WO2023007359A1

WO2023007359A1 - Method and system for providing users with chat interaction experience within emails

Info

Publication number: WO2023007359A1
Application number: PCT/IB2022/056866
Authority: WO
Inventors: Nitin Gupta; Jeetu Narayan; Vageesh DWIVEDI
Original assignee: [24]7.ai, Inc.
Priority date: 2021-07-27
Filing date: 2022-07-26
Publication date: 2023-02-02

Abstract

A method and system for providing a user with chat interaction experience within an email is disclosed. A user interaction data corresponding to the user is accessed from one or more interaction sources. At least one persona type of the user is determined from one or more pre-defined persona types based, at least in part, on the user interaction data. A metadata is generated for the user based on the determined at least one persona type of the user. The metadata includes a set of utterances corresponding to a conversational content. An e-mail is generated based, at least in part, on the metadata and a promotional content received from an enterprise server. The e-mail includes a chat widget based on a dynamic hyper-text markup language (HTML). A chat interaction experience is facilitated between the user and an agent within a body of the e-mail based on the chat widget.

Description

METHOD AND SYSTEM FOR PROVIDING USERS WITH CHAT INTERACTION EXPERIENCE WITHIN EMAILS

Cross-reference to related applications

This application claims priority from Indian provisional patent application 202141033800, filed on July 27, 2021, which is incorporated herein in its entirety by this reference thereto.

The present technology generally relates to digital communication and, more particularly, providing improved user experience within email communications.

Background

Though Electronic Mail (email) is widely used as a tool for communication, emails play a particularly important role in enterprise environments. In addition to being the most common way of exchanging messages internally among employees, enterprises also use emails as a tool to conduct business, for example, as a tool to reach out to existing and prospective customers. For example, enterprises may use emails to showcase product or service offerings, promote new product launches, share offers for sale, provide updates on store openings, etc.

Many enterprises send out bulk emails to all existing and prospective customers with an expectation that some customers may read the emails and then reach out to the enterprises to buy products or avail of services offered by the enterprises. In many cases, the email content is generic and not directed to any specific customer or customer segment. The recipient of the emails referred to as a user or customer receives a large number of emails from multiple enterprises that the user has previously interacted with or whose offerings have seemed to interest the user. Most users ignore such emails due to the sheer volume or irrelevance of the content to their respective needs. As a result, the effectiveness of such email campaigns reduces drastically as the users delete such emails without even opening the emails.

To improve the effectiveness of emails sent out to existing and potential customers, some enterprises create customized content and use appealing graphics and content language to tempt the user to open the emails. In many cases, even if a user opens such a promotional email and is interested in learning more about the enterprise offering, the interaction ends if the user does not explicitly take an additional cognitive step of reaching out to the enterprise to enquire about the offering that the user is interested in. Most users do not take such an additional step and as a result, the promotional email only partially serves the intended purpose. Some enterprises include website links in emails to direct the users to their sites so that the users can receive all the required information. However, most users, nowadays, are averse to clicking on links due to phishing and other related scams.

Accordingly, there is a need to overcome the aforementioned drawbacks and increase the effectiveness of promotional emails. Further, it would be advantageous to not only provide all information that the user requires within the email itself but also address any queries that the user has without the need to redirect the user to an external website such as the enterprise website.

In an embodiment of the invention, a computer-implemented method is disclosed. The method accesses, by a server system, user interaction data corresponding to a user from one or more interaction sources. The method determines, by the server system, at least one persona type of the user from one or more pre-defined persona types based, at least in part, on the user interaction data. The method generates, by the server system, a metadata for the user based, at least in part, on the determined at least one persona type of the user. The metadata includes a set of utterances corresponding to a conversational content. The method generates, by the server system, an electronic mail (e-mail) based, at least in part, on the metadata and a promotional content received from an enterprise server. The e-mail includes a chat widget based on a dynamic hyper-text markup language (HTML). The method facilitates, by the server system, a chat interaction experience between the user and an agent within a body of the e-mail based on the chat widget. The chat interaction experience is facilitated based, at least in part, on the conversational content.

In another embodiment of the invention, a system is disclosed. The system includes at least one processor and a memory. The memory stores machine executable instructions, that when executed by the at least one processor, cause the system to access user interaction data corresponding to a user from one or more interaction sources. The system determines at least one persona type of the user from one or more pre-defined persona types based, at least in part, on the user interaction data. The system generates a metadata for the user based, at least in part, on the determined at least one persona type of the user. The metadata includes a set of utterances corresponding to a conversational content. The system generates an electronic mail (e-mail) based, at least in part, on the metadata and a promotional content received from an enterprise server. The e-mail includes a chat widget based on a dynamic hyper-text markup language (HTML). The system facilitates a chat interaction experience between the user and an agent within a body of the e-mail based on the chat widget. The chat interaction experience is facilitated based, at least in part, on the conversational content.

In yet another embodiment of the invention, a server system is disclosed. The server system includes a communication interface and a memory including executable instructions. The server system includes a processing system communicably coupled to the communication interface and configured to execute the instructions to cause the server system to perform a method. The method accesses user interaction data corresponding to a user from one or more interaction sources. The method determines at least one persona type of the user from one or more pre-defined persona types based, at least in part, on the user interaction data. The method generates a metadata for the user based, at least in part, on the determined at least one persona type of the user. The metadata includes a set of utterances corresponding to a conversational content. The method generates an electronic mail (e-mail) based, at least in part, on the metadata and a promotional content received from an enterprise server. The e-mail includes a chat widget based on a dynamic hyper-text markup language (HTML). The method facilitates a chat interaction experience between the user and an agent within a body of the e-mail based on the chat widget. The chat interaction experience is facilitated based, at least in part, on the conversational content.

The advantages and features of the invention will become better understood with reference to the detailed description taken in conjunction with the accompanying drawings, wherein like elements are identified with like symbols, and in which:

Fig.1

illustrates an example representation of an environment in which various embodiments of the present invention may be practiced.

Fig.2

illustrates a block diagram of a server system configured to provide users with a chat interaction experience within an email, in accordance with an embodiment of the present invention.

Fig.3

illustrates a block diagram depicting process steps performed to generate an email for the user, in accordance with an embodiment of the present invention.

Fig.4

illustrates an example representation of a code snippet depicting JSON structured data for facilitating the chat interaction experience within the email, in accordance with an embodiment of the present invention.

Fig.5

illustrates an example representation of a promotional email providing the chat interaction experience to a user, in accordance with an embodiment of the present invention.

Fig.6

illustrates an example representation for facilitating a chat conversation between an agent and the user within the email, in accordance with an embodiment of the present invention.

Fig.7

is a flow diagram of an example method for providing the user with the chat interaction experience within the email, in accordance with an embodiment of the present invention.

Fig.8

is a simplified block diagram of an electronic device capable of implementing various embodiments of the present invention.

The drawings referred to in this description are not to be understood as being drawn to scale except if specifically noted, and such drawings are only exemplary in nature.

Detailed Description

The best and other modes for carrying out the present invention are presented in terms of the embodiments, herein depicted in FIGS. 1 to 8. The embodiments are described herein for illustrative purposes and are subject to many variations. It is understood that various omissions and substitutions of equivalents are contemplated as circumstances may suggest or render expedient but are intended to cover the application or implementation without departing from the spirit or scope of the invention. Further, it is to be understood that the phraseology and terminology employed herein are for the purpose of the description and should not be regarded as limiting. Any heading utilized within this description is for convenience only and has no legal or limiting effect.

The terms “a” and “an” herein do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced items.

illustrates an example representation of an environment 100 in which various embodiments of the present invention may be practiced. The environment 100 is depicted to include smart electronic devices 104a, 104b, through 104n associated with users 102a, 102b through 102n. The electronic device 104a is depicted as a laptop, the electronic device 104b is depicted as a smartphone, and the electronic device 104n is depicted as a tablet, for illustration purposes.

Some non-exhaustive examples of the electronic device 104a may include a smartphone, a tablet, a laptop, a wearable device, a spatial computing device, and the like. The user 102a can be a person/organization/entity that operates the electronic device 104a to access an email 108. The email 108 may be received and/or viewed in a virtual mailbox 106 (hereinafter referred to as ‘mailbox 106’) logged in with a registered email account of a user such as the user 102a. The user 102a may login to the email account via an email application installed on the electronic device 104a.

