Dynamic Ticket Pricing System Using Real-Time Demand Analysis

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Solution Overview

Problem

Current systems for pricing and managing event tickets, such as sports and concert events, face challenges in accurately forecasting demand, optimizing pricing, and matching prices with customer demographics, often relying on intuition and outdated data, which can lead to suboptimal revenue and inefficient inventory management.

Innovation Solution

A computerized method that analyzes external variables like web traffic, past sales, and demographics to determine optimal ticket prices, uses mathematical models to predict demand, and dynamically adjusts prices or redirects inventory to maximize revenue, while also correlating customer demographics with ticket pricing for targeted marketing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If manual pricing methods based on promoter experience are used, then device complexity is reduced, but measurement precision and manufacturing precision of ticket pricing deteriorates

Engineering Contradiction:

Improvepricing system complexityVSAvoiddemand forecasting accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent replaces manual pricing methods based on promoter experience with an automated computer system that uses mathematical models to analyze external variables (web traffic, radio play time, demographics) and internal data (prior sales, ticket prices) to precisely forecast demand and determine optimal pricing, eliminating the need for manual intervention while significantly improving pricing accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system dynamically adjusts pricing parameters based on real-time analysis of external variables and internal data. The mathematical model continuously processes changing parameters such as web traffic patterns, demographic data, and sales velocity to optimize ticket prices, transforming static manual pricing into dynamic automated pricing that adapts to market conditions

Inventive Principle:

Principle #35Parameter changes

2Ease of operation

If static face value pricing is used, then ease of operation is improved, but productivity and revenue optimization deteriorates

Engineering Contradiction:

Improvepricing operation simplicityVSAvoidrevenue generation efficiency

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The patent implements dynamic pricing that automatically adjusts ticket prices based on real-time demand analysis. The system monitors sales velocity, web traffic, and other external variables to dynamically modify pricing, transforming the static face value pricing into a living system that optimizes revenue while operating through automated processes that maintain ease of use

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The pricing system performs self-optimization by automatically analyzing internal data (prior sales, ticket prices) and external variables to determine optimal pricing without requiring manual intervention. The mathematical model self-adjusts prices based on demand patterns, enabling the system to optimize its own performance while maintaining operational simplicity through automation

Inventive Principle:

Principle #25Self-service

3Ease of manufacture

If section-based pricing is used, then ease of manufacture is improved, but manufacturing precision of relative pricing deteriorates

Engineering Contradiction:

Improvepricing implementation easeVSAvoidseat quality pricing accuracy

Core Design Contradiction:

Ease of manufactureVSManufacturing precision

Solution Approach 1:

The patent applies local quality pricing by assigning different prices to different seats based on their specific characteristics (view quality, proximity to stage) rather than using uniform section-based pricing. The mathematical model analyzes individual seat attributes and external variables to determine optimal pricing for each seat, enabling precise pricing that reflects actual seat quality while maintaining ease of implementation through automated processing

Inventive Principle:

Principle #3Local quality

4Device complexity

If intuition-based pricing decisions are used, then device complexity is reduced, but measurement precision and reliability of pricing deteriorates

Engineering Contradiction:

Improvepricing system structureVSAvoidpricing decision accuracy

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The system incorporates feedback mechanisms by continuously monitoring actual sales data, web traffic, and other external variables to validate and refine the mathematical model's pricing predictions. This feedback loop ensures that pricing decisions are based on reliable, data-driven insights rather than intuition, improving reliability while the automated nature of the system keeps complexity manageable

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS11087243B2Sports and concert event ticket pricing and visualization system

Publication Date: 2021.08.10 TIXTRACK

AI summary

A system and method for displaying seat inventory at a venue and facilitating planning of ticket prices for events at the venue is presented. Methods to predict total revenue for an event are described. Also presented are systems and methods for determining at what price and when to release so-called ‘flex’ price tickets during an on-sale using the sales velocity and sales/inquiry ratios. Determining demand of seats from secondary markets is also described with methods to use the demand for either repricing the seats in the primary market or presenting ‘best value’ seats to a prospective purchaser.