Metasearch 2.0: Consumers turn the tables on revenue managers

June 16, 2006 |

As metasearch players have gained broader consumer acceptance, and perhaps more importantly brokered the deals to provide unfettered access to fares and rates, the true power of these next generation travel technology players has come into focus.

by John Bray

The first wave of metasearch was lauded by many suppliers at the same time it was dismissed vehemently by online intermediaries. However, as metasearch players have gained broader consumer acceptance, and perhaps more importantly brokered the deals to provide unfettered access to fares and rates, the true power of these next generation travel technology players has come into focus. Instead of the mass price deflation that many initially feared, it is instead the true enablement of consumers to find the best product to buy that is now emerging. The almost endless possibilities of the applications that these technologies can provide, that will signal the ultimate success of these players and challenge their intermediary brethren to compete.

Initial signs of this transformation emerged earlier this year with Kayak’s Fare Buzz and FareCompare’s mapping mash-up(1). The power of these applications for consumers soon became apparent as travel search transformed from “what is the best fare from Denver to Miami (perhaps across several suppliers)” to “where can I go next weekend for less than $300,” or “what is the farthest I can go for less than $500.” In the not too distant future, these mapping queries will go even further, allowing consumers to easily mash-up travel-planning elements like weather to imagine “where can I go that is within 20 miles of the beach and over 85 degrees,” or “where can I go that ....” (bounded only by ingenuity and imagination).

With a little of this imagination, several players have recently emerged to say: Given all of this fare data, can’t we empower consumers to predict where airfares will rise or fall, helping them make the decision of if or when to buy. It is no secret that airlines hire Ph.D’s in mathematics, and pay millions of dollars for revenue management systems to predict demand, set rates, and ultimately predict the yield they will receive on a route. To date, however, this faring process has been mysterious for consumers who often wonder “why is it so expensive to fly to ABC when it is much cheaper to fly to XYZ (even when XYZ is much further away then ABC?,” or “I just flew to Chicago two weeks ago and this week the fare is twice as expensive.” This lack of transparency is exactly what Travel 2.0 attempts to abolish, in this case by giving consumers full access to the fare trends.

Currently, three companies have taken slightly different approaches to helping consumers understand these fare trends. FareCompare has continued the trend of consumer empowerment (it recently provided a search feature for the mysterious so-called “Q-UP fares” that automatically upgrade travelers from coach to first/business class at a fraction of the cost) by offering Trip Search. Similarly to the historical buying trend that airlines utilize in their faring algorithms, a query of Denver to Los Angeles graphically provides the minimum, average, and maximum lowest price across their cadre of airline providers over the last year. Given this trend line, a consumer can easily decide when to buy that inevitable trip to the in-laws for Thanksgiving.

Perhaps the most elegant concept behind these tools is their simplicity for consumers. In fact, a new mash-up called FlySpy (still in private beta at publication) reverse engineers some of the mystique associated with the airline industry and makes it extremely transparent. Suppose you are planning a trip to Chicago in the next month, but are flexible about the dates. Instead of a historical fare graph (as FareCompare provides), a FlySpy query returns a graph of flight prices over the next 30 days so that a consumer can quickly look at which days are the cheapest to fly. Booking is initiated by clicking on a point on a graph (simple). Destinations can be overlaid on top of each other as well (e.g., O’Hare and Midway), so that consumers can easily compare fares to find the best departure date, price and destination.

Another new entrant, initially dubbed as Hamlet, but officially launched as FareCast, uses a predictive algorithm and patent pending technology to recommend when you should buy your ticket. Perhaps sensing that the line graph metaphor is a bit too geeky (yawn) for most consumers, FareCast boils all of the charts down to a simple “Buy Now (fares will rise)” or “Wait (fares will drop)” response to your flight query. Its team of 100-plus computer scientists and Ph.D. mathematicians (perhaps no longer employable by the bankrupt airlines) are supporting airlines by nudging consumers to click “buy” without further delay (a value proposition that will surely be debated further).

These services exemplify what Travel 2.0 is all about: flexibility, transparency and consumer control. Expect these services to enable their technology for mash-ups into other travel planning services (e.g., social travel networks) to stimulate travel buying. Feel the disruption?

(1)web application hybrid—a Web site or Web application that combines content from more than one source.

John Bray is the vice president of advisory services at PhoCusWright Inc., where he leads the strategic consulting and custom research practice.