Product Network for Accurate Ad Targeting
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Solution Overview
Problem
Existing online advertising systems lack the ability to accurately determine the interest of customers in related products, leading to inefficient ad placement and reduced revenue, as they rely on limited data such as previous searches and demographics without access to customer purchase history.
Innovation Solution
A system where a service provider maintains a product network based on customer purchase history, using a propensity model to calculate a recommended bid amount for third-party entities, allowing for more accurate ad targeting by identifying related products that customers are likely to be interested in.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If online advertising systems use limited data such as previous searches and demographics for ad targeting, then the system complexity remains low, but the accuracy of determining customer interest in related products deteriorates
Solution Approach 1:
The system performs preliminary actions by maintaining a product network based on customer purchase history before ad targeting decisions are made. The product network pre-establishes relationships between products and customers, enabling more accurate interest determination without increasing real-time processing complexity.
Solution Approach 2:
The patent introduces a product network as an intermediary structure that connects customer purchase history with ad targeting decisions. This intermediary layer processes and structures the data relationships, allowing accurate customer interest determination while managing system complexity through organized data representation.
2Measurement precision
If the system processes bid requests in real-time without pre-computed product networks, then the processing speed is high, but the accuracy of ad targeting deteriorates
Solution Approach 1:
The system performs preliminary computation by maintaining product networks based on customer purchase history in advance. This pre-computation stores structured relationships between products and customers, enabling fast and accurate ad targeting decisions when bid requests are received without requiring complex real-time analysis.
3Productivity
If third-party entities perform all bid request processing independently, then the system architecture remains simple, but processing congestion increases and efficiency deteriorates
Solution Approach 1:
The patent merges the product network maintenance function into the service provider's infrastructure, combining data processing capabilities across multiple entities. This consolidation allows third-party entities to leverage pre-computed product networks, reducing their individual processing loads and eliminating congestion while maintaining architectural simplicity through shared resources.
Data Source
AI summary
A system for maintaining product networks to provide recommendations for bid amounts to third party entity devices. A service provider entity device tracks product purchase history for customers and determines relationships associated with products purchased by the customers. When a webpage is loaded by a customer device, a third party entity device receives a bid request from a publisher device and transmits a bid recommendation request to the service provider entity device. The service provider entity device determines input features including a base bid, a propensity score, and a pacing score based on the relationships. The service provider entity device transmits a bid recommendation response with a recommended bid amount to the third party entity device, based on the input features.