# US 2022/0284453 A1 · Method for creating a store on an online retail platform > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2022/0284453 A1 - Document ID: US20220284453A1 - Status: Published application - Kind: A1 - Application number: 17/625,086 - Filed: 2020-11-29 - Published: 2022-09-08 - Earliest claimed: 2020-11-13 - Assignees: Juda Universe Sdn. Bhd - Applicants: Juda Universe Sdn. Bhd - Inventors: Fu Seng LOO; Fook Wah CHEN - Web page: https://patentgrep.com/patent/US20220284453A1 ## CPC - G06Q 30/0201: Market modelling; Market analysis; Collecting market data - G06Q 30/0643: {graphically representing goods, e.g. 3D product representation} - G06Q 30/0241: Advertisements - G06N 20/00: Machine learning - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract A method for creating a virtual store on an online retail platform that automatically identifies the type of file being uploaded by the merchant from any of media files such as images and video, 3D-scan files, and computer-aided-design (CAD) files. The method then registers certain parameters of the uploaded store, and finds a set of stores located in a multitude of stored files, that are close enough in those parameters to the uploaded store. The method then generates a dataset of information from the set of stores that may be relevant to the uploaded store, and displays this to the merchant. This allows the merchant to select information from this dataset that they wish to apply to the uploaded store, thus saving time and effort when creating a virtual store. ## Claims ### Claim 1 A computer-based method for a user (20) to create a virtual store on an online retail platform, comprising the steps of: a. the user uploading (106) at least one file to a web server (22); b. the web server (22) detecting (108) type of said uploaded file from any of the following types: text information file, media such as images and video, 3D-scan, and computer-aided-design (CAD) file; c. the web server comparing the uploaded file against a multitude of stored files in order to determine a set of said stored files that meet a predetermined level of similarity with said uploaded file; d. the web server (22) analyzing at least one parameter in said set; e. the web server (22) preparing, based on said analysis, a dataset of information that is potentially relevant to said uploaded file; f. the web server (22) displaying said dataset to said user; and g. the user selecting only information from said dataset that they wish to apply to the uploaded store. ### Claim 2 (depends on 1) A computer-based method for a user (20) to create a virtual store on an online retail platform according to claim 1, wherein said at least one parameter include: in-store visitor traffic, duration visitors pause at various products, duration visitors pause at various store locations and shelves, shelf location of most popular products, and most popular location for any product. ### Claim 3 (depends on 2) A computer-based method for a user (20) to create a virtual store on an online retail platform according to claim 2, wherein said parameters are ascertained using a combination of historical heat maps retrieved from in-store infrared cameras located in, and sales information from, physical stores. ### Claim 4 (depends on 2) A computer-based method for a user (20) to create a virtual store on an online retail platform according to claim 2, wherein said parameters are ascertained using a combination of historical “stay-time” maps and sales information of virtual stores. ### Claim 5 (depends on 2) A computer-based method for a user (20) to create a virtual store on an online retail platform according to claim 2, wherein said dataset of information include: a preferred shelf location for a particular product. ### Claim 6 (depends on 2) A computer-based method for a user (20) to create a virtual store on an online retail platform according to claim 2, wherein said dataset of information include: a preferred shelf location for any product ### Claim 7 (depends on 2) A computer-based method for a user (20) to create a virtual store on an online retail platform according to claim 2, wherein the dataset further comprises preferred locations for advertisements. ### Claim 8 (depends on 1) A computer-based method for a user (20) to create a virtual store on an online retail platform according to claim 1, wherein said at least one parameter includes: store layout including visitor walkways and product shelves. ### Claim 9 (depends on 8) A computer-based method for a user (20) to create a virtual store on an online retail platform according to claim 8, wherein said dataset information for said parameter is the preferred location of navigation hotspots within said store, said navigation hotspots comprising user selectable links that take said user to another store, a substore located within said store, or another location within said store. ### Claim 10 (depends on 1) A computer-based method for a user (20) to create a virtual store on an online retail platform according to claim 1 wherein the said predetermined level of similarity comprises a likeness of certain attributes of said store in the uploaded file to like attributes in stores contained in said multitude of stored files, said attributes comprising: store layout including visitor walkways, and locations, positions and sizes of shelves.