Description:FIELD OF INVENTION
[001] The present invention relates to digital platform for ecommerce website. Particularly, a system and method for retrieving and/or managing product(s) digital shelf visibility score.

BACKGROUND OF THE INVENTION

[002] Every major retailer has its own search engine with its own unique algorithms and data points to determine the best results for every search query. Ranking well for one description of your product category doesn’t mean that the product(s) rank would be perfect for another as well. The retailer needs to monitor their product pages to ensure they stay the same (or change in the same ways), or else the people will have disparate perceptions of the existing brand and pages won’t perform as well as they could.

[003] If the retailers wants to prioritize their position on digital shelf they need to actively monitor how much of a retailer’s search traffic is going toward their product pages. In the existing technology google trends is one of the most powerful marketing insight and SEO tracking tools to measure market demand. It is designed to build visual, dynamic insights that detail the lifecycle of a keyword past, present, and potential future. However, there is gap between the brand’s requirements to understand the market share against their competitors and the offerings available in the market.

[004] In the existing technology the brand owners in order to understand their position in the market had to manually perform the search with respect to their products and then outline where their product stands in the market. These searches were a lengthy procedure for the brand owners and were not even accurate. Further these searches were conducted manually by various members associated for this task. So, there was a lot of manual intervention in processing the position of the brand with respect to their competitors.

[005] In view of the problems associated with the above state of art, there is a need for a system and method to make use of publicly available open source data extracted using generic search terms on higher intent to purchase platforms and enable insights by categorizing the brand products to make use of vertical level weights which draw out the most optimal weights applicable for a brand in specific marketplace categories.

OBJECTIVES OF THE INVENTION
[006] The primary objective of the present invention is to provide a system and method for retrieving product information via brand level digital shelf visibility score.

[007] Another objective of the present invention is to provide a solution to the brand owners to fill the gap between brands requirements to understand the market share against their competitors and the offerings available in the market by amalgamating proven tech driven methods along with subject matter expertise to generate quick insights.

[008] Yet another objective is to reduce turnaround time and effectively optimize the process with up-to-date market surveys and employ data backed calculations to arrive at holistic scoring method to identify brands market position relative to competitors.

[009] Another objective is to provide a method that determines the brand level digital shelf visibility score in the market on and across marketplaces by using publicly available data using category specific generic search terms to extract import aspects of each product backed by data driven methodology.

[0010] Yet another objective is to provide a method to make use of publicly available open source data extracted using generic search terms on higher intent to purchase platforms and enable insights by categorizing the brand products to make use of vertical level weights which draw out the most optimal weights applicable for a brand in specific marketplace categories.

[0011] Other objects and advantages of the present invention will become apparent from the following description taken in connection with the accompanying drawings, wherein, by way of illustration and example, the aspects of the present invention are disclosed.

SUMMARY OF THE INVENTION

[0012] The present invention relates to one implementation, a system and method for retrieving product information. The system may comprise at least one processor, an input/output (I/O) interface, and a memory. In one aspect the processor identify product from the metadata using machine learning technique and artificial intelligence technique. Further, the system may comprise a memory for including programs or coded instructions that supplement applications and functions of the system. In one aspect, the memory provides storing, processing, receiving, and generating segregated data by one or more of the programs or the coded instructions. Further the memory includes website directory module, searching module, search storage module, analytical module for analyzing the data. In one aspect, the one or more parameters may comprise Search Term; Marketplace; Product ID; Date; Brand Taxonomy; Label; and Product Position. The searching module retrieves the data related to any particular product as per the input entered by the user. In another aspect the search storage module stores the extraction of the product based on the user input. The analytical module retrieves the products via data-driven approach. Finally, the system may display the identified product digital shelf score via an input/output interface.

BRIEF DESCRIPTION OF DRAWINGS

[0013] The present invention will be better understood after reading the following detailed description of the presently preferred aspects thereof with reference to the appended drawings, in which the features, other aspects and advantages of certain exemplary embodiments of the invention will be more apparent from the accompanying drawing in which:

[0014] Figure 1 illustrates a flow chart depicting the processing of retrieving brand level digital shelf visibility score; and

[0015] Figure 2 illustrates an exemplary embodiment of the processing of retrieving brand level digital shelf visibility score.

DETAILED DESCRIPTION OF THE INVENTION

[0016] The following description describes various features and functions of the disclosed system with reference to the accompanying figures. In the figures, similar symbols identify similar components, unless context dictates otherwise. The illustrative aspects described herein are not meant to be limiting. It may be readily understood that certain aspects of the disclosed system can be arranged and combined in a wide variety of different configurations, all of which have not been contemplated herein.

[0017] Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope of invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.

[0018] Features that are described and/or illustrated with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments and/or in combination with or instead of the features of the other embodiments.

[0019] The terms and words used in the following description are not limited to the bibliographical meanings, but, are merely used to enable a clear and consistent understanding of the invention. Accordingly, it should be apparent to those skilled in the art that the following description of exemplary embodiments of the present invention are provided for illustrative purpose only and not for the purpose of limiting the invention.

