IP Library Granted Patent US 8,584,940
Granted Patent B2
US 8,584,940 · App. 13/345,681 · Granted Nov 19, 2013

Location based discounts

Inventor: Gregory J. Mesaros (Tampa, FL)
Assignee: eWinWin, Inc.
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Quick Facts
Patent No.
US 8,584,940
App. No.
13/345,681
Granted
Nov 19, 2013
Kind
B2
Abstract

The claimed subject matter relates to an architecture for interacting with a multiple criteria buying and/or selling system to conduct business electronically. In particular, the architecture can include a dynamic discount card that includes an information access component for receiving information. In addition, the dynamic discount card can include a presentation component for displaying information to a user via the dynamic discount card.

Claims (44)

1. A method for transmitting an offer to a user, the method comprising:

accessing information associated with a credit or debit card of a user by way of a mobile device, wherein the credit or debit card is registered with a third party;

prompting the user to accept terms and conditions, wherein the terms and conditions permit the third party to access tracked activities of the user, including a real-time location of the mobile device;

setting the credit or debit card as a default payment method;

receiving a plurality of offers by a plurality of sellers, the plurality of offers including pricing information associated with a product or service; and

executing instructions stored in memory, wherein execution of the instructions by a processor:

matches at least one offer of the plurality of offers to the user based on the real-time location information of the mobile device and a category associated with a product or service selected by the user,

permits the user to input new search criteria by way of the mobile device,

analyzes the new search criteria to make at least one inference regarding what information to display to the user,

displays information to the user based on the at least one inference related to the new search criteria, and

presents at least one new offer of the plurality of offers to the user based at least in part on the at least one inference, wherein the user receives the at least one new offer after the user accepts the terms and conditions associated with the at least one new offer and uses the credit or debit card for payment.

2. The method of claim 1 , wherein matching the at least one offer of the plurality of offers to the user is further based on the tracked activities, wherein the tracked activities include user preferences, merchant feedback information, purchasing information, and real-time location information.

3. The method of claim 1 , wherein matching the at least one offer of the plurality of offers to the user is further based on the product or service having been previously tagged by the user and includes an option for the user to share the offer with another user.

4. The method of claim 1 , wherein the execution of instructions by the processor further tracks the at least one new offer to the credit or debit card.

5. The method of claim 1 , wherein the at least one offer of the plurality of offers comprises a further discount that is based at least in part on a previous purchase amount of the user.

6. The method of claim 1 , wherein the real-time location information is provided by a global positioning system.

7. The method of claim 1 , wherein the execution of instructions by the processor further comprises the presenting of an advertisement related to the search criteria and real-time location information.

8. The method of claim 7 , wherein the presenting of the advertisement is tracked according to the particular item offered, information related to how the advertisement was delivered to a particular user, information within the user profile, the location information associated with the user, the time sent to the user, and the actual offer presented to the user.

9. The method of claim 8 , wherein the tracked information includes whether the user purchased the item.

10. The method of claim 1 , wherein the at least one inference is based upon a Bayesian network technique.

11. The method of claim 10 , wherein the Bayesian network technique is a type of statistical model that represents a set of random variables and the conditional dependencies of the random variables.

12. The method of claim 1 , wherein the at least one inference is based upon analyzing data to recognize a pattern.

13. The method of claim 12 , wherein the recognition of a pattern causes a particular offer to be presented to the user.

14. The method of claim 1 , further comprising recording that an offer was viewed by the user but was not purchased.

15. The method of claim 1 , wherein the at least one inference is based on a support vector network model that provides a classification of the user.

16. The method of claim 1 , wherein the new search criteria includes at least one time availability preference of the user.

17. The method of claim 1 , wherein the search criteria includes a minimum rating associated with at least one seller.

18. The method of claim 1 , wherein the matching of at least one offer includes offers presented by way of a shopping bot.

19. The method of claim 1 , wherein receiving the offer includes a purchase.

20. The method of claim 1 , wherein new search criteria includes a quality preference.

21. The method of claim 1 , wherein a registration includes a shipping preference and address associated with the user.

22. A non-transitory computer-readable storage medium having embodied thereon instructions executable by a processor, the instructions corresponding to a method for transmitting an offer to a user, the method comprising:

accessing information associated with a credit or debit card of a user by way of a mobile device, wherein the credit or debit card is registered with a third party;

prompting the user to accept terms and conditions, wherein the terms and conditions permit the third party to access tracked activities of the user, including a real-time location of the mobile device;

setting the credit or debit card as a default payment method;

receiving a plurality of offers by a plurality of sellers, the plurality of offers including pricing information associated with a product or service; and

matching at least one offer of the plurality of offers to the user based on the real-time location information of the mobile device and a category associated with a product or service selected by the user,

permitting the user to input new search criteria by way of the mobile device,

analyzing the new search criteria to make at least one inference regarding what information to display to the user,

displaying information to the user based on the at least one inference related to the new search criteria, and

presenting at least one new offer of the plurality of offers to the user based at least in part on the at least one inference, wherein the user receives the at least one new offer after the user accepts the terms and conditions associated with the at least one new offer and uses the credit or debit card for payment.

23. The non-transitory computer-readable storage medium of claim 22 , wherein the at least one offer of the plurality of offers comprises a further discount.

24. The non-transitory computer-readable storage medium of claim 22 , wherein receiving the offer includes a purchase.

25. The non-transitory computer-readable storage medium of claim 22 , wherein new search criteria includes a quality preference.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 10, 2017
From: MESAROS, GREG
To: VALENTINE COMMUNICATIONS LLC
Reel/Frame 042325/0392 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 5, 2017
From: EWINWIN
To: MESAROS, GREG
Reel/Frame 042252/0025 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 6, 2012
From: MESAROS, GREGORY J.
To: EWINWIN, INC.
Reel/Frame 027812/0936 →
Continuity (6)
Continuation 13251668 · Oct 3, 2011
Continuation 12881923 · Sep 14, 2010
Continuation 12042051 · Mar 4, 2008
Continuation 10867625 · Jun 15, 2004
Provisional Application 60478768 · Jun 16, 2003
Related Publication 20120158475A1 · Jun 21, 2012