Methods and systems for facilitating user-agent interactions using augmented reality (AR) are disclosed. Method includes facilitating interaction between user and agent upon receiving request from user. Method includes receiving AR-based workflow including set of instructions from agent. Method includes receiving viewfinder frame from electronic device associated with user subsequent to initializing AR session in response to executing a first instruction from set of instructions. Method includes iteratively performing plurality of operations till each instruction from set of instructions is executed, plurality of operations includes analyzing viewfinder frame to determine subsequent instruction to be executed from set of instructions. Then, facilitate display of AR image frame. AR image frame is generated based on subsequent instruction. Further, determine execution status of the subsequent instruction by monitoring user while user executes the subsequent instruction. The execution status indicates whether subsequent instruction is successful or unsuccessful. Further, transmit notification indicating execution status to agent.
A chat console includes a chat portion and at least one portion corresponding to an enterprise system application. The chat portion displays text related to a chat interaction between the agent and a customer in real-time in an ongoing manner. The portion related to the enterprise system application displays data relevant to the chat interaction fetched from a respective enterprise system application. The agent console operatively communicates with three enterprise system applications, such that data relevant to the current chat interaction is fetched from each of the three enterprise system applications and displayed in a respective portion within the agent console.
A method and apparatus for providing assistance to customers seeking assistance from agents of an enterprise is disclosed. The method includes receiving a signal indicating the caller's wish to speak with a live agent associated with the enterprise to seek the assistance from the live agent. In response to a receipt of the signal, it is determined whether at least one live agent from among a plurality of live agents associated with the enterprise is available for a voice interaction with the caller. Subsequent to determining that no live agent from among the plurality of live agents is currently available for the voice interaction with the caller, the caller is diverted to an asynchronous messaging channel. A textual messaging-based interaction is facilitated between a messaging agent and the caller on the asynchronous messaging channel to provide the assistance to the caller.
A method and apparatus for providing Web advertisements to online users is disclosed. A balanced set of negative data points and positive data points is derived from a log of Ad impressions and used to train a classifier. In response to an Ad request signal, a plurality of Ads is retrieved from a database. The Ad request signal indicates a request to provide an Ad for a slot available on a Web page associated with a website. The signal is provided in relation to an access of the Web page by an online user and includes information related to the online user. A choice of an Ad is predicted based on the information related to the online user and the plurality of Ads. The Ad is provided to a Web server to cause display of the Ad on the slot when the Web page is displayed to the online user.
G06F 18/23213 - Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
5.
Method and apparatus for facilitating agent conversations with customers of an enterprise
In a method and apparatus for facilitating agent interactions with customers of an enterprise, one or more intents corresponding to an input provided by a customer during a conversation with a Virtual Agent (VA) are predicted. A confidence score corresponding to each intent is computed that is indicative of an ability of the VA to provide an effective response to the input. The confidence score corresponding to each intent is compared with a predefined threshold score. If the confidence score is less than the predefined threshold score, the conversation is deflected from the VA to a human agent to respond to the input of the customer. The conversation is deflected from the human agent to the VA for a subsequent input if a respective confidence score of at least one intent predicted for the subsequent input is greater than or equal to the predefined threshold score.
A method and apparatus for providing multimodal interaction assistance to customers seeking assistance from agents of an enterprise is disclosed. The method includes augmenting an ongoing voice interaction between a caller and an automated agent with a speech synchronized web session. A session identifier and contextual information in relation to the speech synchronized web session are stored in a database. A display of an option to interact with a human agent is caused during the ongoing speech synchronized web session. In response to a selection of the option by the caller, a co-browsing of the speech synchronized web session by the caller and the human agent is facilitated. The co-browsing of the speech synchronized web session and the contextual information stored in relation to the speech synchronized web session enable the human agent to provide assistance to the caller.
A method and apparatus for facilitating persona-based agent interactions with online visitors is disclosed. A plurality of persona related attributes is extracted from a textual transcript of each interaction between an agent of an enterprise and an online visitor. A feature vector data representation is generated based on the plurality of persona related attributes extracted from each interaction to configure a plurality of feature vector data representations. The plurality of feature vector data representations is classified based on a plurality of persona-based clusters, which enables classification of the plurality of online visitors into the plurality of persona-based clusters. A learning model is trained for each persona-based cluster using utterances of online visitors classified into a respective persona-based cluster. The learning model is trained to mimic a visitor persona representative of the respective persona-based cluster. The trained learning model is configured to facilitate the persona-based agent interactions with the online visitors.
G06N 3/04 - Architecture, e.g. interconnection topology
G06N 3/00 - Computing arrangements based on biological models
G10L 15/06 - Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
G10L 15/18 - Speech classification or search using natural language modelling
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G10L 15/16 - Speech classification or search using artificial neural networks
8.
Method and apparatus for facilitating training of agents
A method and apparatus for facilitating training of agents is disclosed. Raw transcripts representing textual form of interactions between the agents and customers of the enterprise are transformed to generate transformed transcripts. An interaction summary is generated in relation to each transformed transcript. A plurality of intent-based interaction clusters are derived using the interaction summary generated in relation to each transformed transcript. The plurality of interactions are classified based on the plurality of intent-based interaction clusters and an interaction flow map is generated for each intent-based interaction cluster based on the interactions classified into the respective intent-based interaction cluster. The generated interaction flow map is capable of facilitating training of agents for interacting with the customers of the enterprise.
G06K 9/62 - Methods or arrangements for recognition using electronic means
H04L 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
A method and apparatus for facilitating interactions between customers and agents are disclosed that include detecting whether a customer is present on a website related to an enterprise. The detection is performed subsequent to an initiation of an interaction with an agent by the customer. When the customer is detected to be present, an option is provided to the agent to offer co-browsing of the web site to the customer. In response to an acceptance of the offer by the customer, a co-browsing session is initiated for facilitating the co-browsing of the website. Digital content is generated based on at least one of the ongoing co-browsing session and the interaction between the customer and the agent and display of the digital content by the agent to the customer is caused. The digital content is displayed during the ongoing co-browsing session to provide assistance to the customer.
A method and apparatus for selecting treatment for visitors to online enterprise channels are disclosed. The method includes receiving information related to a visitor and a current activity of the visitor on an online enterprise channel. The information is transformed to generate transformed data and a plurality of features is extracted from the transformed data. Using the plurality of features, it is determined whether a treatment when rendered to the visitor is capable of increasing a likelihood of the visitor performing a desired action during a current visit to the online enterprise channel. The treatment is selected and rendered if it is determined that the treatment is capable of increasing the likelihood of the visitor performing the desired action. No treatment is rendered if it is determined that no treatment from among the plurality of treatments is capable of increasing the likelihood of the visitor performing the desired action.