In an example, the electronic device 104a may include a portable electronic device such as a smartphone, tablet, personal digital assistant (PDA), phablet, wearable device, smartwatch, laptop, and the like. In another example, the electronic device 104a may include a fixed communication device such as a desktop, mainframe computer, workstation, and the like.

The environment 100 is depicted to include a communication network 110 (hereinafter referred to as ‘network 110’). The network 110 may include wired networks, wireless networks, and combinations thereof. Some examples of the wired networks include the Ethernet, local area networks (LANs), fiber-optic cable networks, and the like. Some examples of the wireless networks include cellular networks like GSM/3G/4G/5G/CDMA networks, wireless LANs, Bluetooth or ZigBee networks, and the like. One example of a combination of wired and wireless networks is the Internet.

It is noted that the electronic device 104a may include necessary applications, such as for example, a web browser application or a software application (e.g., email client application) to enable the user 102a to access the email 108 from a remote email server over the network 110. It is also noted that the user 102a may use the email account to exchange messages, referred to herein as emails, with family members, friends, office colleagues, business partners, etc. Further, the email messages may include both formal and non-formal content.

The user 102a may receive emails from

enterprise servers

112a, 112b, …, 112n (jointly or each singularly represented as ‘enterprise server 112’). In addition, each enterprise server (e.g., the enterprise server 112a) is associated with a specific enterprise. The term ‘enterprise’ as used herein may refer to a corporation, an institution, a small/medium sized company, or even a brick-and-mortar entity. For example, the enterprise may be a banking enterprise, an educational institution, a financial trading enterprise, an aviation company, a consumer goods enterprise or any such public or private sector enterprise. An enterprise may offer products, services and/or information to multiple users, such as the user 102a. In an example, the existing and potential users of such enterprise offerings are referred to as the user 102a.

The enterprise server 112 is configured to send promotional emails to users, such as the user 102a, for driving sales and revenue of the enterprise. The term ‘promotional email’ as used herein refers to a commercial message sent to existing customers or prospective customers of an enterprise for sharing information related to new products/services, promotional discounts, sale offers, and/or other information pertaining to the enterprise. More specifically, the promotional email is usually sent by an enterprise for creating brand awareness, enhancing sales and purchases, generating leads, and the like. Such promotional emails are hereinafter interchangeably referred to as ‘emails’ or simply as ‘mails’, and the recipients of such emails are referred to as users.

The environment 100 depicts an example of a promotional email as the email 108 and an example user as the user 102a. It is noted that though the email 108 includes promotional content related to an enterprise offering, in some embodiments, a promotional email may be embodied as a newsletter email, a survey email, an announcement email, and the like. In one illustrative example, a user may have subscribed to notifications on the best deals for home furnishings on a website related to an enterprise. When the enterprise advertises a sale, the enterprise server 112 may send out one or more promotional emails related to the sale, for example a promotional discount or an offer on a recliner, to all existing and prospective customers on their respective email accounts. It is noted that various users (i.e., the users 102a, 102b, …, 102n) may receive several promotional emails related to a plurality of enterprises in their mailbox 106.

In at least one embodiment, the enterprise server 112 is configured to generate bulk promotional mails, such as the email 108, including promotional content for existing and prospective customers, such as the user 102a. In many scenarios, the enterprise related to the enterprise server 112 curates and customizes promotional content based on the user activity. To that effect, a data collection server 114 is configured to track user activity (i.e., online user behavior) on a plurality of platforms (e.g., social media platforms, e-commerce platforms, etc.). The data collection server 114 may be in operative communication with web servers logging user activity on various interaction channels, such as enterprise websites, third-party websites, messaging platforms, etc., and with other customer touch points, such as the electronic devices 104a associated with the user 102a. In one illustrative example, promotional content for an existing customer who has purchased a product from the enterprise may include information related to a product upgrade or additional accessories related to the product, whereas the promotional content for a prospective customer may include information highlighting key features of a product and/or discounts offered on the product. Such promotional content is stored in the enterprise server 112. In another illustrative example, the online user behavior may indicate that a user (such as the user 102a) has been viewing apparel of different brands on an e-commerce website. Further, the user 102a may have added products to a cart on the e-commerce website. The promotional content curated for such customers may be related to a sale on select brands offered by the e-commerce website.

In one embodiment, the curated and customized promotional content for users may include graphical content and/or textual content related to at least one offering of the enterprise. For example, the email 108 displayed to the user 102a includes content related to a fitness band offered for sale by an enterprise ‘Stayfit’. The email 108 is depicted to display an image of the fitness band and a text portion including text listing technical features of the fitness band, delivery times, and the like. Further, the email 108 may include an embedded call-to-action tab, such as a tab 124 (associated with text ‘PURCHASE NOW’) that prompts an action or a response from the user 102a. The email 108 may be associated with an enterprise manufacturing or distributing fitness bands. The promotional mails, such as the email 108, are designed to attract a customer’s attention and their primary aim is to persuade a customer to click on hyperlinks or tabs (for example, the hyperlink on “collection of fitness bands” or the tab 124 embedded within the email 108) to encourage conversion (for example, purchase, enquiry, website visit, etc.). In one example, upon clicking on the hyperlink, the user 102a may be directed to a website (i.e., website of the enterprise Stayfit), where the user 102a may be shown product specifications along with other details, such as for example manufacturer details, delivery options, EMI options, reviews, ratings, etc.

In many scenarios that are not in accordance with embodiments of the present invention, the user 102a even though interested in the promotional content associated with the email 108 may choose to ignore the email 108 as the user 102a needs additional information and such information is not readily available within the email 108 itself and requires additional effort on behalf of the user 102a to acquire such information, which the user 102a is not ready to do. For example, the user 102a may wish to know the battery life of the fitness band to evaluate whether the fitness band can be used for extended times without frequently recharging a battery of the fitness band. In another illustrative example, the user 102a may wish to know if the fitness band is compatible with Android OS or not. As such information is not mentioned in the email 108, the user 102a may have to perform an additional cognitive step, for example navigate to the enterprise website or chat with an agent (virtual or human agent) on the enterprise website to seek answers to the queries, which may be cumbersome for the user 102a. In many cases, the user 102a may opt to not click on the tab 124 or initiate engagement with the enterprise, leading to revenue loss for the enterprise.

To overcome the aforementioned drawbacks and provide an enhanced experience for users, a server system 122 is disclosed. The server system 122 is configured to improve the effectiveness of promotional emails by not only providing all information that the user 102a requires within the email 108 itself but also addressing any queries that the user 102a has without the need to redirect the user 102a to an external website such as, the enterprise website. To that effect, the server system 122 provides the user 102a with a real-time dynamic chat interaction experience within the email 108 itself.

In one implementation, the server system 122 runs an email chat facilitation application 116. In one implementation, the email chat facilitation application 116 may implement or run one or more machine learning (ML) based models (e.g., an email chat facilitation model 120) to facilitate a bi-directional chat interaction process inside the body of the email 108. In one implementation, the email chat facilitation application 116 may refer to an application or an instance of an application that may be run on the server system 122. The server system 122 is explained in further detail with reference to .

In one embodiment, a database 118 is associated with the server system 122. For instance, the database 118 may be embodied within the server system 122 or communicably coupled to the server system 122. In one embodiment, the database 118 provides storage location to the email chat facilitation model 120. In some embodiments, the database 118 provides storage location to the conversational content, promotional content, the user interaction data, metadata, JSON structural content, dynamic HTML, and any other data associated with the server system 122.

illustrates a block diagram of a server system 200 configured to provide the user 102a with a chat interaction experience within the email 108, in accordance with an embodiment of the present invention. Examples of the server system 200 include, but are not limited to, the server system 122 as shown in . In some embodiments, the server system 200 is embodied as a cloud-based and/or SaaS-based (software as a service) architecture.

The term ‘chat interaction experience’ as used herein primarily refers to a simulated experience of conversing with an agent (e.g., virtual assistant, automated agent, human agent, etc.) within the body of the email 108 itself. More specifically, a chat widget provided within the email 108 is configured to trigger an exchange of chat interaction messages within the email 108. For example, the chat interaction messages may be exchanged between the agent and the user 102a to answer the queries of the user 102a or provide additional information to the user 102a. Such an exchange of chat messages within the email 108, in effect, creates a ‘chat interaction experience’ or a ‘chatbot experience’ within the email 108.

