Pickyourtrail is a travel company that delivers tailor-made international holidays. Their unique matching algorithm and price comparison engine gives you the freedom to create your own customized tour packages suited to your tastes at the best online prices.
Mr. Srinath Shankar is the Co-founder at Pickyourtrail. He is the brain behind the routing, pricing and personalisation algorithm at Pickyourtrail. He holds a Bachelors in Mathematics and an MBA from NMIMS Bombay.
In an interaction with Techxty , Srinath Shankar talks about the role of Big Data in travel – tech companies. Read On!
Tell us something about yourself and what does pickyourtrail do?
A Europe trip back in 2012, changed the way I viewed vacations. While on tour, I met with a lot of people who had booked their travel with leading travel agents, but, were dissatisfied with the service. The main reason of displeasure was how, despite having paid exorbitant amounts for the international vacation, they still felt like they had yet to have a great experience.
Which is when my Co-Founder – Hari Ganapathy and I, understood the need for a player in the industry that tailor-made vacations. Indians were willing to travel, but, were only provided with a ‘one size fits all’ experience.
At Pickyourtrail, we tailor make international holidays . Our unique matching algorithm and price comparison engine gives our clients an opportunity to create their own customized tour packages, suited to their tastes, at the best prices.
Prior to Pickyourtrail, I was with Western Union, and I am an avid traveller myself. I enjoy math and aeroplane modelling, and hold an MBA from NMIMS Bombay.
How can artificial intelligence optimize the customer experience with online services?
In this current age when AI and ML are freely thrown around as Jargons, we have used it under the hood without complicating the experience for the users. Few examples are mentioned below:
- Routing Algorithm: This is an extension of the classical travelling salesman algorithmic problem in the field of computer science and operations research. Our problem statement was “If n number of cities are chosen by a traveller, how to arrive at an order to visit the cities which minimises travel time and cost”. We consider multiple factors like travel time between 2 cities, mode of transport, duration, airline/train hub, international airport etc to come up with an optimised recommendation to travellers. These data points are consistently updated and the machine learning algorithm takes care of updated recommendations to users.
- PDG mapping: What to do in a city is a holy grail question that haunts every traveller. Our PDG flow along with Demographic data collection of travellers gives us a good idea about user preferences. Our personalisation engine tries to match this with experiences/activities in our database and come up with curated recommendations. Our experiences have 40+ metadata points (activity stress level, interest category, suitability, duration etc) to give a highly relevant recommendation to users
- Smart and personalised filters: Having executed 10000+ trips, we understand what Indian travellers want. Our flight recommendation automatically filters flights are not recommended for poor flight duration or with high cancellation history. Similarly, in Hotels, we filter the ones which are not in the city centre or poorly rated.
How do you think technology and travel will grow together?
Nobody doubts the importance of technology on the travel industry, its impact and how it continues to influence the way we travel – be it the destination, mode of travel, what we do there etc. Technology has helped to streamline services and help eliminate redundant intermediaries from the equation.
With technology revolutionising the way the travel industry operates the world over, there are a few aspects that it has helped shape – more affordable booking, decentralising the knowledge (which was monopolised by 1-2 players in the industry), and has also greatly helped improved customer service – which is the core of the travel industry.
According to a study by Think With Google, 57% of the respondents opined that brands should tailor information based on personal preferences or past behaviours. And here is where Machine Learning and Artificial Intelligence come into play. Machine learning helps unlock new insights and opportunities for travel companies to deliver better. Another interesting insight gleaned from this study is the increase in the use of voice and digital assistants. It was found that 1 in 3 travellers across countries were interested in using digital assistants to research or make bookings.
What is most challenging in travel industry?
Lack of customization – If you work with any OTA, it takes 24 to 48 hrs to actually customise your itinerary. So people have to wait in-order to build their own customised personal itinerary
Self-planning is a huge task – If you want to plan everything yourself, people will have to hop about 40 – 45 sites to put together a plan of pricing, routine and logistics of the travel
Money vs time – The average ticket size for vacations is a lakh on our platform. So given that it is a big deal size, but the decision timing is smart, for example if you see our closest or fastest converts happens in less than 30 minutes and on an average a lead or an enquiry to conversion or booking is about 14 days. So bout 2 ½ – 3 lakh ticket size is being decided in 14 days, and there’s a lot of information that has to be processed, trust that has to be gained and that’s also a challenge when people work with other vendors like travel agents or OTA’s and how we build the trust online is a huge challenge.
So broadly the challenges in the industry 1) information is fragmented over a number of places, and hence it can be time consuming and increasing people have more money than time and how do we solve that inequality, number 2) If you go and stand in OTA’s, local travel agents have many constraining packages and no real customer optimization or personalization and how do we break that piece, number 3) It is a very involved purchase in very little amount of time and how do you build trust and ensuring that information overload does not get to people.
What will be the impact of blockchain technology on the future of travel industry?
In all the noise about blockchain in the travel industry, one place where its full potential can be utilized is loyalty programs. Multi-brand hotel chains or airline consortiums can move to single loyalty program, that can be made more effective through block chain.
How is big data analytics helpful for travel-tech companies?
The travel industry probably offers one of the most interactive mobile/web products. This leads to a tremendous amount of customer data that is generated. Big data helps to remove the grain from the chaff and provide a truly personalized experience to the customers. On the other hand, the inventory pricing is also probably the most dynamic in nature, since it is heavily dependent on availability and season. Big data can also help with price discovery and deal hunting.