In-Vehicle Media Monitoring Using Telemetry-Based Demographic Estimation
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Solution Overview
Problem
Existing vehicle telemetry data lacks accurate demographic information for vehicle occupants, limiting targeted media delivery and advertising effectiveness.
Innovation Solution
A neural network is trained using linked panelist-telemetry data to estimate demographics of vehicle occupants, associating telemetry data with demographic information to provide targeted media and advertisements based on estimated demographics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If vehicle telemetry data is collected for media delivery, then media serving capability is improved, but demographic information accuracy deteriorates
Solution Approach 1:
The patent introduces panelist data as an intermediary element that bridges the gap between telemetry data and demographic information. Panelists are selected users who provide demographic data that can be associated with their vehicle's telemetry data, serving as a mediator to infer demographics for non-panelist vehicles. This allows the system to maintain media serving capability while improving demographic accuracy through statistical inference from the panelist subset.
2Productivity
If targeted media delivery is implemented, then advertising effectiveness is improved, but system complexity increases
Solution Approach 1:
The patent applies partial action by implementing targeted media delivery for only a subset of users (panelists) rather than requiring complete demographic data for all users. The system collects detailed demographic information from panelists and uses this partial data set to create targeted advertising campaigns, achieving improved advertising effectiveness without the complexity of comprehensive demographic collection and processing for the entire user base.
Data Source
AI summary
Example methods, apparatus, systems, and articles of manufacture are disclosed for network-based monitoring and serving of media to in-vehicle occupants. An example method includes linking panelist data corresponding to media exposure to first telemetry data collected by a vehicle to create linked panelist-telemetry data; and training a neural network to estimate vehicle occupant demographics based on second telemetry data using a first subgroup of the linked panelist-telemetry data.