How Big Data Will Lead The Way In The Travel Industry

Travel companies are known for capturing and storing massive amounts of data. During every step of the travel journey they collect data such as customer data, flight paths, transactions, yielding, check-ins etc. Every hotel has a CRM package and let’s not forget yield revenue management was invented in the travel industry already years ago. Until recently this data was just stored and travel companies had difficulty actually putting this data to use by combining various datasets. With the sheer amount of computer power, cheap and powerful storage solutions such as Hadoop and many Big Data startups waiting to help out, this information can finally be put to use to make the customer feel more appreciated and better serviced, resulting in more revenue and higher profits.

Especially in the travel industry, such a personal approach is of vital importance and the opportunities for Big Data in the travel industry are therefore tremendous. If we look at the conversion rate on travel website, Graham Cooke tells us that 92% of customers of a travel website will not convert and 60% of visitors never return after a first visit. Big data can help online travel companies to deliver the right message at the right time to the right person and with that increase their conversion rate.

Fortunately, the amount of Big Data startups focussed on the travel industry is growing. Duetto Research is such a company. They aim to help hotels forecast and understand future demand patterns. They are however still very much focused on the financial aspects of room rates and demand, while travel in fact is emotion and with the proper tools organisations can grow revenue simply by delivering the right product to the right person at the right time.

So, knowing what your customers like, or don’t like, can have a severe impact: everyone shares everything on many social networks, especially their personal travel stories. All this information can be used to provide a user a more tailor made message. It is after all no use to show someone who liked the Facebook page “I Hate Snow” a ski holiday advertisement. That is a waste of money and will likely results in a lost potential customer.

Luckily, slowly but slowly travel organisations are adapting to Big Data and more organisations are hiring data scientists and start experimenting with it. A much talked about example is the Mac vs Windows price strategy at Orbitz, where Mac users were steered to 30% higher prices. It was clear that this was a mistake, but it shows the potential Big Data has for the travel industry. For better or for worse.

During a Big Data forum in The Netherlands recently, Diederik Meijerink – analyst at Schiphol Airport, explained that Big Data is also everywhere at Schiphol Airport. Big data is used to measure the amount of people present at Schiphol in real-time, to develop heatmaps for expected noise pollution in the surroundings and to visualize retail sales vs. departure gates to see how far travellers wander off from their departure gate. These are just a few examples, as he explained that in the near future the potential of Big Data in the passenger journey is tremendous.

The challenge in the travel industry will therefore be to connect all these different platforms, websites or products during the journey of a traveller. Would it not be great if a traveller would get a message if his plane is delayed, including the new gate, that would allow him to leave later from work and still plan a meeting. That the hotel he booked receives also a message that he is delayed and now knows the new expected time of arrival and has a refreshment ready to forget the delay? That would truly be exceeding expectations.

Of course, this is just an offline example. Online, speed is everything in travel. Consumers generally move away within seconds if an online answer takes to long. After all there are many other websites around offering exactly the same. Each each of these websites need to sift through millions of records from various sources such as airline agencies or global distribution companies and delivering a result earlier can have a direct impact on revenue. So, speed matters and when speed matters, Big Data is the answer. By building their own Big Data system for example, a German travel company is now able to process 1,000 queries per second while searching through 18 billion offers across 20 parameters and deliver an answer within the second.

Another new player in the market is Hopper, who already have secured $ 21,7 million in funding to build a platform that makes searching for travel options a more complete experience using Big Data tools. With Hopper it will be possible to plan and book a trip just by entering a vague idea that you have in their search engine and the algorithms will do the rest. They are developing already since 2007 and are still in stealth modus, which could indicate that it is indeed a daunting task to change the travel industry with Big Data.

It might be very difficult to combine all that unstructured data that is out there to deliver the best result and experience to the guest, but it is the only way forward. Travel organisations, if they have not already done so, should wake-up and start analysing the right Big Data.

Image Credit: Rodrigo Bellizzi/Shutterstock