Server-Side Sessionizer Engine for Disambiguating Coupled Event Statistics
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Solution Overview
Problem
Existing analytical systems face ambiguities in tracking data due to coupled event statistics across sub-properties and stateless environments, leading to inaccurate event quantification and session identification, particularly in cookie-based and cookieless scenarios.
Innovation Solution
Implementing a sessionizer engine in the analytics system to receive and process tracking data communications, disambiguating coupled and stateless event statistics by ordering them based on event times, and deriving decoupled and state-dependent statistics to accurately quantify events for each sub-property or property, without requiring changes to existing tracking code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If event statistics are coupled and aggregated at client side across sub-properties, then tracking coverage is improved, but measurement precision deteriorates due to ambiguous event quantification
Solution Approach 1:
The patent segments the coupled event statistics by creating separate event streams for each sub-property. The sessionizer engine divides the aggregated statistics into distinct components, assigning events to specific sub-properties based on session context and timing information, thereby resolving the ambiguity while maintaining comprehensive tracking coverage
Solution Approach 2:
The sessionizer engine acts as an intermediary between the coupled event statistics and the final disambiguated results. It processes the aggregated data through session context analysis and timing-based disambiguation, transforming ambiguous coupled statistics into precise sub-property-specific measurements
2Duration of action of stationary object
If cookies are used for tracking, then event statistics can be persisted across sessions, but device complexity increases due to client-side logic requirements
Solution Approach 1:
The patent extracts the sessionization and disambiguation logic from the client-side tracking code and relocates it to the server-side sessionizer engine. This extraction eliminates the need for complex client-side cookie management while maintaining tracking persistence through server-side session context
Solution Approach 2:
The server-side sessionizer engine performs self-service by automatically analyzing timing patterns and session contexts to disambiguate events. This eliminates the need for client-side interpretation logic, as the system self-determines event attribution based on received timing and session data
3Adaptability or versatility
If stateless event statistics are processed, then adaptability to cookieless environments is improved, but measurement precision deteriorates due to lack of state information
Solution Approach 1:
The patent applies preliminary action by using timing-based disambiguation to reconstruct state information before final event attribution. The sessionizer engine analyzes timing patterns in advance to infer session contexts and event sequences, enabling precise measurement even in the absence of persistent state data from cookies
Data Source
AI summary
Tracking data communications are received for single properties that include ambiguous event statistics. The event statistics are disambiguated by an analytics processing system by identifying account and visitor identifier pairs from account identifiers and visitor identifiers in the tracking data communications. For each account and visitor identifier pair, ambiguous event statistics are ordered by the corresponding event times and disambiguated.