Third-Party Media Recommendation System for Ad Targeting
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Solution Overview
Problem
Conventional targeted advertising systems experience low user engagement due to users often ignoring or not paying attention to advertisements, despite collecting user information for personalization.
Innovation Solution
A system that recommends media, including advertisements, based on scores exceeding a relevance threshold, where the recommendation is generated by a contact's device and transmitted to the user's device, incorporating sender identification and status updates on consumption, leveraging relationships and artificial intelligence for precision targeting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional targeted advertising systems collect user information for personalization, then advertisement selection capability is improved, but user engagement remains low
Solution Approach 1:
The patent introduces a contact as an intermediary who forwards advertisements to the target user. Instead of the system directly targeting the user with personalized ads, the contact acts as a mediator who receives and forwards selected advertisements, thereby improving user engagement while maintaining personalized selection capability
Solution Approach 2:
The patent adds a new dimension to the advertising delivery system by involving a third party (contact) in the delivery chain. This transforms the traditional one-to-one advertiser-to-user model into a three-party system, creating new pathways for advertisement delivery that bypass user ad blindness
2Measurement precision
If advertisements are provided to users based on collected information, then targeting precision is improved, but users ignore or pay little attention to advertisements
Solution Approach 1:
A contact serves as an intermediary who receives advertisements from the system and forwards them to the target user. This intermediary approach transforms cold system-generated ads into warm personal recommendations, significantly improving user attention while preserving targeting precision through the system's selection algorithms
Solution Approach 2:
The system creates a copy of the advertisement delivery process through the contact. The contact receives a copy of the selected advertisement and forwards it to the user, transforming the delivery mechanism while maintaining the core targeting functionality
Data Source
AI summary
Aspects of the subject disclosure may include, for example, receiving, from a first client device, a recommendation pertaining to an advertisement, storing a sender identification in association with an identification of the advertisement, wherein the sender identification includes an identification of the first client device, an identification of a first user of the first client device, or a combination thereof, determining that a score associated with the recommendation exceeds a threshold at least in terms of a likelihood of relevance of the advertisement to a second user of a second client device, based on the determining, transmitting the advertisement to the second client device based on the identification of the advertisement, and based on the determining, transmitting the sender identification to the second client device. Other embodiments are disclosed.