A method and apparatus for facilitating a turn-based interaction between a virtual agent and a customer of an enterprise are disclosed. The method includes receiving a conversational input provided by the customer during a turn-based interaction between the customer and the agent. One or more conversational inputs exchanged between the customer and the agent prior to the customer's conversational input are identified by positioning a virtual bounding box of fixed width over textual representation of the turn-based interaction. The conversational input and the one or more conversational inputs configure a set of conversational inputs. At least one context vector representation is generated based on an encoding of the set of conversational inputs. Each word of a virtual agent reply is predicted based on the at least one context vector representation. The virtual agent reply is provided to the customer in response to the conversational input of the customer.
An enterprise application integration system (EAIS) is disclosed that enables customer service applications to access and share data with enterprise information systems in real time.
A method and apparatus for managing agent interactions with customers of an enterprise are disclosed. The method includes generating a value representative of an emotional state of a customer engaged in an ongoing interaction with a virtual agent (VA) associated with the enterprise. The value is generated based, at least in part, on one or more inputs provided by the customer during the ongoing interaction. The value is compared with a predefined emotional threshold range to determine whether the emotional state of the customer is a non-neutral state. The ongoing interaction is deflected to one of a human agent and a specialized VA capable of empathetically handling the ongoing interaction if it is determined that the emotional state of the customer is the non-neutral state.
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
14.
Method and apparatus for facilitating agent conversations with customers of an enterprise
In a method and apparatus for facilitating agent interactions with customers of an enterprise, one or more intents corresponding to an input provided by a customer during a conversation with a Virtual Agent (VA) are predicted. A confidence score corresponding to each intent is computed. The confidence score is indicative of an ability of the VA to provide an effective response to the input. The confidence score corresponding to each intent is compared with a predefined threshold score. If the confidence score is less than the predefined threshold score, the conversation is deflected from the VA to a human agent to respond to the input of the customer. The conversation is deflected from the human agent to the VA for a subsequent input if a respective confidence score of at least one intent predicted for the subsequent input is greater than or equal to the predefined threshold score.
A method and system for authenticating customers on call are disclosed. The method includes providing a notification to a customer on an electronic device associated with the customer. The notification is provided in response to the customer placing a call for seeking an interaction with an agent of an enterprise. The notification is configured to trigger authentication of the customer using an application on the electronic device. A status of the authentication of the customer is received from the application on the electronic device and, if the status of the authentication of the customer is a success, the call is connected to the agent to facilitate the interaction between the customer and the agent.
A method and an apparatus for provisioning optimized content to customers are disclosed. The method includes determining at least one attribute associated with a customer active on a web interface associated with an enterprise. A plurality of baseline contents and a plurality of content elements are accessed from a database and at least one baseline content and at least one content element are selected based on the at least one attribute associated with the customer. A customized advertisement is generated using the at least one baseline content and the at least one content element.
A computer-implemented method and an apparatus for facilitating training of conversational agents are disclosed. The method includes automatically extracting a workflow associated with each conversation from among a plurality of conversations between agents and customers of an enterprise. The workflow is extracted, at least in part, by encoding one or more utterances associated with the respective conversation and mapping the encoded one or more utterances to predefined workflow stages. A clustering of the plurality of conversations is performed based on a similarity among respective extracted workflows. The clustering of the plurality of conversations configures a plurality of workflow groups. At least one conversational agent is trained in customer engagement using a set of conversations associated with at least one workflow group from among the plurality of workflow groups.
G06N 20/10 - Machine learning using kernel methods, e.g. support vector machines [SVM]
18.
Method and apparatus for building a user profile, for personalization using interaction data, and for generating, identifying, and capturing user data across interactions using unique user identification
A computer-implemented method and a system facilitate social recognition of agents. A first user interface (UI) is presented to a customer on a device in proximity to the customer subsequent to a completion of an interaction of the customer with an agent. The first UI comprises one or more survey questions related to a performance of the agent. A determination of whether the performance of the agent satisfies a predetermined condition is performed based on an input received from the customer in response to the one or more survey questions. A second UI is presented to the customer to request the customer to provide an endorsement for the agent if the performance of the agent satisfies the predetermined condition. A posting of the endorsement on one or more social media profiles of the agent is effected upon receiving the endorsement for the agent from the customer.
In accordance with an example embodiment a computer-implemented method and an apparatus for predicting and tracking of mood changes in textual conversations are provided. The method includes determining, by a processor, one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer. Changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation are tracked by the processor. Further, the method includes determining, by the processor, at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics.
A computer-implemented method and an apparatus for notifying customers of agent's availability is disclosed. An input indicative of a customer seeking an interaction with an agent of an enterprise is received on a first interaction channel. Subsequent to receiving the input, it is determined whether at least one agent is available for interacting with the customer. If no agent is available for interacting with the customer, a status message including an estimate of a waiting time for the interaction with the agent is provided to the customer. Subsequent to detecting the availability of the agent, a notification is provided to the customer for informing the customer of the availability of the agent. An interaction is facilitated between the customer and the agent subsequent to providing the notification to the customer. The interaction is facilitated on the first interaction channel or a second interaction channel different than the first interaction channel.
A computer-implemented method and an apparatus facilitate user chat interactions. A chat widget offering chat-based assistance is displayed on one or more Web pages of an enterprise Website. In response to a user selection of the chat widget, a chat window is displayed at a first predetermined position on a Web page. The chat window is repositioned to a second predetermined position in response to a user input indicative of provisioning of a text input. The repositioning of the chat window enables display of a virtual keyboard. The placement of the chat window and the virtual keyboard enables the user to view a substantial portion of the Web page. The chat window is caused to scroll with the Web page in response to a Web page scroll input provided by the user and slide back to a previous position subsequent to completion of a scroll movement of the Web page.
H04L 51/046 - Interoperability with other network applications or services
G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
The stages of an interaction between a potential customer (the user) and a sales representative (the agent) during a sales interaction are identified to understand the interaction factors that drive sales and, by doing so, to serve the customer better and thus increase sales. Initially, a user makes contact with an agent via a communications network. During the interaction, a dropping point is reached, i.e. the point in the interaction at which either the user or the agent ends the interaction. The dropping point and other interaction factors is analyzed. Based upon such analysis, various recommendations are made to the agents to improve the user's sales experience.
