How to increase the effectiveness of your website and advertising? And how AAB testing — an advanced version of split tests — can help with this

Let’s say you’ve decided to launch an advertising campaign. You have several ideas on how to tap into the “pain points” of your audience and don’t know which one will be better, more effective. AB testing will help you with this question — you will compare the audience’s reaction to 2 hypotheses that could affect your client at once. The tool is simple and straightforward. But there are many such testing options (split tests) — some of them may seem more complicated, more time-consuming and costly, but ultimately more effective! How to understand this? Find out the specifics of each. And we especially recommend paying attention to AAB testing. Let’s understand what it is and what it is suitable for.

You will learn from the article:

1. Why split tests are needed and what types of them are available.
2. What is AAA testing and how it differs from AB tests.
3. How AAB testing works and what it provides.
4. What minimum values are required to evaluate the results of AAB testing.
5. What factors can affect the reliability of AAB test results and how to reduce this impact.

What are the types of split tests and why should you conduct them?

Testing allows us to understand the validity of the hypothesis, to test the idea of an advertising campaign by spending the budget on the material that shows greater efficiency in testing.

For example, an AB test divides traffic between two variables — different advertising materials, creatives, etc. This method allows you to analyze which of the proposed options appeals to your audience more and gives you an understanding of which direction to move in.

AA test — logically, this is a test in which two advertising materials are identical. What is its essence? This test should show the same results in two campaigns, because if they differ, the performance and service where the test is performed cannot be trusted. That is, this is checking the reliability of the testing system itself. Does it do anything but waste your money? It’s unlikely, but it does exist.

AAB test — the algorithm assumes that two advertising materials will be identical, and the third will be variable. We will tell you more about it below.

AABB test — the idea of testing is that it is more accurate, or a verification version of A/B testing. If your project requires it, use it. But we recommend paying more attention to the previous option — AAB test.

What is AAB testing and how does it differ from AB testing?

As in AB testing, in the AAV variant, A is the control group and B is the variable. Only here we have two control groups. This is necessary in order to obtain more reliable benchmarks.

Hence, AB testing is a basic, powerful tool for determining the effectiveness of advertising, marketing, and other campaigns that require hypothesis testing. AAA testing is a more advanced version of testing, which, in addition to comparing the effectiveness of two hypotheses, tests the reliability of the control group and, accordingly, the campaign as a whole.

How does AAA testing work and what does it provide?

AAA testing is carried out using special services, such as Google Optimize, Unbounce, Convert.com. There you can add and track the required number of metrics.

AAA tests require more time and money than AB testing, but they give better results, namely:

• show irrelevance of the testing system, if any;
• provide more solid grounds for choosing a particular hypothesis;
• allow for a more detailed analysis of the indicators that influence conversion.

What are the minimum values required to evaluate the results of AAB testing?

Each project has its own individual values. Determine them before starting AAB testing.

Usually, these are the following indicators:

If you do not have the required number of values, we recommend using the following tips:

• additionally use other methods of hypothesis testing: evaluation of user behavior, surveys, competitor research;
• minimize distortions in future tests;
• do not stop running tests to collect statistics.

What factors can affect the reliability of AAB test results and how to reduce this impact?

To ensure that the results of AAB testing are “clean”, consider the factors that can significantly affect them:

1. Users’ devices.

This determines how the changes will look. For example, on large screens, small details are almost invisible.

2. The effect of novelty.

Users will notice a new element on the site, which will bring good results at first. But soon they will get used to it and stop paying attention to it. 

3. The habituation effect.

It directly follows from the previous one — users get used to a certain element and stop responding to it.

4. The buying cycle.

Before making a purchase, users can go through a certain path:

• awareness of the need;
• choice;
• intention to purchase a product;
• purchase.

Therefore, the test period should not end faster than the final stage of this cycle. If you do not follow this rule, you will get incorrect test results.

5. Cross-browser compatibility.

 This is the ability of a website to display and work equally in all commonly used browsers. During AAB testing, you may encounter that changes will not work properly in one of them.

6. Rotation.

The system or script that handles the rotation may not produce the expected and equal distribution between test blocks.

7. Small amount of traffic or required operations.

Evaluation on insufficient data will be irrelevant.

8. Other changes on the site.

Control all changes on the website during AAB testing, as they can have an impact on the test results. 

Seasonality, sales, changes in inventory, and other factors. The following will help to reduce their impact:

• setting up testing for new or old users separately;
• use of several control systems;
• selecting only one traffic source for testing.

Conclusion

AB is a classic way to conduct testing in marketing. However, the results of AB testing can be distorted due to a number of factors, such as:

• speeding up the conclusions on the part of the client, marketer or other specialist;
• a small amount of data for reliable analysis of the result and, as a consequence — premature conclusions.

To avoid this and to verify the reliability of the data obtained in more detail, it is worth using AAA testing.

AAV tests are not very popular compared to AB testing. The reason is that AAB usually requires more time and money, which small projects cannot always provide.

Therefore, this testing method will be useful for arbitrageurs. Especially those who work with large volumes of traffic for testing.

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