Consumer Graph for Cross-Device Ad Sequencing
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Solution Overview
Problem
Current advertising technologies face challenges in optimizing the delivery of video content across multiple platforms, including TV and online media, due to siloed data systems and lack of accurate cross-platform viewer behavior tracking, leading to inefficient ad placement and repeated exposure to the same ads, which can miss or confuse audiences.
Innovation Solution
A computer-implemented method and system that uses a consumer graph to aggregate data from various devices and platforms, allowing for sequential targeting and delivery of advertising content across multiple devices, including TV and mobile, based on demographic and behavioral data, enabling precise control over ad placement and frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If advertising content is delivered across multiple media platforms (TV and online), then ad reach and audience coverage are improved, but data silos and lack of cross-platform tracking cause inefficient ad placement and repeated exposure to the same ads
Solution Approach 1:
The patent merges data from multiple media platforms (TV and online) into a unified consumer graph that tracks individual consumers across devices. This consolidation eliminates data silos and enables coordinated ad delivery across platforms, resolving the contradiction between expanded ad reach and data integration complexity by creating a single integrated data structure that spans multiple media environments.
Solution Approach 2:
The consumer graph serves as a universal data structure that functions across multiple media platforms simultaneously. It enables the system to track and deliver advertising content across TV, mobile devices, and other platforms using a single unified approach, allowing the same core mechanism to handle diverse media environments without requiring separate tracking systems for each platform.
2Reliability
If the same advertising content is repeatedly broadcast across multiple platforms, then brand awareness is improved, but consumers experience confusion and miss key messages due to fragmented delivery
Solution Approach 1:
The system performs preliminary actions by using the consumer graph to identify and track individual consumers across devices before delivering advertising content. This pre-tracking enables the system to coordinate sequential delivery of ad content across multiple platforms, ensuring that consumers receive a coherent narrative sequence rather than fragmented or repeated exposures, thereby maintaining message coherence while still achieving brand awareness.
Solution Approach 2:
The consumer graph provides feedback mechanisms that track consumer exposure and device usage patterns. This feedback enables the system to adjust ad delivery sequences and ensure that consumers receive the complete advertising narrative across devices, preventing message fragmentation while maintaining consistent brand messaging through data-driven coordination.
3Manufacturing precision
If manual coordination of advertising delivery across platforms is attempted, then ad placement precision can be improved, but the complexity and time required for decision-making increases beyond human capability
Solution Approach 1:
The system implements self-service by using the consumer graph to automatically track consumers, identify optimal delivery sequences, and coordinate ad placement across multiple platforms without human intervention. The automated system processes vast amounts of cross-platform data and makes real-time coordination decisions, achieving high ad placement precision while eliminating the time-consuming manual coordination that would be required for comparable results.
Solution Approach 2:
The patent changes the fundamental parameters of ad coordination by transitioning from manual human decision-making to automated computer-based processing. This parameter change enables the system to handle the computational complexity of tracking consumers across multiple devices and platforms, making precise ad placement achievable at scales and speeds that exceed human decision-making capabilities while maintaining or improving precision.
4Adaptability or versatility
If different versions of advertising content are delivered to different device types, then content relevance is improved, but the complexity of managing multiple content versions and delivery schedules increases
Solution Approach 1:
The consumer graph serves as a universal data structure that enables a single coordinated system to manage advertising delivery across multiple device types. Rather than requiring separate management systems for each device, the unified graph tracks consumers across all devices and coordinates content delivery sequences, reducing content management complexity while maintaining the ability to deliver device-appropriate content versions through centralized control.
Data Source
AI summary
The technology relates to sequential or tailored delivery of advertising content across a plurality of media conduits. The invention achieves sequential story telling for advertising campaigns in place of single-series advertising, by delivering over a period of several sessions on a variety of devices. An advertiser can air a campaign on a consumer individual's cell phone device, continue the second portion of the campaign via a desktop browser session, and conclude with the third portion of the campaign on the individual's OTT device. The technology provides advanced controls over targeting and scheduling with high precision.