A context sensitive slider content area provides a slide out mechanism that is automatically actuated when additional information is needed during a chat session between an agent and a visitor, e.g. where a pre-chat and/or exit form is to be completed. The context sensitive slide out content area also provides problem resolution information to the visitor to help in solving problems, e.g. the top five problems; and also provides a self-service step-by-step wizard. A history section is provided with which the visitor can track back all previous steps carried out within the smart client. A history bar provides an iconic representation of all previous activities. A technique is also disclosed for executing various actions, such as form filling or requests for additional services, in a chat session.
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
H04L 51/04 - Real-time or near real-time messaging, e.g. instant messaging [IM]
G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
24.
Method and apparatus for diverting callers to web sessions
A customer support system diverts a customer to an integrated support service to serve the customer better in situations where the use of a single mode of interaction is insufficient. Embodiments of the invention find use where an email or SMS is sent to a customer's smart devices with a link to visual content which helps customer better understand the information.
H04M 1/64 - Automatic arrangements for answering calls; Automatic arrangements for recording messages for absent subscribers; Arrangements for recording conversations
A data assist application allows people to share structured data, and update and/or collaborate in real time. Companies can use embodiments of the invention to send and/or receive structured data. Embodiments of the data assist application work standalone or while a user is talking to a person or a company. In use, information is spread when people share data with non-users. The data are preferably owned and/or controlled by the user and stored on user devices. Further embodiments of the invention integrate with OS-supplied data and third party apps.
A system and a process using that system is provided for creating, analyzing and optimizing a customer journey. The process includes real-time creation and continuing analysis of an “Event Sequence Index,” (ESI) corresponding to a time-stamped labeled set of data points representing cumulative events along the customer journey. The data points are further associated with channels, which are modes of interaction between the customer and the organization, and mapped into a linked directed graph which is amenable to analysis through a recursive pattern matching method, such as a non-deterministic finite automaton, employing DQL (Distributed Query Language). Selected portions of these graphs can be identified, either statistically or causally, as signatures of highly satisfactory or unsatisfactory outcomes and may be stored in memory as real-time predictors of the course of a present customer experience and to suggest statistically feasible and effective interventions. Concurrently, the signatures may be used as feedback to an organization for improvements in customer relations.
A computer implemented method and an apparatus for facilitating voice user interface (VUI) design are provided. The method comprises identifying a plurality of user intentions from user interaction data. The method further comprises associating each user intention with at least one feature from among a plurality of features. One or more features from among the plurality of features are extracted from natural language utterances associated with the user interaction data. Further, the method comprises computing a plurality of distance metrics corresponding to pairs of user intentions from among the plurality of user intentions. A distance metric is computed for each pair of user intentions from among the pairs of user intentions. Furthermore, the method comprises generating a plurality of clusters based on the plurality of distance metrics. Each cluster comprises a set of user intentions. The method further comprises provisioning a VUI design recommendation based on the plurality of clusters.
The disclosure is related to mining of text to derive information from the text that is useful for a variety of purposes. The text mining process can be implemented in a service oriented industry such as a call center, where a customer and an agent engage in a dialog, e.g., to discuss product/service related issues. The messages in dialogues between the customers and the agents are tagged with features that describe an aspect of the conversation. The text mining process can mine various dialogues and identify a set of features and messages based on prediction algorithms. The identified set of features and messages can be used to infer an intent of a particular customer for contacting the agent, and to generate a recommendation based on the determined intent.
User intent is identified while the user browses online and recommendations are provided to the user. The recommendations are based on the identified intent, interests, and preferences of the user who is performing the searches. The determination of user intent and interests is based on a statistical model derived from data compiled from the user and a plurality of other users. Other resources may also be determined to be relevant, for example, because of past interactions of the user, memberships of the user in ecommerce websites, the user's interests and preferences are similar to those of other users, and so on. The result of the user search is a ranked set of recommendations that is provided to the user.
The stages of an interaction between a potential customer (the user) and a sales representative (the agent) during a sales interaction are identified to understand the interaction factors that drive sales and, by doing so, to serve the customer better and thus increase sales. Initially, a user makes contact with an agent via a communications network. During the interaction, a dropping point is reached, i.e. the point in the interaction at which either the user or the agent ends the interaction. The dropping point and other interaction factors is analyzed. Based upon such analysis, various recommendations are made to the agents to improve the user's sales experience.
User interactions are categorized into predefined hierarchical categories by classifying user interactions, such as queries, during a user interaction session by labeling text data into predefined hierarchical categories, and building a scoring model. The scoring model is then executed on untagged user interaction data to classify the user interactions into either action-based or information-based interactions.
G06F 15/18 - in which a program is changed according to experience gained by the computer itself during a complete run; Learning machines (adaptive control systems G05B 13/00;artificial intelligence G06N)
A computer-implemented method and an apparatus manage natural language queries of customers. A natural language query provided by a customer on an enterprise interaction channel is received. The natural language query is analyzed to determine if an answer to the natural language query exists in at least one question-answer (QA) domain from among a plurality of QA domains by analyzing each QA domain from among the plurality of QA domains using a multi-level framework of natural language models. An answer to the natural language query is provided to the customer on the enterprise interaction channel if such an answer in available in the plurality of QA domains. If an answer is not available, then an appropriate response is provided to the customer to assist the customer.
A computer-implemented method and an apparatus facilitate user engagement on enterprise interaction channels. Information related to a current journey of a user on one or more enterprise interaction channels is received. The user is categorized as one of a hot lead, a warm lead, and a non-hot lead based, at least in part, based on the received information related to the current journey of the user. If the user is categorized as the non-hot lead, a user interface (UI) displayed to the user is modified. The UI is modified to facilitate user engagement for converting the user from a non-purchasing entity to a purchasing entity.
G07F 17/32 - Coin-freed apparatus for hiring articles; Coin-freed facilities or services for games, toys, sports, or amusements
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
Embodiments of the invention involve providing automated assistance to an agent operating an agent terminal. A database stores an automated assistance session comprising communications between at least one client terminal and at least one agent terminal during a communication session. The automated assistance session is restored in response to a connection being reestablished with the client terminal after the client terminal disconnects during the communication session. A client communication is received from the client terminal, and a plurality of statements is determined based on the client communication and the communications of the automated assistance session stored in the database. The statements are configured to be manually selected by an agent or automatically selected by an automated agent. The automated agent is engaged for automatically selecting one of the statements in response to a predetermined condition.
