Farecast opens up to major cities
August 21st, 2006
Farecast, a paradigm shifting airline price prediction service, recently opened up their service in over 55 cities. I’ve been keeping my eye on Farecast ever since the first announcement, and personally, I’m very excited to see how successful they’ll be in making ripples across the airline industry, and, in the process of how consumers purchase tickets.
There’s been a lot of buzz about Farecast, including a nice mention in Time magazine as part of the 50 coolest websites. I had the chance to speak to the Farecast team at the TechCrunch 7 party last week, all of whom are excited about Farecast’s potential. The major innovation behind the scenes is the data mining know-how. They’ve worked three years with a team of PhDs, researching methods to predict airline prices with confidence. The end result is that we, as consumers, are able to make more informed decisions at the point of sale.
So, how exactly does Farecast predict prices? Do they have access to some secret treasure trove of information that competitors like Orbitz and Travelocity don’t? The answer is no. It turns out that they use exactly the same information, but, unlike Orbitz, they keep and analyze all past pricing information. It’s an honest reliance on smart data mining and analysis.
But analysis by itself is by no means the end. The presentation of the complex prediction data to the average consumer is pivotal. No one would use a confusing prediction interface, no matter how good the prediction is. It turns out that when Farecast conducted focus groups, there were two types of people: data junkies and prediction acceptors.
The data junkies, whom I identify most with, loved to look at the price prediction graphs–the more data, the better. Then, they take matters into their own hands, and decided whether to buy their tickets now or later. On the other hand, prediction acceptors simply wanted to be told to buy now or wait. They didn’t care to look at any other information, and trusted Farecast’s suggestions. These two main groups are represented in Farecast’s search results page, which has a buy now or wait indicator alongside a price history graph.
If you haven’t yet tried out Farecast, you should definitely take a look, especially since they’ve expanded their search to many major cities. I’ve barely touched on Farecast’s interface, which is intuitive, smooth, and beautiful to look at. Oh, and if you thought Orbitz’s grid view is cool, Farecast’s flexible travel data view options will blow you straight out of the water with its multi-color, multi-graphing, multi-destination goodness.
Overall, the airline industry response to Farecast has been positive, since Farecast has the potential to rake in new customers. Other ticketing services like Orbitz have shown interest in partnering and potentially using Farecast’s technology. If all goes well, be on the lookout for enhanced price analysis, not only at Farecast, but at other services as well.
Farecast, a paradigm shifting airline price prediction service, recently opened up their service in over 55 cities. I’ve been keeping my eye on Farecast ever since the first announcement, and personally, I’m very excited to see how successful they’ll be in making ripples across the airline industry, and, in the process of how consumers purchase tickets.
There’s been a lot of buzz about Farecast, including a nice mention in Time magazine as part of the 50 coolest websites. I had the chance to speak to the Farecast team at the TechCrunch 7 party last week, all of whom are excited about Farecast’s potential. The major innovation behind the scenes is the data mining know-how. They’ve worked three years with a team of PhDs, researching methods to predict airline prices with confidence. The end result is that we, as consumers, are able to make more informed decisions at the point of sale.
So, how exactly does Farecast predict prices? Do they have access to some secret treasure trove of information that competitors like Orbitz and Travelocity don’t? The answer is no. It turns out that they use exactly the same information, but, unlike Orbitz, they keep and analyze all past pricing information. It’s an honest reliance on smart data mining and analysis.
But analysis by itself is by no means the end. The presentation of the complex prediction data to the average consumer is pivotal. No one would use a confusing prediction interface, no matter how good the prediction is. It turns out that when Farecast conducted focus groups, there were two types of people: data junkies and prediction acceptors.
The data junkies, whom I identify most with, loved to look at the price prediction graphs–the more data, the better. Then, they take matters into their own hands, and decided whether to buy their tickets now or later. On the other hand, prediction acceptors simply wanted to be told to buy now or wait. They didn’t care to look at any other information, and trusted Farecast’s suggestions. These two main groups are represented in Farecast’s search results page, which has a buy now or wait indicator alongside a price history graph.
If you haven’t yet tried out Farecast, you should definitely take a look, especially since they’ve expanded their search to many major cities. I’ve barely touched on Farecast’s interface, which is intuitive, smooth, and beautiful to look at. Oh, and if you thought Orbitz’s grid view is cool, Farecast’s flexible travel data view options will blow you straight out of the water with its multi-color, multi-graphing, multi-destination goodness.
Overall, the airline industry response to Farecast has been positive, since Farecast has the potential to rake in new customers. Other ticketing services like Orbitz have shown interest in partnering and potentially using Farecast’s technology. If all goes well, be on the lookout for enhanced price analysis, not only at Farecast, but at other services as well.
