Inferred Sales Estimation for Dynamic Ticket Pricing
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Solution Overview
Problem
In the event ticketing market, brokers face challenges in determining optimal pricing due to fragmented data and lack of visibility into secondary market sales, leading to inefficient transactions and inaccurate pricing strategies.
Innovation Solution
A market evaluation system that uses a database and processor to analyze market data by comparing snapshots over time, assigning scores to determine inferred sales, and updating sales databases, allowing for dynamic and automated pricing strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If brokers rely on traditional manual pricing methods using limited visible data, then pricing decisions can be made with simple processes, but pricing accuracy and transaction efficiency deteriorate due to fragmented market data and lack of sales visibility
Solution Approach 1:
The patent introduces an intermediary system (market evaluation system with processor and database) that mediates between fragmented exchange data and broker pricing decisions. This intermediary aggregates data from multiple exchanges, infers sales from listing disappearance patterns, and provides synthesized pricing intelligence, resolving the contradiction by adding analytical complexity only where needed to transform raw data into actionable pricing insights
2Loss of information
If brokers implement comprehensive market monitoring across all exchanges, then data completeness improves, but system complexity and computational resources worsen
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and storing listing data from multiple exchanges in advance. It proactively captures listing appearances and disappearances, pre-processing the data so that when pricing decisions are needed, the analysis can be performed quickly on already-aggregated data rather than gathering data in real-time, thus reducing the complexity burden at decision points
3Productivity
If brokers use automated pricing systems with comprehensive sales data, then transaction speed and efficiency improve, but the accuracy of sales data deteriorates when data is incomplete or inferred
Solution Approach 1:
The system dynamically adjusts its data collection and analysis approach based on data availability. When direct sales data is available, it uses that for high-confidence pricing. When sales data is incomplete, it dynamically switches to inferring sales from listing disappearance patterns, adjusting the confidence levels and methodology based on the quality and completeness of available data, thus maintaining productivity while managing accuracy expectations
Data Source
AI summary
A method and apparatus for estimating sales across a market with incomplete information taken from one or a plurality of exchanges, is disclosed. Inventory is observed disappearing from the exchanges. There is some probability that the inventory disappeared because it was sold, and some probability that it was withdrawn by the broker for a variety of other reasons. Disappeared inventory is assigned a score that correlates with the likelihood of the listing having been sold. A list of these inferred sales is generated by comparing the score to a threshold. A further refinement removes items from the list should the sold inventory return to the market.