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Introduction

Software manufacturers make sure that they run all the necessary tests before making software public. It is done to remove all defects and check the progress software is going to make among the masses. During testing, errors in the software points it is failing at, and requirements it is not meeting are all tested. The same applies to applications. A/A test is a kind of test that checks the conversion ratio of a mobile application. For that, two identical applications are tested against each other. Contrary to other tests, this test ensures that there is no difference between the two applications. It tests the accuracy of one with respect to the other. 

What A/A Testing Actually is?

Consider the A/A test as an experiment. During the experimentation process, the accurate or predefined set of variables or subjects, which we can call normal, is considered the control. Anomalies or variation in pre-defined values is tested against the control system. This is mostly done by comparing the overall results of both. The same is applied here. One application is set as the control, and the other is the variable is tested against it. The two versions of the same kind of application are tested and then checked for differences. The expected outcome is no different among them. This test is of high statistical importance and significance. 

Usually, two groups of users are handed over two absolutely identical applications, and they are tested. Both bring their own key performance indicator. If they match, the test comes out right as expected. If they do not match, the users are instructed to find the reason behind an unexpected result.

Why do we Test Identical Pages?

The purpose here is not to identify differences; rather, it is to check the accuracy. Most of the time, it is performed to double-check and find the accuracy of an A/B test. The statistical reports made a post this test should show that both are identical. Any statistical difference found shows that there is some problem. It’s either that the test was not carried out in the right way. Keep in mind that you might find some statistical differences while conducting this test. As we are dealing with statistics here, the result or outcome of the test would be a probability, not a certainty. 

Why is A/A Test Conducted?

This test is conducted under three circumstances:

  • To check the accuracy of the tool being used to perform the A/B test.
  • To finalize an optimal sampling rate and size for future A/B tests.
  • To get the best values for conversion rates for all the future tests.

Accuracy of the Testing Tool

The goal is to get identical values for the conversion rate for the two identical samples being tested. Hence, this proves that the tool used for the A/B test is effective and is producing accurate and efficient results. Sometimes, we might find some variation in the results of both tests. The next goal is to identify the cause or reason behind that change. The results must have shown an identical report. The difference could be due to any reason like:

  • The test was not carried out in the right way.
  • The configuration of the tool is faulty.
  • The A/B test is not effective, or there is some problem with the tool.

Finalizing an Optimal Sampling Rate and Size for Future A/B Tests

The tests are being conducted on the basis of statistics. Wherever statistics are involved, there is a chance of error or defect. However, we can avoid the occurrence of this error by increasing our sampling size. By increasing the sample rate, we can overlook small factors that overall affect the accuracy of our results. Hence, A/A test helps you in deciding the value upon which your test would give a minimum error. 

Finding the Best Value of Conversion Rate

You can conduct an A/B test easily, but there is this problem of knowing the value of a particular conversion rate. The conversion rate is the one that is required to compare your results to. So you can call it a reference to compare your results. A/A test helps you find the best value to compare your results with. 

Benefits of Conducting A/A Test

A/A test can identify errors in your program. Apart from the reasons mentioned, it also allows the user to check if the activity which is being carried out was set up accurately, the code has been applied effectively, and it is also working according to the demands, and finally, the reporting that has been done is accurate. But it also requires special care. You are required to monitor your test continuously. Because checking the test frequently helps you identify the best combination and use it for future tests.

Conclusion 

A few apps like SplitMetrics consider A/A tests a pure waste of time and unnecessary, but it is required to check the cleanliness of your system and the application.

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