Description:FIELD OF INVENTION
[0001] The embodiments of the present disclosure generally relate to product price sensitivity, customer price sensitivity, and market price sensitivity in electronic commerce (e-commerce) systems. More particularly, the present disclosure relates to a method and a system for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment.

BACKGROUND
[0002] The following description of the related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of the prior art.
[0003] Generally, tracking and measuring price and price-related drivers in real-time for one or more products may be challenging in electronic commerce (e-commerce). Traditional tools such as a product dashboard and price trackers may allow simple tracking of the price of specific products. However, the traditional tools may not aid in establishing complex relationships between the platform’s price, competitor’s price, offers, customer cohorts, other such pricing drivers, and the like. Further, the traditional tools may not help in understanding the overall health and hygiene of over a million products on the platform.
[0004] Additionally, the price of a product on an e-commerce platform may need to be not only attractive for the customer, but also needs to be economically feasible for the e-commerce platform. The e-commerce platform that sells one or two categories of products may face less of a challenge as it is easier to track pricing and understand the customer’s requirements. However, for the e-commerce platform that sells products in a variety of categories to varied customer segments, maintaining price hygiene, understanding the requirements of customers, tracking offers, and customer satisfaction, all at the same time may be a challenging ask.
[0005] Conventionally, there have been several non-pricing dashboards for analyzing customer visits. The non-pricing dashboards may help one or more merchants to monitor parameters such as requests from customers to a customer service and the responses provided in real-time corresponding to the requests. Another conventional method provides a method for facilitating communications between providers of online services and potential customers, based on the monitored activities of the potential customers. Yet another conventional method may provide dashboards for understanding transaction data for displaying data for one or more particular transactions, transaction types, or transactions that meet specified criteria. Also, another conventional method may provide dashboards for semantically analyzing an internal social network setup in an organization. The executives can gain a better understanding of, and insight into, the organization and its employees. A dashboard tool may be used to visualize the results of the semantic analysis. In another conventional method, the method provides e-commerce customer support activities using an analytics server, which provides real-time information concerning customer visits to an e-commerce website to a merchant that operates the website, for example using a dashboard or other user interface. The real-time information allows the merchant to monitor and optionally interact with customers visiting the website, for example by viewing requests for customer service and providing real-time customer service via interactive user interfaces.
[0006] However, the aforementioned conventional methods may not provide price dashboards, and also multiple dashboards converge to form a fully-functional application that tracks all price-related movements and strategies regarding products, in one place.
[0007] Therefore, there may be a need for a method and a system for solving the shortcomings of the conventional methods, by providing a method and a system for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment.

SUMMARY
[0008] This section is provided to introduce certain objects and aspects of the present invention in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter. In order to overcome at least a few problems associated with the known solutions as provided in the previous section, an object of the present disclosure is to provide a technique for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment.
[0009] It is an object of the present disclosure to provide a method and a system for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment.
[0010] It is another object of the present disclosure to provide a method and a system for creating a pricing suite or a single dashboard application which helps in tracking all price and price drivers of one or more products.
[0011] It is yet another object of the present disclosure to provide a method and a system for providing the pricing-related drivers and dashboards such as, a price perception driver, a competitive pricing driver, an automated pricing driver, a markdown pricing driver, an incentive pricing driver, and a spend effectiveness driver.
[0012] It is yet another object of the present disclosure to provide a method and a system for real-time tracking of the price of one or more products, and to enable derived metrics such as a competitiveness of one or more products, offer adoption for one or more products, offer performance of one or more products, auto pricing of one or more products, price perception of one or more products, and price health of one or more products.
[0013] It is yet another object of the present disclosure to provide a method and a system for providing overview of one function impacting another function with respect to one or more pricing metrics. For instance, by using the e-commerce platform's price and competitors’ price, one can understand the offer-wise performance of sales, thereby providing an overview of the offer construct works best and under which competitive conditions.
[0014] It is yet another object of the present disclosure to provide a method and a system for tracking performance for different types of products by categorizing products into different tiers such as a head tier with top-selling products and a tail tier with low-selling products, which in turn enables running different price constructs.
[0015] It is yet another object of the present disclosure to provide a method and a system for providing an incentive pricing dashboard, which helps in addressing all the issues such as a bad discounting, and multiple offers running on a product, while keeping the price metrics in mind, thereby ensuring effective and efficient pricing for products on offer.
[0016] It is yet another object of the present disclosure to provide a method and a system for identifying old and obsolete products to provide more discounted prices and subsequently remove the old and obsolete products for providing space for fresh selection and inventory of new products.
