Disparities in hotel prices where the biggest differences occur
The emergence of new OTA based integrations 100% XML models or hybrid systems in which in addition to integrations maintains an extranet direct to the hotel, they have meant a new way of understanding the business of brokering, as they find from Ormos Revenue Management Online System. “so feared cannibalization of prices among hoteliers themselves has become a game of children to some channels use prices”, added the sources. In Ormos have analyzed where the greatest disparities are produced by destination, hotel categories, OTA and distributors.
Is that they say from Ormos, many agencies online have created”a real technological engineering designed to make sure the sale either. That includes the breakdown of any binding commitment on what prices received by banks of beds or central reservation refers”.
These incidents occur with more regularity in destinations such as Barcelona (7.2% of the analyzed cases), Madrid (6.35%) and Valencia (5.1%); and hotels of four-star (35.78%), 3 (24.44%) and 5 stars (22.01%). Draws attention to the low incidence in the 2-star, with 5.33%, versus 12.44% of the of 1.
As the main OTA price disparity, they lead the ranking Amoma.com, 14.44% of cases, Muchoviaje.com (12.34%), Bravofly course (11.10%) and Travel Republic (10.21%). Moreover, distributors with a higher number of incidents are Hotelbeds, Restel, Serhs, Tourico Holiday and Expedia.
Not in vain, “for years most central reserves and banks of beds has been more than profitable hoteliers to assume the distribution in a joint position with regard to its direct sales, but the current reality obliges hotels to rethink seriously if this status should be maintained or conversely must come into the distribution of the future ratios as the “control over those receptors channels of hotel prices “.
Million euros in losses
This problem, “very real, it is billion euros of losses in the accounts of exploitation of current hospitality” to lose a client that could attract with its direct sales strategies and that however reach the hotel “with the consequent cost of intermediation”.
Certainly not a single market problem Spanish, since “European capitals like London, Paris and Berlin have disparities in more than 61% of the rates offered in the main meta”, according to the same sources.
Are not alien to him “some big sellers of the market as Booking.com, Viajes El Corte InglÃ©s, Barcelo travel and other agencies with a model of direct selling through extranet with hotel and who are in your same niche markets need to compete with channels in which prices downspouts to ensure the sale are the large base and which have begun to manage a ’yield of disparities””’ focused to seek higher returns in the same”.
Faced with this panorama, they conclude, “is basic to having tools that allow the monitoring of its distribution in those same spaces in which the customer is buying and to establish measures to control such activities which in many cases can damage the brand’s hotel hotelier”.
Types of disparities
In Ormos have defined different types of disparities that we can find in the online world.
Linear: those disparities created linearly with automatic discounts on fees received by any of the.
Opaque: the emergence of opaque rates that become visible in the distribution and allow play with discounts given to the dealer to make use of them, theoretically opaque way.
Package: disparities in which the discount provided by the hotel to carry packages of type flight hotel appears in only hotel sales.
FIT: the emergence of net rates for operating special shown on the online with very high differentials with regard to normal use of the hotels BAR fees.
Availability: created disparities in availability to convert reserves, regardless of the closure of the hotel sales. Only when accessing reserves are notified the change of hotel and suggests establishments with squares.
Release: disparities created by not respecting releases keeping active offers.
Yiedables: carried out selective disparities across each city demand data. Are performed on fewer occasions but looking for more profitable dates.
Markets: disparities that change depending on the search customer market.
KLOK: disparities in bands at night. The activity from 8 pm until 9 o’clock in the morning in regards to disparities created by third parties is higher than in daytime slots.
Weekend: disparities concentrated in weekend between Friday at 8 p.m. and Monday at 9 o’clock in the morning.
Nights: disparities that vary depending on the number of nights.
Load failure: disparities created by the hotel loading failures.