Minimizing Agony, Maximizing Pageviews

On Wednesday at the Launch Conference, travel search engine Hipmunk presented a new mobile version of their web app. But that's not what I want to talk about. I want to talk about Hipmunk's general approach to solving the problem of airfare search, and how it might be applied to other problems. The genius of Hipmunk is in their "agony" algorithm, grounded in the key insight that when people search for airfares, price and departure time are rarely the only considerations. What people really want to know is how agonizing the trip will be, measured as a combination of price, duration, and number of layovers. So Hipmunk sorts your search results by this "agony" score (in descending order of course). Simple. Brilliant. There's so much agony in the world; what else could this model be applied to?

The first thing that jumps to mind is turn-by-turn directions. Most navigation apps provide routes that optimize for distance or time, and in some cases by real-time traffic patterns. But there are a lot of other factors than can contribute to one's agony while driving. For instance, given the choice, I'd much rather drive a scenic route than an interstate, but likely only if the scenic route isn't orders of magnitude more time-consuming. Or maybe I'd like to drive a route with better food options than Shoney's and Roy Rogers. Transit directions could also benefit from applying this model. I'd much rather take a trip that involved a transfer if the two subways were less crowded than the one, provided the trip duration wasn't significantly longer.

Another great application of the "agony" model would be a site that helped you decide whether or not buy something online or at a nearby store. The algorithm could factor in a combination of item cost, shipping cost, shipping duration and return policy of the online option, and compare it to the item cost and travel distance to a local store that carries the item, as well as the real-time availability of that item in the store's inventory ( is working on this last problem).

Sorting by "agony" factor is a powerful idea, and one that is quickly letting Hipmunk soar to the top of the travel search business. What other problems could you apply this model to?

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