[0017] In an aspect, the present disclosure provides a method for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment. The method includes generating a hive dataset for one or more price metrics corresponding to one or more products associated with an electronic commerce (e-commerce) environment. Further, the method includes transmitting the generated hive dataset to one or more Virtual Machines (VMs). Furthermore, the method includes creating one or more pipelines corresponding to each of the one or more price metrics, from the hive dataset transmitted to one or more VMs. The one or more pipelines correspond to pricing-related drivers. Additionally, the method includes generating one or more insights, and associated graphs for each of the one or more pipelines corresponding to each of the pricing-related drivers. Further, the method includes deriving one or more key action items impacting the one or more price metrics. Furthermore, the method includes outputting at least one of one or more insights, the graphs, and the key action items in a workspace, for each of the pricing-related drivers.
[0018] In an embodiment, the method further includes categorizing the one or more products into a plurality of product tiers. Further, the method includes providing a plurality of price constructs for each of the plurality of product tiers, to run the plurality of price constructs in the e-commerce environment. Furthermore, the method includes analyzing a spend effectiveness data and a price health data of the plurality of price construct, upon running the plurality of price constructs in the e-commerce environment. Additionally, the method includes outputting, using a dashboarding tool, a result of the analyzed spend effectiveness data and a price health data.
[0019] In an embodiment, the plurality of product tiers corresponds to at least one of a head product tier with top-selling products and sellers in the e-commerce environment, and a tail product tier with least-selling products and sellers in the e-commerce environment.
[0020] In an embodiment, the one or more price metrics correspond to at least one of competitiveness of pricing for the one or more products, offer adoption for the one or more products, offer performance for the one or more products, auto pricing for the one or more products, price perception of a user for the one or more products, and price health of the one or more products.
[0021] In an embodiment, the pricing-related drivers correspond to at least one of a price perception driver, a competitive pricing driver, an automated pricing driver, a markdown pricing driver, an incentive pricing driver, and a spend effectiveness driver.
[0022] In another aspect, the present disclosure provides a system for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment. The system generates a hive dataset for one or more price metrics corresponding to one or more products associated with an electronic commerce (e-commerce) environment. Further, the system transmits the generated hive dataset to one or more Virtual Machines (VMs). Furthermore, the system creates one or more pipelines corresponding to each of the one or more price metrics, from the hive dataset transmitted to the one or more VMs. The one or more pipelines correspond to pricing-related drivers. Additionally, the system generates one or more insights and associated graphs for each of the one or more pipelines corresponding to each of the pricing-related drivers. Furthermore, the system derives one or more key action items impacting the one or more price metrics. Further, the system outputs, using a dashboarding tool, at least one of the one or more insights, the graphs, and the key action items in a workspace, for each of the pricing-related drivers.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
[0023] The accompanying drawings, which are incorporated herein, and constitute a part of this invention, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present invention. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry/sub-components of each component. It will be appreciated by those skilled in the art that the invention of such drawings includes the invention of electrical components, electronic components, or circuitry commonly used to implement such components.
[0024] FIG. 1 illustrates an exemplary block diagram representation of a network architecture implementing a proposed system for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment, according to embodiments of the present disclosure.
[0025] FIG. 2 illustrates an exemplary detailed block diagram representation of the proposed system, according to embodiments of the present disclosure.
[0026] FIGs. 3A and 3B illustrate exemplary schematic diagram representations of a dashboard and process flow, respectively, corresponding to monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment, according to embodiments of the present disclosure.
[0027] FIG. 4 illustrates a flow chart depicting a method of monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment, according to embodiments of the present disclosure.
[0028] FIG. 5 illustrates a hardware platform for the implementation of the disclosed system according to embodiments of the present disclosure.
[0029] The foregoing shall be more apparent from the following more detailed description of the invention.

DETAILED DESCRIPTION OF INVENTION
[0030] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0031] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that, various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth.
[0032] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments.
[0033] Also, it is noted that individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.
[0034] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive—in a manner similar to the term “comprising” as an open transition word—without precluding any additional or other elements.
[0035] As used herein, "connect", "configure", "couple" and its cognate terms, such as "connects", "connected", "configured", and "coupled" may include a physical connection (such as a wired/wireless connection), a logical connection (such as through logical gates of semiconducting device), other suitable connections, or a combination of such connections, as may be obvious to a skilled person.
[0036] As used herein, "send", "transfer", "transmit", and their cognate terms like "sending", "sent", "transferring", "transmitting", "transferred", "transmitted", etc. include sending or transporting data or information from one unit or component to another unit or component, wherein the content may or may not be modified before or after sending, transferring, transmitting.
[0037] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0038] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed products.
