Description:Field of the Invention
[0001] Embodiments of the present invention relate to a field of secure communications platforms providing communication channels engaging in secure bidirectional communication, more specifically, relates to a method for conversational commerce platform for seamless user experience.
BACKGROUND
[0002] In recent years, conversational commerce has emerged as a significant trend in the e-commerce industry, revolutionizing the interaction with customers. In general, it refers to the use of messaging apps, chatbots, and other communication channels for transactions, customer support, and engaging users in personalized interactions.
[0003] Traditionally, various e-commerce platforms relied on regular web pages and standardized interfaces that allow browsing, purchasing, and handling customer inquiries. However, these traditional approaches often lack the interactivity and ability to provide instant responses. With the advent of natural language processing (NLP), machine learning, and artificial intelligence (AI), the conventional e-commerce platforms began adapting such technologies. Use of such technologies in customer interaction has been successful in creating dynamic, conversational experiences that to some extent may mimic human interactions.
[0004] Many of the e-commerce platforms have integrated chatbots and virtual assistants into messaging apps, websites, and social media platforms, to engage customers in real-time conversations, understand their buying preferences, and offer personalized recommendations. In particular, the currently available conversational commerce platforms have emerged as a powerful tool for driving customer engagement, increasing sales, and delivering personalized experiences in the digital marketplace. Thereby, providing e-commerce platforms an edge over the competitors.
[0005] Moreover, the currently available conversational commerce platforms using chatbots and virtual assistants integrate with various commonly used messaging apps and have capability of providing personalized recommendations, transactional processing, customer support, and so on. However, structuring such a conversation flow can have technical complexity, which can impose difficulty when an end user wishes to focus design resources on business-related, semantic aspects of the chatbot.
[0006] Further, chatbot and virtual assistant systems may also experience “fallout,” i.e., instances when the NLP algorithm does not succeed in matching the end user's utterance to an intent. Back-up techniques, such as asking the end user to rephrase a question, may result in an unpleasant user experience. A bad user experience may result when the NLP algorithm makes a wrong match. Without a continuous feeding/learning process to improve chatbot pattern matching, fallouts and wrong matches may reoccur, and user experiences may quickly deteriorate .
[0007] Other limitations associated with the currently available conversational commerce platforms include that the majority of the available conversational commerce platforms requires its customers to navigate complex menus or interfaces, which in turn make the shopping experience more complex. Further, many currently available conversational commerce platforms do not allow users to converse in natural language.
[0008] An emerging requirement from the conversational commerce platform is to efficiently assist the customer from the pre-purchase stage to post-purchase stage. This may allow users to have a more wholesome, hassle-free experience with real-time updates to enhance transparency and trust in the shopping process.
[0009] Thus, in light of the above-stated discussion, the present invention provides a chatbot system and method for conversational commerce platform and an open network for digital commerce (ONDC) platform for seamless shopping experience. The present chatbot system is more intuitive, personalized, and seamless and may be tailored to the needs and preferences of individual users making the shopping process more convenient and user-friendly by providing consistency and continuity in the shopping journey regardless of the channel used
SUMMARY OF THE INVENTION
[0010] In light of the above, in one aspect of the present disclosure, a computer-implemented method for seamless shopping experience on a conversational chatbot platform is disclosed herein. The method includes integrating the conversational chatbot platform within the open network for digital commerce (ONDC) ecosystem characterized in that:
initializing a query on the conversational chatbot platform installed on a user device via a plurality of channels by a user;
verifying the entered query on a channel from the plurality of channels installed on the user device via a processing assembly over a communication network;
determining if the query is a voice-based query or a text-based query, characterized in that the voice-based query being transmitted to a voice-based channel and subsequently converted to text via a voice-to-text engine before being transmitted to a text-based channel, and the text-based query being directly transmitted to a text-based channel;
transmitting the query in natural language to an artificial intelligence engine module associated with the processing assembly;
accessing a plurality of e-commerce platforms, an open network for digital commerce (ONDC) and validating the user’s identity by the artificial intelligence engine module;
transmitting a validation response to the artificial intelligence engine module upon successful user validation;
personalizing an output based on the validation response and the user queries within a channel from the plurality of channels being accessed to provide personalized and relevant product recommendations,
analysing and determining type of queries via the processing assembly for activating a pre-purchase module if the queries relate to product discovery, or activating a post-purchase module if the query relates to after sale and otherwise; and
providing real-time updates of the product to the users on the user device;
[0011] The conversational commerce platform is any conversational messaging platform.
[0012] In accordance with an embodiment of the present invention, the queries relate to product discovery, the method performs directing, by the pre-purchase module, the user to a product detail page on the user device.
[0013] In accordance with an embodiment of the present invention, the queries relate to product discovery, the method performs adding, by the pre-purchase module, a product to cart and activating a smart coupon module.
[0014] In accordance with an embodiment of the present invention, the queries relate to product discovery, the method generates an order for the product added in cart and provides a post-purchase coupon by a post-purchase coupon module.
[0015] In accordance with an embodiment of the present invention, the queries relate to product discovery, the method performs generating and sending via a payment module, a payment link to the user on the user device for a payment gateway to enable secure payment.
[0016] In accordance with an embodiment of the present invention, the queries relate to product discovery on the open network for digital commerce (ONDC) platform, the method performs tracking the product by the user on the user device upon successful payment.
[0017] In accordance with an embodiment of the present invention, the queries relate to product discovery, the method performs reviewing and rating the product purchased by the user from the e-commerce platforms.
[0018] In accordance with an embodiment of the present invention, the smart coupon module uses intent analysis before suggesting the discount coupons to the user and the post-purchase coupon module gives offer or a mix of offers such as, but not limited to, giving discount coupons for next purchase or giving points for the purchase for accumulating.
[0019] In accordance with an embodiment of the present invention, the method further comprises redirecting the user to track the product when the user selects status inquiry.
[0020] In accordance with an embodiment of the present invention, when the query relates to after sale the post-purchase module directs the user to post-purchase options like status of the product, order cancellations, product refunds, product returns, product ratings or any combination thereof.
[0021] In accordance with an embodiment of the present invention, the queries relating to product discovery includes a product search, a product enquiry, an order status or any combination thereof.
