Duplicate User Detection

Modified on Tue, 23 Jul at 9:15 PM

Introduction to Comprehensive Guide to Duplicate User Detection

Duplicate User Detection is crucial for maintaining data integrity and preventing fraud in digital marketing. This fraud filter helps identify and block repeated clicks and/or from the same user, ensuring accurate tracking and reporting and optimizing the ad spend.


dupicate user detection


Key Features


Allowed Duplicates

  • Defines the maximum number of clicks permitted from the same user within a specified period.


Lookback Time

  • Establishes the timeframe for monitoring duplicate clicks, typically ranging from a few minutes to several hours.


Detection Levels

  • Offer Level: Limits duplicates per specific offer.
  • Publisher Level: Controls duplicates on a publisher basis.
  • SubID Level: Manages duplicates based on SubID.


Detection Mechanisms and Data Points


The system utilizes various data points to detect duplicates:

  • IP Addresses: Both IPv4 and IPv6 are tracked.
  • UUIDs: Unique user identifiers are monitored.
  • Device IDs: Ensures clicks are coming from unique devices.
  • User-Agent: Detects the browser and operating system used.
  • Fingerprinting: Creates a unique identifier based on multiple data points.


Rules Configuration


Users can define specific rules to tailor the duplicate detection process:

  • Rule Creation: Custom rules can be set based on chosen data points.
  • Application Levels: Rules can be applied at different levels (Offer, Publisher, SubID) to provide granular control.


Practical Application


Setting Up

  • Navigate to the Duplicate User Detection filter settings.
  • Define the allowed number of duplicates and the lookback time.
  • Select the data points to be used for detection (IP, UUID, etc.).


Monitoring and Adjustment

  • Regularly monitor the detection reports.
  • Adjust the settings based on observed patterns and requirements.


Benefits

  • Enhanced Data Integrity: Ensures that data reflects true user interactions.
  • Fraud Prevention: Reduces the risk of click fraud by blocking duplicate clicks.
  • Optimized Campaigns: Helps in better campaign performance analysis by filtering out duplicate clicks.


Conclusion


Effective Duplicate User Detection is essential for any digital marketing strategy, especailly CPC campaigns, to maintain accuracy and prevent fraudulent activities. By leveraging comprehensive detection mechanisms and configurable rules, any can ensure reliable data and optimize their campaigns effectively.



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