[0020] It is to be understood that the singular forms “a”, “an” and “the” include plural referents unless the context clearly dictates otherwise.

[0021] It should be emphasized that the term “comprises/comprising” when used in this specification is taken to specify the presence of stated features, steps or components but does not preclude the presence or addition of one or more other features, steps, components or groups thereof.

[0022] Some embodiments of this disclosure, illustrating all its features, will now be discussed in detail. The words “receiving”, "extracting," "identifying,” “updating," "determining," "recommending," and other forms thereof, are intended to be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items.

[0023] The present subject matter discloses a system and method for retrieving product(s) digital shelf visibility score. In an embodiment, a system for searching, extracting and analyzing a product of user’s choice is disclosed. It may be noted that one or more users may access the system. Further, the system may be implemented in a variety of computing devices, such as a laptop, a desktop computer, a notebook, a workstation, a virtual environment, a mainframe computer, a server, a network server, a cloud-based computing environment. The components of the system are communicatively coupled through a network.

[0024] In an embodiment, the network may be, but not limited to, a wireless network, a wired network, or a combination thereof. The network may be implemented as one of the different types of networks, such as intranet, local area network (LAN), wide area network (WAN), the internet, and the like. The network may either be a dedicated network or a shared network. The shared network represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), and the like, to communicate with one another. Further, the network may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, etc.

[0025] In another embodiment, the system may include at least one processor, an input/output (I/O) interface, and a memory. The at least one processor may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, Central Processing Units (CPUs), state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the at least one processor is configured to fetch and execute computer-readable instructions stored in the memory.

[0026] The memory may include any computer-readable medium or computer program product known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or nonvolatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, Solid State Disks (SSD), optical disks, and magnetic tapes. The memory may include routines, programs, objects, components, data structures, etc., which perform particular tasks or implement particular abstract data types. The memory may include programs or coded instructions that supplement applications and functions of the system. In one embodiment, the memory includes the following modules discussed in detail for storing, processing, receiving, and generating segregated data by one or more of the programs or the coded instructions:

[0027] (a) Website Directory Module: In one aspect whenever the user enters their choice on the system to retrieve the data related to any particular product then website directory module plays an important role. It includes links to others sites i.e., plurality of e-commerce website addresses. Further the directory is linked with plurality of vendors supplying various types of products on the plurality of e-commerce website. The information listed about the vendors includes a company(s) name, phone number, address, hours of operation, website, social media accounts, a short description of what the company does, photos, and a listing of products and services that they offer.

[0028] (b) Searching Module: In one aspect digital bot/crawler crawls across the website directory to find and index the products for keywords and phrases, or the words used by a user to find a useful product. The one or more parameter for indexing or searching may comprise the consumer behavior, warehouse logistics, price modeling, Search Term; Marketplace; Product ID; Date; Brand Taxonomy; Label; Product Position etc. Based on the input entered by the user the digital bot extracts the information from the plurality of ecommerce website.

[0029] The digital bot retrieves and indexes contents by crawling into a plurality of webpages to obtain data through a software program. Thus, by applying a search algorithm to the data collected by the crawlers, based on the user input, an index/ catalogue of the required products is generated along with the required information of the product.
[0030] (c) Search Storage Module: The extraction of the product based on the user input may be stored in the search storage module.

[0031] (d) Analytical Module: In another aspect, an analytical module is a data-driven approach applied to the search result based on analysis and interpretation of metadata supported by sets of factual information. The crawlers/digital bot extract the information from the plurality of ecommerce website, which is further segregated in the data driven module.. The data-driven approach is implemented using an algorithm that employs heuristic data models to decipher implicit patterns within the data, which leads to the generation of practical insights and/or to predict brand scores /digital shelf visibility score. Additionally, it leverages machine learning and/or Artificial intelligence models to enhance its analytical capabilities. In one embodiment, a machine learning or artificial intelligence models may be used to analyze the product information stored in the search storage module. The machine learning model or the artificial intelligence technique may be trained based on metadata/product information. The metadata/product information may include consumer behavior, warehouse logistics, price modeling, Search Term; Marketplace; Product ID; Date; Brand Taxonomy; Label; Product Position etc. and all of this is decoded and streamlined with the help of the data-driven approach. The segregated result is again stored in search storage module and further processed to be visualized on the screen of the input/output interface.

[0032] The input/output interface may include a plurality of software and hardware interfaces, for example, a web interface, a graphical user interface, and the like. The I/O interface may allow the system to interact with the user directly by displaying the segregated information related to the product. Further, the I/O interface may enable the system to communicate with other computing devices, such as web servers and external data servers (not shown). The I/O interface can facilitate multiple communications within a wide variety of networks and protocol types, including wired networks, for example, LAN, cable, etc., and wireless networks, such as WLAN, cellular, or satellite. The I/O interface may include one or more ports for connecting a number of devices to one another or to another server.

