Patent Publication Number: US-2019197559-A1

Title: System and method for using a personal bot

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit of prior-filed, co-pending U.S. Provisional Patent Application No. 62/609,519, filed on Dec. 22, 2017, the contents of which are incorporated herein by reference in their entirety. 
    
    
     BACKGROUND 
     The present disclosure is directed to a system and method for contact centers with a computer-telephony arrangement, more specifically to a system and method for using a bot to assist a contact center agent. 
     In a customer service environment, when contacting an organization, customers typically desire human to human interaction in order to solve their problem or answer their query. However, organizations are continuously looking at ways of reducing their workforce (as this typically represents a large portion of their cost) whilst balancing the need to provide customer service to the organization&#39;s standard. 
     In recent years, the advent of synchronous text chat has meant that a customer service representative (CSR) can deal with both a telephone call as well as multiple text chat conversations simultaneously. There are limits today where a CSR can only handle a single telephone call at a time and a few text chats simultaneously. Too many text chats at one time may breach the cognitive load capabilities of a particular CSR. The current level of simultaneously interaction handling that a CSR can perform still does not meet the cost profile of certain organizations who look to reduce costs further. 
     BRIEF SUMMARY 
     The present invention is a method for utilizing a personal bot. The method receives a customer contact, adds the customer contact to a CEC desktop, accesses a customer service module to answer the customer contact, receives and analyzes a customer query within the customer contact, accesses at least one of a customer service module and a document database to formulate a response to the customer query, and calculates a confidence level in the response. 
     The present invention also includes a system for utilizing a personal bot, comprising a processor and a non-transient computer readable medium programmed with computer readable code that upon execution by the processor causes the processor to execute the above method for utilizing a personal bot. 
     The present invention also includes a non-transient computer readable medium programmed with computer readable code that upon execution by a processor causes the processor to execute the above method for utilizing a personal bot. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWING(S) 
         FIG. 1  illustrates a block diagram of an exemplary embodiment of a CEC system using a personal bot according to the present application. 
         FIG. 2  illustrates a block diagram of an exemplary embodiment of a system for utilizing a personal bot according to the present application. 
         FIGS. 3 a , 3 b , and 3 c    illustrate a flow chart of an exemplary embodiment of a method of utilizing a personal bot according to the present application. 
     
    
    
     DETAILED DESCRIPTION 
     In the present description, certain terms have been used for brevity, clearness and understanding. No unnecessary limitations are to be applied therefrom beyond the requirement of the prior art because such terms are used for descriptive purposes only and are intended to be broadly construed. The different systems and methods described herein may be used alone or in combination with other systems and methods. Various equivalents, alternatives and modifications are possible within the scope of the appended claims. Each limitation in the appended claims is intended to invoke interpretation under 35 U.S.C. § 112, sixth paragraph, only if the terms “means for” or “step for” are explicitly recited in the respective limitation. 
     In order to increase the throughput of a particular CSR, a personal bot may augment the CSR and allow the CSR to effectively handle far more synchronous channels in parallel than is possible in current systems. The bot may autonomously handle parts of a phone call or text chat and only require the CSR to take over the chat or phone call when it can&#39;t progress or sees something it doesn&#39;t understand. 
     During a phone call or text chat where the CSR is in control, the CSR may ask the bot to perform basic tasks through text chat or over the phone call. For example, the CSR may ask the bot for customer identification and verification to capture a new address for a house move, or other script driven actions. The bot will suggest when it can take on repetitive tasks such as sending terms and conditions by email or text chat or reading out terms on a call to the customer. The bot may also take over these tasks automatically. This will allow the CSR to deal with other interactions as necessary. In certain embodiments, the bot will auto reply if its confidence level exceeds a given threshold. CSR control will move to become a monitor of multiple customer-bot interactions. When the bot&#39;s confidence level of how to proceed drops does not exceed the threshold, the CSR may take over or otherwise guide the bot. 
     The bot will learn to be like its human CSR counterpart, will communicate with the customer with the same mannerisms (e.g. grammar, style, speed) and, if for a phone call, with the same voice—this will make escalation transparent. For a video chat system, the video may be synthesized to look like the human agent. 