A mechanism for facilitating customer interactions within a customer service environment provides prompt and accurate answers to customer questions. A smart chat facility for use in a customer service environment to predict a customer problem examines a customer chat transcript to identify customer statements that set forth a customer issue and, responsive to this, can route the customer to an agent, an appropriate FAQ, or can implement a problem specific widget in the customer UI. Customer queries are matched with most correct responses and accumulated knowledge is used to predict a best response to future customer queries. The iterative system thus learns from each customer interaction and can adapt to customer responses over time to improve the accuracy of problem prediction.
A computer-implemented method and an apparatus dynamically select content for online visitors. The method includes receiving information related to activity of an online visitor on an enterprise interaction channel and identifying channel data related to the activity. A plurality of content pieces capable of being provided to the online visitor during the ongoing journey is identified. A correlation score is computed for each content piece using the channel data to generate a plurality of correlation scores. The plurality of content pieces are rank-ordered by sorting the plurality of correlation scores. A display of at least one content piece is effected during the ongoing journey of the online visitor on the enterprise interaction channel based on the rank-ordering of the plurality of content pieces.
A computer-implemented method and an apparatus link customer interactions with customer messaging platforms. An input indicating a request for interaction with an enterprise is received from a customer and in response to the received input, a user interface (UI) is displayed requesting the customer to authenticate a personal identity using login credentials corresponding to at least one third-party messaging platform. A customer interaction is facilitated with the enterprise subsequent to successful authentication of the personal identity. The customer interaction is facilitated on an enterprise interaction channel or a third-party messaging platform from among the at least one third-party messaging platform. The third-party messaging platform corresponds to the login credentials provided by the customer to authenticate the customer's personal identity.
A computer-implemented method and an apparatus facilitate customer intent prediction. The method includes receiving natural language communication provided by a customer on at least one enterprise related interaction channel. Textual data corresponding to the natural language communication is generated by converting one or more non-textual portions in the natural language communication to a text form. One or more processing operations are performed on the textual data to generate normalized text. The normalized text is configured to facilitate interpretation of the natural language communication. At least one intention of the customer is predicted, at least in part, based on the normalized text and a reply is provisioned to the customer based on the predicted intention. The reply is provisioned to the customer on the at least one enterprise related interaction channel in response to the natural language communication.
A computer-implemented method and an apparatus reserve agents for enabling zero-waiting time agent interactions for customers requiring agent assistance. The method includes determining if a customer requires agent assistance. If it is determined that the customer requires agent assistance, then it is determined whether an agent associated with relevant skill is capable of being reserved for providing assistance to the customer. The determination of reservation of the agent is performed, at least in part, by generating a data structure representation. The agent is reserved for assisting the customer if it is determined that the agent is capable of being reserved for providing assistance to the customer. An offer for assistance is provisioned to the customer on at least one enterprise related interaction channel subsequent to the reservation of the agent. The reservation of the agent provides wait-less customer interaction with the agent upon customer acceptance of the offer.
A customer support system diverts a customer to an integrated support service to serve the customer better in situations where the use of a single mode of interaction is insufficient. Embodiments of the invention find use where an email or SMS is sent to a customer's smart devices with a link to visual content which helps customer better understand the information.
H04M 1/64 - Automatic arrangements for answering calls; Automatic arrangements for recording messages for absent subscribers; Arrangements for recording conversations
A computer-implemented method and an apparatus facilitate management of customer interactions on multiple interaction channels. A communication quality metric and a contextual environment are tracked for an ongoing customer interaction executed on a first interaction channel. A closure of the first interaction channel is effected based on at least one of: a detected change in a current value associated with the communication quality metric to be below a preset threshold value, a detected or an anticipated change in the contextual environment, and a receipt of a customer request for closing the first interaction channel. The effecting of the closure of the first interaction channel includes a transitioning of the ongoing customer interaction from the first interaction channel to a second interaction channel.
A computer-implemented method and an apparatus for facilitating speech application testing generate a plurality of test scripts. A test script is generated by initiating a voice call interaction with a speech application including a network of interaction nodes, and repeatedly performing, until a stopping condition is encountered, the steps of, executing the voice call interaction by traversing through interaction nodes until an interaction node requiring a response is encountered, selecting an utterance generation mode, determining a response to be provided corresponding to the interaction node, and providing the response to the speech application. The test script comprises instructions for traversing interaction nodes and for provisioning one or more responses during the course of the voice call interaction. One or more test scripts from among the plurality of test scripts are identified based on a pre-determined objective and provided to a user for facilitating testing of the speech application.
One or more media applications are configured to facilitate Web page access. Such media applications receive a request from a user for access to a Web page. The Web page is retrieved from, for example, one or more Web servers, a file, and so on, and the content of the Web page is displayed within the media application. Display of the Web page content within the media application obviates the need to change applications to view the Web page content. By remaining within the application, a more natural and intuitive technique for inter-user communication is provided.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
A computer-implemented method and an apparatus for facilitating stateless representation of interaction flow states associated with customer interactions includes effecting generation of a first uniform resource locator (URL) indicative of a textual input received from a customer during an online interaction. The first URL is configured to identify a state machine and a state within the state machine for facilitating processing of the textual input. An intention of the customer is predicted from the first URL using the state machine and the state within the state machine. At least one next action is determined based on the predicted intention. A second URL including a response to the textual input is generated. The response is determined based on the at least one next action. The second URL is configured to identify a next interaction state for the online interaction. The response is provisioned to the customer during the online interaction.
A computer-implemented method and a system facilitate an acquiring of structured inputs from customers in turn-based online interactions. A UI displayed on a customer device and configured to facilitate a turn-based interaction between a customer and an agent facilitates receipt of a free-form textual input entered by the customer. The free-form textual input is indicative of an assistance desired by the customer from the agent. An interactive form including a plurality of questions is displayed within the UI to enable the customer to provide answers to one or more questions in a pre-defined format. At least one reply to be provided to the customer in response to the free-form textual input is determined based on the answers received from the customer for the one or more questions. The at least one reply is displayed within the UI for facilitating provisioning of the assistance desired by the customer.
