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Big Data Hadoop is Transforming Airlines to Run Customer Loyalty Programs
Did you know the advent of Hadoop has empowered airlines to embark on massive data collection programs? Now the airline are collecting their customer sentiment data & ecommerce behavior from social platforms like Twitter and Facebook and travel companies like Travelocity and kayak.
This data is stored in the Hadoop where they use different platforms to run MapReduce analytical workloads to determine the level of association among different variables like baggage fee, ticket price, equipment failure, route preference, delays, and in-flight food purchase as well as entertainment.
Companies are on the run of installing discovering platform so as to experiment and learn more about their consumers and networks. There might be a connection between equipment failure and customer loyalty. Once you find there is a connection, then it becomes a report.
The airlines sector is in the middle of transformation right now between the previous adoption phase & mainstream adoption of big data solutions. A few years ago it was just possible not practical, but now it’s practical. And that’s the reason why it’s carried out on a larger scale.
The data programs of airlines generally grow out of existing consumer loyalty programs, however, increasingly airlines are expanding their data collection programs to cover all airlines passengers whether or not they have the experience of flying with a given airline company. Only about half of passengers on a given plane belong to a loyalty program of the airline they’re flying or have flown.
For example Qantas that is now actively pursuing consumers on social media sires, it is leading the way with a very innovative concept in its loyalty program as they are now going outside at new retail affiliation that could be important to majority of their consumers. This is really a forward-looking airline.
Hadoop in Airlines
Airline companies are also using Hadoop to store large amounts of their consumers’ web traffic data to have a better idea of what their consumers’ selections are based on and how. By collecting the cookies that every Web user brings with them when they go to any airline company’s website and airline can find out what other sites a particular consumer visited and what other searches he/she performed before buying a ticket.
If and when the customer gets a ticket and identifies himself/herself through a payment, and airline company can go back in the time in effect & find out what other websites he/she visited. This helps the airline company to develop a better model of customer behavior, and recognize which email, advertising, or PPC marketing programs are working well and which are not.
That is in actuality a very common behavior now for companies whose revenues come from digital resources. It is not a novel technique. The database technology itself is making it even more possible to track various kinds of cookies. Historically companies could only track cookies from your main point of entry and that’s your PC> but now, it could be tracked from mobile devices as well.
Attribution as well as path-to-purchase analysis could be challenging and expensive analytical things best done by senior data scientists. But now, with new solutions in hand the bar is being lowered on the entry level. Hence, an ordinary analyst can also start a very sophisticated query and get a result set back that holds a huge value for the organization.
Hence, big data Hadoop is helping airlines indentify their consumers’ behavior and run campaigns or other loyalty programs based on that.
It simply means a Big Data Hadoop training course is going to be beneficial for people planning to pursue a career in aviation field as data scientist or a Hadoop professional.Madrid Software Trainings in association with industry experts provides complete practical big data hadoop training in delhi ncr.
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