     The bot may give context and reminders to the human CSR, for example push compliance rules when a financial query is presented from customer. During interactions the bot and CSR will be able to privately communicate to each other (through text or other visual interface, voice or a direct neural interface). There will be prompts to ensure the CSR always knows whether it is the CSR or the bot who is currently speaking to or text chatting or video chatting to the customer. 
     The bot will learn from the CSR and, over time, increase the range of processes, issues and queries it can help with thereby increasing the parallel throughput of the CSR. The bot will monitor and analyze the CSR&#39;s actions and behavior and learning through desktop process analytics and text and speech analytics. 
     In this system, the personal bot is considered an extension of the human CSR. As it increases range and capabilities, the bot may be able to teach human CSRs as well. 
       FIG. 1  illustrates a block diagram of an exemplary embodiment of a CEC system  100  using a personal bot  110  according to the present application. The CEC system  100  receives and utilizes data from at least one CSR (not shown), at least one external contact (by way of non-limiting example, a customer or potential customer), optionally at least one internal contact (by way of non-limiting example, a supervisor or quality assurance (QA) specialist), and/or any combination thereof. The CEC system  100  includes at least one personal bot  110  connected to at least one customer service module  120  and/or document database  130 , at least one CEC desktop  140 , and at least one optional system input  150 . 
     The personal bot  110  is configured to constantly receive and analyze data within the CEC system  100 . The analysis may be a real-time analysis of streaming data or a batch analysis of data. The personal bot  110  includes at least one set of analytics rules  111  used to analyze data. The analytics rules  111  determine responses to information extracted from the received data, governing which customer service modules  120  and/or document databases  130  are accessed by the personal bot  110 , and what module functions and/or documents are utilized. 
     The analytics rules  111  can also be used to calculate confidence levels for personal bot  110  and to compare them to at least one given threshold. The threshold may be a part of analytics rules  111 . A high confidence level (i.e., exceeding the threshold) indicates an acceptable likelihood that the response is accurate. A low confidence level (i.e., not exceeding the threshold) indicates an unacceptable likelihood that the response is accurate; in such a case, the personal bot  110  may bring the customer contact to the attention of a CSR. 
     The analytics rules  111  may be static or they may be dynamically updated by personal bot  110 , customer service module  120 , and/or a user or third party utilizing the CEC desktop  140  or the system input  150 . Updates to the analytics rules  111  may be manual or automatic. Automatic updates to analytics rules  111  may be triggered by meeting certain criteria within analytics rules  111  of personal bot  110  or within the customer service modules  120 , or may occur at predetermined intervals. Analytics rules  111  may be software programs or separate files executed by a software program. 
     While the exemplary embodiment includes two personal bots  110 , the CEC system  100  may include more personal bots  110  or only one personal bot  110 . In embodiments with multiple personal bots  110 , the personal bots  110  may be constantly connected, periodically connected, interconnected through at least one customer service module  120  and/or document database  130 , or separate. In embodiments with a single personal bot  110 , personal bot  110  is connected, directly or indirectly, to all customer service modules  120 , document databases  130 , the CEC desktops  140 , and/or the system inputs  150 . 
     The customer service modules  120  are connected to personal bot  110 , and optionally other customer service modules  120 , document databases  130 , and/or CEC desktops  140 . In certain embodiments, some customer service modules  120  connect personal bot  110  to certain other customer service modules  120  and/or document databases  130 . Customer service modules  120  provide different customer service functionalities to CEC system  100 . A single customer service module  120  may perform multiple processes, a single process, and/or part of a larger process. In embodiments with multiple personal bots  110 , each personal bot  110  may have its own set of customer service modules  120  or may share all or some specific customer service modules  120 . Customer service modules  120  can be updated by adding, updating, or removing specific customer service modules  120 . The connections between personal bots  110 , customer service modules  120 , document databases  130 , and CEC desktops  140  may also be updated. 
     By way of non-limiting example, customer service modules  120  may perform voice and text analytics, QA analytics, analytics relating to usage of CEC desktop  140  or other available resources, and any other analysis related necessary for the activities of personal bot  110  during customer service interactions. Customer service modules  120  may provide the results of such analyses to personal bot  110  or to other customer service modules  120 . By way of further non-limiting example, customer service modules  120  may also retrieve information for personal bot  110  and/or the CSR, such as customer profiles and history, scripts or templates for communication, internal customer service documentation, and any other customer service information. By way of further non-limiting example, customer service modules  120  may also interact with the functions of CEC desktop  140 . Such interactions may allow another CEC desktop  140  to observe and/or share another CEC desktop  140 , and utilize, update, or transmit or retrieve information to or from certain functions of the CEC desktop  140 . 