G06Q 30/06 - Buying, selling or leasing transactions
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
A context sensitive slider content area provides a slide out mechanism that is automatically actuated when additional information is needed during a chat session between an agent and a visitor, e.g. where a pre-chat and/or exit form is to be completed. The context sensitive slide out content area also provides problem resolution information to the visitor to help in solving problems, e.g. the top five problems; and also provides a self-service step-by-step wizard. A history section is provided with which the visitor can track back all previous steps carried out within the smart client. A history bar provides an iconic representation of all previous activities. A technique is also disclosed for executing various actions, such as form filling or requests for additional services, in a chat session.
G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
47.
Method and apparatus for improving experiences of online visitors to a website
A computer-implemented method and an apparatus for improving experiences of an online visitor visiting a website detects a website access event. A visitor profile is generated by defining a plurality of attributes related to visitor activities on the website. A data field is allocated to each attribute to configure the visitor profile including a plurality of data fields. Each data field is capable of accommodating a respective fixed number of entries determined based on a temporal threshold value computed to determine a number of entries required for storing of information related to past activities that are relevant to current activity of the online visitor on the website. The visitor profile is dynamically updated based on the current activity. At least one intention of the online visitor is predicted based on a state of the visitor profile selected at a chosen time instant during the current activity of the online visitor.
The customer experience is enhanced by detecting leakage-to-voice from chats and providing recommendations to operations, chat agents, and customers. A chat is classified into leakage-to-voice or leakage-to-text chat and actionable recommendations are then provided to operations, chat agents, and customers based on the leakage information. Once leakage is identified, various other insights are extracted from chats and such insights are fed into the knowledge-base. Such insights also used in agent training and are provided to chat agents as recommendations. This results in a better customer experience.
A method and apparatus enables identification of customer characteristics and behavior, and predicts the customer's intent. Such prediction can be used to adopt various business strategies to increase the chances of conversion of customer interaction to a sale, and thereby can increase revenue, and/or enhance the customer's experience.
A computer-implemented method and an apparatus for facilitating staffing of resources receives customer data corresponding to a plurality of customers of an enterprise. At least one intention is predicted for each customer to configure a plurality of intentions. An expected volume of interactions is estimated for at least one time period based on the plurality of intentions. Each interaction in the expected volume of interactions is associated with interaction attributes. Resource data corresponding to a plurality of resources of the enterprise is received. Each resource is associated with a plurality of resource attributes. At least one resource is mapped to each interaction based on a match between resource attributes associated with the at least one resource and the interaction attributes associated with the each interaction. A staffing of the plurality of resources is facilitated based on the mapping of the at least one resource to the each interaction.
An apparatus and method is provided for creating, updating, and deleting business rules with ease by use of a rule manager. Business rules are represented as tables that map a set of inputs to a set of outputs. Inputs are represented as enumerations with predefined allowable values. All possible unique combinations of values for a given set of inputs are automatically generated, and a business user can then set the outputs for each desired input value combination.
A computer-implemented method and an apparatus for facilitating speech application testing generate a plurality of test scripts. A test script is generated by initiating a voice call interaction with a speech application including a network of interaction nodes, and repeatedly performing, until a stopping condition is encountered, the steps of, executing the voice call interaction by traversing through interaction nodes until an interaction node requiring a response is encountered, selecting an utterance generation mode, determining a response to be provided corresponding to the interaction node, and providing the response to the speech application. The test script comprises instructions for traversing interaction nodes and for provisioning one or more responses during the course of the voice call interaction. One or more test scripts from among the plurality of test scripts are identified based on a pre-determined objective and provided to a user for facilitating testing of the speech application.
H04M 1/64 - Automatic arrangements for answering calls; Automatic arrangements for recording messages for absent subscribers; Arrangements for recording conversations
H04M 3/493 - Interactive information services, e.g. directory enquiries
G10L 15/01 - Assessment or evaluation of speech recognition systems
H04M 3/22 - Arrangements for supervision, monitoring or testing
53.
Method, apparatus and non-transitory medium for customizing speed of interaction and servicing on one or more interactions channels based on intention classifiers
A computer-implemented method and apparatus for predicting customer intentions defines a plurality of categories for classifying customer interaction data. The plurality of categories includes at least one action category for classifying information related to customer actions on interaction channels. Data signals corresponding to a customer interaction on one or more interaction channels is received. The data signals include information related to at least one customer action. A sequence of values is generated for each customer action for classifying information related to the each customer action. A value is generated corresponding to each action category to configure the sequence of values. The sequence of values is associated with a fixed length equal to a number of action categories in the at least one action category. The fixed length of the sequence of values facilitates use of one or more intention classifiers to predict an intention of the customer.
Customer journey prediction and resolution is accomplished via a predictive model in which each user is mapped onto all available user journey information corresponding to a specific business. The predictive model is analyzed to understand the characteristics, preferences, and lowest effort resolution for the user related to the services that are subscribed to by the user. The predictive model is analyzed to predict the service or collection of services for each user. Embodiments interact with, provide and receive information from, and react to and/or deliver action to the customer across channels and across services. All customer and system behavior, data, and action is tracked and coordinated and leveraged for continuous feedback and performance improvement.
A computer-implemented method and an apparatus for modeling customer interaction experiences receives interaction data corresponding to one or more interactions between a customer and a customer support representative. At least one language associated with the interaction data is detected. Textual content in a plurality of languages is generated corresponding to the interaction data based at least in part on translating the interaction data using two or more languages different than the at least one language. At least one emotion score is determined for text corresponding to each language from among the plurality of languages. An aggregate emotion score is determined using the at least one emotion score for the text corresponding to the each language. An interaction experience of the customer is modeled based at least in part on the aggregate emotion score.
G06F 17/27 - Automatic analysis, e.g. parsing, orthograph correction
G06Q 10/06 - Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
A data assist application allows people to share structured data, and update and/or collaborate in real time. Companies can use embodiments of the invention to send and/or receive structured data. Embodiments of the data assist application work standalone or while a user is talking to a person or a company. In use, information is spread when people share data with non-users. The data are preferably owned and/or controlled by the user and stored on user devices. Further embodiments of the invention integrate with OS-supplied data and third party apps.
An intelligent IVR system identifies a customer based on previous customer interactions. Customer intent is predicted for an ongoing interaction and personalized services are proactively offered to the customer. A self-optimizing algorithm improves intent prediction, customer identity, and customer willingness to engage and use IVR.
A computer-implemented method and an apparatus for providing customer notification detects the presence of a customer in one or more interaction channels from among a plurality of interaction channels. The presence of the customer in the one or more interaction channels is stored as presence information. Attention information corresponding to the customer is determined in connection with the presence information. The attention information indicates a current attention of the customer. A notification is provided to the customer on an interaction channel from among the plurality of interaction channels over which the customer is identified to be active or most likely to be active, based on the presence information and the attention information.