[0039] Various embodiments of the present disclosure provide a method and a system for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment. The present disclosure provides a method and a system for creating a pricing suite or a single dashboard application which helps in tracking all price and price drivers of one or more products. The present disclosure provides a method and a system for providing the pricing-related drivers and dashboards such as, a price perception driver, a competitive pricing driver, an automated pricing driver, a markdown pricing driver, an incentive pricing driver, and a spend effectiveness driver. The present disclosure provides a method and a system for real-time tracking of the price of one or more products, and to enable derived metrics such as a competitiveness of one or more products, offer adoption for one or more products, offer performance of one or more products, auto pricing of one or more products, price perception of one or more products, and price health of one or more products. The present disclosure provides a method and a system for providing overview of one function impacting another function with respect to one or more pricing metrics. For instance, by using the e-commerce platform's price and competitors’ prices, one can understand the offer-wise performance of sales, thereby providing an overview of the offer construct works best and under which competitive conditions.
[0040] The present disclosure provides a method and a system for tracking performance for different types of products by categorizing products into different tiers such as a head tier with top-selling products and a tail tier with low-selling products, which in turn enables running different price constructs. The present disclosure provides a method and a system for providing an incentive pricing dashboard, which helps in addressing all the issues such as a bad discounting, and multiple offers running on a product, while keeping the price metrics in mind, thereby ensuring effective and efficient pricing for products on offer. The present disclosure provides a method and a system for identifying old and obsolete products to provide more discounted prices and subsequently remove the old and obsolete products for providing space for fresh selection and inventory of new products.
[0041] FIG. 1 illustrates an exemplary block diagram representation of a network architecture 100 implementing a proposed system 110 for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment, according to embodiments of the present disclosure. The network architecture 100 may include the system 110, an electronic device 108, and a centralized server 118. The system 110 may be connected to the centralized server 118 via a communication network 106. The centralized server 118 may include, but is not limited to, a stand-alone server, a remote server, a cloud computing server, a dedicated server, a rack server, a server blade, a server rack, a bank of servers, a server farm, hardware supporting a part of a cloud service or system, a home server, hardware running a virtualized server, one or more processors executing code to function as a server, one or more machines performing server-side functionality as described herein, at least a portion of any of the above, some combination thereof, and the like. The centralized server 118 may be associated with an entity corresponding to an electronic commerce (e-commerce) environment. The communication network 106 may be a wired communication network or a wireless communication network. The wireless communication network may be any wireless communication network capable of transferring data between entities of that network such as, but are not limited to, a Bluetooth, a Zigbee, a Near Field Communication (NFC), a Wireless-Fidelity (Wi-Fi) network, a Light Fidelity (Li-FI) network, a carrier network including a circuit-switched network, a packet switched network, a Public Switched Telephone Network (PSTN), a Content Delivery Network (CDN) network, an Internet, intranets, Local Area Networks (LANs), Wide Area Networks (WANs), mobile communication networks including a Second Generation (2G), a Third Generation (3G), a Fourth Generation (4G), a Fifth Generation (5G), a Sixth Generation (6G), a Long-Term Evolution (LTE) network, a New Radio (NR), a Narrow-Band (NB), an Internet of Things (IoT) network, a Global System for Mobile Communications (GSM) network and a Universal Mobile Telecommunications System (UMTS) network, combinations thereof, and the like.
[0042] The system 110 may be implemented by way of a single device or a combination of multiple devices that may be operatively connected or networked together. For example, the system 110 may be implemented by way of a standalone device such as the centralized server 118, and the like, and may be communicatively coupled to the electronic device 108. In another example, the system 110 may be implemented in/ associated with the electronic device 108. In yet another example, the system 110 may be implemented in/ associated with respective computing device 104-1, 104-2, …..., 104-N (individually referred to as the computing device 104, and collectively referred to as the computing devices 104), associated with one or more user 102-1, 102-2, …..., 102-N (individually referred to as the user 102, and collectively referred to as the users 102). In such a scenario, the system 110 may be replicated in each of the computing devices 104. The users 102 may be a user of, but are not limited to, an electronic commerce (e-commerce) platform, a merchant platform, a hyperlocal platform, a super-mart platform, a media platform, a service providing platform, a social networking platform, a travel/services booking platform, a messaging platform, a bot processing platform, a virtual assistance platform, an Artificial Intelligence (AI) based platform, a blockchain platform, a blockchain marketplace, and the like. In some instances, the user 102 may correspond to an entity/ administrator of platforms/ services.
[0043] The electronic device 108 may be at least one of, an electrical, an electronic, an electromechanical, and a computing device. The electronic device 108 may include, but is not limited to, a mobile device, a smart-phone, a Personal Digital Assistant (PDA), a tablet computer, a phablet computer, a wearable computing device, a Virtual Reality/Augmented Reality (VR/AR) device, a laptop, a desktop, a server, and the like. The system 110 may be implemented in hardware or a suitable combination of hardware and software. The system 110 or the centralized server 118 may be associated with entities (not shown). The entities may include, but are not limited to, an e-commerce company, a merchant organization, a travel company, an airline company, a hotel booking company, a company, an outlet, a manufacturing unit, an enterprise, a facility, an organization, an educational institution, a secured facility, a warehouse facility, a supply chain facility, and the like.
