{"id":5096,"date":"2017-04-05T17:20:11","date_gmt":"2017-04-05T21:20:11","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-digit\/submission\/freebird-using-data-to-get-you-out-of-a-jam-and-onto-a-plane\/"},"modified":"2017-04-05T17:20:11","modified_gmt":"2017-04-05T21:20:11","slug":"freebird-using-data-to-get-you-out-of-a-jam-and-onto-a-plane","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/freebird-using-data-to-get-you-out-of-a-jam-and-onto-a-plane\/","title":{"rendered":"Freebird: Using data to get you out of a jam and onto a plane"},"content":{"rendered":"

We\u2019ve all been there before.<\/strong><\/p>\n

Lined up in front of the gate agent, exasperated after deplaning, totally unsatisfied with a $10 food voucher. Other airlines\u2019 flights are still taking off with empty seats, and the next flight on your airline is slowly filling up, one seat at a time, as the people ahead of you in line get their tickets. If you\u2019re an average traveler and you really need to get somewhere, you have no recourse. You have to wait in line, break the bank for a new ticket, or just give up and cancel your trip.<\/p>\n

After an experience like this stranded HBS student Ethan Bernstein and his classmates in Park City, Utah, Bernstein set out on a one-way entrepreneurial journey to solve last-minute flight delays and cancellations for good. Forgoing a second year at HBS, he partnered with an MIT researcher studying machine learning\u00a0and launched Freebird.<\/p>\n

So what was the big idea?<\/strong><\/p>\n

Using statistical analysis and predictive algorithms to forecast risk, Freebird promises to\u00a0immediately buy a new itinerary on any airline (!!!) for any traveler who purchased the Freebird service and faced a last-minute cancellation or delay (in excess of four hours). <\/em>By connecting\u00a0into airline data systems, Freebird is able to notify passengers immediately via text message as soon as a disruption occurs \u2013 often before the airline makes an announcement and notifies other passengers of the disruption. With just three clicks, travelers can\u00a0get a new seat, avoid the stress of lines, and maybe even get some buffalo wings to go as they walk to the gate of their new flight.<\/p>\n

<\/a><\/p>\n

Freebird: Travel Empowered<\/a><\/p>\n

So isn\u2019t that just like travel insurance?<\/strong><\/p>\n

Not really. For decades, airlines have of course built their own models to forecast demand for individual flights, as well as the likelihood and cost of delays or cancellations. They use these models to forecast revenues and manage costs, but they don\u2019t really use the data to inform the price of their travel insurance products. On top of this, when you tick that travel insurance box at checkout, you\u2019re really insuring the cost <\/em>of your trip, not your trip<\/em> itself. But that just doesn\u2019t cut it when you really need to get to your best friend\u2019s wedding. In that case, you\u2019re less worried about the cost of the trip; you need to prevent a bride- or groomzilla rampage and spare yourself having to tell them you can\u2019t make the ceremony. That\u2019s where Freebird comes in.<\/p>\n

Alright, so how does it work?<\/strong><\/p>\n

Using historical flight-level cancellation and delay data in combination with the historical cost of last-minute bookings, Freebird has built the foundation of a risk model that assesses the probability-adjusted cost of selling the company\u2019s guarantee to any passenger. The aim, of course, is to sell the Freebird guarantee to enough passengers on lower-risk flights to more-than-cover the cost of rebooking customers with cancelled or delayed itineraries.<\/p>\n

The company is still testing its early value capture strategies. For now, Freebird \"\"<\/a>offers an annual subscription or charges a one-time fee of $19 per one-way and $34 per round trip. The company website indicates these prices are part of a \u201claunch promotion,\u201d and suggests variable pricing is coming. A concern with these non-variable pricing structures would obviously be that a subscriber who flies the Chicago to New York shuttle every week in the winter may end up requiring more payouts than they\u2019re worth. Similarly, a single-use traveler may require substantial acquisition costs and still present a relatively high likelihood of payout. For the existing models to work — or even just work well enough to keep some of their investors’ cash\u00a0in the coffers — Freebird will need a broad enough base of customers to achieve the required levels of cross-subsidization.<\/p>\n

Still, one can easily imagine a nice runway for growth as the startup\u2019s risk models and pricing improve. For example, Freebird could improve its risk calculations by incorporating in-year weather patterns, estimating last-minute empty seat inventory across other airlines, and integrating data fields that specify causes of delay (e.g., a maintenance delay last winter may not need to be factored in this year). \u00a0With this data, the company could then roll out sophisticated variable pricing that adjusts subscription or a la carte prices for different fare classes, cancellation risk levels, and estimated empty seat counts for last-minute rebooking.<\/p>\n

What does the future for the company look like?<\/strong><\/p>\n

The company\u2019s progress to date and vision for the future have earned a fair bit of praise from the likes of Forbes, Bloomberg, and travel media company Skift, but the company certainly faces some important challenges.<\/p>\n

\"\"<\/a>First and perhaps foremost, distribution is not an easy nut to crack here. Freebird is currently only available as a standalone purchase on getfreebird.com. Travelers aren\u2019t used to booking their ticket and then subsequently thinking about adding on a service like Freebird\u2019s on a completely different site.<\/p>\n

Second, the data problems will continue to be central to the company\u2019s success. What data should be included in the risk model? Which parameters should the predictive risk algorithm evaluate, and how should each parameter be weighted? Are there thresholds of excess capacity on alternative flights that should determine whether Freebird even offers its service on a specific itinerary? And the list goes on.<\/p>\n

Fly with Freebird<\/strong><\/p>\n

Next time you really need to get somewhere, consider buying Freebird after you buy your flights. Instead of letting a silly maintenance issue or a delay with the inbound plane ruin your trip, take power back into your own hands. Fly with Freebird.<\/p>\n

 <\/p>\n

 <\/p>\n

 <\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

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