FIT RECOMMENDATION VIA COLLABORATIVE INFERENCE

• US 20120030061A1
• Filed: 07/28/2011
• Published: 02/02/2012
• Est. Priority Date: 07/28/2010
• Status: Active Grant

• Current Assignee: True Fit Corp.
• Original Assignee: True Fit Corp.
• Inventors: Lu, Zhidong, Stauffer, John
• Granted Patent: US 8,478,663 B2
• Time in Patent Office: Days
• US Class Current: 705/26.7
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

Some embodiments of the invention provide techniques for recommending a size of a subject item to fit a subject consumer. In some embodiments, clusters of consumers with fit characteristics similar to the subject consumer are identified, using one or more data clustering algorithms, based on any of numerous consumer attributes (e.g., self-reported and/or inferred height, weight, body shape, body characteristics, and/or purchase histories (e.g., consumers with high overlap in terms of sets of products purchased)). Information on other consumers in the cluster may be analyzed to draw conclusions on how different sizes of the subject item may fit the subject consumer. For example, the purchase history of other members of the cluster may be analyzed to determine whether other members purchased a particular size of the item, and if so, the size purchased by the other members may serve as a basis to recommend a size that may best fit the consumer. For example, if other members of the cluster purchased a particular size, then that size may be recommended to the subject consumer, or if other members of the cluster purchased and then returned a particular size (e.g., for being too small), then another (e.g., larger) size may be recommended to the subject consumer.

Claims

1. A method of recommending, to a subject consumer, a size of a subject item for which a plurality of sizes is available, the method comprising:

(A) receiving a request for a recommendation of a size of the subject item to fit the subject consumer;

(B) analyzing information relating to a plurality of consumers to determine one of the plurality of sizes of the subject item likely to fit the subject consumer; and

(C) recommending the size determined in (B) as being likely to fit the subject consumer.

2. The method of claim 1, wherein (B) comprises identifying a cluster of consumers, comprising the plurality of consumers, to which the subject consumer belongs, and analyzing information relating to the plurality of consumers to determine one of the plurality of sizes of the subject item likely to fit the subject consumer.

3. The method of claim 2, wherein the identifying comprises identifying a cluster that is defined by commonality with respect to one or more attributes comprising self-reported and/or inferred body measurements, body shape attributes, and/or sales history.

4. The method of claim 2, wherein the identifying comprises identifying a plurality of clusters of consumers to which the subject consumer belongs, each of the plurality of clusters being defined by commonality with respect to a different attribute.

5. The method of claim 2, wherein the analyzing comprises determining whether a size of the subject item has been successfully purchased by at least one other consumer in the cluster.

6. The method of claim 5, wherein the determining comprises determining whether a size of the subject item was designated as a favorite by at least one other consumer in the cluster.

7. The method of claim 1, wherein (C) comprises providing an indication of confidence that the subject item will fit the subject consumer.

8. The method of claim 7, wherein (C) comprises providing an indication of confidence that the subject item will fit the subject consumer along each of a plurality of dimensions.

9. The method of claim 1, wherein (B) comprises identifying a cluster of items to which the subject item belongs, the cluster of items including a plurality of items, and analyzing information relating to purchases and/or returns by the plurality of consumers of a size of at least one other item in the cluster of items to determine a size of the subject item likely to fit the subject consumer.

10. The method of claim 9, wherein the analyzing comprises employing a known relationship between sizes of the subject item and sizes of the at least one other item in the cluster to determine a size of the subject item likely to fit the subject consumer.

11. The method of claim 1, wherein the subject item is an item of apparel or a pair of shoes.

12. At least one computer readable storage medium having encoded thereon instructions which, when executed, perform a method of recommending, to a subject consumer, a size of a subject item for which a plurality of sizes is available, the method comprising:

(A) receiving a request for a recommendation of a size of the subject item to fit the subject consumer;

(B) analyzing information relating to a plurality of consumers to determine one of the plurality of sizes of the subject item likely to fit the subject consumer; and

(C) recommending the size determined in (C) as being likely to fit the subject consumer.

13. The at least one computer readable storage medium of claim 12, wherein (B) comprises identifying a cluster of consumers, comprising a plurality of consumers, to which the subject consumer belongs, and analyzing information relating to the plurality of consumers to determine one of the plurality of sizes of the subject item likely to fit the subject consumer.

14. The at least one computer readable storage medium of claim 13, wherein the identifying comprises identifying a cluster that is defined by commonality with respect to one or more attributes comprising self-reported and/or inferred body measurements, body shape attributes, and/or sales history.

15. The at least one computer readable storage medium of claim 13, wherein the identifying comprises identifying a plurality of clusters of consumers to which the subject consumer belongs, each of the plurality of clusters being defined by commonality with respect to a different attribute.

16. The at least one computer readable storage medium of claim 13, wherein the analyzing comprises determining whether a size of the subject item has been successfully purchased by at least one other consumer in the cluster.

17. The at least one computer readable storage medium of claim 16, wherein the analyzing comprises determining whether a size of the subject item was designated as a favorite by at least one other consumer in the cluster.

18. The at least one computer readable storage medium of claim 12, wherein (C) comprises providing an indication of confidence that the subject item will fit the subject consumer.

19. The at least one computer readable storage medium of claim 12, wherein (B) comprises identifying a cluster of items to which the subject item belongs, the cluster of items including a plurality of items other than the subject item, and analyzing information relating to purchases and/or returns by the plurality of consumers of a size of at least one other item in the cluster of items to determine a size of the subject item likely to fit the subject consumer.

20. The at least one computer readable storage medium of claim 19, wherein the analyzing comprises employing a known relationship between sizes of the subject item and sizes of the at least one other item in the cluster to determine a size of the subject item likely to fit the subject consumer.

21. A system, comprising:

a facility operable to receive a request for a recommendation of a size of a subject item to fit a subject consumer, a plurality of sizes of the subject item being available;

at least one storage facility storing information on past purchases, by a plurality of consumers, of a plurality of items;

at least one controller operable to analyze information on purchases by one or more of the plurality of consumers to identify a size of the subject item likely to fit the subject consumer; and

a facility operable to recommend the identified size of the subject item.

22. The system of claim 21, wherein the at least one controller is operable to identify a cluster of consumers, comprising the one or more consumers, to which the subject consumer belongs, and to analyze information on purchases by the one or more consumers to identify a size of the subject item likely to fit the subject consumer.