Big Data And New Avenues For The Hospitality Industry
Big Data has been the buzzword in the technology and business space for quite some time now and is showing no signs to cease. Engineers, mathematicians and computer scientists from all over the world are being hired by big names in business to tame and leverage the tremendous potential of big data analytics. The change is so powerful that it has almost wiped out all previous methods of decision making and is going to be the prime mover of companies, government agencies and societies on a global scale.
Essentially, big data and advanced algorithms, coupled with very high amount of computing resource, crunches numbers and churns out probabilities and correlations - the two weapons of any management team. For example, the HR and recruitment team of any company would be happy to get insights on the probability of a new recruit's attrition. The board members would be happy to know the correlation between national GDP, an executive's skill-set and his chances of sabotaging the company, before taking him on board!
On the other side are the clients and customers of any product or service, who would be interested to know the probability that the claims made by the manufacturer or the service provider would be justified by the end results. To illustrate the point, we shall take the travel and hospitality industry as a case study and build the arguments on that basis.
The travel and hospitality industry has two kinds of customers - the first category comprises of seasonal customers who plan month before taking a long vacation and the second one are the random ones. If someone belongs to the second category and needs to travel frequently, stay in hotels and do stuff on the move, there is little big data based predictive models can do to cut costs. However, the first category can be a big gainer with the help of predictive models that operates on the big data framework.
Mathematicians and computer scientists can create highly complex algorithms that give rise to artificial intelligence with unimaginably large amount of data crunching capacities. Such infrastructures are quite capable of running programs with high resource requirement and in turn, can churn out probabilities and correlations between remotely related parameters.
For example, scientists have successfully developed and tested predictive mathematical models that can show an ordinary customer the optimum time and route for travel, so that a vacation can be planned with minimum cost. Such models can suggest, for example, that a person should buy plane tickets from X airlines exactly five days later for travelling to Barcelona after exactly forty three days, during which the tariffs of hotels A, B and C is expected to be minimum, the weather is expected to be pleasant and the overall probability of enjoying a relaxing vacation is very high. If one wants to calculate the optimum itinerary for a trip to Spain, it can also be done easily.
The big data paradigm feeds on astronomical volumes of data and statistical methods suggest that greater the sample size better is the accuracy of the stochastic output. In today's age, there is no dearth of data and therefore, big data analytics is working fine for companies that are adding value to people's lives by application appropriate techniques. When it comes to the hospitality industry, Hotel And Ticket Booking Service providers can also apply these techniques on their own or outsource the same to experts, so that they can provide real and unique values to their customers. These can be a great strategy for them to win customer loyalty, as a customer will surely return to the booking service provider once he realize that while others have bought expensive tickets, he has been benefitted by the booking agent's advice!
Among those who are planning to leverage big data in the hospitality industry, Real Trip Finder is one of the best Hotel And Ticket Booking Service provider in the world. The author, Pritam Dalui, has written this article based on his personal experiences with the agency.
By Pritam Dalui