[0022] In accordance with an embodiment of the present invention, the artificial intelligence engine module comprises a protocol for validating and authenticating the user by using credentials provided by the user on the e- commerce platforms.
[0023] In accordance with an embodiment of the present invention, the artificial intelligence engine module comprises interpreting by the artificial intelligence engine module one or more natural language processing (NLP) algorithms to interpret the intent of the user and generate relevant responses.
[0024] In accordance with an embodiment of the present invention, the method comprises:
using the application programming interfaces (APIs) to access information including a vendor information and/or a product information on the conversational chatbot platform through an open network for digital commerce (ONDC) platform;
facilitating seamless browsing and purchasing of products to the users on the conversational chatbot platform the open network for digital commerce (ONDC) platform;
selecting outlets or vendors or e-commerce platforms for user action;
dynamically updating search results by analyzing the real-time response from the users; and
enabling the users to place simultaneous orders on different e-commerce platforms or vendors in a single transaction.
[0025] In accordance with an embodiment of the present invention, the method includes hyper-personalizing in a plurality of language based on the query.
[0026] In accordance with an embodiment of the present invention, the method includes identifying keywords in the query.
[0027] In accordance with an embodiment of the present invention, the method includes identifying meaning in unstructured and grammatically incorrect sentences.
[0028] In accordance with an embodiment of the present invention, the method further comprises ensuring by the conversational chatbot platform installed on a user device (302) a consistent omnichannel experience across a plurality of e-commerce platforms (324) or the open network for digital commerce (ONDC) platform.
[0029] In accordance with an embodiment of the present invention, the method further comprises offering by the open network for digital commerce (ONDC) platform or the open network for digital commerce (ONDC) platform a seamless access to vendor listings and product information, facilitating streamlined browsing and purchasing processes.
[0030] These and other advantages will be apparent from the present application of the embodiments described herein.
OBJECTIVES OF INVENTION
[0031] According to illustrative embodiments, the present disclosure focuses on a computer-implemented method for conversational commerce platform for seamless shopping experience which overcomes the above-mentioned disadvantages or provide the users with a useful or commercial choice.
[0032] The present disclosure solves all the above major limitations of a computer-implemented method for conversational commerce platform for seamless shopping experience. Further, the present disclosure ensures that the disclosed invention may fulfill following objectives.
[0033] The principal object of this invention is to provide a method for seamless shopping experience on e-commerce platforms or the ONDC (Open Network for Digital Commerce) platform.
[0034] Another objective is to provide a method for conversational chatbot to determine if the query is a voice-based query or a text-based query.
[0035] Yet another objective is to transmit voice-based query to a voice-based channel and subsequently convert to text via a voice-to-text engine before being transmitted to a text-based channel.
[0036] Yet another objective is to directly transmit text-based query to a text-based channel.
[0037] Yet another objective is to provide a method for conversational chatbot offering an omnichannel shopping experience.
[0038] Yet another objective of the present disclosure is to provide a method that allows users to browse and interact in natural language queries.
[0039] Yet another objective of the present disclosure is to provide a method that provides hyper-personalization and provides a tailored shopping experience.
[0040] Yet another objective of the present disclosure is to provide a method that streamlines the shopping process by handling all stages of the customer journey within the chatbot interface.
[0041] Yet another objective of the present disclosure is to provide a method that overcomes frequent switching between different platforms while online shopping.
[0042] Yet another objective of the present disclosure is to provide a method that overcomes the need for contacting customer service separately.
[0043] Yet another objective of the present disclosure is to provide a method that provides real-time updates on order status, delivery schedules, and product availability.
[0044] Yet another objective of the present disclosure is to provide a method that ensures transparency and enhances trust in the online shopping process.
[0045] Yet another objective of the present disclosure is to provide a method that leverages conversational Artificial Intelligence technologies for multilingual support.
BRIEF DESCRIPTION OF THE DRAWINGS
[0046] So that the manner in which the above recited features of the present invention is understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to embodiments, some of which are illustrated in the appended drawings.
[0047] FIG. 1 illustrating a method for seamless shopping experience, in accordance with an exemplary embodiment of the present disclosure;
[0048] FIG. 2 illustrating a computer-implemented method for seamless shopping experience, in accordance with an exemplary embodiment of the present disclosure; and
[0049] FIG. 3 illustrating a system for seamless shopping experience on a conversational chatbot platform, in accordance with an exemplary embodiment of the present disclosure.
DETAILED DESCRIPTION OF THE INVENTION
[0050] In the following detailed description numerous specific details are set forth in order to provide a thorough understanding of the embodiment of invention as illustrative or exemplary embodiments of the disclosure, specific embodiments in which the disclosure may be practiced are described in sufficient detail to enable those skilled in the art to practice the disclosed embodiments.
[0051] Conditional language used herein, such as, among others, "can," "may," "might," "may," “e.g.,” and the like, unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps.
[0052] A “chatbot platform or chatbot” is a computer program that simulates, as experienced by a user of an electronic communication device, e.g., a “smart phone” or laptop computer, a conversation with a human being. The chatbot provides a pleasant experience for the user, for example, a quick resolution of a customer question, or quick provision of a requested service. Further, the chatbot can be a business transaction, e.g., sale of a product or service.
[0053] Systems and methods disclosed herein can provide, among other technical features and benefits that will be appreciated by persons of ordinary skill upon reading this disclosure, the capability to readily construct a variety of chatbots, personalized by the chatbot system user to the system user's particular needs, and to the needs and preferences of the system user's customers, with or without detailed knowledge of natural language processing (NLP).
[0054] In some embodiments, systems and methods disclosed herein may also provide, among other technical features and benefits, a step-in chatbot assistant for live agents. The step-in chatbot assistant can bring machine learning to help improve the system’s accuracy in responding to customer queries, and can significantly shorten agent response time, with operations transparent to the customer and convenient for the live agent.
[0055] Systems and methods of the present invention provides a more tailored shopping experience through conversational commerce platforms, which may effectively provide hyper-personalized recommendations, there is a need for conversational commerce platforms that may allow users to access a wide variety of websites, mobile applications and messaging applications to ensure more consistency for users having access to diverse platforms.