In an embodiment, the server system 200 may be embodied as an interaction platform implemented in a standalone machine or a distributed set of machines connected to a communication network (for example, the network 110 explained with reference to ). For example, the server system 200 may be included within an enterprise server, such as the enterprise server 112. In some embodiments, the server system 200 may be disposed external to the enterprise server 112 and configured to be in operative communication with the enterprise server 112.

The server system 200 includes a computer system 202 and a database 204. The computer system 202 includes at least one processor 206 for executing instructions, a memory module 208, a communication module 210, a storage module 214, and an input/output module 216 (hereinafter referred to as ‘I/O module 216’). The one or more components of the computer system 202 communicate with each other via a bus 212. The components of the server system 200 provided herein may not be exhaustive and the server system 200 may include more or fewer components than those depicted in . Further, two or more components may be embodied in one single component, and/or one component may be configured using multiple sub-components to achieve the desired functionalities. In one embodiment, the database 204 is identical to the database 118.

In one embodiment, the database 204 is integrated within the computer system 202 and configured to store an instance of the email chat facilitation application 116 and one or more components of the email chat facilitation application 116. The one or more components of the email chat facilitation application 116 may include, but are not limited to, an email chat facilitation model 230 associated with the email chat facilitation application 116, and the like. The computer system 202 may include one or more hard disk drives as the database 204. The storage module 214 is any component capable of providing the processor 206 an access to the database 204. The storage module 214 may include, for example, an Advanced Technology Attachment (ATA) adapter, a Serial ATA (SATA) adapter, a Small Computer System Interface (SCSI) adapter, a RAID controller, a SAN adapter, a network adapter, and/or any component providing the processor 206 with access to the database 204.

The processor 206 includes suitable logic, circuitry, and/or interfaces to execute computer-readable instructions for generating the email 108 with an embedded chat widget. Examples of the processor 206 include, but are not limited to, an application-specific integrated circuit (ASIC) processor, a graphical processing unit (GPU), a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a field-programmable gate array (FPGA), and the like. The memory module 208 includes suitable logic, circuitry, and/or interfaces to store a set of computer-readable instructions for performing operations. Examples of the memory module 208 include a random-access memory (RAM), a read-only memory (ROM), a removable storage drive, a hard disk drive (HDD), and the like. It will be apparent to a person skilled in the art that the scope of the disclosure is not limited to realizing the memory module 208 in the server system 200, as described herein. In some embodiments, the memory module 208 may be realized in the form of a database server or cloud storage working in conjunction with the server system 200, without deviating from the scope of the present disclosure.

In an embodiment, the memory module 208 is capable of storing machine-executable instructions. Further, the processor 206 is capable of executing the stored machine-executable instructions. In an embodiment, the processor 206 may be embodied as a multi-core processor, a single-core processor, or a combination of one or more multi-core processors and one or more single-core processors. For example, the processor 206 may be embodied as one or more of various processing devices, such as a coprocessor, a microprocessor, a controller, a digital signal processor (DSP), a processing circuitry with or without an accompanying DSP, or various other processing devices including integrated circuits such as, for example, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a microcontroller unit (MCU), a hardware accelerator, a special-purpose computer chip, or the like. In an embodiment, the processor 206 may be configured to execute hard-coded functionality. In an embodiment, the processor 206 is embodied as an executor of software instructions, wherein the instructions may specifically configure the processor 206 to perform the algorithms and/or operations described herein when the instructions are executed. The modules of the processor 206 may be implemented as software modules, hardware modules, firmware modules, or as a combination thereof.

The memory module 208 may be embodied as one or more volatile memory devices, one or more non-volatile memory devices, and/or a combination of one or more volatile memory devices and non-volatile memory devices. For example, the memory module 208 may be embodied as magnetic storage devices (such as hard disk drives, floppy disks, magnetic tapes, etc.), optical magnetic storage devices (e.g. magneto-optical disks), CD-ROM (compact disc read-only memory), CD-R (compact disc recordable), CD-R/W (compact disc rewritable), DVD (Digital Versatile Disc), BD (Blu-ray® Disc), and semiconductor memories (such as mask ROM, PROM (programmable ROM), EPROM (erasable PROM), flash ROM, RAM (random access memory), etc.).

The processor 206 includes a chatbot framework engine 218, a persona framework engine 220, a metadata generation engine 222, an HTML generation engine 224, an email generation engine 226, and a chat facilitation engine 228. It should be noted that the components, described herein, can be configured in a variety of ways, including electronic circuitries, digital arithmetic and logic blocks, and memory systems in combination with software, firmware, and embedded technologies.

The chatbot framework engine 218 includes suitable logic and/or interfaces for accessing user interaction data corresponding to the user 102a from one or more interaction sources. The term ‘user interaction data’ as used herein refers to data captured by one or more data collection servers, such as the data collection server 114. The user interaction data may include information such as web pages visited, time spent on each web page, menu options accessed, drop-down options selected or clicked, mouse movements, hypertext mark-up language (HTML) links clicked and/or not clicked, focus events (for example, events during which the customer has focused on a link/webpage for a more than a predetermined amount of time), non-focus events (for example, choices the customer did not make from information presented to the customer (for example, products not selected) or non-viewed content derived from scroll history of the customer), touch events (for example, events involving a touch gesture on a touch-sensitive device such as a tablet), non-touch events, and the like.

In an example, the chatbot framework engine 218 is configured to receive the user interaction data related to the users 102a, 102b, …, 102n from the data collection server 114, which is configured to track user activity on a number of interaction channels and customer touch points. Some non-limiting examples of interaction channels include enterprise website, social media/e-commerce, third-party websites, and the like. An example of a customer touch point may include an electronic device, such as the desktop computer used by the user 102a.

In some example scenarios, the user 102a may have subscribed to notifications from an enterprise and accordingly, information related to such notifications (for example, category of notification, personal information, preferences, and the like) may also be stored as the user interaction data. In one example, the one or more interaction sources include web servers hosting web pages associated with the website of the enterprise and logging information related to the user activity on the website of the enterprise.

In addition, the chatbot framework engine 218 is configured to access conversational content. In an embodiment, the enterprise server 112 provides the conversational content to the chatbot framework engine 218. The term ‘conversational content’ as used herein refers to a plurality of utterances that is typically exchanged during a chat conversation between an enterprise agent (e.g., virtual agent, chatbot, human agent, etc.) and a customer (e.g., the user 102a) of the enterprise. The plurality of utterances may include introductory messages, common queries, quick responses, detailed answers to queries, default messages (for example, utterances displaying options to connect with enterprise via alternate channels), promotional messages (such as sales, discounts, offers, coupons, etc.), and any related content such as, URLs, videos, animated images that may supplement a response.

An example utterance provided by a customer of an enterprise selling car insurance policies during a chat interaction may be ‘What is the coverage offered by XYZ car insurance policy?’. A response provided by a chat agent (hereinafter referred to as a chatbot) to such a query may be an utterance, such as ‘accidental coverage’ or ‘non-collision coverage’. Similarly, the user 102a may ask ‘What are the payment terms of the car insurance policy?’ and the chatbot may respond with an utterance ‘quarterly’ or ‘yearly’. The enterprise server 112 provides such utterances exchanged during a chat interaction and embodied in form of a textual transcript to the chatbot framework engine 218.

In one example, the enterprise server 112 may provide utterances like ‘Are there any special discounts on the car insurance policy’, ‘Offer for the month of August’, ‘Would you like to know more’ to the chatbot framework engine 218 as part of the conversational content. It is noted that the utterances mentioned above are for example purposes only and the conversational content provided by the enterprise server 112 may include a comprehensive list of utterances that an agent may likely encounter or likely utter during an interaction with customers on a daily basis related to the enterprise. In one embodiment, the conversational content provided by the enterprise (i.e., by the enterprise server 112) is stored in the database 204.

