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Google’s Machine Learning Technology Can Ace up the Travel Industry

Written By : Smriti Srivastava

The technology of machine learning is benefiting almost every industry but the most significant modification can be seen in the travel sector. People traveling to different cultures face linguistics issues which machine learning advancements of translation have curbed down.

Interestingly, tech-giant Google is making a major shift into the travel industry while enabling customers to book air tickets, hotels, and packages. It is also aiding customers in accessing stuff which they might have never come across on their own. It is psychologically authentic that if a person doesn't understand the language he/she is likely to avoid the opportunity. Here enters machine learning which has made traveler understand and avail the benefits of the package and services.

In particular, the advantages of Google Translate are making dynamic changes in the way people travel. Also, over time as the Google services will advance, travelers will find it easy to visit any place across the globe.

Not only in regards to translation but the technology is helping the travel industry in other ways too.

Google embraces a team which analyses flight delays in order to send alerts to customers regarding their flight is late even before they get notified by the airline itself. The customers can also discover the information while doing a google search for their flight number.

Even travel companies are feeding all sorts of information (regarding delays, arrival and departure time along with their complete status) into a huge ML system which then forwards it to customers.

Transparently, leading players of the travel sector are deploying ML not only to scale up their business outcomes but to originally revamp the outcomes as well. Another way round, using this technology travel marketer learn more about customer choices and preferences and providing with the relevant material faster. ML is undoubtedly making travel marketing analytics more predictive and deep.

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