[0056] Referring now to FIG. 1 to FIG. 3 to describe various exemplary embodiments of the present disclosure. FIG. 1 illustrating a method 100 for seamless shopping experience, in accordance with an exemplary embodiment of the present disclosure.
[0057] The chatbot is a conversational chatbot platform designed to interact with a plurality of users and facilitate their shopping experience on the e-commerce platforms or the Open Network for Digital Commerce (ONDC) platform. The method 100 may assist the users in various stages of the shopping journey, from pre-order inquiries to placing orders, tracking deliveries, handling returns, and providing customer support. It may leverage natural language processing (NLP) capabilities and integrate with the e-commerce platforms or the Open Network for Digital Commerce (ONDC) APIs.
[0058] The method 100 for seamless shopping experience on a conversational chatbot platform may comprise the following steps.
[0059] At 102, starting the conversational chatbot platform. At 104, selecting a channel from a plurality of channel 304. At 106, determining if the chat is text-based or voice based. At 108, initializing a voice-based channel 306 and converting audio/voice data to text data using voice-to-text engine 308, if the chat is voice-based. At 110, initializing a text-based channel 310, if the chat is text-based. At 112, transmitting text data to the Artificial Intelligence Engine Module 316 or AI engine. At 114, using e-commerce framework to validate users through transmitting and receiving validation response 336 from AI engine. At 116, personalizing the suggestions provided to the user. At 118, generation of queries such as, but not limited to, product search, enquiry, order status, order cancellation, refund, and return.
[0060] At 120, determining if the query is about product discovery. At 122, initiating a pre-purchase module 318, if the query is about product discovery. At, 124, redirecting to the product detail page. At 126, opening the cart. At 128, initiating a smart coupon module 328. At 130, order generation. At 132, initiating a post-purchase coupon module 330. At 134, initiating a payment module 326. At 136, initiating tracking. At 138, enabling reviews and ratings. At 140, initiating a post-purchase module 320, if the query is not about product discovery. At 142, order cancellation and returning to the payment module 326. At 144, checking status and redirecting to tracking. At 146, reloading and returning to the payment module 326. At 148, providing ratings by the user and redirecting to reviews and ratings. At 150, logout/quit/close the conversational chatbot platform.
[0061] The method 100 may provide the users with a consistent and seamless shopping experience across various messaging platforms. The method 100 may involve novel approaches to user interface design, data synchronization, and customer engagement. Implementing omnichannel capabilities that ensure continuity and convenience for users might not be obvious without significant innovation.
[0062] In an exemplary embodiment, the method 100 may have ability to handle post-purchase interactions, such as order tracking, returns, and customer support, and may involve complex backend integrations and business logic. The method 100 may allow the user to manage their orders and resolve issues efficiently through conversational interactions to streamline processes and enhance user satisfaction.
[0063] FIG. 2 illustrates a flowchart showcasing steps of a computer-implemented method 200 for seamless shopping experience on a conversational chatbot platform. The method 200 wherein the conversational commerce platform may be any conversational messaging platform and the method 200 may comprise following steps.
[0064] At 204, initializing a query on the conversational chatbot platform installed on a user device 302 via a plurality of channels 304 by a user.
[0065] At 206, verifying the entered query on a channel from the plurality of channels 304 installed on the user device 302 via a processing assembly 314 over a communication network 312.
[0066] At 208, determining if the query is a voice-based query 332 or a text-based query 334, characterized in that the voice-based query 332 being transmitted to a voice-based channel 306 and subsequently converted to text via a voice-to-text engine 308 before being transmitted to a text-based channel 310, and the text-based query 334 being directly transmitted to a text-based channel 310.
[0067] At 210, transmitting the query in natural language to an artificial intelligence engine module 316 associated with the processing assembly 314.
[0068] At 212, accessing a plurality of e-commerce platforms 324, the open network for digital commerce (ONDC) platform and validating the user’s identity by the artificial intelligence engine module 316.
[0069] At 214, transmitting a validation response 336 to the artificial intelligence engine module 316 upon successful user validation.
[0070] At 216, personalizing an output based on the validation response 336 attained from the e-commerce platforms or the open network for digital commerce (ONDC) platform and the user queries within a channel from the plurality of channels 304 being accessed to provide personalized and relevant product recommendations.
[0071] In particular, the user queries may be in natural language relate to a plurality of domains including, but not limited to, product search, enquiry, order status, order cancellation, refund, and return. In a preferred embodiment, user queries in multiple languages are supported.
[0072] At 218, analyzing and determining type of queries via the processing assembly 314 for activating a pre-purchase module 318 if the queries relate to product discovery, or activating a post-purchase module 320 if the query relates to after sale and otherwise.
[0073] At 220, providing real-time updates of the product to the users on the user device 302.
[0074] In a preferred embodiment, the conversational commerce platform may be any conversational messaging platform comprising but not limited to WhatsApp messenger.
[0075] Alternative embodiment may include a Facebook messenger or any messaging platform.
[0076] When the queries relate to product discovery the method 200 may perform directing, by the pre-purchase module 318, the user to a product detail page on the user device 302.
[0077] When the queries relate to product discovery the method 200 may perform adding, by the pre-purchase module 318, a product to cart and activating a smart coupon module 328.
[0078] When the queries relate to product discovery on the e-commerce platforms or the open network for digital commerce (ONDC) platform, the method 200 may perform generating, an order for the product added in cart. Further, the method may comprise providing a post-purchase coupon by a post-purchase coupon module 330.
[0079] When the queries relate to product discovery the method 200 may perform generating and sending via a payment module 326, a payment link to the user on the user device 302 for a payment gateway to enable secure payment.
[0080] When the queries relate to product discovery the method 200 may perform tracking the product by the user on the user device 302 upon successful payment.
[0081] When the queries relate to product discovery on the e-commerce platforms or the open network for digital commerce (ONDC) platform and add the product to the cart, if the user end up buying the product, the method 200 may perform reviewing and rating of the purchased product by the user from the e-commerce platforms 324.
[0082] The smart coupon module 328 may use intent analysis before suggesting the discount coupons to the user and the post-purchase coupon module 330 gives an offer or a mix of offers such as, but not limited to, giving discount coupons for next purchase or giving points for the purchase for accumulating. In an embodiment, the pre-purchase module 318 provides a plurality of discount coupons to the user based on a plurality of parameters which may further comprise discount coupons based on product buying behavior, discounts based on historical data, and so forth.
