Travel Booking System Using Historical Data Analysis
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Solution Overview
Problem
Travelers often incur costly changes in their bookings due to inflexible travel arrangements, and existing systems fail to provide effective suggestions for initial bookings that minimize future changes and associated penalties.
Innovation Solution
A system that tracks travel behavior patterns and generates aggregate data to suggest better booking methods by analyzing historical data and external events, offering cost-effective alternatives for initial bookings that reduce the likelihood of costly changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If travelers book according to pre-determined rules or accustomed arrangements, then booking process is simple and quick, but costly changes occur at the last minute
Solution Approach 1:
The system performs preliminary analysis of travel history data and aggregate patterns before making booking recommendations. By pre-calculating optimal booking types based on historical data and predicting potential changes, the system enables travelers to make informed initial bookings that minimize future change costs, rather than reacting to problems after they occur.
Solution Approach 2:
The system continuously collects and analyzes travel history data, change patterns, and aggregate information from multiple travelers. This feedback loop allows the system to refine its recommendations over time, learning from actual booking outcomes and change behaviors to improve future booking suggestions and reduce costly changes.
2Adaptability or versatility
If travelers choose flexible travel arrangements to avoid change penalties, then change flexibility is improved, but initial booking cost increases
Solution Approach 1:
The system dynamically adjusts booking recommendations by analyzing multiple parameters including travel history, destination, timing, traveler preferences, and aggregate data from similar trips. Rather than recommending uniformly flexible (and expensive) bookings, the system optimizes the flexibility parameter based on the specific situation, recommending the appropriate level of flexibility to minimize total cost while meeting traveler needs.
Solution Approach 2:
The system applies different booking recommendations to different segments of travel arrangements based on specific characteristics. Instead of a one-size-fits-all approach, it analyzes each booking context individually and recommends appropriate flexibility levels for specific routes, time periods, and traveler profiles, optimizing cost-effectiveness locally rather than globally.
3Measurement precision
If the system provides detailed analysis and recommendations based on aggregate data, then booking accuracy is improved, but system complexity increases
Solution Approach 1:
The system consolidates multiple functions into a unified platform that collects travel history data, analyzes aggregate patterns, generates predictions, and provides recommendations all in one system. By making the system multi-functional and self-contained, it reduces the need for separate external tools and data sources, managing complexity internally while delivering comprehensive accurate recommendations.
Data Source
AI summary
In one embodiment, a method that can be performed on a system, is provided for automatic review of travel changes and improved suggestions and rules set. In one embodiment, the method comprises generating an aggregate of travel history data based on one or more travelers, the data including changes made to travel selections of an itinerary following an initial purchase of the travel selections; receiving a request for travel options in relation to a requested travel itinerary; and generating a first set of travel options for the requested travel itinerary, based at least in part on the aggregate of travel history data, the first set of travel options to result in a cost lower than a second set of travel options, if changes are made to selected travel options of the requested travel itinerary following an initial purchase of the selected travel options.