Unquestionably, machine learning can do wonders with previously unheard-of varieties and volumes of data. With the uplift in the data volume, the domain of data analysis has emerged exponentially recently. Machine learning comprises software that can learn from data. For instance, a machine learning program could see a million digital images of trees and teach itself to tell the difference between them.

Predictive analytics is a process that uses artificial intelligence and machine learning to make predictions about future events. This typically involves studying past data that would help to identify meaningful patterns that can suggest future events. This would help to alert people about what is coming. In the travel industry, predictive analytics finds its implementation in dynamic pricing for revenue management increasing the bottom line and price prediction which is used to predict the best time to book hotels or flight. Let’s see how?

Predicting the Best Time to Book Hotel or Flight
What will a travel agency do with predictive analytics? The answer is pretty much fanciful. The most realistic idea that is involved in machine learning is studying and analyzing traveler’s booking habits giving a clear picture of demand with the help of booking sources, search and historical data and making meaningful predictions about the way you might ensure satisfied traveling experience.

How about predicting the right time to opt for hotel or flight bookings? Let’s understand it with an example. If you are going on a business trip to Italy, you would surely lookup for the cheapest options for hotel booking and try to know about the best time to do it. And many of the times, you will end up seeing hundreds of suggestions. Isn’t true? You would dig more into the process and realize that it is quite a frustrating process. Thanks to the travel agencies that are using predictive analytics. They will come up with the best options and will also let you whether it is the right time to go for that option or not. This way, you can make the right decision.

With predictive analytics, the booking systems gather historical data about travelers like you and predict future price movements taking into account all the external factors like seasonal trends, demand growth, limited-time special offers, weather, provider and the availability of places, seats, and rooms etc which have the dependability on price changes. The tool may even predict the best times of day to avoid an expensive flight based on price and availability analysis.

About Predictive Models for Flight Booking
Optimal timing for flight ticket booking from the perspective of the customer is quite challenging. Most of the time, buyers can lack in having sufficient information for reasoning about future flight pricing patterns.  That is why agencies use various predictive models for computing future prices and estimate whether this is the right or best time to book the flight ticket.

This is basically done with the help of machine learning. Many agencies use Python & R for implementing predictive models and automation.

They aim at automating script to collect historical data and other external data, cleaning and preparing data using several statistical tactics or logics, analyzing or building models, and merging models & calculating accuracy.

It’s a Wrap!
The predictive analytics offers countless benefits for the travel business. With the help of machine learning, travel agencies can focus on saving money, improving policy compliance, and helping travellers enjoy their travel experience.