OFFER BASED RESTAURANT RESERVATIONS

• US 20130013350A1
• Filed: 07/08/2011
• Published: 01/10/2013
• Est. Priority Date: 07/08/2011
• Status: Abandoned Application

• Current Assignee: OpenTable, Inc. (Booking Holdings, Inc., fka Priceline Group Inc.)
• Original Assignee: OpenTable, Inc. (Booking Holdings, Inc., fka Priceline Group Inc.)
• Inventors: McCullough, Charles Norman, Teoh, Elaine, Valdivia, Edgard
• Application Number:
  US13/179,348
• Publication Number:
  US 20130013350A1
• Time in Patent Office: Days
• US Class Current: 705/5
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A system for offer based restaurant reservations comprises a processor and a memory. The processor is configured to: receive a request for a reservation including a set of attributes such as a date or date range, a time range, a location, a cuisine, and a party size; determine a set of available reservations based on an actual table availability for the date, time, and the party size; determine one or more offers based on the date, time, and the party size; determine an overlapping subset between the set of available reservations and the one or more offers; and provide an indication of the overlapping subset. The memory is coupled to the processor and is configured to provide the processor with instructions.

Claims

1. A system for offer based restaurant reservations, comprising:

a processor configured to;

determine a set of available reservations based on an actual table availability for a date, a time, and a party size, wherein the actual table availability is determined by calculating combinations and permutations for table availability of a restaurant;

determine one or more offers based on the date, the time, and the party size;

determine an overlapping subset between the set of available reservations and the one or more offers; and

a memory coupled to the processor and configured to provide the processor with instructions.

2. A system as in claim 1, further comprising receiving a request for a reservation including receiving the date, the time, and the party size.

3. A system as in claim 1, further comprising providing the overlapping subset.

4. A system as in claim 1, wherein combinations and permutations include possible table combinations or separations or other arrangements possible for a restaurant.

5. A system as in claim 1, wherein the actual table availability is determined in real time.

6. A system as in claim 5, wherein the determination of availability uses a combination and/or permutation calculation based at least in part on one or more of the following:

up to date reservation information, usage information, and configuration information.

7. A system as in claim 1, wherein the one or more offers is/are determined in real time.

8. A system as in claim 1, wherein the one or more offers are based at least in part on one or more of the following:

a start date for an offer, a stop date for an offer, an offer day, an offer hour.

9. A system as in claim 1, wherein the one or more offers are based at least in part on one or more of the following:

a daily maximum cover, a number of seated covers, a cap for number of offers, a number of offers, an amount of offer, a diner'"'"'s location, a diner'"'"'s proximity to a restaurant, an availability of an offer, a diner'"'"'s history of restaurant use, or an arrival rate limit.

10. A system as in claim 1, wherein actual table availability is based on one or more of the following:

a daily maximum cover, a number of seated covers a diner'"'"'s location, a diner'"'"'s proximity to a restaurant, a diner'"'"'s history of restaurant use, or an arrival rate limit.

11. A system as in claim 1, wherein the one or more offers are based at least in part on one or more of the following:

a minimum party size and a maximum party size.

12. A system as in claim 1, wherein the overlapping subset includes one or more reservations each with an associated offer for the date and the party size.

13. A system as in claim 10, wherein the overlapping subset includes one or more reservations each with an associated offer for times around the time.

14. A system as in claim 1, wherein the one or more offers change in one or more of the following:

a graded way, a stepwise fashion, or a linear fashion.

15. A system as in claim 1, wherein the one or more offers are made automatically based at least in part on a rule set.

16. A system as in claim 15, wherein an automated offer start or end is based at least in part on triggering events or prespecified conditions.

17. A system as in claim 16, wherein the trigger event is triggered based on one or more of the following:

a user behavior, a user geographic location, a user spending history, a visit history, a time spent on a page, a page viewing history, a dining history, a preferred cuisine, and a dining location.