An interactive voice response system receives a communication initiated by a remote requesting party. Based upon receipt at the interactive voice response system of the communication, visual data to provide to the remote requesting party as part of an integrated interactive script is determined. The visual data is provided to the remote requesting party as part of the integrated interactive script. Depending upon a selection of the remote requesting party, individual elements of the integrated interactive script are sent to the remote requesting party iteratively based upon interaction between the remote requesting party and the interactive voice response system, or multiple individual elements of the integrated interactive script are sent together to the remote requesting party, and individually presented to the remote requesting party based upon interaction between the remote requesting party and the interactive voice response system.
H04M 1/64 - Automatic arrangements for answering calls; Automatic arrangements for recording messages for absent subscribers; Arrangements for recording conversations
H04M 3/493 - Interactive information services, e.g. directory enquiries
H04W 4/16 - Communication-related supplementary services, e.g. call-transfer or call-hold
60.
Method and apparatus for predicting intent in IVR using natural language queries
An IVR system is disclosed in which customer experience is enhanced by improving the accuracy and intent prediction capabilities of an interactive voice response system. Customers are allowed to make a natural language queries to specify their intent, while the accuracy of traditional IVR systems is maintained by using key features in language along with the customer's past transactions, CRM attributes, and customer segment attributes to identify customer intent.
A system for providing automated assistance to an agent includes a database that stores an automated assistance session in association with a client terminal. The automated assistance session comprises communications between the client terminal and an agent terminal during a communication session. The automated assistance session is restored in response to a connection being reestablished with the client terminal after the client terminal disconnects during the communication session. A client communication is received from the client terminal, and a plurality of statements is determined based on the client communication and the communications of the automated assistance session stored in the database. The statements are configured to be manually selected by an agent or automatically selected by an automated agent. The automated agent is engaged for automatically selecting one of the statements in response to a predetermined condition.
A computer-implemented method and an apparatus for personalizing customer interaction experiences receives an input corresponding to at least one of a business objective and a customer interaction channel. A customer classification framework is selected based on the input. The customer classification framework is associated with a plurality of persona types, where each persona type is associated with a set of behavioral traits. A persona type for a customer is predicted from among the plurality of persona types during an interaction on the customer interaction channel. A propensity of the customer to perform at least one action is predicted based on the persona type. A provisioning of personalized interaction experience to the customer is facilitated based on the predicted propensity of the customer to perform the at least one action.
In accordance with an example embodiment a computer-implemented method and an apparatus for predicting and tracking of mood changes in textual conversations are provided. The method includes determining, by a processor, one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer. Changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation are tracked by the processor. Further, the method includes determining, by the processor, at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics.
A predictive model generator that enhances customer experience, reduces the cost of servicing a customer, and prevents customer attrition by predicting the appropriate interaction channel through analysis of different types of data and filtering of irrelevant data. The model includes a customer interaction data engine for transforming data into a proper format for storage, data warehouse for receiving data from a variety of sources, and a predictive engine for analyzing the data and building models.
With regard to searches and, more particularly, to searches performed on information repositories belonging to an enterprise, a centralized management system is used by the enterprise to manage the predictive search experience for users. A system offers a rich resolution experience to the end users based on user intent as determined from a variety of mechanisms, such as keywords, end user journey, clustered journey, etc. Also disclosed herein is a system that derives and offers various suggestions to end users to help them accomplish their objectives.
The customer experience is enhanced by detecting leakage-to-voice from chats and providing recommendations to operations, chat agents, and customers. A chat is classified into leakage-to-voice or leakage-to-text chat and actionable recommendations are then provided to operations, chat agents, and customers based on the leakage information. Once leakage is identified, various other insights are extracted from chats and such insights are fed into the knowledge-base. Such insights also used in agent training and are provided to chat agents as recommendations. This results in a better customer experience.
An interactive voice response system receives an initial communication initiated by a remote requesting party and addressed to a numbered communications address. Based upon receipt at the interactive voice response system of the initial communication, visual data to provide to the remote requesting party as part of an integrated interactive script is determined. The visual data is provided to the remote requesting party as part of the integrated interactive script. Depending upon a preference of the remote requesting party, individual elements of the interactive script are sent to the remote requesting party iteratively based upon interaction between the remote requesting party and the interactive voice response system, or multiple individual elements of the interactive script are sent together to the remote requesting party, and individually presented to the remote requesting party based upon interaction between the remote requesting party and the interactive voice response system.
H04M 1/64 - Automatic arrangements for answering calls; Automatic arrangements for recording messages for absent subscribers; Arrangements for recording conversations
H04M 3/493 - Interactive information services, e.g. directory enquiries
68.
Implementing a network of intelligent virtual service agents to provide personalized automated responses
An intelligent virtual service agent implemented on a computer platform is assigned a responsibility to automatically interact with different users across a communication network when a predetermined characteristic of content provided by the different users is identified. Content provided by a user over the communication network is analyzed to determine whether the content provided by the user possesses the predetermined characteristic. When the content possesses the predetermined characteristic, account data of the user for an account specific to the user is obtained, and the account data specific to the user is analyzed. The intelligent virtual service agent is assigned to automatically interact with the user based on the account data specific to the user and based on determining that the content possesses the predetermined characteristic.
The disclosure is related to mining of text to derive information from the text that is useful for a variety of purposes. The text mining process can be implemented in a service oriented industry such as a call center, where a customer and an agent engage in a dialog, e.g., to discuss product/service related issues. The messages in dialogues between the customers and the agents are tagged with features that describe an aspect of the conversation. The text mining process can mine various dialogues and identify a set of features and messages based on prediction algorithms. The identified set of features and messages can be used to infer an intent of a particular customer for contacting the agent, and to generate a recommendation based on the determined intent.
A context sensitive slider content area provides a slide out mechanism that is automatically actuated when additional information is needed during a chat session between an agent and a visitor, e.g. where a pre-chat and/or exit form is to be completed. The context sensitive slide out content area also provides problem resolution information to the visitor to help in solving problems, e.g. the top five problems; and also provides a self-service step-by-step wizard. A history section is provided with which the visitor can track back all previous steps carried out within the smart client. A history bar provides an iconic representation of all previous activities. A technique is also disclosed for executing various actions, such as form filling or requests for additional services, in a chat session.