In some embodiments, the chatbot framework engine 218 is configured to monitor one or more platforms associated with one or more accounts corresponding to the user 102a to determine user activity. The chatbot framework engine 218 is then configured to generate the user interaction data based, at least in part, on the determined user activity. In an example, the one or more platforms may include social media platforms associated with the user 102a, enterprise accounts associated with the user 102a, online shopping accounts associated with the user 102a, and the like. Further, the chatbot framework engine 218 may use web scraping to determine user activity (such as purchase history, returns, replacements, refunds, reviews, ratings, and the like). Based on the user activity, the chatbot framework engine 218 may access the user interaction data.

The provisioning of the chat interaction experience within the email 108 by the server system 200 is hereinafter explained with reference to one user, such as the user 102a explained with reference to . It is noted that the server system 200 may be caused to serve, or more specifically, send promotional emails providing chat interaction experience to several other users to effectively promote an enterprise and enhance customer experience whilst providing desired assistance to the users.

Moreover, the chatbot framework engine 218 is configured to receive promotional content from the enterprise server 112. The enterprise server 112 includes appealing text and graphics related to a product or a service being offered for sale by the corresponding enterprise. In some embodiments, the promotional content and the conversational content are stored in the database 204. In addition, the chatbot framework engine 218 accesses the conversational content and the promotional content for customizing promotional mails for the user 102a.

The persona framework engine 220 includes suitable logic and/or interfaces for determining at least one persona type of the user 102a from one or more pre-defined persona types based, at least in part, on the user interaction data. The term ‘persona type’ or ‘persona’ as used interchangeably hereinafter refers to characteristics reflecting behavioral patterns, goals, motives, and personal values of an individual. It is noted that the term ‘personas’ as used herein is distinct from the concept of customer profiles, that are used in various kinds of analytics, where similar groups of individuals are identified based on certain commonality in their attributes, which may not necessarily reflect behavioral similarity, or similarity in goals and motives.

In an example, the one or more pre-defined persona types include: a researcher (a customer who is likely to investigate alternative products thoroughly and read and compare product specifications before making a purchase), a loyal customer (a customer with a strong affinity to a single or a selected few brands or products or services), a convenience customer (a customer who has a firm decision on what he/she wants to buy and who is wanting to make a purchase quickly), and the like. In another example, the one or more pre-defined persona types include: a compulsive buyer (a customer who has a high propensity to buy products he/she might not require and who is very likely to agree to an up-sell/cross-sell offer made by an agent), a deal seeker (a customer who is seeking motivation to get the best available deal or discount for a product or purchase), a stump (a customer who is convinced against making a purchase and is very unlikely to make a purchase regardless of the quality or timeliness of customer service), and the like.

In at least some embodiments, the persona framework engine 220 is configured to deploy machine learning models (e.g., the email chat facilitation model 230) for determining one or more persona types for each user based on the corresponding user interaction data. In general, machine learning model is a program that discovers patterns in a training dataset. In an example, the training dataset may include user behavior on various web pages which may be evaluated to discover that the user 102a is a compulsive buyer who has high propensity to buy products he/she might not require and who is very likely to agree to an up-sell/cross-sell offer made by an agent.

To that effect, the persona framework engine 220 may utilize sophisticated algorithms, such as for example algorithms based on Logistic Regression, Linear Regression, Naïve Bayes, Rule Engines, neural networks, Linear Discriminant Analysis, decision trees, support vector machines, k-nearest neighbor, K-means, and the like, for predicting persona type of the user 102a. The persona framework engine 220 is then configured to pass information about the determined at least one persona type of the user 102a to the metadata generation engine 222.

In some embodiments, the chatbot framework engine 218 is configured to select a set of promotional content from the promotional content based, at least in part, on the determined at least one persona type of the user 102a. The set of promotional content is in one or more formats. The one or more formats include at least one of: (a) text, (b) audio, (c) video, (d) multimedia, and the like. In an example, the chatbot framework engine 218 may select graphical promotional content (e.g., images, multimedia such as animations, gifs, etc.) to generate the email 108 if the determined persona type of the user 102a is a stump. In another example, the chatbot framework engine 218 may select textual promotional content to generate the email 108 if the determined persona type of the user 102a is a compulsive buyer.

The metadata generation engine 222 includes suitable logic and/or interfaces for generating a metadata for the user 102a based, at least in part, on the determined at least one persona type of the user 102a. The metadata includes a set of utterances corresponding to the conversational content. More specifically, the metadata generation engine 222 is configured to select the set of utterances related to the determined at least one persona type of the user 102a. Without loss of generality, the metadata generation engine 222 is then configured to structure the set of utterances related to the at least one persona type of the user 102a as a Java script Object Notation (JSON) structured data. It should be noted that the metadata generation engine 222 may also structure the utterances in any other format that is different than the JSON.

More specifically, the set of utterances related to the at least one persona type may be defined on a dialog tree in a structured format. For example, the dialog tree may start with a greeting/introduction, followed by one or more queries which customers of a particular persona type are likely to ask an agent or a chatbot for initiating a conversation along with corresponding responses. The dialog tree may branch out to another set of queries associated with respective responses likely to be encountered in the chat interaction with the user 102a, and so forth. It shall be noted that when the conversation spans over the entire dialog tree and if all pre-stored responses are exhausted, the metadata may include an utterance that redirects the user 102a to a different channel (for example, an enterprise website, customer care numbers, and the like) for further information.

In general, JavaScript Object Notation (JSON) is a standard text-based format for representing structured data based on JavaScript object syntax. Typically, JSON is employed to serialize and transmit structured data over a communication network, such as the network 110. Accordingly, JSON can be utilized to facilitate the exchange of data between a server system such as the server system 200 and a client (e.g., the electronic device 104a) in conjunction with a web, or other representational state transfer (REST)-based, application/service. The metadata generation engine 222 further transmits the JSON structured data to the HTML generation engine 224.

The HTML generation engine 224 includes suitable logic and/or interfaces for generating a dynamic hyper-text markup language (HTML) based on the metadata received from the metadata generation engine 222. In one embodiment, the dynamic HTML includes pre-canned utterances. The pre-canned utterances are selected from the set of utterances based, at least in part, on the conversational content and the promotional content provided by the server system 200. In one embodiment, the pre-canned utterances are selected from the set of utterances based on the user interaction data associated with the user 102a.

Generally, “dynamic HTML” is a collective term for a combination of HTML tags and options that can make web pages animated and interactive (such as, the chat interaction experience). It is depicted that the HTML generation engine 224 is configured to generate the dynamic HTML based on the metadata; however, for a person skilled in the art, the HTML generation engine 224 can also generate other web development languages including, for example, Cascading Style Sheets (CSS), JavaScript, Java, React, HTML, Angular, Scala, and the like.

As explained above, a set of appropriate utterances (i.e., pre-canned utterances) may be selected from the conversational content based on the determined at least one persona type of the user 102a. The selected utterances may be used to generate JSON structured data, which captures combinations of possible chat conversational flows with the user 102a. The HTML generation engine 224 is configured to generate an HTML script corresponding to the JSON structured data and the HTML script is capable of dynamically changing the next selection of conversational input (i.e., selection of utterance to display) based on a response from the user 102a. Such an HTML script is referred to herein as ‘dynamic HTML’.

In at least some embodiments, pre-canned utterances are provided as chat messages using dynamic HTML embedded within the email 108 to facilitate such a chat interaction experience within the email 108. The pre-canned utterances are configured to resolve queries or provide additional information, thereby providing necessary assistance to the user 102a within the email 108 itself, as will be explained in further detail later. The HTML generation engine 224 is then configured to transmit the dynamic HTML to the email generation engine 226.

The email generation engine 226 includes suitable logic and/or interfaces for generating the electronic mail (email) 108 based, at least in part, on the metadata (including the conversational content), and the promotional content received from the enterprise server 112. The email 108 includes a chat widget based on the dynamic HTML. The chat widget provides the user 102a with the chat interaction experience to communicate with the agent. More specifically, the email generation engine 226 embeds the dynamic HTML within the body of the email 108 to facilitate the chat interaction experience via the chat widget. The dynamic HTML further provides the chat interaction experience to the user 102a. In some examples, the email generation engine 226 handles the size and positioning of the chat widget in the email 108.