     Document databases  130  are connected to personal bot  110  and may be connected to other document databases  130  and/or customer service modules  120 . Document databases  130  store documents for use by CEC system  100 . By way of non-limiting example, document databases  130  may store customer profiles and history, scripts or templates for communication, help screens, forms, internal customer service documentation, routing logs, analysis results, and any other customer service information. Documents stored in document databases  130  may be categorized by type, matter, applicable process, or any other possible classification schema. Document databases  130  and the information contained therein can be updated by adding or removing information to documents in document database(s)  130 , adding or removing entire documents to or from document database(s)  130 , or adding or removing entire specific document database(s)  130 . The connections between personal bots  110 , customer service modules  120 , and document databases  130  may also be updated. 
     CEC desktop  140  receives and displays documents from document databases  130  and the results of any analyses from customer service modules  120 , if applicable, as relayed by personal bot  110 . Processes from customer service modules  120  may also interact with the processes of CEC desktop  140 . By way of non-limiting example, if the personal bot  110  is unable to assist a customer, the CSR may use CEC desktop  140  to take over the interaction. If personal bot  110  is used to train a CSR, personal bot  110  may route training exercises or allow “eavesdropping” through CEC desktop  140 . 
     System input  150  allows a user to update analytics rules  111 . This allows a supervisor, system administrator, or other third party to make changes precisely to analytics rules  111 , as opposed to updates which may be caused by usage or made through CEC desktop  140 . System input  150  connects to at least one personal bot  110 . 
       FIG. 2  illustrates a block diagram of an exemplary embodiment of a system  200  for utilizing a personal bot  110  according to the present application. The system  200  is generally a computing system that includes a processing system  206 , a storage system  204 , software  202 , a communication interface  208 , and at least one user interface  210 . The processing system  206  loads and executes software  202  from the storage system  204 , including a software module  220 . When executed by computing system  200 , software module  220  directs the processing system  206  to operate as described in herein in further detail in accordance with the method  300  for using the personal bot  110 , described below. 
     The computing system  200  includes a software module  220  for performing the function of CEC system  100 . Although computing system  200  as depicted in  FIG. 2  includes one software module  220  in the present example, it should be understood that more modules could provide the same operation. Similarly, while the description as provided herein refers to a computing system  200  and a processing system  206 , it is to be recognized that implementations of such systems can be performed using one or more processors, which may be communicatively connected, and such implementations are considered to be within the scope of the description. It is also contemplated that these components of computing system  200  may be operating in a number of physical locations. 
     The processing system  206  can comprise a microprocessor and other circuitry that retrieves and executes software  202  from storage system  204 . The processing system  206  can be implemented within a single processing device but can also be distributed across multiple processing devices or sub-systems that cooperate in existing program instructions. Examples of processing systems  206  include general purpose central processing units, application specific processors, and logic devices, as well as any other type of processing device, combinations of processing devices, or variations thereof. 
     The storage system  204  can comprise any storage media readable by processing system  206 , and capable of storing software  202 . The storage system  204  can include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other information. The storage system  204  can be implemented as a single storage device but may also be implemented across multiple storage devices or sub-systems. The storage system  204  can further include additional elements, such a controller capable of communicating with the processing system  206 . 
     Examples of storage media include random access memory, read only memory, magnetic discs, optical discs, flash memory, virtual memory, and non-virtual memory, magnetic sets, magnetic tape, magnetic disc storage or other magnetic storage devices, or any other medium which can be used to store the desired information and that may be accessed by an instruction execution system, as well as any combination or variation thereof, or any other type of storage medium. In some implementations, the storage media can be a non-transitory storage media. In some implementations, at least a portion of the storage media may be transitory. Storage media may be internal or external to system  200 . 
