Travel Search Engines All Offices Address & Location

Flight searches such as Google Flights, Skyscanner, Kayak, and Momondo can, and in many cases do, compare airfares across hundreds of airlines and travel websites, allowing you to search the prices of all providers simultaneously, offer price alerts, and enable you to see dates as flexible, such as Skyscanner’s Everywhere search or Momondo‘s Flight Insight search. The most popular Indian websites are ixigo, Yatra, and MakeMyTrip when it comes to local and international bookings, and some, such as Expedia, Priceline, and Hopper, also provide full-fledged travel booking services. Alongside the increase in demand of air travel has been the creation of search tools that will enable the user to search, compare, and book flight tickets. Flight search engines (also known as meta-search engines) are a type of intermediary between the airlines and online travel agencies (OTAs) and their users. 

Popular Search Engine Used By Travelers

These engines gather air-fares and flight itineraries and make what is a fragmented and opaque marketplace to look like a transparent commodity. Skyscanner – Skyscanner is the ultimate search engine which browses the internet to locate the most ideal flights, hotels and car hire deals to your next travel. Kayak Other well-known travel search engines include Kayak that allows one to find flights, hotels, and car rentals. Google Flights – Google Flights is a flight search engine. Momondo – Find flight, hotel and car offers and make direct bookings with the travelers. Hipmunk – Hipmunk is a travel site through which you can compare and make a book about the hotels and flights. HotelsCombined – HotelsCombined is an online hotel price comparison search engine (Hotel search) as it lists hundreds of hotels and allows you to find the hotel that you best fit in at the lowest rate. Google Hotel Search – Google hotel search. Hotel Finder – Find your perfect hotel on Booking.com. Trivago – Find the hotel prices of your choice on more than 200 booking sites at once. Rome2rio – Find out how you can travel anywhere by plane, bus, train, ferry and car.

Journey Of Travel Meta Search

These tools were first released in the middle of the 90s and basically scraped the airlines websites of a timetable. At the beginning of 2000s, meta-search engines were developed, providing customers with an opportunity to receive the results of various Online Travel Agencies (OTAs) and airline ticket systems in one interface. Companies that were some of the first to begin the business include Kayak (2004) and Skyscanner (2003). Over the next two decades, the industry has since evolved into three sub-verticals; meta-search engines (e.g., Google Flights, Momondo) that do not sell tickets but display results, OTAs (e.g., Expedia, Booking.com) that do sell tickets, as well as result in meta-search engines which are smaller, or focus on a specific geographic area. The development of flight search engines is closely connected with deregulation of airline pricing. Deregulation of airlines, mainly in the US and EU, has given airlines the freedom to rely on dynamic pricing processes to revise the price of the tickets with every minute based on the supply and demand and changes done by rival airlines. Consequently, flight search engines represent the most frequented platform of presenting these variable prices to its customers and elevates the worth of real-time data retrieval and ranking algorithms. Once data has been normalized, the engine runs pricing algorithms to compute the effective fare (i.e. price of the journey including tax, fees and optional services). The results are then ranked by the engine using a multi-objective scoring model (price, length of flight, number of legs, time of departure/arrival and airline quality). This ranking is increasingly being grounded on machine learning. They train a monitored algorithm based on historical click-through rates and conversions to determine the probability of a user to book a given trip, and rank results. Reinforcement learning is also used by them to adjust the algorithm, depending on the real responses to the results. They target the trade-off between the short-term value (higher commissions) and the long-term one (repeat customers).