ADAPTABLE SYSTEMS AND METHODS FOR MATCHING AVAILABLE CLOTHING TO APPROPRIATE CUSTOMERS BASED ON PROFILE DATA

Abstract

Systems and methods are described for serving clients by having the client measure some favorite clothing items to develop a clothing fit profile that is a better way for a consumer to seek out clothing purchases both online and offline. Using measurements from articles of clothing also removes the anxiety many people feel about measuring their own bodies when clothing shopping. Ultimately, this type of data allows for completely personalized shopping to be available to users, whether they prefer to shop on or offline.

Claims

1. A method for providing a user with a selection of available articles which most closely match a set of criteria provided by the user, comprising: providing to a user an input interface identifying a set of criteria to be used to develop the selection of available articles; collecting data responsive to the set of criteria and input by the user in the input interface and establishing a user profile therefrom; comparing the user profile to data in a database regarding available articles; selecting particular ones of the available articles which most closely match the data in user profile; and preparing and transmitting to the user a communication concerning the selection of available articles.

2. The method as recited in claim 1 wherein the articles comprise articles of clothing.

3. The method as recited in claim 2, wherein the set of criteria comprises a set of specified measurements and sizing information.

4. The method as recited in claim 1, wherein the set of criteria comprises one or more of reduced prices for articles of a specific brand, from a specific store or chain of stores, or from a combination of previously matched items.

5. The method as recited in claim 1, wherein the set of criteria comprises one or more specific article brands.

6. The method as recited in claim 1, wherein the set of criteria comprises a plurality of article brands sourced from a particular store or chain of stores.

7. The method as recited in claim 1, wherein the input interface is displayed on a screen of a personal computer or communications device.

8. The method as recited in claim 1, wherein the communication is transmitted to the user by push notifications through a mobile phone application, text, email, or via an alert message on a website account.

9. The method as recited in claim 3, wherein the set of specified measurements and sizing information includes one or more of favorite clothing item measurements or sizes and body measurements.

10. The method as recited in claim 9, wherein clothing item and body measurements comprise a distance between a user's armpit across their upper arm.

11. The method as recited in claim 9, wherein clothing item and body measurements comprise a distance from armpit-to-armpit on a user.

12. The method as recited in claim 9, wherein clothing item and body measurements comprise a bottom hem width for a user.

13. The method as recited in claim 9, wherein clothing item and body measurements comprise a sleeve inseam measurement for a user.

14. The method as recited in claim 9, wherein clothing item and body measurements comprise a shoulder to bottom hem front measurement for a user.

15. The method as recited in claim 9, wherein clothing item and body measurements comprise a shoulder to bottom hem back measurement for a user.

16. The method as recited in claim 9, wherein clothing item and body measurements comprise the widest section of a breast measurement for a user.

17. The method as recited in claim 9, wherein clothing item and body measurements comprise a specific band height measurement for a user.

18. The method as recited in claim 9, wherein clothing item and body measurements comprise a specific measurement across a widest part of a leg opening for a user.

19. The method as recited in claim 1, and further comprising crowdsourcing data from a plurality of users to populate the database.

20. The method as recited in claim 1, and further comprising collecting data from market sources of the articles to populate the database.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0016] FIG. 1 is a summary of database profiles used in the inventive systems and methods for comparison and for generating results and clothing recommendations to a user; and

[0017] FIG. 2 illustrates an example of methodology utilized to generate suitable additional clothing measurements for the database used in the inventive systems and methods.

DETAILED DESCRIPTION OF THE INVENTION

[0018] The invention reinvents the approach a consumer takes when looking for clothing purchases, in an innovative way. Currently, as noted above, a consumer is forced to “hunt” through a very time-consuming trial-and-error process for articles of clothing that fits in a way the consumer likes, and to identify clothing brands that most consistently fit their body proportions. The massive inconsistency in current sizing presentation to consumers is archaic and impractical. Turning clothes shopping into a data-matching process, as in the present invention, provides consumers with a powerful and pleasurable shopping experience, with more options, more styles to choose from, and personalized recommendations based on how they like things to fit—not a predetermined size. Additionally, although the present focus of the invention is the curation of a personalized sale catalog based on a consumer's profile information with respect to fit, such catalogs may also be curated for reduced rate purchases from a specific brand, store, or a combination of previously matched items, based on brand-specific preferences of the consumer, or store-specific preferences of the consumer with multiple brands, for both new and resale clothing.

