In this contriibuted article, Mindtree’s Suman Nambiar, europe head of travel and hospitality industry group, and Ranjith Kutty, senior director and head of solutions and new business / travel, transportation and hospitality vertical in North America, discuss how the future of technology will change the travel industry.
Think Iron Man, think Jarvis, the “Just A Rather Very Intelligent System”. When the first Iron Man film came out, Jarvis was science fiction, but by the time the third film was released, we were already familiar with Siri, Cortana and the snappily named Android voice commands – suddenly, a virtual personal assistant that you could talk to was in our pockets.
From being a fun party trick at first, these assistants have been ingesting billions of queries and getting sharper and more useful every day – more and more of us use them as interfaces to our smartphones and tablets, to check the weather, to listen to text messages and reply whilst driving, to plan our schedules, to open apps and to remind us to feed the cat.
As these assistants get better, so does their strength in handling complex natural language queries that cut across applications, which is a perfect fit for travel planning and management. This begs the obvious question – how will enterprises respond to the new digitally enabled consumer? How can the travel industry use intelligent systems to serve the customer better?
The travel industry has unprecedented opportunities to sell better and serve better, but given the investments that technology companies like Google, Apple and IBM Watson Labs (to name just three of many) are making in the travel sector, the industry needs to respond quickly before the consumer gets used to dealing with a completely different class of intermediary who offers them a more intelligent, better targeted, more intuitive model of interaction. And it is not the technologies that stand in the way of the industry doing this today, as they all exist; as the travel industry shifts to being more customer focused and understanding what they can and cannot do with data, this future is already within reach.
Consider someone driving along the M25 on her way to a meeting one morning in the near future – a grey January’s giving way to a grey February and she wants some sunshine. She asks her smartphone to look for a sunny break for a week in March, travelling on her preferred airline.
Based on her preferences, the airline knows that she’s been to Santorini before and has given it excellent ratings for a sunny break in winter – the airline system interfaces with her phone to create a completely customised package, departing on a Friday afternoon from the nearest airport after the last meeting in her calendar, with a cab picking her up from the office (and a cab to take her to work that morning, since she will not be driving).
A poolside room is chosen at one of the hotels where she has loyalty points; these points are then used for a free upgrade to a higher class of room. Also booked are a rental car from her preferred company, optional excursions to places she has not been yet (based on information she has shared on a variety of social media) and suggestions for hikes, as well as two reservations at restaurants, again based on information she has shared with the airline as well as on social media.
The offer sounds good to her, so she asks her virtual assistant for a quick scan of her current and credit card accounts and then chooses a card to pay with, still using voice commands. The airline then confirms the bookings and sends the itinerary to her online travel planner as well as her calendar.
On the day of travel, before her last meeting, she gets a message from the airline, saying that they will send the cab 15 minutes earlier as the security lines are longer than usual for a Friday evening. She is checked in online and takes less than a minute to drop off her bag, which already has an electronic bag tag.
Since security now has biometric systems, it proceeds faster than usual and she gets a text message from the airline with a 20% voucher for a drink and a snack at two of the restaurants she prefers.
By the time she lands in Frankfurt 20 minutes later than scheduled, she is relaxed because she has already seen a message with a revision to her itinerary to a slightly later interconnecting flight, because the airline has been able to predict a delay to the inbound flight ahead of time thanks to predictive analytics, and a confirmation that her preferred choice of rental car will still be held for her.
We could go on, but this is an illustration of what is already possible today.
Intelligent systems that have the ability to “learn” and adapt will help companies focus on the customer better. A combination of supervised and unsupervised learning enables these systems to be more context aware and this combined with predictive analytics applied to a wealth of data provides a very powerful platform for customer engagement.
This enables enterprises to make the much needed shift from serving requests that customers make, to anticipating the request and acting on it ahead of time. An ecosystem of such enterprises that effectively engage intelligent systems across industries such as retail, banking and travel to name just a few, will be able to sell to the customer not just want they need, but also what they want.