[0044] Further, the system 110 may include a processor 112, an Input/Output (I/O) interface 114, and a memory 116. The Input/Output (I/O) interface 114 of the system 110 may be used to receive user inputs, from the computing devices 104 associated with the users 102. Further, system 110 may also include other units such as a display unit, an input unit, an output unit, and the like, however the same are not shown in FIG. 1, for the purpose of clarity. Also, in FIG. 1 only a few units are shown, however, the system 110 or the network architecture 100 may include multiple such units or the system 110/ network architecture 100 may include any such numbers of the units, obvious to a person skilled in the art or as required to implement the features of the present disclosure. The system 110 may be a hardware device including the processor 112 executing machine-readable program instructions to monitor at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment.
[0045] Execution of the machine-readable program instructions by the processor 112 may enable the proposed system 110 to monitor at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment. The “hardware” may comprise a combination of discrete components, an integrated circuit, an application-specific integrated circuit, a field-programmable gate array, a digital signal processor, or other suitable hardware. The “software” may comprise one or more objects, agents, threads, lines of code, subroutines, separate software applications, two or more lines of code, or other suitable software structures operating in one or more software applications or on one or more processors. The processor 112 may include, for example, but is not limited to, microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, and any devices that manipulate data or signals based on operational instructions, and the like. Among other capabilities, the processor 112 may fetch and execute computer-readable instructions in the memory 116 operationally coupled with the system 110 for performing tasks such as data processing, input/output processing, feature extraction, and/or any other functions. Any reference to a task in the present disclosure may refer to an operation being or that may be performed on data.
[0046] In the example that follows, assume that a user 102 of the system 110 desires to improve/add additional features to monitor at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment. In this instance, the user 102 may include an administrator of a website, an administrator of an e-commerce site, an administrator of a social media site, an administrator of an e-commerce application/ social media application/other applications, an administrator of media content (e.g., television content, video-on-demand content, online video content, graphical content, image content, augmented/virtual reality content, metaverse content), an administrator of supply chain platform, an administrator of blockchain marketplace, an administrator of a travel/services booking platform, an administrator of merchant platform, among other examples, and the like. The system 110 when associated with the electronic device 108 or the centralized server 118 may include, but is not limited to, a touch panel, a soft keypad, a hard keypad (including buttons), and the like.
[0047] In an embodiment, the system 110 may generate a hive dataset for one or more price metrics corresponding to one or more products associated with an electronic commerce (e-commerce) environment. In an embodiment, the one or more price metrics corresponds to, but are not limited to, a competitiveness of pricing for the one or more products, an offer adoption for the one or more products, an offer performance for the one or more products, an auto pricing for the one or more products, a price perception of a user for the one or more products, a price health of the one or more products, and the like. The hive dataset is an example dataset and should not be considered to be limited to the hive dataset. The system 110 may use similar type of dataset based on a requirement.
[0048] In an embodiment, the system 110 may transmit the generated hive dataset to one or more Virtual Machines (VMs).
[0049] In an embodiment, the system 110 may create one or more pipelines corresponding to each of the one or more price metrics, from the hive dataset transmitted to the one or more VMs. The one or more pipelines correspond to pricing-related drivers. In an embodiment, the pricing-related drivers correspond to, but are not limited to, a price perception driver, a competitive pricing driver, an automated pricing driver, a markdown pricing driver, an incentive pricing driver, a spend effectiveness driver, and the like.
[0050] In an embodiment, the system 110 may generate one or more insights, and associated graphs for each of the one or more pipelines corresponding to each of the pricing-related drivers.
[0051] In an embodiment, the system 110 may derive one or more key action items impacting the one or more price metrics.
[0052] In an embodiment, the system 110 may output, using a dashboarding tool, at least one of the one or more insights, the graphs, and the key action items in a workspace, for each of the pricing-related drivers.
[0053] In an embodiment, the system 110 may further categorize the one or more products into a plurality of product tiers. In an embodiment, the plurality of product tiers corresponds to, but is not limited to, a head product tier with top-selling products and sellers in the e-commerce environment, a tail product tier with least selling products and sellers in the e-commerce environment, and the like.
[0054] Further, the system 110 may provide a plurality of price constructs for each of the plurality of product tiers, to run the plurality of price constructs in the e-commerce environment. Furthermore, the system 110 may analyze a spend effectiveness data and a price health data of the plurality of price construct, upon running the plurality of price constructs in the e-commerce environment. Additionally, the system 110 may output a result of the analyzed spend effectiveness data and a price health data.
[0055] FIG. 2 illustrates an exemplary detailed block diagram representation of the proposed system 110, according to embodiments of the present disclosure. The system 110 may include the processor 112, the Input/Output (I/O) interface 114, and the memory 116. In some implementations, the system 110 may include data 202, and modules 204. As an example, the data 202 may be stored in the memory 116 configured in the system 110 as shown in FIG. 2.