[0019] FIG. 1 illustrates an example according to the principles of the present invention, of a consumer profile created with favorite clothing measurements, optional body measurements, and other preferences, which allow a database 5 to identify best options for the consumer and take away the most frustrating part of searching for clothing options. As indicated in the first box 10, the consumer may also optionally list items for resale. This data is stored in the illustrated database 5, as shown. The second box 15 permits clothing manufacturers, retailers, and resellers or rental companies to populate the database 5, in the event they wish to make their inventory available for matching in order to promote sales of their clothing products. Their participation requires data, in the form of additional measurements, beyond the standard sizing currently provided to consumers. As noted above, any data entered by such entities is also transferred to the illustrated database 5.

[0020] The third box 20 illustrates the entry into the database 5 of crowd-sourced data, which comprises exact measurements of clothing available for purchase online or in-store, those measurements being the same as are input in the first two boxes 10, 15, as well as the data provided from consumer at-home measurements, after it has been rendered anonymous by being scrubbed of any identification to particular consumers. This crowd-sourced data can be utilized for analysis, and industry reporting is inevitably created. This valuable data, aggregated for the first time ever, provides true insight into consumer preferences for clothing size and fit. Incentives may be employed to encourage users to supply this data, or to permit their submitted data to be used in this way in accordance with applicable data privacy laws, including waived or reduced application fees, reduced subscription, membership, or service fees, special pricing, and the like. Many industry brands and segments will use this data to improve their product offerings. This data, also, is transferred to the database 5, as illustrated.

[0021] FIG. 2 illustrates exemplary, but not necessarily exhaustive, clothing measurements for use in the present invention. The top portion shows current standard measurements provided to the consumer for a jacket under present practice, which includes length, bust, and standardized sizing (e.g. sizes 00-6XL), and designations such as petite or regular. As noted above, these types of sizing guidelines vary widely by manufacturer, and often fail to account for particular unique body proportions in the population.

[0022] The lower portion of FIG. 2 illustrates, as noted above, additional measurements to be used under the present invention. For the example of a jacket, such measurements may include the armpit across the upper arm, armpit-to-armpit, cuff, and shoulder to hem. Of course, other measurements may be utilized as well, within the scope of the invention, and these measurements are in addition to, rather than a replacement for, the standardized sizing and measurements shown in the upper portion of FIG. 2. Additional measurements will be added as necessary as style trends and clothing design require.

[0023] Referring again to FIG. 1, the lower two text boxes 25 and 30 describe the function of the database and associated analysis, in terms of providing useful matching clothing recommendations for particular clients. In particular, the database is analyzed, using appropriate algorithms, in order to make recommendations for clothing available for purchase to consumer profiles with matching data. Crowd-sourced data provides new metrics for the fashion industry concerning what consumers truly want and what they wear. The consumer profile is run against manufacturer, retailer, reseller, and crowd-sourced data to identify the best matches and consumers are alerted, when matches are determined, with appropriate purchasing recommendations. These alerts may be provided via push notifications, through a mobile phone application, text, email, or otherwise in accordance with consumer preference. Some consumers may simply opt for web access to their account, so that they may view their recommendations at their leisure, when they are in the market for clothes. The system may also permit listings created by consumers for sale to other consumers, using the matching algorithms, which may also be subject to the notification process, should a user opt in for such a service.

[0024] Thus, what is described herein is a personalized, curated, custom shopping catalog, based on fit profile and preference data in each customer's account. A user is able to search by clothing category, at will, to populate a personalized shopping experience in which all items curated are already vetted as fit options for the user. Other possibilities within the scope of the invention is to curate such a catalog for other purposes, such as for reduced rate purchases from a specific brand, store, or combination of previously matched items (sale pricing curation), a brand-specific catalog, or a personalized catalog that is store specific with multiple brands.

[0025] While the invention has been discussed herein as being applicable to clothing, this system may be modified and used for other purposes as well, such as skincare and cosmetics, for example. The applicability of this matching service extends to any product wherein individualized, detailed and personalized data concerning consumer preference and body type will enable a much improved and applicable search through associated product databases for suitable and preferred products.

[0026] Therefore, although exemplary embodiments of the invention have been shown and described, it is to be understood that all the terms used herein are descriptive rather than limiting, and that many changes, modifications, and substitutions may be made by one having ordinary skill in the art without departing from the spirit and scope of the invention, which is to be limited only in accordance with the following claims.