Further, the email generation engine 226 is configured to transmit the email 108 to an email account associated with the user 102a. The user 102a may further access the email 108 in the virtual mailbox 106 on a graphical user interface (GUI) rendered on the electronic device 104a of the user 102a. If the user 102a wants to chat with the agent, the user 102a can click on the chat widget to facilitate the chat interaction experience with the agent.

The chat facilitation engine 228 includes suitable logic and/or interfaces for provisioning an interface to facilitate the chat interaction experience between the user 102a and the agent (e.g., virtual agent, chatbot, human agent, etc.) within the body of the email 108 via the chat widget. The chat interaction experience is facilitated based, at least in part, on the conversational content (e.g., pre-canned utterances). In an example, the user 102a can interact or chat with the agent (e.g., chatbot) regarding the offering (i.e., product or service) described in the promotional email 108. In an example, the user 102a may ask questions related to the offering offered by the enterprise server 112. In another example, the user 102a may ask additional questions related to the products or services offered by the enterprise server 112. In one non-limiting example, the chat facilitation engine 228 is invoked once the user 102a clicks on the chat widget.

In one embodiment, the interface provided by the chat facilitation engine 228 is configured to receive a user query in the chat widget from the electronic device 104a of the user 102a. The user query is received in one or more communication formats. The one or more communication formats include text, audio, video, animation, gif, and the like. The interface provided by the chat facilitation engine 228 is further configured to electronically provide pre-canned utterances as chat messages based, at least in part, on the dynamic HTML embedded within the email 108 to facilitate the chat interaction experience. The pre-canned utterances are provided to resolve the user query. In case of receiving the user query in any communication format other than textual data, the logic provided by the chat facilitation engine 228 may use machine learning-based algorithms or models (e.g., the email chat facilitation model 230) to understand the user query and then provide the pre-canned utterances based on the analysis of the user query. In one non-limiting example, the chat facilitation engine 228 may use natural language processing (NLP) to understand the user query and then provide the pre-canned utterance as a response accordingly.

The dynamic HTML has pre-canned structured data that dynamically selects the next action (for example, a response) based on a current action, such as a query from the user 102a. In an illustrative example, the user 102a may enquire about additional charges that may be incurred while purchasing furniture. The chat facilitation engine 228 selects an utterance from the structured data (i.e., the dialog tree) that specifies different charges for installing the furniture and accordingly, provides sufficient information (i.e., transport charges, installation charges, maintenance charges, etc.) for the user 102a within the chat widget. The provision of the chat interaction experience within the email 108 increases the effectiveness of promotional emails by providing all information that the user 102a requires within the email 108 itself.

If the agent (e.g., virtual agent, chatbot) is unable to resolve the queries of the user 102a based on the conversational content, the chat facilitation engine 228 is configured to facilitate the chat interaction experience between the user 102a and a human agent. More specifically, the chat facilitation engine 228 is configured to assign a human agent associated with the enterprise server 112 to resolve the queries of the user 102a.

illustrates a block diagram 300 depicting process steps performed to generate the email 108 for the user 102a, in accordance with an embodiment of the invention. As explained with reference to , the chatbot framework engine 218 receives the user interaction data in relation to users, such as the user 102a. In , the chatbot framework engine 218 is depicted to receive a user interaction data 302 corresponding to a user (such as the user 102a shown in ). Further, the storage module 214 of the server system 200 stores the promotional content for the email 108 (shown as promotional content 304) and conversational content 306 provided by the enterprise server 112 related to the enterprise.

In at least one example, the chatbot framework engine 218, in conjunction with the code/instructions stored in the memory module 208, is configured to: (1) determine the at least one persona type of the user 102a, (2) generate the metadata for the user 102a based on the determined persona type, and (3) generate a dynamic HTML 308 for the user 102a based on the metadata. To this effect, the chatbot framework engine 218 includes the persona framework engine 220, the metadata generation engine 222 and the HTML generation engine 224.

In an embodiment, the persona framework engine 220 is configured to determine the at least one persona type of the user 102a based on the user interaction data 302 collated corresponding to the user 102a. An example of a persona type may be a ‘convenience customer’ that corresponds to a customer characterized by the behavioral trait that he/she is focused and is looking for expeditious delivery of service. In an embodiment, a behavioral trait as referred to herein corresponds to a biological, sociological or a psychological characteristic.

An example of a psychological characteristic may be a degree of decidedness associated with a customer while making a purchase. For example, some customers dither for a long time and check out various options multiple times before making a purchase, whereas some customers are more decisive in their purchasing options. An example of a sociological characteristic may correspond to a likelihood measure of a customer to socialize a negative sentiment or an experience. For example, a customer upon having a bad experience with a product purchase may share his/her experience on social networks and/or complain bitterly on public forums, whereas another customer may choose to return the product and opt for another product, while avoiding socializing his/her experience.

An example of a biological characteristic may correspond to gender or even age-based inclination towards consumption of products/services or information. For example, a middle-aged female may be more likely to purchase a facial product associated with aging, whereas a middle-aged man may be more likely to purchase a hair care related product. It is noted that examples of customer biological, sociological, and psychological characteristics are provided herein for illustrative purposes and may not be considered limiting the scope of set of behavioral traits associated with a persona type and that each personality type may include one or more such behavioral traits.

In an embodiment, the persona framework engine 220 is configured to store various customer persona classification frameworks or taxonomies capable of facilitating segregation of users based on persona types. In an embodiment, the persona framework engine 220 may identify behavioral traits exhibited or associated with the user 102a based, at least in part, on the user interaction data 302. More specifically, the persona framework engine 220 is configured to analyze the user interaction data 302 collated corresponding to the customer (i.e., the user 102a) to identify behavioral traits associated with the user 102a. The persona framework engine 220 is then configured to compare the identified behavioral traits of the user 102a with pre-defined sets of behavioral traits associated with the one or more pre-defined persona types to identify at least one match.

For example, the behavioral traits exhibited, mentioned, inferred, or predicted based on the user interaction data 302 may be compared with pre-defined sets of behavioral traits associated with the one or more pre-defined persona types in a customer persona classification framework to identify a presence of a match. The persona framework engine 220 determines the at least one persona type of the user 102a based on the identified at least one match. More specifically, the matching persona type is identified as the persona type of the user 102a. The determined persona type may be a single persona, or an aggregation of all historic personas over specified durations or time or over N previous interactions.

In an embodiment, the metadata generation engine 222 is configured to generate the metadata for the user 102a based on the determined persona type. More specifically, the metadata generation engine 222 is configured to select the set of utterances from the conversational content 306 based on the determined at least one persona type of the user 102a.

In an illustrative example, the metadata generation engine 222 may be configured to select a set of utterances (i.e., possible queries and/or responses from the conversational content 306) corresponding to a customer of a persona type ‘discount seeker’. For example, the set of utterances related to an enterprise dealing with Air Conditioners (ACs) for a persona type ‘discount seeker’ may include utterances such as, ‘Offer on ACs’, ‘20% off on model AX10BC123‘, ‘10% off on model GH56AC2XX’, ‘no processing fee on EMI’, ‘Current offers on ACs’, ‘Model on discount’, and the like while engaging in an interaction with an agent/chatbot.

In some example embodiments, the metadata generation engine 222 is configured to embed/integrate personal information related to the user 102a (for example, name, subscription information, date of birth, and the like) collated from the user interaction data 302 to personalize the conversation during the chat interaction. To that effect, the generation of metadata for the user 102a may include encryption/ encoding to preserve the integrity of the metadata related to the user 102a.

Accordingly, the set of utterances related to the determined persona type are selected and structured as a JSON structured data to ensure that a chat widget providing the chat interaction experience within the email 108 can independently provision appropriate messages (for example, responses, quick responses, prompts, etc.) to handle possible queries from the customer of persona type ‘discount seeker’ and provide the required assistance to the customer within the email 108 itself. An example code snippet depicting JSON structured data is shown and explained with reference to .

The HTML generation engine 224 is then configured to generate the dynamic hyper-text markup language (HTML) 308 based on the metadata. As explained above, the dynamic HTML 308 includes pre-canned utterances selected from the set of utterances based, at least in part, on the conversational content 306 and the promotional content 304. In one example, the pre-canned utterances can be selected from the set of utterances based on the user interaction data 302.