[0056] In an embodiment, the data 202 may include hive data 206, price metrics data 208, Virtual Machine (VM) data 210, pipeline data 212, graph data 214, key action items data 216, insights data 218, and other data 220. In an embodiment, the data 202 may be stored in the memory 116 in the form of various data structures. Additionally, the data 202 can be organized using data models, such as relational or hierarchical data models. The other data 218 may store data, including temporary data and temporary files, generated by the modules 204 for performing the various functions of the system 110.
[0057] In an embodiment, the modules 204, may include a generating module 222, a transmitting module 224, a creating module 226, a deriving module 228, an outputting module 230, and other modules 232.
[0058] In an embodiment, the data 202 stored in the memory 116 may be processed by the modules 204 of the system 110. The modules 204 may be stored within the memory 116. In an example, the modules 204 communicatively coupled to the processor 112 configured in the system 110, may also be present outside the memory 116, as shown in FIG. 2, and implemented as hardware. As used herein, the term modules refer to an Application-Specific Integrated Circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and memory that execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.
[0059] In an embodiment, the generating module 22 may generate a hive dataset for one or more price metrics corresponding to one or more products associated with an electronic commerce (e-commerce) environment. In an embodiment, the one or more price metrics correspond to, but are not limited to, a competitiveness of pricing for the one or more products, an offer adoption for the one or more products, an offer performance for the one or more products, an auto pricing for the one or more products, a price perception of a user for the one or more products, a price health of the one or more products, and the like. In an embodiment, the hive dataset for one or more price metrics may be stored as the hive data 206. In an embodiment, the one or more price metrics corresponding to one or more products may be stored as the price metrics data 208.
[0060] In an embodiment, the transmitting module 224 may transmit the generated hive dataset to one or more Virtual Machines (VMs). In an embodiment, the one or more Virtual Machines (VMs)may be stored as the Virtual Machine (VM) data 210.
[0061] In an embodiment, the creating module 226 may create one or more pipelines corresponding to each of the one or more price metrics, from the hive dataset transmitted to the one or more VMs. The one or more pipelines correspond to pricing-related drivers. In an embodiment, the pricing-related drivers correspond to, but are not limited to, a price perception driver, a competitive pricing driver, an automated pricing driver, a markdown pricing driver, an incentive pricing driver, a spend effectiveness driver, and the like. In an embodiment, the created one or more pipelines may be stored as the pipeline data 212.
[0062] In an embodiment, the generating module 222 may generate one or more insights, and associated graphs for each of the one or more pipelines corresponding to each of the pricing-related drivers. The one or more insights may be stored as the insights data 218. Further, the associated graphs for each of the one or more pipelines may be stored as the graph data 214.
[0063] In an embodiment, the deriving module 228 may derive one or more key action items impacting the one or more price metrics. In an embodiment, the derived one or more key action items impacting the one or more price metrics may be stored as the key action items data 216.
[0064] In an embodiment, the outputting module 230 may output, using a dashboarding tool, at least one of the one or more insights, the graphs, and the key action items in a workspace, for each of the pricing-related drivers.
[0065] In an embodiment, the system 110 may further categorize one or more products into a plurality of product tiers. In an embodiment, the plurality of product tiers corresponds to, but is not limited to, a head product tier with top-selling products and sellers in the e-commerce environment, a tail product tier with least-selling products and sellers in the e-commerce environment, and the like.
[0066] Further, the system 110 may provide a plurality of price constructs for each of the plurality of product tiers, to run the plurality of price constructs in the e-commerce environment. Furthermore, the system 110 may analyze spend effectiveness data and price health data of the plurality of price constructs, upon running the plurality of price constructs in the e-commerce environment. Additionally, the system 110 may output a result of the analyzed spend effectiveness data and price health data.
Exemplary scenario:
[0067] Consider, that processor 112 creates individual pipelines for each of the price metrics that are needed to be tracked as shown in FIG. 3A. For example, the processor 112 may create, for example, a hive data set and move the hive dataset to a Virtual Machine (VM) using, for example, Azure®, and the like. The processor 112 may use a dashboarding tool such as, for example, Power BI®, which may allow to output insights using one or more price metrics. After creating the relevant graphs and views, the processor 112 may publish the dashboard in a workspace using a suitable application as shown in FIG. 3B. This process is repeated ‘N’ a number of times for every pricing principle. After publishing all the dashboards onto the same workspace, the processor 112 may publish a complete pricing application.
[0068] The dashboard may include price metrics, which form a building block of each pricing principle. By tracking the essential price metrics on a daily/weekly/monthly basis, the user 102 can understand the impact of the pricing of the product due to certain business decisions. Further, the dashboard may include insights, for understanding the impact of each of the price metrics on different pricing aspects. Further, the dashboard may include actionability information. The processor 112 may use the insights to derive the key action items which may impact the price metrics. By allowing each dashboard to use the insights to derive the key action items which may impact the price metrics, the processor 112 may establish a cyclic process that helps in providing clarity over the pricing decisions of the products.
