Dynamic Floor Pricing for Real-Time Ad Auctions
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Solution Overview
Problem
Internet publishers face challenges in accurately valuing their online advertising inventory, leading to unfair pricing in real-time bidding auctions due to lack of knowledge about impression values, resulting in low clearing prices and unfair compensation.
Innovation Solution
A system and method for determining dynamic market pricing based on real-time and historical auction data, which generates fair prices for publishers and advertisers, allowing for dynamic floor pricing to be applied in real-time auctions, ensuring that publishers receive fair compensation and advertisers pay a fair price.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If publishers set static floor prices with little or no knowledge of impression values, then the pricing system is simple to operate, but the clearing prices are too low and unfair to publishers
Solution Approach 1:
The system performs preliminary actions by collecting historical auction data and computing statistical metrics (mean, median, standard deviation) before the actual auction takes place. This advance preparation enables accurate floor price determination without adding complexity during the real-time auction process itself.
Solution Approach 2:
The patent introduces an intermediary pricing system that acts as a mediator between publishers and advertisers. This intermediary computes fair floor prices based on historical data and market conditions, eliminating the need for publishers to have direct knowledge of impression values while ensuring fair compensation.
2Reliability
If informed advertisers bid based on accurate knowledge of impression values, then advertisers can make informed bidding decisions, but publishers receive unfairly low prices due to lack of valuation knowledge
Solution Approach 1:
The system implements feedback mechanisms by continuously collecting auction data and using statistical analysis to determine fair floor prices. This feedback loop ensures that publishers receive fair compensation based on actual market conditions without needing direct knowledge of impression values, while informed advertisers still operate with accurate information.
Solution Approach 2:
The patent enables the pricing system to serve itself by automatically computing floor prices based on historical auction data and statistical metrics. This self-service capability eliminates information asymmetry, allowing the system to determine fair prices independently without requiring publishers to possess specialized valuation knowledge.
3Productivity
If real-time bidding auctions use second highest bidder pricing with static floors, then the auction process is fast and efficient, but the clearing prices are often too low and unfair to publishers
Solution Approach 1:
The system performs preliminary computation of statistical metrics (mean, median, standard deviation) from historical auction data before the real-time auction occurs. This advance preparation enables the use of accurate, data-driven floor prices without slowing down the real-time bidding process, maintaining both speed and pricing accuracy.
Solution Approach 2:
The patent transforms the floor price parameter from a static, publisher-set value to a dynamically computed value based on statistical analysis of historical auction data. This parameter change enables accurate reflection of market value while maintaining the efficiency of real-time bidding mechanisms.
Data Source
AI summary
A system and methods for generating dynamic market pricing that is fair for both publishers and advertisers and the use of the pricing in real-time auctions. When a user views content over the internet, an online publisher provides content to the user with executable instructions, which notify an advertisement source that there is an impression for filling by an advertiser. The impression is submitted to a real-time bidding market for competing advertisers to bid to fill the impression with an advertisement. The system and methods generate dynamic pricing for the individual competing advertisers and use the dynamic pricing to compare advertiser bids to determine a highest or winning bid and a clearing price associated with the highest or winning bid.