Traffic Distribution Result

Traffic distribution into the different test groups of the A/B test.

When conducting an A/B test, not only do you need to distribute your users to different test groups, you also need to write a logic for each test group. After the integration stages, the distribution of users into different test groups can be done through the Hackle SDK.

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Test Groups

The test groups are basically the different groups that are exposed to the versions (features, screens, algorithms, etc) of a page of an experiment. Test groups include both the control test group A and treatment test groups B, C, D, etc., that are exposed to the "improved" versions of the pages.
The test groups can be set on the dashboard and further information on the test groups can be found on the What is a Test Group? document.

variation

By passing the experiment key to the variation() method, you can distribute users and receive the result for the specific experiment. After that, Hackle will implement the logic of the page/feature version corresponding to each test group.

In the example code below, we are passing an experiment key of 42, and there are two test groups, A and B.

// Determines the test group to assign the user in an A/B tests with an experiment key of 42.
// For undetermined cases, the user is returned to test group A.
Variation variation = hackleApp.variation(42);

// Logic for the assigned test group.
if (variation == Variation.A) {
  // Logic for test group A
} else if (variation == Variation.B) {
  // Logic for test group B
}
// Determines the test group to assign the user in an A/B tests with an experiment key of 42.
// For undetermined cases, the user is returned to test group A.
val variation = hackleApp.variation(42)

// Logic for the assigned test group.
if (variation == Variation.A) {
  // Logic for test group A
} else if (variation == Variation.B) {
  // Logic for test group B
}

variationDetail

The variationDetail() method works the same as the variation() method but provides the reason for a user being distributed to a specific group. This method can be a useful tool to see if the distribution is working properly.
You must pass the experiment key as a parameter. For the example code below, we are passing experimental key 42.

// Traffic distribution details 
Decision decision = hackleApp.variationDetail(42);

// Test group determined from distribution
Variation variation = decision.getVariation();

// Reason for distribution to a test group
DecisionReason reason = decision.getReason();
// Traffic distribution details 
val decision = hackleApp.variationDetail(42)

// Test group determined from distribution
val variation = decision.variation

// Reason for distribution to a test group
val reason = decision.reason

You will receive the reason for the distribution or the allocation of a specific user to a specific test group in the form of SDK_NOT_READY. Please refer to the table below for the full list of different distribution reasons.

ReasonDescriptionDistribution Result
SDK_NOT_READYThe SDK is not ready to use.
(e.g. initialized with the wrong SDK key)
(control) Test Group A
EXPERIMENT_NOT_FOUNDNo A/B tests were found for the experimental key you passed.
The experiment key may be incorrect or the experiment may be in the archive status.
(control) Test Group A
EXPERIMENT_DRAFTThe A/B test is ready to start.(control) Test Group A
EXPERIMENT_PAUSEDThe A/B test has been paused(control) Test Group A
EXPERIMENT_COMPLETEDA/B test has ended.Final winning test group from the experiment
OVERRIDDENUsers are distributed to a specific test group by manual assignment.Manually assigned test group
TRAFFIC_NOT_ALLOCATEDA/B test is running, but user has not been assigned to the experiment.(control) Test Group A
TRAFFIC_ALLOCATEDUser has been assigned to A/B test.Assigned test group
VARIATION_DROPPEDThe test group was removed from the A/B test.(control) Test Group A
EXCEPTIONAn unknown error has occurred.(control) Test Group A