User Identification App for Shared Device Audience Measurement
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Solution Overview
Problem
Existing audience measurement methods fail to accurately identify individual users of applications and media channels on shared electronic devices, such as tablets and smart TVs, leading to inaccurate data on consumer exposure to advertisements and media usage.
Innovation Solution
A user-identification application is implemented on devices to associate users with applications and media channels by collecting user input during setup, allowing for real-time identification of users without requiring self-identification, and updating associations as new applications are launched or installed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional audience measurement methods are used on shared devices, then device-level media consumption can be tracked, but individual user identification accuracy deteriorates
Solution Approach 1:
The system segments user identification by creating separate user profiles and associating specific applications with individual users. The user-identification application divides the shared device usage into distinct user sessions, tracking which user is using which application at any given time, thereby achieving accurate individual user identification on shared devices.
Solution Approach 2:
The system performs preliminary user setup and application association before actual media consumption occurs. During the setup phase, users are registered and their preferences are captured, and applications are pre-associated with users based on this information. This preliminary action enables automatic user identification during subsequent usage without requiring real-time intervention.
2Measurement precision
If user self-identification is required for each application launch, then accurate user-to-application associations can be established, but user convenience deteriorates
Solution Approach 1:
The system captures user preferences and performs application associations during the initial setup phase, before users need to use the applications. This preliminary action stores user-to-application mappings that are automatically applied during subsequent launches, eliminating the need for repeated user input and maintaining both accuracy and convenience.
Solution Approach 2:
The user-identification application automatically performs user identification and application association without requiring manual user input during each application launch. The system uses pre-captured user preferences and stored associations to self-determine which user is using which application, providing accurate tracking while maintaining ease of operation.
3Ease of operation
If real-time user identification is implemented without self-identification, then user convenience is improved, but identification accuracy may deteriorate
Solution Approach 1:
The system performs preliminary user setup and preference capture during installation, storing user-to-application associations before real-time tracking begins. This preliminary action creates a database of user preferences that the automatic identification system relies upon, ensuring that real-time identification is both non-intrusive and accurate based on pre-established user behavior patterns.
Solution Approach 2:
The system incorporates feedback mechanisms where user corrections or confirmations of automatic identification can be captured and used to refine future identification accuracy. This feedback loop allows the system to learn from user responses and improve its automatic identification algorithms, maintaining accuracy while minimizing user input requirements.
Data Source
AI summary
Methods and apparatus are disclosed to identify users associated with device application usage. A disclosed example method involves obtaining demographics of persons to participate in a panel for an audience research study, identifying a set of applications to be monitored, providing devices associated with the persons in the panel with a meter to record usage of the applications and with a user-to-application associator, the user-to-application associator to define associations between the applications to be monitored and the persons associate with the device before the applications are launched, receiving data from a first one of the devices identifying a first one of the persons as a primary user of a first one of the applications in the set of applications, receiving data from the first device identifying usage of the first application, and associating the demographics of the first person with the usage of the first application.