[0083] The method 200 may further comprise redirecting the user to track the product when the user selects status inquiry.
[0084] When the query may relate to after sale the post-purchase module 320 directs the user to post-purchase options like status of the product, order cancellations, product refunds, product returns, product ratings or any combination thereof.
[0085] The queries may include a product discovery, a product search, a product enquiry, an order status and so forth.
[0086] The artificial intelligence engine module 316 may comprise a protocol for validating and authenticating the user by using credentials provided by the user on the e- commerce platforms 324.
[0087] The artificial intelligence engine module 316 may comprise interpreting by the artificial intelligence engine module 316 one or more natural language processing NLP algorithms to interpret the intent of the user and generate relevant responses.
[0088] The method 200 may comprise using the application programming interfaces (APIs) to access information including a vendor information and/or a product information on the conversational chatbot platform through the e-commerce platforms or the open network for digital commerce (ONDC) platform 324.
[0089] The method 200 may comprise selecting outlets or vendors or e-commerce platforms 324 for user action.
[0090] The method 200 may comprise dynamically updating search results by analyzing the real-time response from the users.
[0091] The method 200 may comprise enabling the users to place simultaneous orders on different e-commerce platforms 324 or vendors in a single transaction.
[0092] The method 200 may include hyper-personalizing in a plurality of language based on the query.
[0093] The method 200 may include identifying keywords in the query.
[0094] The method 200 may include identifying meaning in unstructured and grammatically incorrect sentences.
[0095] The method 200 may further comprise ensuring by the conversational chatbot platform installed on a user device (302) a consistent omnichannel experience across a plurality of e-commerce platforms (324) or the open network for digital commerce (ONDC) platform.
[0096] The method 200 may further comprise offering, by the e-commerce platforms or the open network for digital commerce (ONDC) platform, seamless access to vendor listings and product information, facilitating streamlined browsing and purchasing processes. The method 200 may facilitate seamless integration with the e-commerce platforms 114 or the ONDC platform to enable effortless interactions with the ONDC API for a cohesive shopping experience.
[0097] FIG. 3 illustrates a block diagram for a system 300 for seamless shopping experience on a conversational chatbot platform titled ‘Ukti’, in accordance with an exemplary embodiment of the present disclosure.
[0098] The system 300 may comprise a user device 302, a plurality of channel 304, a voice-based channel 306, a voice-to-text engine 308, a text-based channel 310, a communication network 312, a processing assembly 314, an artificial intelligence engine module 316, a pre-purchase module 318, a post-purchase module 320, a plurality of natural language processing (NLP) module 322, a plurality of e-commerce platform 324, a payment module 326, a smart coupon module 328, a post-purchase coupon module 330, a voice based query 332, a text based query 334, and a validation response 336.
[0099] The user device 302 may be a desktop computer, a laptop computer, a user computer, a tablet computer, a personal digital assistant (PDA), a cellular telephone, a communication network appliance, a camera, a smartphone, an enhanced general packet radio service (EGPRS) mobile phone, a media player, a navigation device, an email device, a game console, or a combination of any these data processing devices or any other data processing devices.
[00100] According to an embodiment of the present invention, the user device 302 comprises a graphical user interface, a memory, a processor, and an application console. The user device 302 may be configured to enable the user to receive data and transmit data within the system 300. Further, the users of the user device 302 may be any individual, customer, buyer or group of individuals/ customers/buyers and the like.
[00101] In different embodiments, the system 300 consists of a plurality of user devices 302a-302n. The user device 302 may have an interactive feature that aids in establishing bi-lateral communication with the user. Embodiments of the present invention are intended to include or otherwise cover any type of the graphical user interface including known, related art, and/or later developed technologies. The graphical user interface may be further configured to display output data associated with system 300, allow users to input instructions, and display responses and results. Further, the graphical user interface may be, but is not limited to, a digital display, a touch screen display, and so forth.
[00102] The memory may use one or more non-transitory computer-readable storage having computer readable instructions stored thereon. The memory may be operable to store credentials relating to the registered user. In some embodiments, the memory may be a Read Only Memory (ROM), a Random-Access Memory (RAM), an erasable programmable read only memory (EPROM), an electrically erasable programmable read only memory (EEPROM), a hard disk, a removable media drive for handling memory cards including known, related art, and/or later developed technologies. Further, the memory may be another type of dynamic storage device that stores information and instructions for execution by the processor. The memory also stores temporary variables and other intermediate information used during execution of the instructions by the processor.
[00103] The processor may process any input data provided in a prescribed manner. The processor may have any computational module, such as, but not limited to, a microprocessor, a microcontroller, or any other type of processor or a combination thereof.
[00104] In an embodiment of the present invention, the processor is any well-known processor, such as processors from Intel Corporation. Alternatively, in another embodiment, the processor is a dedicated controller such as an ASIC. Similarly, in yet another embodiment, the user device 302 may include a processing unit comprising a collection of processors which may or may not operate in parallel.
[00105] In accordance with an embodiment of the present invention, the instructions may be any set of instructions to be executed directly (such as machine code) or indirectly (such as scripts) by the processor. In that regard, the terms “instructions,” and “steps” may be used interchangeably herein.
[00106] In alternative embodiments, the user device 302 may also include a Global Positioning System (GPS) module to track location of the user.
[00107] In a preferred embodiment the user device 302 may receive input in text form and receive input in audio form the user. The user device 302 may allow the users access to multiple messaging platforms. Further, the user device 302 may allow the users to scan from their preferred platform, ensuring continuity in their shopping journey. The user device 302 may be integrated with any messaging application including, existing, prior art, or later developed application or technology.
[00108] In some embodiments, the user device 302 may use frontend technologies such as, but not limited to, React, Swift, and Flutter for building responsive and interactive interfaces across different platforms. The user device 302 may be capable of handling various types of the user input, including text entry, selection from dropdown menus or checkboxes, button clicks, and more. The user device 302 may be capable of validating the credential of the user. The user device 302 may enable hyper-personalization, conversing in a plurality of language, identification of keywords, and identification of meaning in unstructured and grammatically incorrect sentence query.
