
  • New features and functions
  • For a meaningful test, only one element may be changed in the version.
  • This is the only way to clearly determine whether the change also led to a change in user behavior.

What does multi variate testing (MVT) entail?

Multivariate testing is a technique for testing more than one variant of a hypothesis. Unlike split testing, multiple variables are tested together to find the ideal combination. This allows descriptions, videos, banners, or headers and footers to be tested together. If the test method is executed optimally, no further split tests are necessary. This approach reduces the time required and at the same time provides detailed insights into the user behaviour of the target group. Used continuously, it is possible to sustainably increase the conversion rate.

Which tools are used for A/B testing?

Every company is unique and subject to constant change. Therefore, in order to obtain useful test results, individual solutions are required, which are developed based on the company’s own requirements. A popular alternative to paid applications is Google Optimize, which works seamlessly with Google Analytics. However, the range of functions of the free program is limited, which means that
analyses can only be carried out to a limited extent. For a detailed and comprehensive evaluation, it is therefore recommended to use a professional application. Popular software solutions that are suitable for split testing are, for example:

    • Crazy Egg
    • AB Tasty
    • Webtrekk/MAPP
    • HubSpot
    • Optimizely
    • VWO
    • Freshmarketer
    • Omniconvert
    • etracker

The applications have different strengths and weaknesses as well as different focuses. For example, Crazy Egg or HubSpot are particularly suitable for those who want to improve landing pages or usability. Those who want to check dynamic websites should, in turn, take a look at Optimizely. Applications such as VWO, AB Tasty, Freshmarketer and Omniconvert are available for simple and fast evaluation of conversions and click rates as well as for optimisation. All applications score with their practical functions which are easy to use.

How to plan A/B tests?

Since split testing or A/B testing is usually more time-consuming and cost-intensive than classic testing measures, the individual tests must be planned in detail. The cornerstone is comprehensive research. Hypotheses are created on the basis of the research. The hypotheses show which options can achieve the best results. Subsequently, the two most promising hypotheses are selected, implemented and tested. For informative test results, the tests must be run until sufficient test data is available for both variants.

Which advantages and disadvantages to expect from the different test methods?

The use of A/B testing has all sorts of advantages for marketers. For example, it is possible to obtain an objective view of the versions to be tested. Furthermore, one gains insights into the preferences and interests of the target group, whereby the results can be implemented immediately. In addition, the tests can be conducted without prior technical knowledge, offering maximum flexibility. However, the use of the test method only makes sense if one wants to compare individual objects with each other. If several elements are changed at the same time, the results of the web analysis are no longer clear. To not confuse existing customers with constant changes, the tests should be performed on new customers. The size of the sample is also crucial for meaningful test results. As traffic decreases, so does the relevance of the test results.


Split testing is one of the best methods for making sustainable decisions in performance marketing. This approach offers marketers the chance to get to know their customers better and understand what needs and habits their visitors have. This leads to more targeted marketing and also reveals untapped opportunities and potential. For these reasons, A/B testing should not be missing from any future-oriented marketing strategy. However, the introduction of the test method takes time. Thus, framework conditions have to be created and processes have to be established so that the strength of the concept can fully unfold.

Are you curious and would like to learn more about split testing? Then contact us by phone or via our contact form. Our experienced team of experts will be happy to take time for you and support you in conversion optimisation using A/B testing.


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