System and method for predictive booking of reservations based on historical aggregation and events

• US 7,765,119 B2
• Filed: 10/16/2006
• Issued: 07/27/2010
• Est. Priority Date: 10/16/2006
• Status: Active Grant

• Current Assignee: Deem, Incorporated (Jack Taylor Family Voting Trust U A D 4 14 99)
• Original Assignee: Rearden Commerce Inc
• Inventors: Messa, Suzette
• Primary Examiner(s): Hayes; John W
• Assistant Examiner(s): Jung; Allen J
• Application Number:
  US11/549,962
• Publication Number:
  US 20080091478A1
• Time in Patent Office: 1,380 Days
• Field of Search: 705/5
• US Class Current: 705/5
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202

Abstract

In one embodiment, a method that can be performed on a system, is provided for predictive booking or reservations based on historical aggregation and events. In one embodiment, the method comprises surveying prices paid for traveler purchases or reservations to identify price increases for travel purchases or reservations, wherein the price increases include a increase in a price of a travel purchase during an identified period of time; identifying a correlation between identified price increases for travel purchases or reservations and identified events; predicting of future price increases in select travel bookings based on the identified correlation between the identified price increases for travel purchases or reservations and identified events; and determining whether to purchase or reserve a set of travel bookings based on the predicting of the future price increases.

Claims

1. A method comprising:

performing a post-travel analysis for each of a plurality of travelers after each traveler returns from a trip;

storing results from the post-travel analysis in a data repository or database;

surveying prices paid for travel purchases or reservations to identify price increases for travel purchases or reservations, wherein the price increases include an increase in a price of a travel purchase during an identified period of time, and wherein the travel purchases or reservations surveyed are purchases or reservations repeated more often than a threshold frequency;

identifying, by a computer system, a correlation between identified price increases for travel purchases or reservations and identified events;

predicting, by the computer system, of future price increases in select travel bookings based on the identified correlation between the identified price increases for travel purchases or reservations and the identified events;

purchasing or reserving, using the an electronic services computer system, a set of travel bookings for a first event of the identified events based on the following;

the predicting of the future price increases, the post-travel analysis, purchases or reservations already executed for an event, and a relationship of current purchases or reservations to total purchase or reservation expectations for the event based on stored historical aggregate data from prior travelers;

subsequent to purchasing or reserving the set of travel bookings, receiving a request from a customer for information regarding available travel resources for the first event; and

selling one or more of the set of travel bookings to the customer.

2. The method of claim 1, further comprising identifying a quantity of selected travel bookings to be purchased or reserved, the identifying of the quantity based on the identified correlation between the price increases and identified events.

3. The method of claim 1, wherein the identified period of time is at least one of daily, weekly, monthly, and yearly.

4. The method of claim 1, wherein the surveying prices includes surveying for past and future travel purchases or reservations.

5. The method of claim 4, wherein purchasing or reserving the set of travel bookings is performed automatically.

6. The method of claim 4, wherein the identified events include at least one of an internal event and an external event.

7. The method of claim 4, wherein the identified events include a company event.

8. The method of claim 4, wherein the identified events include one or more of a sporting event, a holiday, trade shows, and exhibits.

9. The method of claim 6, wherein the travel bookings include a booking for at least one of an airline flight, auto rental, and hotel room.

19. The method of claim 1, further comprising, prior to selling the one or more travel bookings to the customer, causing display of a prediction to the customer as to when a resource associated with one or more of the travel bookings will sell out.

10. A non-transitory machine readable medium having stored thereon a set of instructions which when executed perform a method comprising:

surveying prices paid for travel purchases or reservations to identify price increases for travel purchases or reservations, wherein the price increases include an increase in a price of a travel purchase during an identified period of time, and wherein the travel purchases or reservations surveyed are purchases or reservations repeated more often than a threshold frequency;

identifying a correlation between identified price increases for travel purchases or reservations and identified events;

predicting of future price increases in select travel bookings based on the identified correlation between the identified price increases for travel purchases or reservations and identified events;

purchasing or reserving a set of travel bookings for a first event of the identified events based on the predicting of the future price increases;

subsequent to purchasing or reserving the set of travel bookings, receiving a request from a customer for information regarding available travel resources associated with the first event; and

selling one or more of the set of travel bookings to a customer;

wherein the surveying prices includes surveying for past and future travel purchases or reservations.

11. The machine readable medium of claim 10, further comprising identifying a quantity of selected travel bookings to be purchased or reserved, the identifying of the quantity based on the identified correlation between the price increases and identified events.

12. The machine readable medium of claim 10, wherein the identified period of time is at least one of daily, weekly, monthly, and yearly.

13. The machine readable medium of claim 10, wherein purchasing or reserving the set of travel bookings is performed automatically.

14. The machine readable medium of claim 10, wherein purchasing or reserving the set of travel bookings is performed by a person.

15. The machine readable medium of claim 10, wherein the identified events include at least one of an internal event and an external event.

16. The machine readable medium of claim 10, wherein the identified events include a company event.

17. The machine readable medium of claim 10, wherein the identified events include one or more of a sporting event, a holiday, trade shows, and exhibits.

18. The machine readable medium of claim 15, wherein the travel bookings include a booking for at least one of an airline flight, auto rental, and hotel room.

20. The machine readable medium of claim 10, wherein the method further comprises:

performing a post-travel analysis for each of a plurality of travelers after each traveler returns from a trip;

storing results from the post-travel analysis in a data repository or database; and

wherein the purchasing or reserving is further based on the post-travel analysis.

21. A method comprising:

surveying prices paid for travel purchases or reservations to identify price increases for the travel purchases or reservations, wherein the price increases include an increase in a price of a travel purchase during an identified period of time;

preparing, using a computer system, a correlation of the identified price increases with identified events;

preparing, using the computer system, a prediction of future price increases for a first event of the identified events based on the correlation;

reserving, using the computer system, a set of travel bookings to secure additional capacity for expected customer demand for the first event, the reserving being based on the prediction of future price increases;

receiving a request from a customer for information regarding available travel resources associated with the first event;

sending a prediction for display to the customer regarding when a resource associated with the first event will sell out; and

after receiving the request and sending the prediction, selling one or more of the set of travel bookings for the first event to the customer.