Collaborative Ticketing System Dynamic Pricing
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Solution Overview
Problem
Conventional ticketing services do not effectively recommend events or friends to invite based on user and friend event-related behaviors, nor do they offer variable pricing based on invited friends' ticket purchases, leading to missed opportunities for increased ticket sales and revenue.
Innovation Solution
A collaborative ticketing system that generates offers based on user preferences, social connections, and event characteristics, allowing users to invite friends for discounted tickets, pre-purchase concessions, and provides personalized event recommendations, thereby increasing ticket sales and revenue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional ticketing services provide basic event information and ticket purchase functionality, then users can obtain event information and purchase tickets, but the system fails to effectively recommend events or friends based on user behaviors, resulting in missed opportunities for increased ticket sales and revenue
Solution Approach 1:
The system implements feedback mechanisms by tracking user and friend event-related behaviors, analyzing this data to generate personalized event recommendations and friend suggestions, thereby converting lost behavioral information into actionable insights that drive ticket sales
Solution Approach 2:
The system automatically collects, analyzes, and utilizes user behavioral data without requiring explicit user input, enabling self-service recommendation generation that personalizes event suggestions based on observed user patterns and friend interactions
2Productivity
If the system offers variable pricing based on invited friends' ticket purchases, then revenue opportunities increase, but the system complexity increases due to dynamic pricing calculations and friend invitation tracking
Solution Approach 1:
The system implements dynamic pricing that automatically adjusts based on the number of invited friends who purchase tickets, allowing revenue optimization through variable pricing while the automated nature of the system manages the complexity of calculations and tracking
Solution Approach 2:
The system pre-establishes pricing rules and friend invitation tracking mechanisms in advance, so that when friends are invited and purchase tickets, the variable pricing calculations are automatically applied based on pre-configured parameters, reducing real-time system complexity
Data Source
AI summary
Features are disclosed relating to a collaborative ticketing system that manages various aspects of ticketing for events (e.g., movies, concerts, sporting events, and the like) using knowledge about the contacts, friends, and other social connections of system users. The collaborative ticketing system may generate dynamic ticket offers that are based on the number of friends, invited by users, ultimately obtaining tickets. The collaborative ticketing system can also streamline the procurement of concessions and other event-related items by allowing users to pre-purchase such items (e.g., in connection with ticket offers), and then pick up the items at the event venue with little or no wait. In addition, users can preview event-related content (e.g., movie trailers) for event providers (e.g., movie studios), and answer questions or otherwise provide feedback about the event-related content in return for special offers, rewards, and other considerations.