18. A system as in claim 16, wherein actual table availability is based on one or more of the following:

a user behavior, a user geographic location, a user spending history, a visit history, a time spent on a page, a page viewing history, a dining history, a preferred cuisine, and a dining location.

19. A system as in claim 15, wherein an automated offer start or end is based at least in part on a percentage full of a restaurant.

20. A system as in claim 15, wherein an automated offer start or end is based at least in part on revenue optimization.

21. A system as in claim 15, wherein an automated offer start or end is based at least in part on resource optimization.

22. A method for offer based restaurant reservations, comprising:

determining a set of available reservations based on an actual table availability for a date, a time, and a party size, wherein the actual table availability is determined by calculating combinations and permutations for table availability of a restaurant;

determining one or more offers based on the date, the time, and the party size; and

determining an overlapping subset between the set of available reservations and the one or more offers.

25. A system as in claim 22, wherein generating the plurality of available tables includes searching all possible permutations and combinations of table availability at plurality of restaurants.

26. A system as in claim 22, wherein generating the plurality of available tables includes searching allocations or allotments of a plurality of restaurants.

27. A system as in claim 22, wherein generating the plurality of available tables includes searching table availabilities each associated with a time slot in a plurality of restaurants.

28. A system as in claim 22, wherein the trigger event is triggered based at least in part on revenue optimization.

29. A system as in claim 22, wherein the trigger event is triggered based at least in part on resource optimization.

30. A system as in claim 22, wherein the trigger event is triggered based at least in part on a user behavior.

31. A system as in claim 22, wherein the trigger event is triggered based at least in part on a user geographic location.

32. A system as in claim 22, wherein the trigger event is triggered based at least in part on a user spending history.

33. A system as in claim 22, wherein the trigger event is triggered based at least in part on a visit history.

34. A system as in claim 22, wherein the trigger event is triggered based at least in part on a time spent on a page.

35. A system as in claim 22, wherein the trigger event is triggered based at least in part on a page viewing history.

36. A system as in claim 22, wherein the trigger event is triggered based at least in part on a dining history.

37. A system as in claim 22, wherein the trigger event is triggered based at least in part on a preferred cuisine.

38. A system as in claim 22, wherein the trigger event is triggered based at least in part on a dining location.

23. A computer program product for offer based restaurant reservations, the computer program product being embodied in a computer readable storage medium and comprising computer instructions for:

determining a set of available reservations based on an actual table availability for a date, a time, and a party size, wherein the actual table availability is determined by calculating combinations and permutations for table availability of a restaurant;

determining one or more offers based on the date, the time, and the party size; and

determining an overlapping subset between the set of available reservations and the one or more offers.

24. A system for offer based restaurant reservations, comprising:

a processor configured to;

generate a plurality of available tables using availability rules;

filter the plurality of available tables to determine a set of pertinent available tables;

generate a plurality of offers using offer rules;

filter the plurality of offers to determine a set of pertinent offers;

determine an overlapping subset between the set of pertinent available tables and the set of pertinent offers;

in the event that a trigger event occurs, provide an offer to a user from the overlapping subset; and

a memory coupled to the processor and configured to provide the processor with instructions.

39. A method for offer based restaurant reservations, comprising:

generating a plurality of available tables using availability rules;

filtering the plurality of available tables to determine a set of pertinent available tables;

generating a plurality of offers using offer rules;

filtering the plurality of offers to determine a set of pertinent offers;

determining an overlapping subset between the set of pertinent available tables and the set of pertinent offers;

in the event that a trigger event occurs, providing an offer to a user from the overlapping subset.

40. A computer program product for offer based restaurant reservations, the computer program product being embodied in a computer readable storage medium and comprising computer instructions for:

generating a plurality of available tables using availability rules;

filtering the plurality of available tables to determine a set of pertinent available tables;

generating a plurality of offers using offer rules;

filtering the plurality of offers to determine a set of pertinent offers;

determining an overlapping subset between the set of pertinent available tables and the set of pertinent offers;

in the event that a trigger event occurs, providing an offer to a user from the overlapping subset.