OTT Audience Measurement via Demographic Data Intermediary
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Solution Overview
Problem
Over-the-top (OTT) devices lack accurate demographic impression tracking due to their inability to operate with cookies and the difficulty in installing panelist meter software, leading to incomplete and inaccurate demographic data for audience measurement, which affects the accuracy of media exposure metrics.
Innovation Solution
An audience measurement entity (AME) gathers demographic data from OTT service providers and combines it with panelist data to create demographic and viewer assignment models, allowing for accurate attribution of media exposure to specific demographics without the need for software installation on OTT devices, by leveraging user-registration models and external demographic sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If panelist meter software is installed on OTT devices to track demographic impressions, then measurement precision improves, but device complexity and ease of operation worsen due to installation difficulties
Solution Approach 1:
The patent introduces an intermediary measurement system that operates at the network level rather than requiring direct installation on OTT devices. The system uses available household identifiers and demographic data from user registration models as intermediaries to bridge the gap between OTT device usage and demographic attribution, eliminating the need for complex software installation while maintaining measurement capability
Solution Approach 2:
The patent creates a virtual measurement environment by copying and analyzing household identification data and demographic information from external sources rather than installing physical measurement software on the OTT device itself. This allows demographic tracking through data replication and analysis from alternative sources
2Measurement precision
If cookies are used on OTT devices for demographic tracking, then measurement precision improves, but adaptability worsens due to OTT devices' inability to operate with cookies
Solution Approach 1:
Instead of attempting to make OTT devices compatible with cookie-based tracking (adapting the device), the patent inverts the approach by bringing the measurement capability to the data sources that already exist in the system. It uses household identifiers and demographic data from user registration models that are already part of the OTT service infrastructure, eliminating the need for cookie technology on OTT devices
3Measurement precision
If external demographic sources are leveraged to create demographic models, then measurement precision improves, but device complexity increases due to data integration requirements
Solution Approach 1:
The patent creates a universal measurement framework that can process and integrate multiple types of demographic data sources through a single standardized system. The measurement entity develops demographic models that can accommodate various external demographic sources and user registration models, allowing the same infrastructure to handle diverse data types without requiring separate complex integration systems for each source
Data Source
AI summary
Methods and apparatus for over the top (OTT) media measurement are disclosed herein. Example methods include comparing, with an on-site meter in communication with an OTT service provider server, household data maintained by the OTT service provider server with anonymized panelist data provided by an audience measurement entity to identify a first person predicted to be included in a first household according to the anonymized panelist data but not included in the first household according to the household data, accessing media impressions collected by the OTT service provider server and corresponding to media accessed with a first OTT device associated with the first household, and crediting, with the on-site meter, usage of the first OTT device associated with access of the media to the first person based on the media impressions and demographic data obtained from the anonymized panelist data and attributed to the first person.