[0069] Further, the pricing-related drivers and principles may include, but are not limited to, a price perception driver, a competitive pricing driver, an automated pricing driver, a markdown pricing driver, an incentive pricing driver, a spend effectiveness driver, and the like. For example, the price perception driver may be depicted as the price perception dashboard to view the price of products by the customers. In the price perception dashboard, each customer views prices differently. The e-commerce platform may need to convey value and information to the customer he is seeking. This price perception dashboard provides, but is not limited to, prices of products, deals on the e-commerce platform, value callouts on deals, and good prices, offers, and components that customers interact with most. Understanding each of the aspects may be essential to get a grasp of how the customer is perceiving prices on the platform.
[0070] Further, the competitive pricing driver may be depicted as a competitive pricing dashboard to check the pricing pattern of the product by a competitor. A Customer Insights (CI) segment in the dashboard tool may enable the merchant to monitor price competitiveness against different market competitors on a day-to-day basis for all categories. Further, the CI segment may also help to identify target portfolios having the scope for price improvement prioritized on demand. The dashboard tool may also enable the merchant to understand the depth of prices against the competitors and a degree of correction that needs to be performed on a current price of the product, based on the depth of prices against the competitors. The competitive pricing dashboard may enable close monitoring of price competitiveness across all events and regular business days.
[0071] Furthermore, the automated pricing driver may be depicted as an automated pricing dashboard to analyze the effectiveness of automated pricing vs. manual pricing. The automated pricing dashboard may enable respective sell-side teams to take pricing decisions, based on the inventory status and age of the product. The automated pricing dashboard may be used to measure the effectiveness of automated pricing vs. manual pricing and track key metrics with respect to business performance.
[0072] Additionally, the markdown pricing driver may be depicted as the markdown pricing dashboard to determine a pricing strategy for an old-aged product. For example, the products that become old and obsolete in the e-commerce platform, can be sold to the customer at a discount. The markdown pricing dashboard may identify old and obsolete products, provide pricing, and removing from the e-commerce platform to ensure a fresh selection and inventory of products to take up the space in the e-commerce platform.
[0073] Further, the incentive pricing driver may be depicted as an incentive pricing dashboard to determine the pricing strategy of a product during an offer or promotion. At any given point in time, a product can have multiple offers/promotions running on top of it. These offers are often targeted toward meeting a specific business use case. The incentive pricing dashboard caters to a merchants/e-commerce platform for understanding the performance of the offers for different customer cohorts and in different periods. It is important to understand if the offer construct is working in the desired direction, if not immediate actions are needed to be taken. The challenge while catering to a large portfolio is tracking bad discounting offers i.e., if an undesired offer is running on a product or not. It is important to not only spot this daily but also important to predetermine this for any important upcoming event. The incentive pricing dashboard helps address all these issues while keeping the business metrics in mind, thereby ensuring effective and efficient pricing is done for products on offer.
[0074] Furthermore, the spend effectiveness driver may be depicted as a spend effectiveness dashboard to determine the efficiency of the pricing during events. During any sale day on an e-commerce platform, the prices of a product are discounted to boost customer frenzy and sales. The spend effectiveness dashboard enables measuring the efficiency of price discounts by understanding revenue per cost. The spend effectiveness dashboard helps in the understanding deepness of the pricing of the product compared to regular business days and its effectiveness. The spend effectiveness dashboard helps to compare pricing strategies across periods. Further, the spend effectiveness dashboard may be used to drive the reduction of the portfolio.
[0075] FIG. 4 illustrates a flow chart depicting a method 400 of monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment, according to embodiments of the present disclosure.
[0076] At block 402, the method 400 includes generating, by the processor associated 112 with the system 110, a hive dataset for one or more price metrics corresponding to one or more products associated with an electronic commerce (e-commerce) environment.
[0077] At block 404, the method 400 includes transmitting, by the processor 112, the generated hive dataset to one or more Virtual Machines (VMs).
[0078] At block 406, the method 400 includes creating, by the processor 112, one or more pipelines corresponding to each of the one or more price metrics, from the hive dataset transmitted to the one or more VMs. The one or more pipelines correspond to pricing-related drivers.
[0079] At block 408, the method 400 includes generating, by the processor 112, one or more insights, and associated graphs for each of the one or more pipelines corresponding to each of the pricing-related drivers.
[0080] At block 410, the method 400 includes deriving, by the processor 112, one or more key action items impacting the one or more price metrics.
[0081] At block 412, the method 400 includes outputting, by the processor 112, using a dashboarding tool, at least one of the one or more insights, the graphs, and the key action items in a workspace, for each of the pricing-related drivers.
