Data Science in the Field of Travel and Transportation

Posted by Rohith Reddy on September 1st, 2022

This Article Shows You The Use of Data Science in Travel and Transportation.

  1. Finding MVCs (Most Valuable Customers)

Naturally, some clients will travel farther than others. This means that, in order to prevent customer turnover, businesses need to be highly aware of the major players.

The data on MVCs that loyalty programs have provided to the travel industry is already enormous. Compared to the cost of maintaining a current customer, the cost of obtaining a new one is far higher. It is tricky to predict what MVCs may desire in the future by fusing this historical data with real-time and predictive analytics.

  1. Safer Travel

Big data can potentially save lives when it comes to safety. Modern vehicles, including cars, trains, and airplanes, are outfitted with various sensors. Link external: open in new These deliver a constant stream of real-time information about every part of the journey to control centers (e.g., airmanship or driver behavior, environment, mechanical performance, etc.).

Transportation data scientists are developing sophisticated algorithms using this information to forecast issues and, even better, avoid them.

Is a vital component deteriorating? Before it causes a problem, replace it.

One of your drivers frequently overlooks a crucial step. Take them off the route so they can get retrained.

A problem that cannot be resolved in midair? Have a maintenance person on hand when they arrive with the appropriate tools.

  1. Greater Efficiency

Data scientists are gathering information from every corner of the digital realm, in addition to sensors, to streamline daily operations.

Collecting information on daily advanced booking trends, internal historical data, and consumer behavioral insights helps create the finest "no seat left unoccupied" yield management system. This information is supplied by collecting traffic and weather data to reroute passengers, alter itineraries, and predict delays and fuel needs. The data is then combined. Using predictive algorithms to route smartphone users to the closest open parking spaces. 

  1. Up-Selling and Cross-Selling

Let's say you're traveling to California for a two-day business conference, and you've decided to take a weekend to explore the city. You're looking for a flight that leaves Sunday and returns early Monday.

If your airline has invested in big data, it will offer you cross-selling and up-selling opportunities from the moment you begin your search.

  • Obtain a personalized offer in your inbox.

  • Be pre-booked for Economy Plus seating.

  • Tempt yourself with deals on hotels that work with your flight.

  • Receive a discount dinner coupon from the steward.

  • Discover a weekend city tour advertisement on your in-flight entertainment system.

  1. Genuinely Customized Offers

The travel industry now uses big data to build 360-degree views of each consumer. Businesses now have the option of providing recommendations in place of generic ones.

  • Processing images

  • Predictive modeling

  • Behavioral targeting, such as analyzing website user behavior,

  • social media, such as travel-related posts and friend reviews.

  • Records of location tracking

Are you looking for a career change in data science? 

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Rohith Reddy

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Rohith Reddy
Joined: July 7th, 2022
Articles Posted: 19

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