G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
Customer journey prediction and resolution is accomplished via a predictive model in which each user is mapped onto all available user journey information corresponding to a specific business. The predictive model is analyzed to understand the characteristics, preferences, and lowest effort resolution for the user related to the services that are subscribed to by the user. The predictive model is analyzed to predict the service or collection of services for each user. Embodiments interact with, provide and receive information from, and react to and/or deliver action to the customer across channels and across services. All customer and system behavior, data, and action is tracked and coordinated and leveraged for continuous feedback and performance improvement.
A computer implemented method and an apparatus for facilitating voice user interface (VUI) design are provided. The method comprises identifying a plurality of user intentions from user interaction data. The method further comprises associating each user intention with at least one feature from among a plurality of features. One or more features from among the plurality of features are extracted from natural language utterances associated with the user interaction data. Further, the method comprises computing a plurality of distance metrics corresponding to pairs of user intentions from among the plurality of user intentions. A distance metric is computed for each pair of user intentions from among the pairs of user intentions. Furthermore, the method comprises generating a plurality of clusters based on the plurality of distance metrics. Each cluster comprises a set of user intentions. The method further comprises provisioning a VUI design recommendation based on the plurality of clusters.
A computer implemented method and an apparatus for determining user browsing behavior are provided. One or more web pages corresponding to a web domain are configured by associating the one or more web pages with tags. A control file is downloaded on a user device when a first web page access by a user to a tagged web page from among the one or more tagged web pages is detected. The control file facilitates recording of user activity related to a web domain on one or more tabs of a web browser associated with the user device. Recorded user activity corresponding to at least one web browsing session is received and user browsing behavior is determined based on the recorded user activity.
When conducting the same or similar search, different users can use different search terms and phrases, resulting in an increase in the quantity of unique search terms and phrases. The intent of the various search terms and phrases is determined based on clustering of the terms and phrases of the various users. User search terms bare clustered using semantic and syntactic distances. Thus, the search engine receives a search query from a user and computes a similarity between and among user search terms. The computation uses syntactic techniques to analyze lexical aspects of linguistic terms, and semantic techniques to consider activity of the user in the particular field of interest. A similarity metric is used to determine the similarity between two search terms by computing their syntactic and semantic distances. A clustering technique is then used to cluster search terms based on their pair-wise distance.
A system predicts the intent of a user and proactively offers to perform a query that satisfies that intent. Upon the user's acceptance of the offer, the system begins a search for related information. The system examines such factors as search terms typed or spoken by said user, historical attributes of said user, historical journey attributes of said user, current journey attributes of said user, user location, user movement, current time, user profile, user calendar, user information stored on, or associated with, a device within the user's possession. The system then makes a prediction of any of the user's intent, query category, and issue category. Based upon the results of the system's prediction, a query that is relevant to the user's intent and/or issue categories is presented and, upon the user's command, the results of the search are returned to the user.
An intelligent virtual service agent implemented on a computer platform with a processor and a memory is assigned a responsibility to automatically interact with different users via different mediums across a communication network when a predetermined characteristic of content provided by the users is identified. Content provided by a user is received over the communication network. The content provided by the user is analyzed to determine whether the content provided by the user possesses the predetermined characteristic. A determined is made, based on the analyzing, that the content possesses the predetermined characteristic. The intelligent virtual service agent is assigned to automatically interact with the user based on determining that the content possesses the predetermined characteristic.
User interactions are categorized into predefined hierarchical categories by classifying user interactions, such as queries, during a user interaction session by labeling text data into predefined hierarchical categories, and building a scoring model. The scoring model is then executed on untagged user interaction data to classify the user interactions into either action-based or information-based interactions.
G06F 15/18 - in which a program is changed according to experience gained by the computer itself during a complete run; Learning machines (adaptive control systems G05B 13/00;artificial intelligence G06N)
G06N 99/00 - Subject matter not provided for in other groups of this subclass
Embodiments of the invention relate to chat and, more particularly, to determining an that is to be action taken based on the type of chat session. The resolution of the chat is categorized to decide the necessary steps taken and also to monitor the agent's performance. A chat filter extracts relevant portions of a chat session. The relevant factors are taken into consideration and scored based on the feature vectors. A model is built and the type of resolution is determined. An analysis of the chat session is then performed taking into consideration several factors.
A company/organization is enabled to optimize sessions from an agent's perspective across multiple channels. Actions may be performed, such as monitoring the journey of a user across a self service application, raising alerts to the agent based on the journey, selecting an appropriate agent to whom a session may be routed, raising alerts for a supervisor, enabling the supervisor to track sessions and intervene if required, enable the agent to run commands from an interaction window, push links to launch applications to supplement the primary interaction through appropriate mechanisms, show appropriate responses to the agent on analyzing the session, and providing shortcut keys for the agent to allow the agent to insert appropriate responses into a chat session. Analysis is provided for the sessions, data is extracted from the sessions, and appropriate forms are populated with the data from the session and with agent information.
Embodiments of the invention relate to managing user interactions and, more particularly, to performing analysis on data generated by user interactions. Embodiments of the invention use text mining to extract personal information of users from user interactions automatically. A topic model is used to reduce the number of dimensions required to represent the text, yet all the information of interest is highly pronounced. This enables a lower dimensional representation of the data leading to significantly faster computations.
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
G06F 17/30 - Information retrieval; Database structures therefor
81.
Method and apparatus for building a user profile, for personalization using interaction data, and for generating, identifying, and capturing user data across interactions using unique user identification
A user profile is creates, and personalization is provided, by compiling interaction data. The interaction data is compiled to generate a value index or score from a user model. Parameterized data is used to build tools which help decide an engagement strategy and modes of engagement with a user. Several facets relating to the user, such as user behavior, user interests, products bought, intent, chat language, and so on, are compiled to create a user profile based personalization technique. In another embodiment, a unique ID is provided that can be mapped across multiple channels for use by the user to contact various organizations across multiple channels, and thus upgrade the user's experience.
User intent is identified while the user browses online and recommendations are provided to the user. The recommendations are based on the identified intent, interests, and preferences of the user who is performing the searches. The determination of user intent and interests is based on a statistical model derived from data compiled from the user and a plurality of other users. Other resources may also be determined to be relevant, for example, because of past interactions of the user, memberships of the user in ecommerce websites, the user's interests and preferences are similar to those of other users, and so on. The result of the user search is a ranked set of recommendations that is provided to the user.