[0082] The order in which the method 400 is described is not intended to be construed as a limitation, and any number of the described method blocks may be combined or otherwise performed in any order to implement the method 400 or an alternate method. Additionally, individual blocks may be deleted from the method 400 without departing from the spirit and scope of the present disclosure described herein. Furthermore, the method 400 may be implemented in any suitable hardware, software, firmware, or a combination thereof, that exists in the related art or that is later developed. The method 400 describes, without limitation, the implementation of the system 110. A person of skill in the art will understand that method 400 may be modified appropriately for implementation in various manners without departing from the scope and spirit of the disclosure.
[0083] FIG. 5 illustrates a hardware platform 500 for implementation of the disclosed system 110, according to an example embodiment of the present disclosure. For the sake of brevity, the construction, and operational features of the system 110 which are explained in detail above are not explained in detail herein. Particularly, computing machines such as but not limited to internal/external server clusters, quantum computers, desktops, laptops, smartphones, tablets, and wearables which may be used to execute the system 110 or may include the structure of the hardware platform 500. As illustrated, the hardware platform 500 may include additional components not shown, and that some of the components described may be removed and/or modified. For example, a computer system with multiple GPUs may be located on external-cloud platforms including Amazon® Web Services, or internal corporate cloud computing clusters, or organizational computing resources, and the like.
[0084] The hardware platform 500 may be a computer system such as the system 110 that may be used with the embodiments described herein. The computer system may represent a computational platform that includes components that may be in a server or another computer system. The computer system may execute, by the processor 505 (e.g., a single or multiple processors) or other hardware processing circuit, the methods, functions, and other processes described herein. These methods, functions, and other processes may be embodied as machine-readable instructions stored on a computer-readable medium, which may be non-transitory, such as hardware storage devices (e.g., RAM (random access memory), ROM (read-only memory), EPROM (erasable, programmable ROM), EEPROM (electrically erasable, programmable ROM), hard drives, and flash memory). The computer system may include the processor 505 that executes software instructions or code stored on a non-transitory computer-readable storage medium 510 to perform methods of the present disclosure. The software code includes, for example, instructions to gather data and documents and analyze documents. In an example, the modules 204, may be software codes or components performing these steps.
[0085] The instructions on the computer-readable storage medium 510 are read and stored the instructions in storage 515 or in random access memory (RAM). The storage 515 may provide a space for keeping static data where at least some instructions could be stored for later execution. The stored instructions may be further compiled to generate other representations of the instructions and dynamically stored in the RAM such as RAM 520. The processor 505 may read instructions from the RAM 520 and perform actions as instructed.
[0086] The computer system may further include the output device 525 to provide at least some of the results of the execution as output including, but not limited to, visual information to users, such as external agents. The output device 525 may include a display on computing devices and virtual reality glasses. For example, the display may be a mobile phone screen or a laptop screen. GUIs and/or text may be presented as an output on the display screen. The computer system may further include an input device 530 to provide a user or another device with mechanisms for entering data and/or otherwise interacting with the computer system. The input device 530 may include, for example, a keyboard, a keypad, a mouse, or a touchscreen. Each of these output devices 525 and input device 530 may be joined by one or more additional peripherals. For example, the output device 525 may be used to display the results such as bot responses by the executable chatbot.
[0087] A network communicator 535 may be provided to connect the computer system to a network and in turn to other devices connected to the network including other clients, servers, data stores, and interfaces, for instance. A network communicator 535 may include, for example, a network adapter such as a LAN adapter or a wireless adapter. The computer system may include a data sources interface 540 to access the data source 545. The data source 545 may be an information resource. As an example, a database of exceptions and rules may be provided as the data source 545. Moreover, knowledge repositories and curated data may be other examples of the data source 545.
[0088] While considerable emphasis has been placed herein on the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the invention. These and other changes in the preferred embodiments of the invention will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be implemented merely as illustrative of the invention and not as a limitation.

ADVANTAGES OF THE PRESENT DISCLOSURE
[0089] The present disclosure provides a method and a system for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment.
[0090] The present disclosure provides a method and a system for creating a pricing suite or a single dashboard application that helps in tracking all price and price drivers of one or more products.
[0091] The present disclosure provides a method and a system for providing the pricing-related drivers and dashboards such as, a price perception driver, a competitive pricing driver, an automated pricing driver, a markdown pricing driver, an incentive pricing driver, and a spend effectiveness driver.
[0092] The present disclosure provides a method and a system for real-time tracking of the price of one or more products, and to enable derived metrics such as a competitiveness of one or more products, offer adoption for one or more products, offer performance of one or more products, auto pricing of one or more products, price perception of one or more products, and price health of one or more products.
[0093] The present disclosure provides a method and a system for providing overview of one function impacting another function with respect to one or more pricing metrics. For instance, by using the e-commerce platform's price and competitors’ price, one can understand the offer-wise performance of sales, thereby providing an overview of the offer construct works best and under which competitive conditions.
