How Big Data helps customize your travel
Online travel agents are using analytics to provide a differentiated, personalized experience to their customers
Mumbai: Five years ago, Radhika Balaji, 28, now a senior executive with an insurance firm, used to visit a travel agent for booking her annual pilgrimage to Vaishno Devi, the Hindu temple. The travel agent would ask her to pick one of the three hotels that he would have shortlisted for her—and she would faithfully do so, going by her budget and preference.
At the time, travellers booking on the Internet had few choices in the absence of a recommendation-based online model. But thanks to Big Data analytics, this gap is closing, allowing online travel agents (OTAs) to offer exactly what other travel agents were offering Balaji.
Enter Big Data
Sample this. You search for “hotels in Goa” on Cleartrip.com or any other OTA site. You see an exhaustive list of hotels across “star categories”, “price barometers” and “areas”, among various other filters. Scanning through this list might be easy if you’re surfing on your 13-inch laptop screen, but a hassle if you’re trying to do the same from your 3-inch mobile screen.
But what if Cleartrip intuitively filtered this search down to only, say, 13 hotels and asked you to choose from them? “That’s what Big Data can enable OTAs like us to do,” says Samyukth Sridharan, president and chief operating officer of Cleartrip.com. “Provide the capability to store data, dissect and dice it, analyse and draw inferences from it…and finally, make real-time use of it while building features and tools on our mobile app and website.”
Sridharan says his firm stores every single user search, action (for example, applying a filter for a 2-star hotel) and tertiary parameters like whether the person came to Cleartrip directly or via a Google search.
OTAs use this data to create individual “DNAs”—a person with a unique search/booking pattern. It then compares the DNA with those of other users—often running into thousands—who have earlier shown similar patterns. Using this data helps OTAs draw inferences of many kinds, including a sense of when one will buy (buying propensity) and how much one will pay for (willingness to pay).
How big is this market? According to travel research firm PhoCusWright Inc’s India online travel overview sixth edition, the Indian online leisure and unmanaged business travel market stood at $8.8 billion in 2013 and is expected to rise to $12.5 billion by 2015, an increase of 41%. Online travel penetration will rise to 43% by 2015, it said.
OTA newfound love
While Big Data has been around for decades, it is only recently that businesses have begun to understand how it can help glean insights into customer behaviour, improve supply chain efficiency and positively impact other areas of business performance, says Sanket Atal, chief technology officer at MakeMyTrip.com. “For a travel company such as ours, Big Data serves as the key enabler to engage better with customers and deliver service efficiently and intelligently. Analytics helps enhance efficiency at the business end and the experience at the customer end by developing new approaches to customer management, revenue management and internal operations,” Atal points out.
Atal says personalization will be a big part of e-commerce moving forward, as guest expectations of more personal experiences are on the rise. His focus for the next few years will be to build a solid foundation for personalization. For instance, Sachin Sinnur is a regular business traveller who flies from Mumbai to Bangalore frequently. He almost always selects IndiGo flights and stays in budget hotels. Now when Sinnur logs on to his OTA site from his mobile phone, it doesn’t waste his time—it shows his favourite flight and hotel directly and upfront. And he is happy about that.
Chetan Kapoor, research analyst (Asia Pacific) at PhoCusWright, says that earlier, most online companies would strategize based on incoming traffic/IP addresses and SEM (soft error mitigation). But with access to Big Data tools which even scan social networks, companies are able to “listen in” on potential consumers’ opinions, needs and desires, and deliver results accordingly.
He says several online travel companies are dabbling with Big Data one way or another in an attempt to personalize their service and offers to customers.
“Online travel companies like DealAngel Inc and Hopper are scanning the web, and crunching a lot of price data and inventory, to deliver the best travel deals. But generally, these are still very early days, and Big Data is only going to get bigger with increasing posts/content by users across various social networks,” he says.
With online traffic moving towards mobile web and applications, Kapoor says, Big Data on mobiles can fundamentally alter how Big Data tools and analytics can be used.
For decades, companies have been making business decisions based on transactional data stored in relational databases. Beyond that critical data, however, is a potential treasure trove of non-traditional, less structured data. This is where the benefit of Big Data and personalization comes in. “Big Data also offers us the chance to put the fun back into travel, which at its very heart is about improving the customer experience. We want to be present at various touchpoints for our customer, both pre- and post-sales,” Atal says.
Take another example of a regular—perhaps even a first time—traveller searching for “hotels around popular beaches in Goa”. How do OTAs deliver search results to his or her query in the most optimum manner without tipping off the searcher?
That is where OTAs look back into their data and, based on previously drawn inferences of travellers (who also searched for “hotels around popular beaches in Goa” in that particular price range), throw up results for this traveller.
If Cleartrip.com infers that most people who searched for “hotels around popular beaches in Goa” in the past have opted for 3-star hotels around the Baga or Calangute beach, it will probably show the same results for this traveller too.
MakeMyTrip.com sends out targeted mailers and offers based on customer purchase patterns and behaviour to drive personalized interactions with customers.
Show me the money
So how is Big Data being implemented now? Sharat Dhall, president of Yatra.com, says his firm is leveraging a combination of in-house and third-party technologies to develop a more holistic and consolidated view of customers and offer more personalized experiences to customers. “Several pilots are currently under way to evaluate the impact on user experience. One example is a cross-sell engine which is geared towards providing significant value to customers who are searching for flights. The cross-sell engine recommends relevant hotel and flight combinations that maximize savings for the user. Another example is... a customized set of flight results based on what is most relevant for the user,” notes Dhall.
While the pilots are under way and it is too early to draw conclusions, the initial results are promising, says Dhall. “For example, users accessing a recommended flight and hotel combination are twice more likely to convert than an average user. This indicates that we are headed in the right direction in terms of offering value and a differentiated buying experience,” Dhall says.
The key to generating returns on investment from Big Data lies in putting customers’ needs first and building solutions that address them, Dhall says.
MakeMyTrip uses and is open to continue using third-party solutions to become more effective in leveraging information. It is also a big advocate of open-source and collaborative approaches to technology.
“Yatra is pursuing a hybrid approach with in-house technology and partnerships with multiple vendors. We feel this approach enables us to build institutional knowledge regarding Big Data and yet leverage the best-in-class external technology,” Dhall says.
Sridharan of Cleartrip.com says the challenge for users is to have to face “the cognitive dissonance” of browsing through scores of hotels and pick the one most suited to their needs. “With Big Data analytics, our aim is to cut that time down to as small as possible, so that the traveller enjoys the trip without suffering through endless planning,” he adds.
Radhika Balaji endorses it. She says she books the annual Vaishno Devi trip for her parents while she is travelling back home after work in a crowded metro train. “It takes only minutes to book the whole trip,” she adds.
This is the sixth in a seven-part series.
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