A computing method and system is disclosed for analyzing interactions between a user and a customer support agent. Typical interactions include inquiries about a product or service, and a service call. When the user purchases a good or service, or successfully completes a service call, the customer converts, e.g. the sales pitch or service solution was successful. If the customer does not convert, then the interaction between user and agent is analyzed to determine why the user did not convert and whether the user should be categorized for potential retargeting.
The propensity and intent of a user to make a purchase is predicted based on product search queries and chat streams. The contents of the data sources, including search queries and chat streams, are analyzed for product names and product attributes. The results of the analyses are used to predict user needs. Product names and attributes are extracted from the data sources. The extracted information is mapped onto abstract product categories. Based on the abstract product categories, offers for products and services are made to the user.
The stages of an interaction between a potential customer (the user) and a sales representative (the agent) during a sales interaction are identified to understand the interaction factors that drive sales and, by doing so, to serve the customer better and thus increase sales. Initially, a user makes contact with an agent via a communications network. During the interaction, a dropping point is reached, i.e. the point in the interaction at which either the user or the agent ends the interaction. The dropping point and other interaction factors is analyzed. Based upon such analysis, various recommendations are made to the agents to improve the user's sales experience.
The customer experience is enhanced by detecting leakage-to-voice from chats and providing recommendations to operations, chat agents, and customers. A chat is classified into leakage-to-voice or leakage-to-text chat and actionable recommendations are then provided to operations, chat agents, and customers based on the leakage information. Once leakage is identified, various other insights are extracted from chats and such insights are fed into the knowledge-base. Such insights also used in agent training and are provided to chat agents as recommendations. This results in a better customer experience.
A context-aware computing system for delivering surveys to a customer. The choice of which survey to send to a customer may be tailored based on a click path (route), customer history, and customer interests. A customer browsing a Web page initiates the survey decision process. A control module selects a survey to send to a customer based on the criteria above and customer intent. Customer responses are then harvested from the Web-based survey.
An IVR system is disclosed in which customer experience is enhanced by improving the accuracy and intent prediction capabilities of an interactive voice response system. Customers are allowed to make a natural language queries to specify their intent, while the accuracy of traditional IVR systems is maintained by using key features in language along with the customer's past transactions, CRM attributes, and customer segment attributes to identify customer intent.
The location of a user is obtained and, based on the location of the user and services available to, or requested by the user, a notification handler sends appropriate notifications to the user.
An intelligent IVR system identifies a customer based on previous customer interactions. Customer intent is predicted for an ongoing interaction and personalized services are proactively offered to the customer. A self-optimizing algorithm improves intent prediction, customer identity, and customer willingness to engage and use IVR.
A method and apparatus for a computer-implemented technique for maximizing customer satisfaction and first call resolution, including converting telephone calls into online chats, while minimizing cost is provided. Techniques for incorporating analytics as applied to customer data into particular strategies for call deflection, targeting particular individuals to increase chat acceptance rate, and computing a customer's wait time are also provided.
G06F 3/00 - Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
A mechanism for facilitating customer interactions within a customer service environment provides prompt and accurate answers to customer questions. A smart chat facility for use in a customer service environment to predict a customer problem examines a customer chat transcript to identify customer statements that set forth a customer issue and, responsive to this, can route the customer to an agent, an appropriate FAQ, or can implement a problem specific widget in the customer UI. Customer queries are matched with most correct responses and accumulated knowledge is used to predict a best response to future customer queries. The iterative system thus learns from each customer interaction and can adapt to customer responses over time to improve the accuracy of problem prediction.
Unique customer identification and behavior is linked between either concurrent or sequential channels of engagement. Unique identifiers are created, captured, and/or passed between these multiple contact channels, e.g. Web, mobile, IVR, phone, automotive, television, to identify and tag the customer and their context, e.g. history, pass behavior, steps progressed, obstacles and/or issues encountered, etc., uniquely.
A customer support system diverts a customer to an integrated support service to serve the customer better in situations where the use of a single mode of interaction is insufficient. Embodiments of the invention find use where an email or SMS is sent to a customer's smart devices with a link to visual content which helps customer better understand the information.
H04M 1/64 - Automatic arrangements for answering calls; Automatic arrangements for recording messages for absent subscribers; Arrangements for recording conversations
A data assist application allows people to share structured data, and update and/or collaborate in real time. Companies can use embodiments of the invention to send and/or receive structured data. Embodiments of the data assist application work standalone or while a user is talking to a person or a company. In use, information is spread when people share data with non-users. The data are preferably owned and/or controlled by the user and stored on user devices. Further embodiments of the invention integrate with OS-supplied data and third party apps.
An apparatus and method is provided for creating, updating, and deleting business rules with ease by use of a rule manager. Business rules are represented as tables that map a set of inputs to a set of outputs. Inputs are represented as enumerations with predefined allowable values. All possible unique combinations of values for a given set of inputs are automatically generated, and a business user can then set the outputs for each desired input value combination.
An enterprise application integration system (EAIS) is disclosed that enables customer service applications to access and share data with enterprise information systems in real time.
A method and apparatus enables identification of customer characteristics and behavior, and predicts the customer's intent. Such prediction can be used to adopt various business strategies to increase the chances of conversion of customer interaction to a sale, and thereby can increase revenue, and/or enhance the customer's experience.
A company/organization is enabled to optimize sessions from an agent's perspective across multiple channels. Actions may be performed, such as monitoring the journey of a user across a self service application, raising alerts to the agent based on the journey, selecting an appropriate agent to whom a session may be routed, raising alerts for a supervisor, enabling the supervisor to track sessions and intervene if required, enable the agent to run commands from an interaction window, push links to launch applications to supplement the primary interaction through appropriate mechanisms, show appropriate responses to the agent on analyzing the session, and providing shortcut keys for the agent to allow the agent to insert appropriate responses into a chat session. Analysis is provided for the sessions, data is extracted from the sessions, and appropriate forms are populated with the data from the session and with agent information.
Customer journey prediction and resolution is accomplished via a predictive model in which each user is mapped onto all available user journey information corresponding to a specific business. The predictive model is analyzed to understand the characteristics, preferences, and lowest effort resolution for the user related to the services that are subscribed to by the user. The predictive model is analyzed to predict the service or collection of services for each user. Embodiments interact with, provide and receive information from, and react to and/or deliver action to the customer across channels and across services. All customer and system behavior, data, and action is tracked and coordinated and leveraged for continuous feedback and performance improvement.
patents