[0094] The present disclosure provides a method and a system for tracking performance for different types of products by categorizing products into different tiers such as a head tier with top-selling products and a tail tier with low-selling products, which in turn enables running different price constructs.
[0095] The present disclosure provides a method and a system for providing an incentive pricing dashboard, which helps in addressing all the issues such as a bad discounting, and multiple offers running on a product, while keeping the price metrics in mind, thereby ensuring effective and efficient pricing for products on offer.
[0096] The present disclosure provides a method and a system for identifying old and obsolete products to provide more discounted prices and subsequently remove the old and obsolete products for providing space for fresh selection and inventory of new products.
 
, Claims:1. A method for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment, the method comprising:
generating, by a processor (112) associated with a system (110), a hive dataset for one or more price metrics corresponding to one or more products associated with an electronic commerce (e-commerce) environment;
transmitting, by the processor (112), the generated hive dataset to one or more Virtual Machines (VMs);
creating, by the processor (112), one or more pipelines corresponding to each of the one or more price metrics, from the hive dataset transmitted to the one or more VMs, wherein the one or more pipelines correspond to pricing-related drivers;
generating, by the processor (112), one or more insights and associated graphs for each of the one or more pipelines corresponding to each of the pricing-related drivers;
deriving, by the processor (112), one or more key action items impacting the one or more price metrics; and
outputting, by the processor (112), using a dashboarding tool, at least one of the one or more insights, the graphs, and the key action items in a workspace, for each of the pricing-related drivers.

2. The method as claimed in claim 1 further comprises:
categorizing, by the processor (112), the one or more products into a plurality of product tiers;
providing, by the processor (112), a plurality of price constructs for each of the plurality of product tiers, to run the plurality of price constructs in the e-commerce environment;
analyzing, by the processor (112), a spend effectiveness data and a price health data of the plurality of price construct, upon running the plurality of price constructs in the e-commerce environment; and
outputting, by the processor (112), a result of the analyzed spend effectiveness data and a price health data.

3. The method as claimed in claim 2, wherein the plurality of product tiers corresponds to at least one of a head product tier with top selling products and sellers in the e-commerce environment, and a tail product tier with least selling products and sellers in the e-commerce environment.

4. The method as claimed in claim 1, wherein the one or more price metrics corresponds to at least one of competitiveness of pricing for the one or more products, offer adoption for the one or more products, offer performance for the one or more products, auto pricing for the one or more products, price perception of a user (102) for the one or more products, and price health of the one or more products.

5. The method as claimed in claim 1, wherein the pricing-related drivers correspond to at least one of a price perception driver, a competitive pricing driver, an automated pricing driver, a markdown pricing driver, an incentive pricing driver, and a spend effectiveness driver.

6. A system (110) for monitoring at least one of a pricing and pricing-related drivers corresponding to a product in an electronic commerce (e-commerce) environment, the system (110) comprising:
a processor (112); and
a memory (116) coupled to the processor (112), wherein the memory (116) comprises processor-executable instructions, which on execution, cause the processor (112) to:
generate a hive dataset for one or more price metrics corresponding to one or more products associated with an electronic commerce (e-commerce) environment;
transmit the generated hive dataset to one or more Virtual Machines (VMs);
create one or more pipelines corresponding to each of the one or more price metrics, from the hive dataset transmitted to the one or more VMs, wherein the one or more pipelines correspond to pricing-related drivers;
generate one or more insights, and associated graphs for each of the one or more pipelines corresponding to each of the pricing-related drivers;
derive one or more key action items impacting the one or more price metrics; and
output, using a dashboarding tool, at least one of the one or more insights, the graphs, and the key action items in a workspace, for each of the pricing-related drivers.

7. The system (110) as claimed in claim 6, wherein the processor (112) is further configured to:
categorize the one or more products into a plurality of product tiers;
provide a plurality of price constructs for each of the plurality of product tiers, to run the plurality of price constructs in the e-commerce environment;
analyze a spend effectiveness data and a price health data of the plurality of price constructs, upon running the plurality of price constructs in the e-commerce environment; and
output a result of the analyzed spend effectiveness data and a price health data.

8. The system (110) as claimed in claim 7, wherein the plurality of product tiers corresponds to at least one of a head product tier with top selling products and sellers in the e-commerce environment, and a tail product tier with least selling products and sellers in the e-commerce environment.
9. The system (110) as claimed in claim 6, wherein the one or more price metrics corresponds to at least one of competitiveness of pricing for the one or more products, offers adoption for the one or more products, offers performance for the one or more products, auto pricing for the one or more products, price perception of a user (102) for the one or more products, and price health of the one or more products.

10. The system (110) as claimed in claim 6, wherein the pricing-related drivers correspond to at least one of a price perception driver, a competitive pricing driver, an automated pricing driver, a markdown pricing driver, an incentive pricing driver, and a spend effectiveness driver.