The HTML generation engine 224 is further configured to generate an HTML script 308 corresponding to JSON structured data and the HTML script 308 is capable of dynamically changing the next selection of conversational input (i.e., selection of utterance to display) based on a response from the user 102a. In some embodiments, the processor is configured to select the set of promotional content (i.e., textual, and visual content) from the promotional content 304 based on the determined persona type of the user 102a. For example, textual content for a user of persona type ‘researcher’ may include key features, specifications, manufacturer details, and the like that may add credibility to the product.

The email generation engine 226 is configured to generate the email 108 based on the set of promotional content selected for the user 102a and embed the dynamic HTML 308 in the email 108 to configure the email 108. The dynamic HTML 308 embedded within the email 108 is configured to provide the user 102a with an experience of chatting with a chatbot within the email 108 itself, thereby increasing the effectiveness of the mail 108. The promotional email 108 embedded with the dynamic HTML 308 may be provided by the server system 200 using the communication module 210 either to an email server associated with the enterprise or directly to the user 102a on behalf of the enterprise.

illustrates an example representation 400 of a code snippet 402 depicting JSON structured data for facilitating the chat interaction experience within the email 108, in accordance with an embodiment of the present invention.

In one illustrative example, the user 102a may be shown a question with three options (for example, quick responses) - a simple text, link, and video. The metadata generation engine 222 is configured to map or create a relationship between each utterance (for example, a query) and the next utterance (for example, response) to create a dynamic styling or dynamic mapping. It is noted that the utterances may be selected from the conversational content 306. For example, three options (option A, option B, and option C) are presented corresponding to a query posted by the user 102a (for example, modes of working of an air fryer). As shown in the code snippet 402, option A is mapped to response A (text), option B is mapped to response B (text and link), and option C is mapped to response C (text and link to video). As an example, when the user 102a selects option B, the user 102a may be directed to an external website and a selection input on option C may display a video within the email 108. It shall be noted that such dialog trees may be defined for a comprehensive set of utterances related to each persona type of the user 102a and stored in a storage module, such as the database 204.

illustrates an example representation 500 of a promotional email 510 providing the chat interaction experience to a user 502, in accordance with an embodiment of the present invention. The user 502 can be an example of any of the users 102a through 102n. More specifically, the example representation 500 depicts the user 502 accessing an email application 506 on an electronic device 504 (exemplarily depicted to be a personal computer) for accessing one or more emails received in a mailbox 508 associated with the registered email address of the user 502.

In an illustrative example, the user 502 may have subscribed to receive news related to new products/services being offered by the enterprise (e.g., the enterprise server 112). On the launch of a product, the enterprise server 112 may generate promotional content to be included in the emails and send such information to the server system 200. In an example, the server system 200 may receive the promotional content via the communication module 210 and further store the promotional content in the storage module 214 (or the database 204). The server system 200 may also receive conversational content 306 in relation to the promotional content and store the conversational content 306 in the storage module 214 (or the database 204).

Also, the server system 200 may access the user interaction data 302. For example, the user interaction data may include information related to the subscription of the user 502 to receive new product updates from the enterprise server 112. As explained above, the server system 200 is configured to select an email content (from the promotional content) related to the new product launch being offered for sale by the enterprise server 112 based on the determined at least one persona type of the user 502. Further, based on the determined at least one persona type of the user 502, the server system 200 selects conversational content 306 from the storage module 214 to generate metadata in form of JSON structured data. The JSON structured data is then used to generate a dynamic HTML, which is then embedded in the selected email content to configure the promotional email 510. The promotional email 510 is hereinafter referred to as email 510.

The email 510 is depicted to include the following textual content:
‘HI DAVID!
GREETINGS FROM PHOTOBOOK ENTERPRISE!
MEMORIES ARE FOR ETERNITY!
WOULD YOU LIKE TO PRESERVE THOSE TREASURED MEMORIES?
GET A PROFESSIONALLY DESIGNED PHOTOBOOK TODAY!’

Further, the email 510 includes image content related to a printed photobook. It is noted that the email 510 displaying the image content related to the printed photobook along with the corresponding text is shown herein for illustration purposes only. The email 510 from other enterprises may similarly include promotional content related to enterprise product and/or service offerings to prospective and existing customers. Further, it is to be noted that the email 510 may include other information such as, sender information, recipient information, date, and time the mail 510 was received at, attachments, call to action tabs, and the like.

In addition to the text and image content, the email 510 includes a chat widget 512. The chat widget is exemplarily depicted to display an introductory message associated with text ‘HI DAVID! I’M HERE TO HELP YOU WITH CUSTOMIZING YOUR PHOTOBOOK!’. The introductory message is followed by options to provide quick responses. The quick responses are predefined textual inputs (i.e., utterances) embedded within a chat window of the chat widget 512 to enable the user 502 to raise queries or respond to questions by a touch or click input on the corresponding option. It is noted that these quick responses are usually a part of the set of utterances selected based on the determined at least one persona type of the user 502. Accordingly, the chat widget 512 displays an option 514 and an option 516 associated with text ‘STYLE AND SIZE’ and ‘CUSTOMIZATION OPTIONS’, respectively. In one illustrative example, a persona type of the user 502 may be identified as a ‘researcher’, and accordingly the introductory message and the options included in the chat widget 512 are chosen to appeal to the persona type of the user 502.

The chat widget 512 included within the email 510 enables a conversation of limited nature within the email 510 itself and is configured to provide necessary information related to the enterprise offering or resolve queries of the user 502, in effect providing chat interaction experience to the user 502. An example chat conversation between the agent and the user 502 within the email 510 is illustrated in .

illustrates an example representation 600 for facilitating a chat conversation between an agent and the user 502 within the email 510, in accordance with an embodiment of the present invention. In an illustrative example, the user 502 may have selected the option 514 (shown in ) within the chat widget 512. The selection of the option 514 may trigger display of various size and style options as quick responses (see, options 602 and 604) to the user 502 as shown in . As already explained, dynamic HTML corresponding to the user 502 models a JSON structured data that captures probable queries and corresponding responses on a dialog tree. As such, each query may be related with a response or vice versa to predict a next action (response) based on selection input provided by the user 502 to provide the chat interaction experience for the user 502 within the email 510.

The chat widget 512 may further prompt the user 502 to respond by providing

options

606, 608, 610 in the form of quick responses. More specifically, a next set of actions (i.e., the

options

606, 608 and 610) to continue the chat interaction experience within the email 510 may be provisioned based on the metadata (i.e., JSON structured data) modeling the dynamic HTML. The option 606 is associated with text ‘BOOK A DESIGN’, the option 608 is associated with text ‘GET A DEMO’ and the option 610 is associated with text ‘COST’.

When the user 502 selects the option 606, the chat widget 512 is configured to provide steps to guide the user 502 into customizing a photobook. If the user 502 prefers to see a video demo, he may provide a selection input (i.e., click or touch) on the option 608. Accordingly, a video content embedded within the dynamic HTML may be played back for the user 502 within the email 510. On receiving a selection input on the option 610 associated with text ‘COST’, the chat widget 512 may be configured to provide cost associated with different styles and/or sizes of photobooks available for customization to the user 502 as shown in .

More specifically, the dynamic HTML may be configured to map each response, for example, the option 602 with a specific response (i.e., pertaining to steps for customization and purchase of a photobook), the option 604 with a video content and the option 606 with pricing information of various photobooks to create a dynamic styling that provisions a chat interaction experience for the user 502 within the email 510.

Such instant handling of customer queries and providing required assistance within the email 510 significantly improves user experience as opposed to a scenario where the user 502 is redirected to the enterprise website to explore myriad options presented on the enterprise website. Moreover, facilitating user interaction within the email 510 increases the advertising enterprise’s brand awareness by providing an option for conversion of the user 502 within the email 510. In some embodiments, if the chat interaction experience spans the entire dialog tree (i.e., the JSON structured data) and if the user 502 requires further assistance, the dynamic HTML may include an utterance (i.e., a pre-canned response) that provides an option to conduct the interaction (e.g., with a human agent) on a different communication channel facilitated by the enterprise, such as voice channel or a chat channel on the enterprise website.

is a flow diagram of an example method 700 for providing the user 102a with the chat interaction experience within the email 108, in accordance with an embodiment of the present invention. The method 700 depicted in the flow diagram may be executed by, for example, the server system 200. Operations of the flowchart, and combinations of operation in the flowchart, may be implemented by, for example, hardware, firmware, a processor, circuitry and/or a different device associated with the execution of software that includes one or more computer program instructions. The operations of the method 700 are described herein with help of the server system 200. It is noted that, the operations of the method 700 can be described and/or practiced by using a system other than the server system 200. The method 700 starts at operation 702.

