Attribution Server Cross-Device Content Exposure Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Content marketers face challenges in tracking viewership and attributing ad exposure to content consumption across multiple devices, leading to inefficient digital advertising and difficulty in identifying likely viewers for new content, due to the complexity of coordinating messaging across different mediums and technologies.
Innovation Solution
A method and system for content exposure attribution that determines associations between devices based on shared identifiers and geolocation, allowing for the tracking of content renderings across multiple devices and attributing value to media placements, using a relevancy-matching server to communicate targeted data to devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If content marketers track viewership across multiple devices using traditional methods, then they can identify some audience behavior, but the complexity of coordinating messaging across different mediums and technologies makes tracking inefficient and attribution difficult
Solution Approach 1:
The patent introduces an attribution server as an intermediary component that receives data from multiple devices and content delivery networks. This server consolidates viewing data, device identifiers, and content information into a unified attribution system, simplifying the complex task of tracking viewership across heterogeneous devices and mediums while improving measurement precision.
2Productivity
If digital advertising targets consumers across multiple devices, then ad reach is expanded, but the organization lacks data associated with consumers who have previously seen advertisements on one device before watching content on a different device, leading to inefficient spending
Solution Approach 1:
The patent implements a feedback mechanism where the attribution server continuously receives data about content viewing events, device identifiers, and advertisement exposures. This feedback loop enables the system to learn consumer behavior patterns across devices, allowing organizations to optimize advertising spending by targeting consumers who have previously engaged with content or advertisements, thereby improving advertising efficiency while recovering previously lost behavioral information.
3Productivity
If the organization spends substantially in purchasing digital advertising to promote content, then content visibility is increased, but the organization is unaware of the efficacy of ad exposure leading to purchase and actual viewing of content
Solution Approach 1:
The attribution server establishes a feedback system that tracks content viewing events and correlates them with advertisement exposure data. By receiving continuous streams of viewing information, device identifiers, and content metadata, the system provides organizations with actionable insights about ad efficacy, enabling them to measure the direct impact of digital advertising on content consumption and optimize future promotional campaigns accordingly.
Data Source
AI summary
A method of an attribution server is disclosed. The method includes determining that one or more request(s) is received through the computer network from a first device based on accessing first data related to renderings of a first content on the first device, and determining rendering of a second content on a second device based on accessing second data related to renderings of content on the second device. The method also includes determining that the first content and the second content are related, determining likely association of the first device and the second device with a same user, and determining that the same user is likely to have rendered the second content on the second device based on exposure thereof to the first content on the first device.