ITEM DISCOVERY TOOLS AND METHODS FOR SHOPPING IN AN ELECTRONIC COMMERCE ENVIRONMENT

• US 20120284145A1
• Filed: 05/04/2011
• Published: 11/08/2012
• Est. Priority Date: 05/04/2011
• Status: Active Grant

• Current Assignee: Etsy Incorporated
• Original Assignee: Etsy Incorporated
• Inventors: Kalin, Robert, Fodor, Gregory Jr.
• Granted Patent: US 8,762,226 B2
• Time in Patent Office: Days
• US Class Current: 705/26.7
• CPC Class Codes: G06Q 30/0603 Catalogue ordering
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

A computer-implemented method includes prompting a first user to select one or more images representing merchandise items, receiving one or more image selections from the first user through the user interface, and determining a shopping preference of the first user based, at least in part, on the image selections. The shopping preference of the first user includes information about the merchandise items represented by the image selections. The method further includes identifying a second user having a shopping preference that is substantially similar to the shopping preference of the first user. The shopping preference of the second user includes information about one or more preferred merchandise items of the second user. The method further includes generating at least one shopping recommendation based on the shopping preference of the second user, and presenting the shopping recommendation to the first user.

Claims

1. A computer-implemented method, comprising:

prompting, through a user interface, a first user to select one or more images each representing one or more merchandise items, the one or more images being stored in an image database and to be displayed to the first user through the user interface;

receiving, by a computer system, one or more image selections from the first user through the user interface;

determining a shopping preference of the first user based, at least in part, on the one or more image selections, the shopping preference of the first user including information about the one or more merchandise items represented by the one or more image selections;

identifying a second user having a shopping preference that is substantially similar to the shopping preference of the first user, the shopping preference of the second user including information, stored in a user preference database, about one or more preferred merchandise items of the second user;

generating at least one shopping recommendation based on the shopping preference of the second user; and

presenting the at least one shopping recommendation to the first user through the user interface.

2. The computer-implemented method of claim 1, wherein identifying the second user includes assigning, by the computer system, a score to the second user according to an algorithm operative to use different types of activity stored in an activity database including a frequency at which the second user has identified, to the computer system, the one or more preferred merchandise items of the second user, wherein the computer-implemented method further comprises ranking the second user according to the score, and wherein generating the at least one shopping recommendation is further based on the ranking of the second user.

3. The computer-implemented method of claim 1, wherein identifying the second user includes assigning, by the computer system, a score to the second user according to an algorithm operative to use different types of activity stored in an activity database including, for each of the one or more preferred merchandise items of the second user, a quantity of the one or more preferred merchandise items of the second user that are preferred by a user other than the second user, wherein the computer-implemented method further comprises ranking the second user according to the score, and wherein generating the at least one shopping recommendation is further based on the ranking of the second user.

4. The computer-implemented method of claim 1, wherein identifying the second user includes assigning, by the computer system, a score to the second user according to an algorithm operative to use different types of activity stored in an activity database including a percentage of the one or more preferred merchandise items of the second user that have been purchased by a user other than the second user, wherein the computer-implemented method further comprises ranking the second user according to the score, and wherein generating the at least one shopping recommendation is further based on the ranking of the second user.

5. The computer-implemented method of claim 1, wherein identifying the second user includes assigning, by the computer system, a score to the second user according to an algorithm operative to use different types of activity stored in an activity database including a percentage of the one or more preferred merchandise items of the second user that have been purchased by the second user, wherein the computer-implemented method further comprises ranking the second user according to the score, and wherein generating the at least one shopping recommendation is further based on the ranking of the second user.

6. The computer-implemented method of claim 1, wherein the one or more preferred merchandise items of the second user includes at least one of a favorite item of the second user, an item purchased by the second user, an item sold by the second user, an item browsed by the second user, and an item curated by the second user in a treasury.

7. The computer-implemented method of claim 1, wherein the at least one shopping recommendation includes at least one of the one or more preferred merchandise items of the second user.

8. The computer-implemented method of claim 1, wherein the at least one shopping recommendation includes a username of the second user, the username being selectable by the first user within the user interface to cause the computer system to provide, to the first user through the user interface, information about the second user including a list of favorite items of the second user.

9. The computer-implemented method of claim 1, further comprising choosing, by the computer system, the one or more images from the image database based on the shopping preference of the second user.

10. The computer-implemented method of claim 1, wherein the one or more image selections includes a first image of a first merchandise item and a second image of a second merchandise item, and wherein the one or more preferred merchandise items of the second user includes the first merchandise item and the second merchandise item.

11. The computer-implemented method of claim 10, wherein the first image is included in a first group of images and the second image is included in a second group of images, and wherein prompting the first user includes prompting, through the user interface, the first user to select one or more images from the first group of images prior to prompting the first user to select one or more images from the second group of images.

12. The computer-implemented method of claim 1, wherein the information about the one or more merchandise items includes a description of a respective one of the one or more merchandise items, the description to be stored in an item listing database, the description including at least one of a name, color, style, shape, texture, material, construction, origin, age, function, and appearance.

13. The computer-implemented method of claim 1, wherein the information about the one or more preferred merchandise items of the second user includes an association between each of the one or more preferred merchandise items of the second user and a user profile of the second user.

14. The computer-implemented method of claim 1, further comprising storing shopping recommendation data including the at least one shopping recommendation in a shopping recommendation database, and enabling the first user to retrieve the shopping recommendation data through the user interface.