[0033] In a preferred embodiment, a system for retrieving product(s) digital shelf visibility score, comprising: at least one processor; a memory coupled to a processor by wired/ wireless network, comprising:
i. website directory module to retrieve the plurality of e-commerce website addresses;
ii. searching module to retrieve the data related to any particular product as per the input entered by the user;
iii. search storage module to store the extraction of the product based on the user input; and
iv. analytical module configured with a machine learning and/ or artificial intelligence model to retrieve the product(s) digital shelf score via a data-driven approach;
Further, the system comprises an input/output interface for displaying the identified product digital shelf visibility score. The searching module of the memory comprising of crawlers/digital bot to extract information from a plurality of e-commerce platform. The analytical module configured in the memory identifies product digital shelf visibility score by analyzing and segregating the data stored in the search storage module via the machine learning model and artificial intelligence model. The system for retrieving product(s) digital shelf visibility score is configured in a plurality of computing devices to establish connection between a plurality of users.

[0034] The method for retrieving product information via the system of the present invention comprising the following steps:
• entering data related to a product by a user on an Input/Output (I/O) interface;
• retrieving data by a website directory module based on input data fed by the user into the I/O interface;
• finding and storing of products into a searching module based on a plurality of parameters of the product fed by the user, said searching module comprises of a plurality of digital bots/ crawlers for crawling across data retrieved by the website directory module;
• analyzing and segregating search results by an analytical module, said analytical module is configured with a machine learning model and/ or artificial intelligence model to analyze and segregate the product information stored in the search storage module to identify product digital shelf visibility score;
• storing segregated results of the products into the search storage module; and
• displaying identified product digital shelf visibility score on an input/output interface.

[0035] In an exemplary embodiment Figure 2 illustrates the process of retrieving brand level digital shelf visibility score:
• Searching for different type of products i.e., S1 may be a headphone and S2 may be mobile phone etc. ;
• Further these searches were conducted on various e-commerce platform for example A1 is amazon and F1 is flipkart;
• Further what is the product that is shown first or in second place or at any other place for example P1 may be a boat brand headphone and P2 may be JBL headphone etc.;
• D1 and D2 illustrates the various dates on which these products were searched;
• Further which brand headphones were displayed to customer first is retrieved from the database. For example B1 is boat brand and B2 is apple brand;
• Further based on their category they are classified i.e., headphone are for audio category and mobile phone for voice category;
• Then there is another very specific content that is advertisement i.e., how different brand are advertising their products to secure a position where the customer is able to see a certain brand product everywhere; and
• Lastly there is the brand position or product position on various ecommerce platform which is visible to the brand owners.

[0036] While this invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
, Claims:WE CLAIM:
1. A method for retrieving product(s) digital shelf visibility score, comprising:
• entering data related to a product(s) by a user on an Input/Output (I/O) interface;
• retrieving data by a website directory module based on input data fed by the user into the I/O interface;
• finding products based on a plurality of parameters of the product fed by the user and storing product information in a searching module, said searching module comprises of a plurality of digital bots/ crawlers for crawling across data retrieved by the website directory module;
• analyzing and segregating the product information stored in the search storage module to identify product digital shelf visibility score;
• storing segregated results of the products into the search storage module; and
• displaying identified product digital shelf visibility score on an input/output interface.

2. The method as claimed in claim 1, wherein the searching module comprising a plurality of digital bots/crawlers crawls across the website directory module to find and index the products for keywords and/ or phrases fed by the user.

3. The method as claimed in claim 1, wherein the product information comprises of consumer behavior, warehouse logistics, price modeling, search term, marketplace, product id, date, brand taxonomy, label, product position.

4. A system for retrieving product(s) digital shelf visibility score, comprising:
• at least one processor;
• a memory coupled to a processor by wired/ wireless network, comprising:
v. website directory module to retrieve the plurality of e-commerce website addresses;
vi. searching module to retrieve the data related to any particular product as per the input entered by the user;
vii. search storage module to store the extraction of the product based on the user input; and
viii. analytical module configured with a machine learning and/ or artificial intelligence model to retrieve the product(s) digital shelf score via a data-driven approach;
• an input/output interface for displaying the identified product digital shelf visibility score;
wherein,
I. the searching module of the memory comprising of crawlers/digital bot to extract information from a plurality of e-commerce platform, and
II. analytical module identifies product digital shelf visibility score by analyzing and segregating the data stored in the search storage module via the machine learning model and artificial intelligence model.

5. The system as claimed in claim 4, wherein the system is configured in a plurality of computing devices to provide connection between a plurality of users.

6. The system as claimed in claim 4, wherein the processor, the memory and the I/O interface of the system communicate with each other via a wired and/or wireless network.

7. The system as claimed in claim 4, wherein the network is selected from, but not limited to intranet, local area network (LAN), wide area network (WAN), the internet, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP).

8. The system as claimed in claim 4, wherein the processor is selected from, but not limited to, microprocessors, microcomputers, microcontrollers, digital signal processors, Central Processing Units (CPUs), state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions.

9. The system as claimed in claim 4, wherein the at least one processor is configured to fetch and execute computer-readable instructions stored in the memory.

10. The system as claimed in claim 4, wherein the I/O interface further includes one or more ports for connecting a number of computing devices to one another or to another server.