Revenue management system
AssigneeChris Ternoey
InventorsChris Ternoey, Diana Jelescu
Life of this patent
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Abstract
A method and system for optimizing dynamic prices of reserved date-constrained services such as airline flight reservations or hotel stay reservations. Comparative trials of complex pricing policies are employed according to an application schedule that has a periodic character with respect to the arrival date of quoting circumstances. On the basis of the comparative trials, some policies are identified as contributing less revenue on average to the system than other policies. The underperforming policies are then eliminated from the application schedule, which increases the expected future revenue of the resulting system.
Claims5
A method of optimizing the process of quoting prices for reserving a date-constrained service comprising the steps:
- defining a family of candidate pricing policies wherein each of said pricing policies is comprised of a rule for determining the quoted price based on the parameters of the quote request as well as the time and circumstance of the service provider;
- generating an application schedule, wherein said application schedule comprises a plurality of pairs of data, wherein the first element of each said pair represents a unique quote circumstance and the second element of each said pair represents a specific member of said family of candidate policies, and wherein said plurality of pairs represents an unambiguous logical mapping from all possible quote circumstances to associated pricing policies;
- responding to a quote request by searching said application schedule for the unique data pair that corresponds to the parameters of said quote request and by identifying the secondary element of said unique data pair as the applicable pricing policy to be applied in response to said quote request;
- applying said applicable pricing policy to the parameters of said quote request and time and circumstance of service provider to determine the price value that should be quoted as a final response to said quote request;
- computing a performance metric associated with any sale resulting from said quoting process;
- summing said performance metric over all sales transactions associated with each member of said family of candidate policies;
- comparing said summed performance metric of each member of said family of candidate policies and eliminating one of said members of said family of candidate pricing policies based on the value of its associated summed performance metric;
- whereby sub-optimal members of said family of candidate policies are thus identified and removed from said family of pricing policies and a more nearly optimal family of pricing policies is thus determined.
Dependencies are inferred from the claim text.