1. import java.util.HashMap; 
2. // Create the User Attributes object 
3. HashMap<String, String> userAttributes = new HashMap<>(); 
4. // Add the User Attribute values 
5. userAttributes.put("Browser", "Chrome"); 
6. userAttributes.put("Device", "Desktop");
7. userAttributes.put("OS", "Windows 10");
8.  // Activate the FullStack A/B Test Experiment 
9. String variationName = pageSenseClient.trackGoal(experimentName, userId, goalName, userAttributes); 

How this API Works

Audience Targeting

1. If the user’s attributes match the audience targeting conditions, the API proceeds to the next step.
2. If the user does not meet these conditions, the API immediately returns null, indicating that the user is not eligible to be included in the experiment.
   

User Qualification

1. The API checks whether the User Storage Service is enabled. If it is enabled, the API will check for any stored variation for the user. If a variation has already been assigned and stored for the user in the User Storage Service, the API retrieves and returns that stored variation.
   
2. If no stored variation exists, the API proceeds to allocate a new variation using variation bucketing.
   
3. The API applies the MurmurHash algorithm to the user's ID (userId). This hashing algorithm consistently generates a unique numeric value between 0 and 9999 for each user ID, which serves as the user's hash value.
   
4. Each variation within the experiment is assigned a specific range of hash values that corresponds to the variation’s allocated traffic percentage.
   
5. The API checks if the user’s hash value falls within any of these defined ranges. If it does, the user will be considered qualified for the experiment. If the hash value falls outside all assigned ranges, it means the user is not qualified for the experiment and the goals will not be tracked.
   

Tracking and Analytics

Using trackGoal without user attributes

Method:

How the API Works

1. In this version of the API, only the experiment name and user ID are required.
   
2. The audience targeting step is still executed; however, since no user attributes are provided, the user will qualify only for the experiments where the audience targeting criteria is configured as “All Visitors.”
   
3. If the experiment includes any additional audience targeting conditions—such as device type, location, or custom attributes—the user will automatically fail the qualification check due to the absence of user attribute data for evaluation.
   
4. For experiments that allow “All Visitors,” the MurmurHash algorithm is applied to thee User Id to get the User's unique has value based on experiment's traffic allocation. If the user's hash value falls within the defined range of any variation, that user is qualified for the experiment  and the goal conversion details will be sent to the PageSense server.
   
5. If the user's hash value falls outside all defined variation ranges—due to the experiment’s traffic allocation configured, the user will not qualify for the experiment and no goal conversion details will be sent to the PageSense Server.