15. A computer-implemented method, comprising:

mapping each of a plurality of merchandise items listed in a database to at least one of a plurality of users of an e-commerce website based on a ranking of each of the at least one of the plurality of users;

generating a first webpage having a first plurality of user-selectable images each representing one of a first subset of the plurality of merchandise items;

providing the first webpage to a survey subject through a user interface of a user computing system connected to the e-commerce website over a communications network;

receiving, through the user interface, a first image selection from the survey subject, the first image selection representing one of the plurality of merchandise items selected by the survey subject;

generating a second webpage having a second plurality of user-selectable images each representing one of a second subset of the plurality of merchandise items;

providing the second webpage to the survey subject through the user interface of the user computing system;

receiving, through the user interface, a second image selection from the survey subject, the second image selection representing one of the plurality of merchandise items selected by the survey subject;

generating a third webpage having a list of recommended users including at least one of the plurality of users that is mapped to the merchandise item associated with the first image selection and the merchandise item associated with the second image selection; and

providing the third webpage to the survey subject through the user interface of the user computing system.

16. The computer-implemented method of claim 15, further comprising mapping each of the plurality of merchandise items to at least one of the plurality of users of the e-commerce website based on a preference of the at least one of the plurality of users for a respective one of the plurality of items.

17. The computer-implemented method of claim 15, wherein at least one of the first plurality of images and at least one of the second plurality of images each represent a merchandise item preferred by the at least one of the plurality of users.

18. The computer-implemented method of claim 17, wherein the merchandise item preferred by the at least one of the plurality of users is a favorite item of the at least one of the plurality of users.

19. The computer-implemented method of claim 17, wherein the merchandise item preferred by the at least one of the plurality of users is an item offered for sale by the at least one of the plurality of users.

20. The computer-implemented method of claim 17, wherein the merchandise item preferred by the at least one of the plurality of users is an item curated by the at least one of the plurality of users in a treasury.

21. The computer-implemented method of claim 15, further comprising ranking each of the at least one of the plurality of users based on how frequently the respective one of the plurality of users has selected any merchandise item as a favorite merchandise item over a period of time.

22. The computer-implemented method of claim 21, wherein the period of time is approximately 120 days.

23. The computer-implemented method of claim 21, wherein the frequency that the respective one of the plurality of users has selected any merchandise item as a favorite merchandise item is approximately five or more merchandise items per day.

24. The computer-implemented method of claim 15, further comprising ranking each of the at least one of the plurality of users based on how frequently one or more other users have selected a merchandise item as a favorite merchandise item that is the same merchandise item that the at least one of the plurality of users has selected as a favorite merchandise item.

25. The computer-implemented method of claim 24, wherein the frequency that the one or more other users have selected the merchandise item as a favorite merchandise item is approximately 500 times.

26. The computer-implemented method of claim 25, further comprising ranking each of the at least one of the plurality of users based on the frequency with which a favorite merchandise item of the at least one of the plurality of users has been purchased by any user other than the at least one of the plurality of users.

27. The computer-implemented method of claim 15, further comprising ranking each of the at least one of the plurality of users based on the frequency with which a favorite merchandise item of one of the at least one of the plurality of users has been purchased by the same one of the at least one of the plurality of users.

28. A computer readable medium having computer-executable instructions stored thereon, the computer-executable instructions when executed by a computer causing the computer to perform a method comprising:

prompting, through a user interface, a first user to select one or more images representing merchandise items, the images being stored in an image database;

receiving, by the computer, one or more responses from the first user through the user interface;

determining a shopping preference of the first user based, at least in part, on the one or more image selections, the shopping preference of the first user including information about the merchandise items represented by the one or more image selections;

identifying a second user having a shopping preference that is substantially similar to the shopping preference of the first user, the shopping preference of the second user including information, stored in a user preference database, about one or more preferred merchandise items of the second user;

generating at least one shopping recommendation based on the shopping preference of the second user; and

presenting the at least one shopping recommendation to the first user through the user interface.

29. A computer readable medium having computer-executable instructions stored thereon, the computer-executable instructions when executed by a computer causing the computer to perform a method comprising:

mapping each of a plurality of merchandise items listed in a database to at least one of a plurality of users of an e-commerce website based on a ranking of each of the at least one of the plurality of users;

generating a first webpage having a first plurality of user-selectable images each representing one of a first subset of the plurality of merchandise items;

providing the first webpage to a survey subject through a user interface of a user computing system connected to the e-commerce website over a communications network;

receiving, through the user interface, a first image selection from the survey subject, the first image selection representing one of the plurality of merchandise items selected by the survey subject;

generating a second webpage having a second plurality of user-selectable images each representing one of a second subset of the plurality of merchandise items;

providing the second webpage to the survey subject through the user interface of the user computing system;

receiving, through the user interface, a second image selection from the survey subject, the second image selection representing one of the plurality of merchandise items selected by the survey subject;

generating a third webpage having a list of recommended users including at least one of the plurality of users that is mapped to the merchandise item associated with the first image selection and the merchandise item associated with the second image selection; and

providing the third webpage to the survey subject through the user interface of the user computing system.

30. A system, comprising:

a memory;

at least one processor coupled to the memory, the processor being configured to prompt, through a user interface, a first user to select one or more images each representing one or more merchandise items, the one or more images being stored in the memory and to be displayed to the first user through the user interface, the processor being further configured to receive one or more image selections from the first user through the user interface, the processor to determine a shopping preference of the first user based, at least in part, on the one or more image selections, the shopping preference of the first user including information about the one or more merchandise items represented by the one or more image selections, the processor being further configured to identify a second user having a shopping preference that is substantially similar to the shopping preference of the first user, the shopping preference of the second user including information, stored in the memory, about one or more preferred merchandise items of the second user, the processor being further configured to generate at least one shopping recommendation based on the shopping preference of the second user, and the processor being further configured to present the at least one shopping recommendation to the first user through the user interface.