The travel industry is no stranger to Data Science disruption – especially air travel. Online flight finders have been snapping up data scientists from other industries in order to make better use of the available data, and airlines have been building and opening APIs.
Many services are using this opportunity to offer the cheapest or most convenient flights, but FLYR Labs have a slightly different perspective: Rather than have customers watching flight prices fluctuate, trying to find the perfect time to buy, FLYR offers a predictive service that allows customers to see how cheap a flight is likely to get and lock in that price.
We spoke to Alex Mans, Co-Founder and CTO of FLYR Labs, to find out more about his story and the vision of FLYR Labs.
You’ve been involved in successful technology startups for over a decade now. Can you share any observations or remarkable milestones from that period, from a personal perspective?
The major changes that have driven my decision making over the past decade relate to the fact that with every year that passes, formerly impossible tasks become within reach of anyone who dares to take them on.
When it comes to utilizing data for bettering people’s lives or simplifying the complex, I learned not to be afraid of thinking big as there’ll pretty much always a solution within reach.
How about in terms of technology shifts and the development of data driven technology?
Over time, we moved from descriptive analytics (“What happened?”) to diagnostic analytics (“Why did it happen?)”.
Early on for example, I was involved with a company that analyzed (internet) network traffic to determine whether security threats were present on a company’s local network. This was diagnostic analytics while most people were still focussed on general error reporting or building dashboards to manually sift through data.
Right now, every industry or vertical is trying to move towards the next major category in data analysis. Predictive analytics (“What will happen?”).
The most important and life-changing shift that we’re starting to see today is a move into the realm of prescriptive analytics (“How can we make it happen?”). Intelligent, prescriptive technologies are the ultimate force in forcing changing and simplicity in people’s lives. Done right, it gives people peace of mind.
FLYR’s technology falls into that category as we predict what airfares will look like in the near future and structure that information in ways that the use can easily consume and act upon (e.g. “Don’t buy this flight yet, we are confident that we can find you a better deal”).
Fluctuating airfares is one of the most interesting predictive analytics applications we’ve come across. How did you land on this as your problem to solve with FLYR?
As many of us, I noticed the huge volatility in airline ticket pricing and figured there had to be some kind of recognizable logic to it.
I did a lot of research into how airlines price their seats. I figured that with the right data, understanding airlines based on how they change their ticket prices would be feasible and value could be extracted from that knowledge.
One of your offerings is the Foresight API. What kind of use-cases can we expect to see for this? What does your target market look like?
Foresight is the API that sits right on top of our prediction technology. Foresight can return a day-by-day prediction of how airfares will move for specific flights, complex combinations of flights or simply at a aggregate (route) level.
This technology and API is made available to any company that wants to integrate it into their products, including online travel agencies, meta-search companies, etc.
Looking at the consumer facing side with GetFLYR.com – can you break down how the services works?
Getflyr.com is dedicated to the 98% of people that search for flights, but have no intention of booking today. For those people, we provide the tools to deal with highly volatile airfares while they finalize their plans.
A graph (powered by Foresight) will tell you how much money is at stake if you wait while fares are expected to increase. If we believe fares are going down, you can quickly see in what savings holding off on your booking would result.
To track a flight and it’s predictions for longer periods of time, you can set a FareBeacon alert that tells you when the time to buy has arrived.
If complete peace of mind is what you want, then FareKeep is the thing for you. Instead of purchasing a flight at say 300 USD today, you can lock-in that fare for a small fee (usually anywhere in between 3 USD and 30 USD) for a week. If fares go up over those 7 days, we will pay for the increase. If fares go down or we find you a better deal, you have the option to pocked the savings.
How much data goes into powering your product, and what does your technology stack look like?
Every hour, FLYR receives millions of airfares from all over the world that feed into our data pipeline. This data pipeline normalizes the data before storing it in a massive database. We use a combination of NoSQL and SQL databases, depending on the storage purpose (e.g. pricing data vs. transactional data).
Whenever we get new airfare data, our prediction algorithms are automatically retrained and distributed to the server cluster that sits right underneath our Foresight API.
As an entrepreneurially minded person, what technological advances excite you most for the future?
As mentioned previously, I see us moving in a world full of prescriptive technology. Technologies that understand what we are looking for and help us to achieve our underlying goals based on predicting will happen next.
The major considerations and in some cases also challenges will evolve around balancing relevance and trust between the user and technology.
Alex Mans, CTO of FLYR Labs, is an entrepreneur with 8+ years of experience in launching and growing online and offline tech products. Focussed on assembling great teams with diverse complementary backgrounds and expert skill levels. Ability to connect and work with entrepreneurs, engineers, designers, marketeers, investors and academics by continuously trying to achieve a deeper understanding of technology, design, research and finance.
(image credit: curimedia)
