Systems and methods for matching venues and attractions

• US 8,234,150 B1
• Filed: 11/15/2011
• Issued: 07/31/2012
• Est. Priority Date: 06/21/2011
• Status: Expired due to Fees

• Current Assignee: Kickdrum LLC
• Original Assignee: Kickdrum LLC
• Inventors: Pickton, Kacie Maiken, Barel, David
• Primary Examiner(s): Jasmin, Lynda
• Assistant Examiner(s): Walker, George H
• Application Number:
  US13/297,090
• Time in Patent Office: 259 Days
• Field of Search: 705/7.31
• US Class Current: 705/7.31
• CPC Class Codes: G06Q 10/101 Collaborative creation, e.g. joint development of products or services
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• CPC Class Codes: G06Q 30/0261 based on user location

Abstract

Certain embodiments disclosed herein provide devices, systems, and methods of using location-based virtual audience feedback to estimate interest in an attraction at one or more venues. Certain embodiments provide devices, systems, and methods of using location-based virtual audience feedback and/or other audience data to estimate interest in a plurality of attractions or other items of interest at a particular venue.

Claims

1. A system for matching an attraction with one or more venues, the system comprising:

a database that stores information about an attraction, venues that are capable of hosting the attraction, and consumers who may have interest in the attraction;

a computer that has access to the database and that is configured to;

receive indications of interest from at least some of the consumers, wherein each indication of interest is generated by an action performed by an interested consumer using an electronic device configured to send indications of interest to the computer, and wherein each indication of interest indicates that the interested consumer has interest in the attraction or interest in a category of attractions to which the attraction belongs;

receive location information that identifies a location corresponding to each interested consumer;

determine interest metrics representing a level of interest in the attraction for each interested consumer, wherein the interest metrics are based at least partially on the received indications of interest;

determine social influence metrics representing likelihoods that consumers will be influenced by actions of others;

determine participation metrics representing a rate of participation in past events for each interested consumer;

weight the interest metrics, the location information, the social influence metrics, the participation metrics according to their relative importance in calculating the likelihoods that specific consumers would attend the event;

calculate likelihoods that specific consumers would attend an event at a specific venue featuring the attraction, wherein the calculation takes into account the interest metrics, the location information, the social influence metrics, the participation metrics, and a location of the specific venue;

calculate a demand prediction for the event by summing the likelihoods that specific consumers would attend the event;

identify one or more geographical regions where there is a concentration of interest in the attraction, based on one or more demand predictions; and

match the attraction with a proposed venue within each of the one or more geographical regions.

2. The system of claim 1, wherein the computer is configured to communicate information identifying the proposed venue within each of the one or more geographical regions to an agent for the attraction.

3. The system of claim 1, wherein the computer is configured to receive indications of interest by receiving a notification when the at least one of the consumers uses an electronic device to search for an attraction.

4. The system of claim 1, wherein the computer is configured to receive indications of interest by receiving a notification when the at least one of the consumers uses an electronic device to visit an attraction profile page.

5. The system of claim 1, wherein the computer is configured to receive indications of interest by receiving a notification when the at least one of the consumers uses an electronic device to connect with a person associated with an attraction on a social network.

6. The system of claim 1, wherein the computer is configured to receive indications of interest by receiving a notification when the at least one of the consumers uses an electronic device to operate a user interface element adapted to express consumer interest in an attraction.

7. A system for generating a demand prediction for an event, the system comprising:

a database that stores information about an attraction, venues that are capable of hosting the attraction, and consumers who may have interest in the attraction;

a computer that has access to the database and that is configured to;

receive indications of interest from at least some of the consumers, wherein each indication of interest is generated by an action performed by an interested consumer using an electronic device configured to send indications of interest to the computer, and wherein each indication of interest indicates that the interested consumer has interest in the attraction or interest in a category of attractions to which the attraction belongs;

receive location information that identifies a location corresponding to each interested consumer;

determine interest metrics representing a level of interest in the attraction for each interested consumer, wherein the interest metrics are based at least partially on the received indications of interest;

determine social influence metrics representing likelihoods that consumers will be influenced by actions of others;

determine participation metrics representing a rate of participation in past events for each interested consumer;

weight the interest metrics, the location information, the social influence metrics, the participation metrics according to their relative importance in calculating the likelihoods that specific consumers would attend the event;

calculate likelihoods that specific consumers would attend an event at a specific venue featuring the attraction, wherein the calculation takes into account the interest metrics, the location information, the social influence metrics, the participation metrics, and a location of the specific venue;

calculate a demand prediction for the event by summing the likelihoods that specific consumers would attend the event.

8. The system of claim 7, wherein the computer is configured to estimate the profitability of the event, based at least partially on the demand prediction for the event.

9. The system of claim 8, wherein the computer is configured to provide information about one or more events that are estimated to be most profitable to an agent for the attraction.

10. The system of claim 7, wherein the computer is configured to:

identify one or more geographical regions where the demand prediction is highest; and

match the attraction with a proposed venue within each of the one or more geographical regions.

11. The system of claim 10, wherein the proposed venue would result in an event with the highest estimated profitability compared to other venues within the geographical region of the proposed venue.

12. A computer-implemented method of calculating a demand prediction for an event, the method comprising:

receiving indications with a computer of interest from consumers, wherein each indication of interest is generated by an action performed by an interested consumer using an electronic device, and wherein each indication of interest shows that the interested consumer has interest in an attraction or interest in a category of attractions to which the attraction belongs;

receiving with the computer location information that identifies a location corresponding to each interested consumer;

determining with the computer interest metrics representing a level of interest in the attraction for each interested consumer, wherein the interest metrics are based at least partially on the received indications of interest;

determining with the computer social influence metrics representing likelihoods that consumers will be influenced by actions of others;

determining with the computer participation metrics representing a rate of participation in past events for each interested consumer;

weighting the interest metrics, the location information, the social influence metrics, the participation metrics according to their relative importance in calculating the likelihoods that specific consumers would attend the event;

calculating with the computer likelihoods that specific consumers would attend an event at a specific venue featuring the attraction, wherein the calculation takes into account the interest metrics, the location information, the social influence metrics, the participation metrics, and a location of the specific venue;

calculating with the computer a demand prediction for the event by summing the likelihoods that specific consumers would attend the event.

13. The method of claim 12, further comprising identifying one or more geographical regions where there is a concentration of interest in the attraction, based on one or more demand predictions.

14. The method of claim 13, further comprising matching the attraction with a proposed venue within each of the one or more geographical regions.

15. The method of claim 14, further comprising selecting the proposed venue such that the projected profitability of the event at the proposed venue is greater than or equal to the projected profitability of an event featuring the same attraction at another venue within the same geographical region as the proposed venue.

16. The method of claim 12, wherein the interest metrics are based at least in part on how recently the indications of interest occurred.

17. The method of claim 12, wherein the interest metrics are based at least in part on a number of times that a consumer operates a user interface element configured to register interest in the attraction.