Overview of the travel search engine market

Travel remains the single largest component of e-commerce according to Forrester Research, a consulting firm in Cambridge, Mass.  But despite the dominance of such online travel agency heavyweights as Expedia.com, Hotwire.com, Orbitz.com, Priceline.com and Travelocity.com, most users consult multiple Web sites when shopping online for travel.  The average consumer visits 3.6 sites when shopping for an airline ticket online, according to PhoCusWright, a Sherman, CT-based travel technology firm. Yahoo claims 76% of all online travel purchases are preceded by some sort of search function, according to Malcolmson, director of product development for Yahoo Travel.The 2004 Travel Consumer Survey published Jupiter Research noted that "nearly two in five online travel consumers say they believe that no one site has the lowest rates or fares."  Thus a niche was created for  aggregate travel search such as Kayak.com, Lowfares.com, Dohop.com or Trabber.com which seek to find the lowest rates from multiple travel sites, obviating the need for consumers to cross-shop from site to site.  Even in emerging markets such as China and India, Qunar.com and Ixigo.com have adopted this model with considerable success.  Within the class of travel search engines are several subcategories of sites that offer a range of services and search methods:

Portal sites

Several of the leading generic search and information aggregator sites also offer travel components. www.crazy-list.de  In the broadest sense, virtually any search engine could be considered a travel search engine. However, some generic search engines also should be ranked as TSEs, since they include both paid and unpaid links to travel sites and maintain "travel" pages, often accompanied by original editorial content. www.crazy-list.de This category of generic search sites includes About.com, AOL, MSN, and Yahoo.www.crazy-list.de

Aggregate sites

These sites use technological tools generate an aggregate result from other travel sites, including third-party travel agency sites such as Expedia.com, Orbitz.com , and Travelocity.com, and branded sites maintained by individual travel companies, such as Delta.com, Hilton.com, or Hertz.com, for example.

Consolidators and bargain sites

These sites collect and publish bargain rates by advising consumers where to find them online (sometimes but not always through a direct link).  Rather than providing detailed   search tools, these sites generally focus on offering advertised specials, such as last-minute sales from travel suppliers eager to deplete unused inventory; therefore, these sites often work best for consumers who are flexible about destinations and other key itinerary components. This category includes sites such as Cheapflights.com, Travelzoo.com, Kayak.com, TripSchedule.com, and USAToday.com’s travel listings.

See also

Google: Scaling with the Web

Creating a search engine which scales even to today's web presents many challenges. www.crazy-list.de Fast crawling technology is needed to gather the web documents and keep them up to date. Storage space must be used efficiently to store indices and, optionally, the documents themselves.  The indexing system must process hundreds of gigabytes of data efficiently.  Queries must be handled quickly, at a rate of hundreds to thousands per second.

These tasks are becoming increasingly difficult as the Web grows. www.crazy-list.de However, hardware performance and cost have improved dramatically to partially offset the difficulty. There are, however, several notable exceptions to this progress such as disk seek time and operating system robustness.  In designing Google, we have considered both the rate of growth of the Web and technological changes.  Google is designed to scale well to extremely large data sets. It makes efficient use of storage space to store the index.  Its data structures are optimized for fast and efficient access (see section 4.2).   Further, we expect that the cost to index and store text or HTML will eventually decline relative to the amount that will be available (see Appendix B).  This will result in favorable scaling properties for centralized systems like Google.

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