Psychographic Device Fingerprinting for Accurate Viewership Tracking
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Solution Overview
Problem
Current methods for determining viewership of video entertainment, such as the Nielsen system, are unreliable and inadequate for tracking viewership on diverse computing devices, especially with the rise of streaming video and varied device types, as they fail to accurately differentiate among multiple users of shared devices and account for new digital broadcasting standards.
Innovation Solution
The generation of psychographic device fingerprints, which combine device hardware parameters and behavioral data, to uniquely identify users or user groups on shared computing devices, enabling accurate viewership tracking and targeted content delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional Nielsen rating systems (diaries or set meters) are used to collect viewership data, then data collection can be implemented, but the accuracy and reliability of viewership measurement deteriorates due to human error, device compatibility issues, and inability to differentiate users on shared devices
Solution Approach 1:
The patent changes the measurement parameters from simple device-level detection to multi-dimensional psychographic profiling. By collecting and analyzing multiple parameters (device hardware specifications, software configurations, user interaction patterns, browsing history, and behavioral characteristics), the system transforms inadequate single-parameter viewership data into comprehensive multi-parameter psychographic profiles that accurately identify individual users and their preferences across diverse computing devices
Solution Approach 2:
The patent creates a composite measurement approach by combining multiple data sources and detection methods. The psychographic device fingerprinting system integrates device hardware parameters, software environment data, and observed user behavioral patterns into a composite identification profile. This composite approach compensates for the weaknesses of individual measurement methods and achieves both high accuracy and reliability in viewership measurement
2Reliability
If set meters are deployed to automatically monitor TV viewing, then human error in data collection is eliminated, but the system fails to adapt to new digital broadcasting standards and diverse computing devices
Solution Approach 1:
The patent implements a universal measurement system that functions across multiple device types and platforms. The psychographic device fingerprinting methodology is designed to work on various computing devices (personal computers, laptops, tablets, smartphones) and adapts to different operating systems and browsers. The system collects device-specific parameters and creates standardized psychographic profiles that are universally comparable, enabling consistent viewership measurement across the entire ecosystem of digital devices without requiring device-specific implementations
Solution Approach 2:
The patent creates a dynamic measurement system that automatically adapts to changing device configurations, software versions, and broadcasting standards. Rather than requiring manual updates for each new device type or standard, the system dynamically collects current device parameters, learns user behavioral patterns in real-time, and automatically adjusts its measurement approach. This dynamic adaptation ensures continuous compatibility with emerging technologies while maintaining reliable and consistent data collection
3Device complexity
If device fingerprinting uses only hardware parameters, then device identification is simple, but it cannot differentiate among multiple users of the same device
Solution Approach 1:
The patent segments the identification process into distinct layers: device-level fingerprinting using hardware parameters, and user-level psychographic profiling using behavioral data. This segmentation allows the system to first identify the device through relatively simple hardware parameters, then differentiate individual users on that device through analysis of their unique interaction patterns, browsing preferences, and behavioral characteristics. The segmented approach maintains system simplicity while achieving precise user identification
4Measurement precision
If psychographic device fingerprinting combines multiple data parameters, then user identification accuracy improves, but system complexity increases
Solution Approach 1:
The patent introduces intermediary components that simplify the collection and processing of multiple data parameters. Browser plugins or device agents serve as intermediaries between the various data sources (hardware, software, user behavior) and the central analysis system. These intermediaries automatically collect and standardize parameters locally, performing preliminary processing and filtering before transmitting consolidated data to the server. This intermediary layer reduces the complexity burden on both the client devices and the central system while enabling comprehensive multi-parameter analysis for accurate user identification
Data Source
AI summary
A system for generating a psychographic device fingerprint includes a server in communication with a network and memory storing a program which, when executed by the server, performs steps for (a) detecting reception at a computing device of media content delivered via the network, (b) reading device elements stored on the computing device, (c) reading a geographic indicator from the computing device, (d) reading a content indicator identifying the media content, (e) determining a timing parameter associated with reception of the content at the computing device, and (f) deriving from the device type, the geographic indicator, the content indicator, and the timing parameter, the psychographic device fingerprint as computer readable code uniquely identifying a user of the computing device. The steps may further include recording media content received by multiple computing devices, and generating a viewership report relating computing devices and psychographic device fingerprints to the media content received.