Usage of Data Science in Travel and Tourism Industry

Remember your last trip? Did you get your tickets directly from the ticket office? I doubt it. In today’s fast-tracked world, finding time to travel to a booking office and get your tickets is a luxury only few can afford. Besides, why bother if you can get your tickets in just a couple of clicks via your laptop or even your smartphone?

The travel and the tech industry are working in tandem to create the perfect experience for the modern traveler and provide numerous facilities in one shot. Almost every modern travel and tourism industry working on Data science and machine learning concepts to make the user experience seamless and be the best in the lot.

To satisfy all the needs of the increasing number of users and process enormous chunks of data the machine learning algorithms are vital. Data becomes an analytical tool as far as airlines, hotels booking and reservation websites, and many others are striving to improve their services every day.

Let’s understand how Data science is changing the travel industry forever.

1. Recommendation engines

Like the personalized content suggestions on YouTube, Netflix or the “Featured Recommendations” box on Amazon, online travel booking providers often provide tailored suggestions, based on your recent searches and bookings.

For example, when searching on makemytrip for flights to London, you will be offered several accommodation options for your trip. Similarly, Yatra offers alternative destinations you might like for your next trip. Analyzing this algorithm, the online travel agencies can offer rent a car deals, alternate travel dates or routes, new travel destinations based on the customer’s preferences, or even some recommended local destinations.

2. Flight fare and hotel price forecasting

Flight prices and hotel bills are ever-changing and vary a lot depending on the provider. Nobody has time to track all those changes one by one. Thus, smart tools that monitor and send out timely alerts with hot deals are currently in high demand in the travel industry. For example, if during the last several holiday seasons all the prices of flights from Bengaluru to Delhi grew significantly a couple of weeks before Diwali, the same tendency might occur this year as well. In this case, the analytics will say that waiting could be too risky and prompt you to book your flight immediately. Similarly, if the price for flights to Bengaluru usually drops below average a week before Diwali, you will be offered to wait and book your flight closer to the date.

3. Intelligent travel assistants

As convenience is the king in today’s world, smart concierge services, powered by artificial intelligence (AI) are gaining momentum in various industries. Travel booking is only one of the areas being heavily automated by algorithms. AI algorithms, trained to perform a specific task on a user’s request are usually termed as “bots” or “Chabot”. Instant messaging platforms are widely adopted by some prominent brands as a great way to reach out to the clients and build better customer relations.

4. Optimized disruption management

Mostly applied to business and corporate travel, disruption management is always a time-sensitive task, requiring an instant response. While the chances to get impacted by a storm or a volcano eruption are very small, the risk of a travel disruption is still quite high: there are thousands of delays and several hundreds of canceled flights every day. With the recent upgrade in technology, it became feasible to predict such disturbance and efficiently mitigate the loss for both the traveler and the carrier. The moment for data science here lies in predicting travel disruptions based on available information about weather, delays, and other relevant airport service data. For example, if there is heavy snowfall at your destination point and all flights are redirected to another airport, a smart assistant can check for available hotels there or change booking from your actual place of arrival to your initial destination.

5. Customer support

Combining virtual assistants with human ones, not only can help you grow your brand loyalty, but also optimize your business performance. For example, if a passenger’s luggage is lost, reporting the loss or even conducting an automated search through a virtual assistant might significantly speed up the process of finding it. This approach eliminates the bureaucracy and paperwork, which is a great way to rehabilitate yourself in terms of customer experience. Moreover, offering a free bonus for any inconvenience caused is an even better way to retain your customers.

6. Sentiment analysis in social media

90 percent of travelers with a smartphone share their experiences and photos in social media and reviews services. Every minute, about 2800 traveler reviews are submitted online. This is bulk of valuable data that companies can analyze to improve their services. For instance, Google Cloud Natural Language API is an off-the-shelf application programming interface that can be tweaked and integrated with analytical tools to provide real-time analysis of all brand-related reviews. The maturity of natural language processing and sentiment analysis allows for adopting accurate analytical tools without time-consuming data gathering.

7. Fraud detection

Airlines and travel industries face eCommerce fraud the most. They lose billions of dollars every year having to refund stolen money to customers. Payment fraud is one of the most popular types of scams in this industry that entails using a stolen credit card for booking flights or accommodation. User behavior analysis apply profiling and machine learning technologies can help prevent and detect fraudulent transactions from happening. AI solutions for fraud detection are appropriate for online platforms and mobile booking apps also seek for a customized machine learning models to predict and detect fraud that allowed them to lessen chargebacks to 50 percent.

 

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