[00109] The channels 304 may be integrated in the user device 302 and the channels 304 allows interaction with various platforms such as, but not limited to websites, mobile applications, or messaging applications. This ensures consistency, continuity, and convenience in the shopping journey, regardless of the user's preferred channel.
[00110] The voice-based channel 306 may receive voice-based query 332 from channel 304. In a preferred embodiment, the voice-based channel 306 may act as a voice input interface. In an exemplary embodiment, the user may interact with the system 300 by speaking their queries into a microphone. This interface can be integrated into various user devices 302, including, but not limited to, smartphones, smart speakers, or dedicated hardware devices.
[00111] In accordance with an embodiment of the present invention, the voice-based channel 306 may link to the communication network 312.
[00112] The voice-to-text engine 308 may receive voice-based input from the voice-based channel 306. The voice-to-text engine 308 may convert the voice-based query 332 to a text-based query 334. In some embodiments, automatic speech recognition (ASR) technology may be used for conversion. The ASR may analyze the audio or voice input and transcribe it into text data.
[00113] In accordance with an embodiment of the present invention, the voice-to-text engine 308 may employ Natural Language Understanding algorithms enabling hyper-personalization, conversing in a plurality of language, translating in a plurality of languages, identification of keywords, and identification of meaning in unstructured and grammatically incorrect sentence query.
[00114] The text-based channel 310 may receive text-based query 334 from channel 304 and receive input from the voice-to-text engine 308. The text-based channel 310 may receive input as text form of the voice-based query 332, as converted by the voice-to-text engine 308.
[00115] The communication network 312 may be linked to the user device 302 and the communication network 312 configured to provide internet connectivity. The communication network 312 may employ any communication technologies including existing, prior art and later developed technologies.
[00116] The communication network 312 include, but not limited to, a large computer communication network, Internet, wireless networks, local area communication network (LAN), wide area communication network (WAN), private networks, a cellular communication network, corporate network having one or more wireless access points or a combination thereof connecting any number of mobile clients, fixed clients, and servers and so forth. Examples of communication network 312 may include the Internet, a WI-FI connection, a Bluetooth connection, a Zigbee connection, a communication network, a wireless communication network, a 3G communication network, a 4G communication network, a 5G communication network, a USB connection, or any combination thereof any transceiver, or any combination thereof by triangulation, by a local positioning (LPS) device, by a global positioning system (GPS), or by any combination thereof.
[00117] In accordance with another embodiment, the communication may be based through sound-based communication such as but not limited to tone tag. Embodiments of the present invention are intended to include or otherwise cover any type of communication, including known, related art, and/or later developed technologies. Alternatively, the communication network 312 may be a decentralized network/ centralized network. In particular, the decentralized network may be a decentralized blockchain network/ centralized blockchain network.
[00118] In yet alternative embodiments, the communication network 312 may be capable of connecting to external computing resources.
[00119] The processing assembly 314 may be integrated with the artificial intelligence (AI) engine module 316, the pre-purchase module 318, the post-purchase module 320, and the plurality of natural language processing (NLP) module 322.
[00120] The processing assembly 314 may be operable to leverage user data, browsing history, and past purchases to suggest relevant products, promotions, or deals to users, enhancing personalization, and highlighting opportunities. The processing assembly 314 may be operable to ensure interoperability and seamless integration with a plurality of platforms and services.
[00121] In some embodiments, the processing assembly 314 may support cross-platform compatibility, enabling the users to access through a plurality of platform or device. Additionally, the system 300 may have integrated APIs that allow interaction with different platforms. In a preferred embodiment, the processing assembly 314 may perform data transformation to harmonize data collected from various platforms to enhance the user experience.
[00122] In an embodiment of the present disclosure, the processing assembly 314 may integrate various services within the open network for digital commerce (ONDC) ecosystem, such as, but not limited to, logistics providers, inventory systems, and customer support platforms. The processing assembly 314 may incorporate analytics and machine learning algorithms to gather insights from user interactions and improve its recommendation engine over time. This involves technologies for data analytics including, but not limited to, Apache Spark or TensorFlow, to analyze user behavior and preferences.
[00123] The processing assembly 314 may leverage cloud computing services, such as, but not limited to, Amazon Web Services (AWS) or Microsoft Azure, for hosting its infrastructure and ensuring scalability and availability. Cloud services provide the flexibility to scale resources based on demand and optimize costs.
[00124] The processing assembly 314 may also gain real-time insights into user behavior, which enables the system 300 to change recommendations as per the changes detected in the user behavior and preferences. The processing module 314 may aid in scalability of the system 300 and make it capable of handling large traffic, maintain integrity of the data, and seamless availability to the user.
[00125] The artificial intelligence engine module 316 may be integrated with the processing assembly 314 and the artificial intelligence engine module 308 configured to access a plurality of e-commerce platforms 324. The artificial intelligence engine module 316 may offer personalized recommendations and assistance based on user preferences and past interactions, which enhances the relevance of product suggestions and improves overall user satisfaction.
[00126] In some embodiments, the artificial intelligence engine module 316 may continuously learn from user interactions and feedback, as well as from the data gathered from the e-commerce platforms 324. The artificial intelligence engine module 316 may improve its recommendations and decision-making capabilities over time, providing users with increasingly relevant and tailored approaches.
[00127] The artificial intelligence engine module 316 can be configured to provide, on the user device 302, for entry of intents and, associated with each intent, a response, and customer expressions. The artificial intelligence engine module 316 applies stemming to the customer expressions.
[00128] In alternative embodiments, the artificial intelligence engine module 316 can be coupled to an artificial intelligence (AI) connector platform. The AI connector platform can include an NLP core and Application Connectors. Features of the NLP core of the AI connector platform can include a library of interfaces and protocol translation applications, for each of the different NLP engines. In an aspect, the interfaces and protocol translation applications provided by the NLP core can be configured to present chatbot conversations with a generic interface that conversation controllers, such as the conversation controllers can consume without consideration of which NLP engine is being applied. The Application Connectors can provide interface, for example, through a channel integration platform, to one or more chatbot channels, such as a customer browser accessible web site, or a social media page or other messaging account collectively referenced herein, for brevity, as “chatbot channels.” Features of the application connectors can include provision of a middle-tier layer to account for channel specific nuances, e.g., various particularities of different chatbot channels.