     As described in further detail herein, computing system  200  receives and transmits data through communication interface  208 . The data can include verbal or textual communications, such as, but not limited to, queries to or from a customer, responses to such queries, and/or details about a request, a work order, or another set of data that will necessitate an interaction between a customer and the CSR and/or system  200 . In embodiments, the communication interface  208  also operates to send and/or receive information, such as, but not limited to, information to/from other systems to which computing system  200  is communicatively connected, and to receive and process information as described in greater detail above. Such information can include responses to customer queries, average handling time, and the subject matter and nature of the communication requested by the customer. 
     The at least one user interface  210  can include a mouse, a keyboard, a voice input device, a touch input device for receiving a gesture from a user, a motion input device for detecting non-touch gestures and other motions by a user, and/or other comparable input devices and associated processing elements capable of receiving user input from a user. Output devices such as a video display or graphical display can display CEC desktop(s)  140 , documents, or another interface further associated with embodiments of the system and method as disclosed herein. Speakers, electronic transmitters, printers, haptic devices and other types of output devices may also be included in the user interface  210 . A CSR or other staff can communicate with computing system  200  through the user interface  210  in order to view documents, enter or receive data or information, enter information, manage an interaction, or any number of other tasks the CSR or other staff may want to complete with computing system  200 . 
       FIGS. 3 a , 3 b , and 3 c    illustrate a flow chart of an exemplary embodiment of a method  300  of utilizing a personal bot according to the present application. 
     As shown in  FIG. 3 a   , in step  302 , the CEC desktop  140  receives a CSR log in. 
     In step  304 , the CEC system  100  receives a customer contact. 
     In step  306 , the CEC system  100  adds the customer contact to the CSR&#39;s CEC desktop  140 . The display on CEC desktop  140  may include prompts to ensure the CSR always knows whether it is the CSR or personal bot  110  who is currently speaking to, text chatting, video chatting, or otherwise interacting with the customer. 
     In optional step  308 , CEC system  100  receives manual direction from the CSR for personal bot  110  to answer the customer contact. 
     In step  310 , personal bot  110  automatically accesses a customer service module  120  to answer the customer contact. 
     In step  312 , personal bot  110  receives and analyzes a query from the customer within the customer contact. 
     As shown in  FIG. 3 b   , in step  314 , personal bot  110  accesses at least one customer service module  120  and/or document database  130  to formulate a response to the customer&#39;s query. 
     In step  316 , personal bot  110  calculates a confidence level in the response. 
     In optional step  318 , personal bot  110  answers the customer&#39;s query with the response due to a high calculated confidence level. The answer to the query may take the form of outputting the response on CEC desktop  140 , either simultaneously with providing the response to the customer, or for the CSR to provide to the customer. Alternately, personal bot  110  may simply answer the query without providing the response to the CSR. 
     In optional step  320 , the customer contact is activated for the CSR on CEC desktop  140  due to a low calculated confidence level. CEC system  100  may provide a notification to the CSR on CEC desktop  140  that the customer contact is active, such as an audiovisual alert. Optionally, the notification may include the response to the query formulated by personal bot  110  and/or the calculated confidence level. 
     In optional step  322 , the CSR answers the customer&#39;s query. This may require the CSR to manually access at least one customer service module  120  and/or document database  130  through CEC desktop  140 . 
     As shown in  FIG. 3 c   , in optional step  324 , the customer provides another query and returns to step  308 . 
     In optional step  326 , CEC system  100  receives customer feedback for any of the preceding steps. 
     In optional step  328 , personal bot  110  accesses at least one customer service module  120  and/or document database  130  to record any information related to the customer&#39;s query, such as, but not limited to, the nature of the query, the answer provided, or any customer feedback. 
     In optional step  330 , personal bot  110  uses analytics rules  111  and data from the preceding interactions to analyze the preceding interactions. 
     In optional step  332 , personal bot  110  updates analytics rules  111  to improve its performance. 
     Due to the multi-channeled nature of personal bot  110 , any of the various steps may take place serially, simultaneously, or substantially overlapping with other steps. 
     In the foregoing description, certain terms have been used for brevity, clearness, and understanding. No unnecessary limitations are to be inferred therefrom beyond the requirement of the prior art because such terms are used for descriptive purposes and are intended to be broadly construed. The different configurations, systems, and method steps described herein may be used alone or in combination with other configurations, systems and method steps. It is to be expected that various equivalents, alternatives and modifications are possible within the scope of the appended claims.