Ad Placement Reservation System for Targeting Precision
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Solution Overview
Problem
Advertisers face difficulties in collecting and processing traffic data and targeting rules from multiple publishers, making it time-consuming and challenging to identify high-return placements for online advertising, with risks of serving errors and discrepancies in advertisement delivery.
Innovation Solution
A method and system for reservation and ranking of placements, which includes receiving placement inventory data, identifying target placements based on advertiser queries, providing reservation data, and reconciling advertisement performance, to automate the placement reservation process and reduce errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If advertisers manually collect and process traffic data and targeting rules from multiple publishers, then they can identify placements for advertising, but the process becomes time-consuming and complex
Solution Approach 1:
The patent introduces an intermediary system that acts as a mediator between advertisers and publishers. This system automatically collects placement inventory data from multiple publishers, processes targeting rules, and identifies suitable placements for advertisers, eliminating the need for manual data collection and analysis while maintaining high accuracy in placement identification.
Solution Approach 2:
The patent replaces the manual mechanical process of collecting and analyzing placement data with an automated computational system. The system uses algorithms to process traffic data, evaluate targeting rules, and identify placements automatically, substituting human effort with machine-based processing that is both faster and more accurate.
2Loss of information
If advertisers manually contact publishers to request placement information, then they can obtain traffic data, but the process becomes difficult and time-consuming
Solution Approach 1:
The patent creates a universal platform that serves multiple functions: collecting placement inventory data from various publishers, storing it in a standardized format, processing targeting rules, and providing it to advertisers. This multi-functional system eliminates the need for advertisers to individually contact each publisher, making data collection easy and accessible.
Solution Approach 2:
The system acts as an intermediary that centralizes placement data from multiple publishers. Instead of advertisers contacting each publisher separately, the intermediary automatically gathers, standardizes, and makes the data accessible to all advertisers through a single interface, greatly improving ease of operation.
3Reliability
If placements are reserved manually with varying availability and pricing, then advertisers can secure placements, but serving errors and discrepancies occur
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors placement performance, serving status, and delivery accuracy. When discrepancies or serving errors are detected, the system automatically adjusts and reconciles the data between advertisers and publishers, ensuring reliable advertisement delivery while managing system complexity through automated feedback loops.
Solution Approach 2:
The patent replaces manual placement reservation and tracking with an automated system that electronically manages reservations, monitors serving status, and reconciles discrepancies. This substitution of manual processes with automated mechanical systems reduces serving errors and improves reliability while managing complexity through systematic automation.
Data Source
AI summary
A reservation system can identify available placements based on targeting criteria provided by advertisers and placement inventory data provided by publishers. The reservation system can receive reservation data for the available placements from the publishers and provide the reservation data with the available placements to the advertisers. The available placements and can be ranked and presented to the advertisers based on a first precision with which the placement can satisfy the advertiser's targeting criteria. A second precision can be determined for each placement that has enabled targeting rules. In turn, the reservation system can rank and present the placements based on the first and second precisions.