[00129] From a technical user's perspective, Application Connectors can be tools for front-end integration, and the NLP core can be a tool for backend integration. The AI connector platform can interface, for example, through an NLP plug-in, to one or to a plurality of the NLP engines.
[00130] Further, the artificial intelligence engine module 316 may include a protocol for validating and authenticating the user/s’ using credentials provided by the user through the user device 302. The artificial intelligence engine module 316 may include natural language processing (NLP) algorithms to interpret the user’ intent and generate relevant responses.
[00131] In accordance with an embodiment of the present invention, the user device 302 may allow the user to interact using natural language queries and assessing and responding to the user queries in natural language by an artificial intelligence engine module (316), using the application programming interfaces (APIs) to access vendor and product information through the e-commerce platforms 324 or an open network for digital commerce (ONDC) platform module, facilitating seamless browsing and purchasing of products available on the e-commerce platforms or the open network for digital commerce (ONDC) platform, initiating search for the user queries with respect to the relevant domain.
[00132] The pre-purchase module 318 may include pre-purchase actions such as, but not limited to, redirecting the user to the product detail page.
[00133] This may enable users to discover products based on tailored requirements represents an innovative departure from traditional browsing methods and could contribute to its non-obviousness. The user may initiate product discovery by specifying their criteria, such as price, delivery cost, time slot preferences, and so forth that may obtain personalized product recommendations based on these criteria that may aid the users to find the most suitable options.
[00134] The post-purchase module 320 may include post-purchase actions such as, but not limited to, return, refunds, and customer service enquiry.
[00135] In a preferred embodiment, post-purchase action may be performed by integrating complex backend analytics and business logic. It may allow the vendors to manage their orders and resolve issues efficiently through conversational interactions to streamline processes and enhance user satisfaction. It may allow the user to track their orders, receive notifications, and stay informed throughout the entire process.
[00136] In a preferred embodiment, the users may be able to switch the pre-order inquiries to post-purchase support to complete transactions and access assistance without having to switch between different platforms or contact customer service separately.
[00137] The natural language processing (NLP) module 322 may employ a plurality of natural language processing (NLP) algorithms. The NLP algorithms may identify specific entities mentioned in the user queries, such as, but not limited to, product names, categories, or user details. In particular, the natural language processing (NLP) algorithms may provide the ability to understand the user queries, preferences, and intent. The natural language processing (NLP) algorithms may involve a plurality of sophisticated algorithms and techniques.
[00138] In an embodiment of the present disclosure, the natural language processing (NLP) algorithms may enable effectively interpreting and responding to the user inquiries in a conversational manner, particularly within the context of unique product discovery criteria. The product discovery may specify specific criteria such as but not limited to price, delivery cost, and time slot preferences, introducing a novel dimension to the shopping experience. In some embodiment, the natural language processing (NLP) algorithms may potentially be powered by ChatGPT APIs,
[00139] The processing assembly 314 may use a robust backend infrastructure to handle various aspects of the shopping process, including, but not limited to, order management, inventory tracking, and user authentication. In an embodiment of the present disclosure, the backend infrastructure may ensure orders are accurately recorded, and tracked. The backend infrastructure may be built using technologies comprising Node.js, Python, MongoDB, Kafka or any similar technologies to ensure scalability, reliability, and performance.
[00140] In some embodiments, the backend infrastructure may integrate with external systems and services, such as third-party APIs for shipping, product recommendations, or marketing tools. The backend infrastructure facilitates seamless communication and data exchange between the backend module and external systems. The backend infrastructure may handle aspects of the shopping process, including, but not limited to, order management, inventory tracking, and user authentication. The backend infrastructure may employ machine learning algorithms to gather insights from user interactions and improve recommendations.
[00141] The e-commerce platform 324 may transmit and receive a validation response 336 from the artificial intelligence engine module 316. The validation response 336 may be utilized for verifying user credentials on the e-commerce platform 324. In a preferred embodiment, the e-commerce platform 324 may encompass various e-commerce frameworks.
[00142] In an embodiment of the present disclosure, the e-commerce platform 324 may provide options for selecting outlets or vendors or e-commerce platforms for the action of the users, dynamically updating search results on analyzing the real-time response from the users, enabling the users to place simultaneous orders on different e-commerce platforms 324 or vendors in a single transaction.
[00143] The payment module 326 may be linked to the processing assembly 314 and the communication network 312. The payment module 316 may be enabled to complete the user action (purchase of product/service/goods). In particular, the payment module 326 generates and sends payment links to the customer on the desired payment gateway to enable secure payment. In a preferred embodiment, the payment module 326 may authenticate the credentials of the user via the payment generated.
[00144] In accordance with an embodiment of the present invention, the payment module 326 is configured to display a plurality of payment methods to make payment. The payment may be done through any payment methods selected from internet banking, a debit card payment, a credit card payment, a digital wallet or a unified payment interface (UPI) and similar payment methods. In particular, the user may save one or more bank accounts including Name of the Account Holder, Bank Name, Sort Code, IFSC Code, Bank address, CIF number, a five-digit branch code, country code, registered mobile number and similar details. Alternatively, the user may save one or more card details including Card Name, Card Number, Expiry Date and CVV and alike details for fast payment. Moreover, the user selects any one of the debit cards and credit cards as a primary card for payments. Subsequently, the user deletes bank details or card details of any one of the saved bank accounts, or saved debit cards or saved credit cards at any time. Alternatively, the payment transaction may be facilitated by scanning the QR code.
[00145] The smart coupon module 328 may be linked to the processing assembly 314 and the smart coupon module 328 may generate coupons during checkout. The smart coupon module 328 may use intent analysis before suggesting the discount coupons to the user. In a preferred embodiment, the smart coupon module 328 may leverage analytics and machine learning to predict the intent of the user and analyze the past transaction and browsing history of the user.
[00146] In some embodiments, the smart coupon module 328 may deliver personalized offers based on the user’s purchase history, preferences, or analyzed intent of purchase. This hyper-personalization helps make the offer more relevant and enticing to the individual user.
[00147] The post-purchase coupon module 330 may be linked to the processing assembly 314 and the post-purchase coupon module 330 may generate coupons during checkout.
