The New Vertical Search

Instead of searching the "now," search the yet-to-be. Farecast uses data to generate both understanding and deeper value.

Perhaps the single most compelling way for consumers to conceive of the value proposition of the Internet is the redistribution of power. The power to create, the power to speak, and the power to know flow out through digital channels to the world at large. Any closed community — banks, car dealers, governments — seems to cower in fear in the face of a connected world.

This is most evident in shopping. Anyone who bought a car in advance of widespread Internet adoption hardly needs to have the benefit of open information explained. Walking onto a car lot today is a much different experience than it was as recently as the early ’90s. Today, consumers come to the car lot loaded for bear:; they not only know the history of the car they’re considering (if it’s used), but also what the dealer paid, how many he’s got sitting in the back, and what the guy down the street is selling it for. Shoot, you almost have to feel sorry for the poor auto dealer.

What about travel? Buying airplane tickets is a classically frustrating experience. Not only did the person sitting next to you most likely pay a different price than you, but there seems to be absolutely no logic behind the difference. Airlines seem to have an extraordinarily complex system dictating how you do business with them. They insist you use it, but refuse to provide details of how it works. Who do they think they are? Google?

(OK. That wasn’t fair. Google’s getting better. Let’s stay on topic.)

Bucking the System

Then, along came Farecast. What an extraordinary concept. If you haven’t seen it, Farecast is an airline ticket price forecast engine. The airlines won’t reveal their method of setting prices. Doing so would wreck the system (they believe), because people would begin to shift purchasing to buy a ticket when it’s cheapest. That’s no good.

Farecast invests in deep data. They capture the fluctuations of airline prices and feed that information into a predictive model. If you’re going to fly from JFK to SFO in six weeks, you can put your dates in to the Farecast system. Farecast will certainly tell you what prices are right now on all the major carries. But anyone can do that.

What Farecast does best is take the data it knows about how that ticket price changes to tell you, with a certain degree of confidence whether or not you should buy that ticket right now, or a week from now when it believes the price will drop significantly. Suddenly, the ticket buyer has the power. The airlines, of course, didn’t reveal their secrets. But they didn’t have to. With the ability to watch the flow of data and process it with Great Big Computers, the power flows, once again, to the people.

Should Airlines Be Upset?

Let’s say airlines should price tickets differently, that the system they’ve devised, cryptic though it may be, represents a level of efficiency that an airline requires in order to be successful. This is giving them the benefit of the doubt.

If the system were truly fair, airlines shouldn’t care when people buy their tickets. And if it’s most efficient to buy tickets at a certain time (that’s beneficial to the airline), the airline would want consumers to buy then. They would, therefore, make the situation the best for everyone. The airline would know they have a full flight (or whatever it is they need) and the consumer would spend the least money necessary.

Either way, it doesn’t matter because Farecast uses the ability to crunch data to solve the problem for us. The other interesting thing that’s happened is that we’ve seen a real shift in the notion of what a vertical search engine could be and how it can help consumers in remarkable ways.

The New Vertical Search Concept

Travel search engines have been around a good long while. I have a clear memory of using Travelocity at least 10 years ago. The ability to look across carriers for a fare (as well as a route and time) that works for you is really powerful. But these engines do specific crawls of content and provide it to you. It’s a glimpse into the now.

What Farecast does is give you a look into the “to be.” They’re taking all the data that’s available to them and using it to its (and our) advantage. This novel use of data to generate a higher-level of understanding and a deeper value is truly amazing.

There certainly are precedents. The Amazon book recommendation engine is probably the earliest, in which data are analyzed on the backend to provide a more compelling front end experience. Farecast seems to take things a giant step further, using data analysis not to upsell, but to provide consumers with deeper understanding of the world in which they operate.

All the vertical search players should take a long look at what Farecast has done and ask themselves a simple question: “what could we do with what we know to make the consumer’s experience way freakin’ better?”

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