Item discovery tools and methods for shopping in an electronic commerce environment

• US 8,762,226 B2
• Filed: 05/04/2011
• Issued: 06/24/2014
• Est. Priority Date: 05/04/2011
• Status: Active Grant

• Current Assignee: Etsy Incorporated
• Original Assignee: Etsy Incorporated
• Inventors: Kalin, Robert, Fodor, Gregory Jr.
• Primary Examiner(s): Le, Michelle L
• Application Number:
  US13/100,810
• Publication Number:
  US 20120284145A1
• Time in Patent Office: 1,147 Days
• Field of Search: 705/14, 705/26, 705/7, 706/21
• 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 performed on an e-commerce computer system, the method comprising:

identifying a plurality of tastemakers from a plurality of users of an e-commerce website, the plurality of tastemakers selected responsive to acts of;

assigning, by the e-commerce computer system, a score to each of the plurality of users of the e-commerce website based upon an activity of the each of the plurality of users on the e-commerce website; and

identifying as tastemakers a first group of the plurality of users who are assigned a higher score than a second group of the plurality of users;

forming an association between a first user and a tastemaker by presenting an image survey to the first user, the image survey including;

prompting, through a user interface of a user computing system, the first user to select a first image from a first group of images, each of the images in the first group of images representing one or more merchandise items, each of the images in the first group of images being stored in an image database of the e-commerce computer system and displayed to the first user through the user interface, each of the images in the first group of images representing an item identified as preferred by at least one tastemaker by a preferred item identification engine operating on the e-commerce computer system,

prompting, through the user interface, the first user to select a second image from a second group of images, each of the images in the second group of images representing one or more merchandise items identified as preferred by a tastemaker who was also identified to prefer the merchandise item represented by the first image, each of the images in the second group of images being stored in the image database and displayed to the first user through the user interface, and

receiving, through a computer network, by the e-commerce computer system, an image selection of the first image and an image selection of the second image from the first user through the user interface;

determining, by the e-commerce computer system, a shopping preference of the first user based, at least in part, on the association formed between the first user and the tastemaker, the shopping preference of the first user including information about the one or more merchandise items represented by the first image and the one or more merchandise items represented by the second image;

identifying, by the e-commerce computer system, 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 of the e-commerce computer system, about one or more preferred merchandise items of the second user;

generating, by the e-commerce computer system, at least one shopping recommendation based on the shopping preference of the second user utilizing a recommendation engine of the e-commerce computer system; 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, one of the first group of images and the second group of images from the image database based on the shopping preference of the second user.

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

11. 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.

12. 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.

13. 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.

30. The computer-implemented method of claim 1, wherein the second user is the tastemaker.

14. An e-commerce computer system including a non-transient computer readable medium having computer-executable instructions stored thereon, the computer-executable instructions when executed by the e-commerce computer system causing the e-commerce computer system to perform a method comprising:

identifying a plurality of tastemakers from a plurality of users of an e-commerce website, the plurality of tastemakers selected responsive to acts of;

assigning a score to each of the plurality of users of the e-commerce website based upon an activity of the each of the plurality of users on the e-commerce website; and

identifying as tastemakers a first group of the plurality of users who are assigned a higher score than a second group of the plurality of users;

mapping each of a plurality of merchandise items listed in a database to at least one of the plurality of tastemakers;

forming an association between a survey subject and a tastemaker by presenting an image survey to the survey subject, the image survey including;

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 the 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, and

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 tastemakers 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.

15. The e-commerce computer system of claim 14, wherein the method further comprises mapping each of the plurality of merchandise items to at least one of the plurality of tastemakers based on a preference of the at least one of the plurality of tastemakers for a respective one of the plurality of items.

16. The e-commerce computer system of claim 14, 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 tastemakers.

17. The e-commerce computer system of claim 16, wherein the merchandise item preferred by the at least one of the plurality of tastemakers is a favorite item of the at least one of the plurality of tastemakers.

18. The computer-implemented method of claim 16, wherein the merchandise item preferred by the at least one of the plurality of tastemakers is an item offered for sale by the at least one of the plurality of tastemakers.

19. The e-commerce computer system of claim 16, wherein the merchandise item preferred by the at least one of the plurality of tastemakers is an item curated by the at least one of the plurality of tastemakers in a treasury.

20. The e-commerce computer system of claim 14, wherein the method further comprising comprises assigning the score to each 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.

21. The e-commerce computer system of claim 20, wherein the period of time is approximately 120 days.

22. The e-commerce computer system of claim 20, 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.

23. The e-commerce computer system of claim 14, wherein the method further comprises assigning the score to each 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.

24. The e-commerce computer system of claim 23, wherein the frequency that the one or more other users have selected the merchandise item as a favorite merchandise item is approximately 500 times.

25. The e-commerce computer system of claim 24, wherein the method further comprises assigning the score to each of the plurality of users based on the frequency with which a favorite merchandise item of each of the plurality of users has been purchased by any user other than the respective one of the plurality of users.

26. The e-commerce computer system of claim 14, wherein the method further comprises assigning the score to each of the plurality of users based on the frequency with which a favorite merchandise item of one of the plurality of users has been purchased by the same one of the plurality of users.

27. A non-transient 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:

identifying a plurality of tastemakers from a plurality of users of an e-commerce website, the plurality of tastemakers selected responsive to acts of;

assigning a score to each of the plurality of users of the e-commerce website based upon an activity of the each of the plurality of users on the e-commerce website; and

identifying as tastemakers a first group of the plurality of users who are assigned a higher score than a second group of the plurality of users;

forming an association between a first user and a tastemaker by presenting an image survey to the first user, the image survey including;

prompting, through a user interface, the first user to select one or more images representing merchandise items, the one or more images being stored in an image database, the one or more images each representing an item identified as preferred by at least one tastemaker by a preferred item identification engine operating on the e-commerce system, and

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 association formed between the first user and the tastemaker, 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.

28. A non-transient 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:

identifying a plurality of tastemakers from a plurality of users of an e-commerce website, the plurality of tastemakers selected responsive to acts of;

assigning a score to the plurality of users of the e-commerce website based upon an activity of the plurality of users on the e-commerce website; and

identifying as tastemakers a first group of the plurality of users who are assigned a higher score than a second group of the plurality of users;

mapping each of a plurality of merchandise items listed in a database to at least one of the plurality of tastemakers;

forming an association between a survey subject and a tastemaker by presenting an image survey to the survey subject, the image survey including;

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 the 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, and

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 tastemakers 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.

29. A system, comprising:

a memory;

at least one processor coupled to the memory, the processor being configured to identify a plurality of tastemakers from a plurality of users of an e-commerce website, the plurality of tastemakers selected responsive to acts of assigning a score to each of the plurality of users of the e-commerce website based upon an activity of the each of the plurality of users on the e-commerce website and identifying as tastemakers a first group of the plurality of users who are assigned a higher score than a second group of the plurality of users, the processor being further configured to form an association between a first user and a tastemaker by presenting an image survey to the first user, the image survey including 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 each representing an item identified as preferred by at least one tastemaker by a preferred item identification engine operating on the e-commerce system, the one or more images being stored in the memory and to be displayed to the first user through the user interface, and receiving one or more image selections from the first user through the user interface, the processor being further configured to determine a shopping preference of the first user based, at least in part, on the association formed between the first user and the tastemaker, 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.