Probability of Presence Determination via Beacon Instructions
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Solution Overview
Problem
Current media monitoring methods, such as server logs, are prone to over-counting and under-counting errors due to tampering and caching issues, and audience measurement entities lack accurate demographic data for non-registered users, leading to incomplete media exposure metrics.
Innovation Solution
The system employs beacon instructions to collect media monitoring data from Internet-connected devices, leveraging database proprietors' cookies to identify users and redirect unregistered devices for demographic data collection, enabling the determination of probability of presence by comparing demographic and non-demographic impressions across devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional server logs and panel member monitoring are used, then media exposure metrics can be collected, but accuracy is reduced due to over-counting and under-counting errors from tampering and caching issues
Solution Approach 1:
The patent introduces beacon instructions as an intermediary mechanism embedded in media content. These beacons are executed by media presentation devices and transmit standardized exposure data to the AME, eliminating direct reliance on vulnerable server logs. The beacon acts as a trusted mediator that ensures accurate tracking without tampering or caching interference.
Solution Approach 2:
The system creates a virtual copy of the media exposure event through beacon instructions that replicate the essential exposure data (content ID, timestamp, device ID). This digital copy is transmitted to the AME for processing, allowing verification and cross-referencing without modifying the original media delivery, thus preventing both over-counting and under-counting errors.
2Loss of information
If only registered panel members are monitored, then demographic data can be obtained, but coverage is limited resulting in incomplete media exposure metrics
Solution Approach 1:
The beacon instruction system serves multiple functions: it tracks registered panel members, identifies non-registered users through device fingerprints, and collects demographic data from both groups. This universal approach allows the AME to process exposure data from any media presentation device regardless of user registration status, eliminating the limitation of traditional panel-only monitoring.
Solution Approach 2:
The system performs preliminary identification and data collection for non-registered users through device fingerprinting and cookie retrieval before the actual media exposure measurement. By pre-establishing user profiles and demographic associations, the system ensures that when exposure events occur, complete demographic data is already available for analysis, preventing information loss.
3Measurement precision
If beacon instructions are used to track unregistered devices, then user presence can be determined, but system complexity increases due to cookie retrieval and device fingerprinting
Solution Approach 1:
The system leverages existing web technologies (cookies, device fingerprints) that are already present in users' browsers and devices. Rather than implementing complex new tracking mechanisms, the beacon instructions utilize these self-existing identifiers to identify and track users. This self-service approach minimizes additional system complexity while maintaining high measurement precision.
Solution Approach 2:
The beacon instruction acts as a simplified intermediary that consolidates multiple identification methods (cookies, device fingerprints) into a single standardized data transmission protocol. This intermediary layer manages the complexity of retrieving and correlating various user identifiers without requiring the AME to directly handle complex device-level tracking operations.
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture are disclosed for determining a probability of presence for a user of a first device at a second media presentation with a second device. An example apparatus includes memory, instructions in the apparatus, and processor circuitry to execute the instructions to determine a first probability of presence based on a first demographic impression, a non-demographic impression, and a shared data item, the first demographic impression logged by a database proprietor for a first device, the shared data item provided by the first device, the first probability of presence indicative of a likelihood that a user of the first device corresponds to the non-demographic impression.