At operation 702 of the method 700, user interaction data 302 corresponding to a user (such as, the user 102a of ) is accessed from the one or more interaction sources by a server system, such as the server system 200 explained with reference to FIGS. 1 to 6. As explained with reference to , the user interaction data 302 may be tracked over a pre-defined time interval and collected by data collection servers logging customer activity, and web servers hosting and managing third-party websites.

At operation 704 of the method 700, at least one persona type is determined for the user 102a from the one or more pre-defined persona types based on the user interaction data 302. More specifically, at least one persona type of the user 102a is determined based on the user interaction data 302. For example, a user who is likely to thoroughly investigate alternative products before making a purchase and read and compare product specifications may be predicted to be a ‘researcher’ based on the user interaction data 302.

At operation 706 of the method 700, a metadata is generated for the user 102a based on the determined at least one persona type of the user 102a. The metadata includes a set of utterances corresponding to the conversational content 306. Generation of metadata as a dialog tree is explained with reference to .

At operation 708 of the method 700, the electronic mail (email) 108 is generated for the user 102a based, at least in part, on the metadata and a promotional content received from the enterprise server 112. The e-mail 108 includes a chat widget based on the dynamic hyper-text markup language (HTML).

At operation 710 of the method 700, the chat interaction experience is facilitated between the user 102a and an agent within a body of the e-mail 108 based on the chat widget. The chat interaction experience is facilitated based, at least in part, on the conversational content 306.

is a simplified block diagram of an electronic device 800 capable of implementing various embodiments of the present invention. For example, the electronic device 800 may correspond to the electronic device 104a of the user 102a. The electronic device 800 is depicted to include one or more applications 806. For example, the one or more applications 806 may include the email chat facilitation application 116 of . The email chat facilitation application 116 can be an instance of the application that is hosted and managed by the server system 200. One of the one or more applications 806 on the electronic device 800 is capable of communicating with a server system for providing chat interaction experience within the body of an email as explained above.

It should be understood that the electronic device 800 as illustrated and hereinafter described is merely illustrative of one type of device and should not be taken to limit the scope of the embodiments. As such, it should be appreciated that at least some of the components described below in connection with the electronic device 800 may be optional and thus in an embodiment may include more, less, or different components than those described in connection with the embodiment of the . As such, among other examples, the electronic device 800 could be any of a mobile electronic device, for example, cellular phones, tablet computers, laptops, mobile computers, personal digital assistants (PDAs), mobile televisions, mobile digital assistants, or any combination of the aforementioned, and other types of communication or multimedia devices.

The illustrated electronic device 800 includes a controller or a processor 802 (e.g., a signal processor, microprocessor, ASIC, or other control and processing logic circuitry) for performing such tasks as signal coding, data processing, image processing, input/output processing, power control, and/or other functions. An operating system 804 controls the allocation and usage of the components of the electronic device 800 and supports for one or more operations of the application (see, the applications 806), such as the email chat facilitation application 116 that implements one or more of the innovative features described herein. In addition, the applications 806 may include common mobile computing applications (e.g., email applications, calendars, contact managers, web browsers, messaging applications) or any other computing application.

The illustrated electronic device 800 includes one or more memory components, for example, a non-removable memory 808 and/or removable memory 810. The non-removable memory 808 and/or the removable memory 810 may be collectively known as a database in an embodiment. The non-removable memory 808 can include RAM, ROM, flash memory, a hard disk, or other well-known memory storage technologies. The removable memory 810 can include flash memory, smart cards, or a Subscriber Identity Module (SIM). The one or more memory components can be used for storing data and/or code for running the operating system 804 and the applications 806. The electronic device 800 may further include a user identity module (UIM) 812. The UIM 812 may be a memory device having a processor built in. The UIM 812 may include, for example, a subscriber identity module (SIM), a universal integrated circuit card (UICC), a universal subscriber identity module (USIM), a removable user identity module (R-UIM), or any other smart card. The UIM 812 typically stores information elements related to a mobile subscriber. The UIM 812 in form of the SIM card is well known in Global System for Mobile (GSM) communication systems, Code Division Multiple Access (CDMA) systems, or with third generation (3G) wireless communication protocols such as Universal Mobile Telecommunications System (UMTS), CDMA9000, wideband CDMA (WCDMA) and time division-synchronous CDMA (TD-SCDMA), or with fourth-generation (4G) wireless communication protocols such as LTE (Long-Term Evolution).

The electronic device 800 can support one or more input devices 820 and one or more output devices 830. Examples of the input devices 820 may include, but are not limited to, a touch screen/a display screen 822 (e.g., capable of capturing finger tap inputs, finger gesture inputs, multi-finger tap inputs, multi-finger gesture inputs, or keystroke inputs from a virtual keyboard or keypad), a microphone 824 (e.g., capable of capturing voice input), a camera module 826 (e.g., capable of capturing still picture images and/or video images), and a physical keyboard 828. Examples of the output devices 830 may include, but are not limited to, a speaker 832 and a display 834. Other possible output devices can include piezoelectric or other haptic output devices. Some devices can serve more than one input/output function. For example, the touch screen 822 and the display 834 can be combined into a single input/output device.

A wireless modem 840 can be coupled to one or more antennas (not shown in the ) and can support two-way communications between the processor 802 and external devices, as is well understood in the art. The wireless modem 840 is shown generically and can include, for example, a cellular modem 842 for communicating at long range with the mobile communication network, a Wi-Fi compatible modem 844 for communicating at short range with an external Bluetooth-equipped device or a local wireless data network or router, and/or a Bluetooth-compatible modem 846. The wireless modem 840 is typically configured for communication with one or more cellular networks, such as a GSM network for data and voice communications within a single cellular network, between cellular networks, or between the electronic device 800 and a public switched telephone network (PSTN).

The electronic device 800 can further include one or more input/output ports 850, a power supply 852, one or more sensors 854 for example, an accelerometer, a gyroscope, a compass, or an infrared proximity sensor for detecting the orientation or motion of the electronic device 800 and biometric sensors for scanning biometric identity of an authorized user, a transceiver 856 (for wirelessly transmitting analog or digital signals) and/or a physical connector 860, which can be a USB port, IEEE 1294 (FireWire) port, and/or RS-232 port. The illustrated components are not required or all-inclusive, as any of the components shown can be deleted and other components can be added.

Various embodiments disclosed herein provide numerous advantages. More specifically, the embodiments disclosed herein suggest techniques for providing users with a chat interaction experience within an email. Such seamless interaction within the email increases the effectiveness of promotional emails by providing all information that a user requires within the email itself and even addresses any queries that the user has without the need to redirect the user to an external website, such as the enterprise website, thereby reducing drop-offs and enhancing user experience. Moreover, such chat interactions provided within the email result in significant time savings by saving the user hassles of navigating through myriad options that may be presented to a customer on the enterprise website and increases engagement level of the users.

Although the present invention has been described with reference to specific exemplary embodiments, it is noted that various modifications and changes may be made to these embodiments without departing from the broad spirit and scope of the present invention. For example, the various operations, blocks, etc., described herein may be enabled and operated using hardware circuitry (for example, complementary metal oxide semiconductor (CMOS) based logic circuitry), firmware, software and/or any combination of hardware, firmware, and/or software (for example, embodied in a machine-readable medium). For example, the systems and methods may be embodied using transistors, logic gates, and electrical circuits (for example, application specific integrated circuit (ASIC) circuitry and/or in Digital Signal Processor (DSP) circuitry).

