Deal Score Metric for Event Ticket Quality Comparison
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Solution Overview
Problem
Consumers face difficulty in comparing the quality of event tickets due to varying factors such as location and price, making it hard to identify the best deals in the market for event tickets.
Innovation Solution
A deal value metric, or 'deal score,' is introduced to quantify the quality of tickets based on price, location, and other variables, allowing for direct comparison across different seats and events, using algorithms that consider historical data, ticket availability, and consumer preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If ticket inventory is aggregated across multiple venues and events, then consumers gain access to more ticket options, but it becomes difficult to identify the best deals among the large amount of inventory
Solution Approach 1:
The patent transforms multiple ticket quality parameters (location, price, venue characteristics) into a single standardized metric called 'deal score'. This parameter transformation allows consumers to directly compare tickets across different venues and events by converting complex multi-dimensional quality assessment into a unified numerical scale, resolving the difficulty of identifying best deals in aggregated inventory.
2Measurement precision
If tickets are priced based on location and other quality factors, then price reflects ticket quality, but consumers cannot simply identify best deals by looking at cheapest tickets as they can in other markets
Solution Approach 1:
The patent introduces an intermediary metric called 'deal score' that mediates between complex ticket quality factors (location, price, venue characteristics) and consumer decision-making. This intermediary transforms precise but complex quality measurements into an easily interpretable single value, allowing consumers to efficiently identify best deals without needing to analyze multiple quality dimensions separately.
3Ease of operation
If a standardized deal score system is implemented, then consumers can directly compare ticket quality across venues and events, but the system requires algorithms that consider historical data, ticket availability, and consumer preferences
Solution Approach 1:
The patent performs preliminary computation by pre-calculating deal scores for all tickets using algorithms that consider historical data, ticket availability, and consumer preferences. This preliminary action transforms complex quality assessment into pre-computed standardized scores that can be easily displayed and compared by consumers, shifting the computational complexity from the user interface to the backend processing system.
Data Source
AI summary
A deal value metric (or “deal score”) enables consumers to identify the quality of a ticket listing, and facilitates direct comparison of available event tickets having varying quality throughout a venue. The deal value metric disclosed herein also permits simultaneous comparison of tickets among multiple similar events, and provides a helpful criterion to supplement conventional search filters such as location or price.