[00148] In a preferred embodiment, the post-purchase coupon module 330 may offer discounts, promotions, coupons or loyalty points to the user after they have completed a purchase. The post-purchase coupon module 330 may be aimed at encouraging repeat purchases, increasing customer loyalty, and driving additional revenue. After a user completes a purchase on any e-commerce platform 324, the post-purchase coupon module 330 is triggered to display a special offer or coupon code to the user. This trigger may occur, but not limited to, on the order confirmation page, in a follow-up email, or through a pop-up notification. The users may redeem the coupon code or discount offer during checkout on their next purchase.
[00149] In a preferred embodiment, the smart coupon module 338 and the post-purchase coupon module 330 may generate a unique coupon code. This code is typically displayed on the screen or included in the email notification sent to the customer. In an embodiment of the present disclosure, the smart coupon module 338 and the post-purchase coupon module 330 may provide details about the offer, including any terms and conditions, expiration date, and eligible products or categories. Clear and concise information helps ensure that customers understand how to redeem the offer.
[00150] In an embodiment of the present disclosure, the e-commerce platform 324 may be configured to recognize and apply the discount automatically when the user enters the coupon code or meets the criteria for the offer.
[00151] In a preferred embodiment, the system 300 may incorporate security by implementing SSL encryption for secure communication between users and the server. This ensures the protection of sensitive information and enhances trust in the platform. In a preferred embodiment, the chatbot system 300 may allow users to have the option to escalate queries to human agents for additional support. This feature provides users with the flexibility to seek assistance from customer service representatives when needed. In some embodiments, any other suitable security measure for ensuring data privacy and access control.
[00152] In some embodiments, the system 300 may have versatility to extend beyond its core functionalities, offering potential for alternative embodiments, variants, add-ons, and accessories to further enhance the user experience within the ONDC ecosystem.
[00153] In some embodiments, the system 300 may be a specialized version tailored to specific industries or use cases, such as, but not limited to, fashion, electronics, or groceries. Each variant may offer unique features and functionalities tailored to the needs of its target audience, providing a more tailored shopping experience.
[00154] In some embodiments, the system 300 may include a voice recognition technology add-on, allowing users to interact through voice commands. This hands-free experience would cater to users who prefer voice interactions or have accessibility needs, expanding reach and usability.
[00155] In some embodiments, the system 300 may offer personalized subscription services, recommending products based on users' preferences and automatically replenishing essentials such as groceries or household items on a recurring basis. This subscription model would streamline the shopping process and ensure convenience for users.
[00156] The system 300 may have omnichannel capabilities that ensure continuity and convenience for users and provide data effective synchronization and customer engagement. The system 300 may be intuitive and user-friendly, which eliminates the need for complex menus or interfaces. The system 300 may allow users to select their desired products and place orders directly.
[00157] The system 300 may facilitate the entire transaction process, from adding items to the cart to making payments and confirming orders. The system 300 may provide real-time updates on order status, allowing users to track their orders throughout the delivery process. This feature enhances transparency and keeps users informed about the progress of their purchases.
[00158] The system 300 may leverage the e-commerce platforms 324 or the ONDC platform API to list vendors and their products. Users may browse through a wide range of products available on the platform, enhancing their choices and shopping experience. The system 300 may allow the user to directly place an order. The system 300 may facilitate the entire transaction process, from adding items to the cart to making payments and confirming orders.
[00159] In an alternate embodiment, In particular, the e-commerce platforms or the open network for digital commerce (ONDC) platform may be capable of ensuring a consistent omnichannel experience across various platforms, including websites, mobile apps, and messaging applications. Further, the open network for the e-commerce platforms or digital commerce (ONDC) platform may be capable of offering seamless access to vendor listings and product information, facilitating streamlined browsing and purchasing processes. Further, the e-commerce platforms or the open network for digital commerce (ONDC) platform may perform seamless integration with the other open network for digital commerce (ONDC) platform and allow effortless interaction with the ONDC APIs providing a cohesive shopping experience could require innovative approaches and technical expertise.
[00160] In an alternative exemplary embodiment, the user may simultaneously place orders for a plurality of orders comprises grocery items, food items, dishes or any other products together from different e-commerce platforms or vendors in a single transaction.
[00161] At 120, the user responses are evaluated to determine a preferred manner to proceed with the action path for product discovery including either pre-purchase actions or post-purchase actions
[00162] In an alternative exemplary embodiment, the method may comprise steps of requesting the conversational chatbot platform to add one or more users to a conversation chat creating a group chat wherein the request is initiated a buyer, sending an invitation by the conversational chatbot platform to the one or more users to join the group chat;`wherein on the group chat the buyer can ask for information relating to product information, product recommendations, payment options and alike information. The conversational chatbot platform acts as a service provider where multiple users can view products and have a conversation simultaneously.
[00163] In an alternative exemplary embodiment, the method may include steps of requesting by the user to transfer the chat to a support person. In particular, the conversational chatbot platform creates a group chat between the user, human agent and the conversational chatbot platform. Moreover, in that the conversational chatbot platform goes into an inactive state when the support person is active in the group chat, and when the support person or the user leaves the group chat the conversational chatbot platform becomes active to self learn and update user intent user preferences, providing the personalized recommendations.
[00164] Advantageously, the system 300 is a cutting-edge conversational commerce platform revolutionizing the shopping experience within the e-commerce platforms or the Open Network for Digital Commerce (ONDC) ecosystem. “Ukti” enables users to interact naturally, using natural language queries to discover and purchase products effortlessly. Leveraging advanced natural language processing (NLP) algorithms through the artificial intelligence engine module 316, The system 300 understands user preferences and provides personalized product recommendations, enhancing the relevance of search results.
[00165] Key advantages of the system 300 includes being a conversational interface, allowing them to browse and purchase products using natural language queries, which may eliminate the need to navigate through complex menus or interfaces, making the shopping process more convenient and user-friendly.
[00166] Another advantage is hyper-personalities, it understands and interprets user preferences and allows it to offer more tailored product recommendations. This may help the users in discovering the relevant products more efficiently, leading to a more tailored shopping experience.
[00167] Yet another advantage is the omnichannel experience may allow the user to search on a single application rather than going on multiple mobile applications, websites and multiple e-commerce platforms, which may ensure consistency and continuity in the shopping journey, regardless of the user's preferred channel.