Particularly, the system 200 and its various components such as the processor 206, the memory module 208, the I/O module 216, and the communication module 210 may be enabled using software and/or using transistors, logic gates, and electrical circuits (for example, integrated circuit circuitry such as ASIC circuitry). Various embodiments of the present invention may include one or more computer programs stored or otherwise embodied on a computer-readable medium, wherein the computer programs are configured to cause a processor or computer to perform one or more operations (for example, operations explained herein with reference to ). A computer-readable medium storing, embodying, or encoded with a computer program, or similar language, may be embodied as a tangible data storage device storing one or more software programs that are configured to cause a processor or computer to perform one or more operations. Such operations may be, for example, any of the steps or operations described herein. In some embodiments, the computer programs may be stored and provided to a computer using any type of non-transitory computer readable media. Non-transitory computer readable media include any type of tangible storage media. Examples of non-transitory computer readable media include magnetic storage media (such as floppy disks, magnetic tapes, hard disk drives, etc.), optical magnetic storage media (e.g., magneto-optical disks), CD-ROM (compact disc read only memory), CD-R (compact disc recordable), CD-R/W (compact disc rewritable), DVD (Digital Versatile Disc), BD (Blu-ray (registered trademark) Disc), and semiconductor memories (such as mask ROM, PROM (programmable ROM), EPROM (erasable PROM), flash ROM, RAM (random access memory), etc.). Additionally, a tangible data storage device may be embodied as one or more volatile memory devices, one or more non-volatile memory devices, and/or a combination of one or more volatile memory devices and non-volatile memory devices. In some embodiments, the computer programs may be provided to a computer using any type of transitory computer readable media. Examples of transitory computer readable media include electric signals, optical signals, and electromagnetic waves. Transitory computer readable media can provide the program to a computer via a wired communication line (e.g., electric wires, and optical fibers) or a wireless communication line.

Various embodiments of the present invention, as discussed above, may be practiced with steps and/or operations in a different order, and/or with hardware elements in configurations, which are different than those which are disclosed. Therefore, although the invention has been described based upon these exemplary embodiments, it is noted that certain modifications, variations, and alternative constructions may be apparent and well within the spirit and scope of the invention.

Although various exemplary embodiments of the present invention are described herein in a language specific to structural features and/or methodological acts, the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as exemplary forms of implementing the claims.

Claims

A computer-implemented method, comprising:
accessing, by a server system, user interaction data corresponding to a user from one or more interaction sources;
determining, by the server system, at least one persona type of the user from one or more pre-defined persona types based, at least in part, on the user interaction data;
generating, by the server system, a metadata for the user based, at least in part, on the determined at least one persona type of the user, the metadata comprising a set of utterances corresponding to a conversational content;
generating, by the server system, an electronic mail (e-mail) based, at least in part, on the metadata and a promotional content received from an enterprise server, the e-mail comprising a chat widget based on a dynamic hyper-text markup language (HTML); and
facilitating, by the server system, a chat interaction experience between the user and an agent within a body of the e-mail based on the chat widget, the chat interaction experience facilitated based, at least in part, on the conversational content.
The method of claim 1, further comprising:
transmitting, by the server system, the e-mail to an e-mail account associated with the user.
The method of claim 1, further comprising:
generating, by the server system, the dynamic hyper-text markup language (HTML) based on the metadata; and
embedding, by the server system, the dynamic HTML within the body of the email to facilitate the chat interaction experience via the chat widget.
The method of claim 3, wherein the dynamic HTML comprises pre-canned utterances, the pre-canned utterances selected from a set of utterances based, at least in part, on a conversational content and a promotional content.
The method of claim 1, further comprising:
monitoring, by the server system, one or more platforms associated with one or more accounts corresponding to the user to determine user activity; and
generating, by the server system, the user interaction data based, at least in part, on the determined user activity.
The method of claim 1, further comprising:
identifying, by the server system, behavioral traits associated with the user based, at least in part, on the user interaction data;
comparing, by the server system, the identified behavioral traits of the user with pre-defined sets of behavioral traits associated with the one or more pre-defined persona types to identify at least one match; and
determining, by the server system, the at least one persona type of the user based on the identified at least one match.
The method of claim 1, further comprising:
selecting, by the server system, the set of utterances related to the determined at least one persona type of the user; and
structuring, by the server system, the set of utterances as a Java script Object Notation (JSON) structured data.
The method of claim 1, further comprising:
selecting, by the server system, a set of promotional content from the promotional content in one or more formats based, at least in part, on the determined at least one persona type of the user, wherein the one or more formats comprises at least one of: (a) text, (b) audio, (c) video, and (d) multimedia.
The method of claim 1, further comprising:
receiving, by the server system, user query in the chat widget from an electronic device of the user, wherein the user query is received in one or more communication formats; and
electronically providing, by the server system, pre-canned utterances as chat messages based, at least in part, on the dynamic HTML embedded within the email to facilitate the chat interaction experience, wherein the pre-canned utterances are provided to resolve the user query.
A system, comprising:
at least one processor; and
a memory having stored therein machine executable instructions, that when executed by the at least one processor, cause the system to:
access user interaction data corresponding to a user from one or more interaction sources;
determine at least one persona type of the user from one or more pre-defined persona types based, at least in part, on the user interaction data;
generate a metadata for the user based, at least in part, on the determined at least one persona type of the user, the metadata comprising a set of utterances corresponding to a conversational content;
generate an electronic mail (e-mail) based, at least in part, on the metadata and a promotional content received from an enterprise server, the e-mail comprising a chat widget based on a dynamic hyper-text markup language (HTML); and
facilitate a chat interaction experience between the user and an agent within a body of the e-mail based on the chat widget, the chat interaction experience facilitated based, at least in part, on the conversational content.
The system of claim 10, wherein the system is further caused to:
generate the dynamic hyper-text markup language (HTML) based on the metadata; and
embed the dynamic HTML within the body of the email to facilitate the chat interaction experience via the chat widget.
The system of claim 11, wherein the dynamic HTML comprises pre-canned utterances, wherein the pre-canned utterances are selected from the set of utterances based, at least in part, on a conversational content and a promotional content.
The system of claim 10, wherein the system is further caused to:
monitor one or more platforms associated with one or more accounts corresponding to the user to determine user activity; and
generate the user interaction data based, at least in part, on the determined user activity.
The system of claim 10, wherein the system is further caused to:
identify behavioral traits associated with the user based, at least in part, on the user interaction data;
compare the identified behavioral traits of the user with pre-defined sets of behavioral traits associated with the one or more pre-defined persona types to identify at least one match; and
determine the at least one persona type of the user based on the identified at least one match.
The system of claim 10, wherein the system is further caused to:
select the set of utterances related to the determined at least one persona type of the user; and
structure the set of utterances as a Java script Object Notation (JSON) structured data.
A server system, comprising:
a communication interface;
a memory comprising executable instructions; and
a processing system communicably coupled to the communication interface and configured to execute the instructions to cause the server system to perform a method comprising:
accessing user interaction data corresponding to a user from one or more interaction sources;
determining at least one persona type of the user from one or more pre-defined persona types based, at least in part, on the user interaction data;
generating a metadata for the user based, at least in part, on the determined at least one persona type of the user, the metadata comprising a set of utterances corresponding to a conversational content;
generating an electronic mail (e-mail) based, at least in part, on the metadata and a promotional content received from an enterprise server, the e-mail comprising a chat widget based on a dynamic hyper-text markup language (HTML); and
facilitating a chat interaction experience between the user and an agent within a body of the e-mail based on the chat widget, the chat interaction experience facilitated based, at least in part, on the conversational content.
The server system of claim 16, further comprising:
generating a dynamic hyper-text markup language (HTML) based on the metadata; and
embedding the dynamic HTML within the body of the email to facilitate the chat interaction experience via the chat widget.
The server system of claim 17, wherein the dynamic HTML comprises pre-canned utterances, wherein the pre-canned utterances are selected from a set of utterances based, at least in part, on a conversational content and a promotional content
The server system of claim 16, further comprising:
monitoring one or more platforms associated with one or more accounts corresponding to the user to determine user activity; and
generating the user interaction data based, at least in part, on the determined user activity
The server system of claim 16, further comprising:
identifying behavioral traits associated with the user based, at least in part, on the user interaction data;
comparing identified behavioral traits of the user with pre-defined sets of behavioral traits associated with the one or more pre-defined persona types to identify at least one match; and
determining the at least one persona type of the user based on the identified at least one match.