[00168] The system 300 advantageously streamline the shopping process by handling all stages of the customer journey within the chatbot interface. From pre-order inquiries to post-purchase support, users can complete transactions and access assistance without having to switch between different platforms or contact customer service separately. It may provide users with real-time updates on order status, delivery schedules, and product availability, enhancing transparency and trust in the shopping process. Users may track their orders, receive notifications, and stay informed throughout the entire process.

, Claims:1. A computer-implemented method (200) for seamless shopping experience on a conversational chatbot platform within an open network for digital commerce (ONDC) ecosystem by providing pre purchase and post purchase assistance to an user comprising steps of:
integrating the conversational chatbot platform within the open network for digital commerce (ONDC) ecosystem with one or more open network for digital commerce (ONDC) platforms characterized in that:
initializing a query on the conversational chatbot platform installed on a user device (302) via a plurality of channels (304) by the user;
verifying the entered query on a channel from the plurality of channels (304) installed on the user device (302) via a processing assembly (314) over a communication network (312);
determining if the query is a voice-based query (332) or a text-based query (334), characterized in that the voice-based query (332) being transmitted to a voice-based channel (306) and subsequently converted to text via a voice-to-text engine (308) before being transmitted to a text-based channel (310), and the text-based query (334) being directly transmitted to a text-based channel (310);
transmitting the query in natural language to an artificial intelligence engine module (316) associated with the processing assembly (314);
accessing a plurality of e-commerce platforms (324), the open network for digital commerce (ONDC) platforms from the conversational chatbot platform and validating the user’s identity by the artificial intelligence engine module (316);
transmitting a validation response (336) to the artificial intelligence engine module (316) upon successful user validation;
personalizing an output based on the validation response (336) and the user queries within a channel from the plurality of channels (304) being accessed to provide personalized and relevant product recommendations;
analyzing and determining type of queries via the processing assembly (314) for activating a pre-purchase module (318) if the queries relate to product discovery, or activating a post-purchase module (320) if the query relates to after sale and otherwise; and
providing real-time updates of the product to the users on the user device (302);
enabling the users to place simultaneous orders on the e-commerce platforms (324) and/or the open network for digital commerce (ONDC) platform (324) in a single transaction; and
wherein the conversational chatbot platform is any conversational commerce messaging platform.
2. The method (200) as claimed in claim 1, wherein when the queries relate to product discovery the method (200) performs:
directing, by the pre-purchase module (318), the user to a product detail page on the user device (302);
adding, by the pre-purchase module (318), a product to cart and activating a smart coupon module (328);
generating, an order for the product added in cart and provide a post-purchase coupon by a post-purchase coupon module (330);
generating and sending via a payment module (326), a payment link to the user on the user device (302) for a payment gateway to enable secure payment;
tracking the product by the user on the user device (302) upon successful payment or when the user selects an option of status inquiry; and
reviewing and rating the product purchased by the user from the e-commerce platforms (324);
wherein the conversational chatbot platform is configured to hyper-personalize in a plurality of language based on the query; and/or identify keywords in the query; and/or identify meaning in unstructured and grammatically incorrect sentence query.
.
3. The method (200) as claimed in claim 1, wherein the smart coupon module (328) uses intent analysis and suggests one or more discount coupons to the user during pre purchase and the post-purchase coupon module (330) gives an offer or a mix of offers having future discount coupons, reward points for the purchase done and alike offers after the purchase.
4. The method (200) as claimed in claim 1, wherein when the query relates to after sale the post-purchase module (320) directs the user to post-purchase options like status of the product, order cancellations, product refunds, product returns, product ratings or any combination thereof.
5. The method (200) as claimed in claim 1, wherein queries relating to product discovery includes a product search, a product enquiry, an order status or any combination thereof.
6. The method (200) as claimed in claim 1, wherein the artificial intelligence engine module (316) comprises:
protocol for validating and authenticating the user by using credentials provided by the user on the e- commerce platforms (324); and
interpreting by the artificial intelligence engine module (316) one or more natural language processing (NLP) algorithms to interpret the intent of the user and generate relevant responses.
7. The method (200) as claimed in claim 1, wherein the method (200) comprises:
using the application programming interfaces (APIs) to access information including a vendor information and/or a product information on the conversational chatbot platform through the e-commerce platforms or an open network for digital commerce (ONDC) platform;
facilitating seamless browsing and purchasing of products to the users on the conversational chatbot platform, the e-commerce platforms or the open network for digital commerce (ONDC) platform;
selecting outlets or vendors or e-commerce platforms (324) for user action;
dynamically updating search results by analyzing the real-time response from the users;
8. The method (200) as claimed in claim 1, wherein the method (200) further comprises:
understanding by the conversational chatbot platform, user intent, user preferences, providing the personalized recommendations;
incorporating by the conversational chatbot platform, insights gained by a backend module for improved intent analysis of the user;
incorporating by the conversational chatbot platform, the analytics to continuously improve its recommendations, delivering tailored and relevant product suggestions;
wherein the conversational chatbot platform ensures a consistent omnichannel experience across a plurality of e-commerce platforms (324) or the open network for digital commerce (ONDC) platform; and offers integration of the plurality of e-commerce platforms (324) or the open network for digital commerce (ONDC) platform facilitating a seamless and streamlined browsing and pre purchasing process and post purchasing process.
9. The method (200) as claimed in claim 1, wherein the method (200) further comprises:
requesting the conversational chatbot platform to add one or more users to a conversation chat creating a group chat; wherein the request is initiated a buyer;
sending an invitation by the conversational chatbot platform to the one or more users to join the group chat; wherein on the group chat the buyer can ask for information relating to product information, product recommendations, payment options and alike information; and
wherein the conversational chatbot platform acts as a service provider where multiple users can view products and have a conversation simultaneously.
10.The method (200) as claimed in claim 1, wherein the method (200) further comprises:
requesting by the user to transfer the chat to a support person, wherein the conversational chatbot platform creates a group chat between the user, human agent and the conversational chatbot platform, characterized in that the conversational chatbot platform goes into an inactive state when the support person is active in that the group chat, and when the support person or the user leaves the group chat the conversational chatbot platform becomes active to self learn and update user intent user preferences, providing the personalized recommendations.