Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-13, 15-29, 31, and 32 are pending.
Claims 1, 7, 17, and 23 have been amended.
Claims 14 and 30 were previously cancelled. No claims are added.
Response to Arguments
Applicant's arguments filed January 1, 2026, have been fully considered. With regards to Applicant’s arguments regarding Section 112(f), it is again noted that no rejection is set forth. Section 112(f) is an interpretation, not a rejection. Indefiniteness rejections are Section 112(b).
Applicant argues that the claims connote sufficiently definite structure, but fail to identify such structure. Rather, as also note in the arguments, the claims seem to refer to specific classes of software modules, and the Section 112(f) interpretation in view of paragraphs [0188]-[0190] of the instant specification provide the necessary structural basis for the claims. It is also noted that, while the claims set forth a processor and a memory, two elements with well understood structural basis, the remaining limitations of claim 1 are set forth without reference to the previously recited processor and memory. That is, after reciting the processor and the memory, claim 1 recites “said communication system comprising:” before reciting a variety of “system” limitations with no structural basis. As such, Applicant’s argument that the processor and memory “implement” the “ticket system” and “inbox/feed system” is not correct in view of the language “said communication system comprising:” before reciting those “system” limitations. As such, the interpretation is maintained.
Applicant's arguments with respect to the Section 103 rejection have been fully considered but they are not persuasive. The arguments are directed to the combination of Williams and Lange, but fail to identify any deficiency in the relied upon teaching for the limitation being discussed, which is found in Williams alone. Futhermore, while the arguments are directed to the limitation reciting “a list of agents and their activity information” which is clearly shown in Fig. 23 of Williams, nothing in the claims actually requires multiple agents. Rather, claims 1 and 17 recite “activities from at least one agent associated with said supported system”. As such, the whole of Applicants arguments in not directed to the limitations of the claims on file. As such, the arguments are not persuasive. The rejection has been updated as necessary to address the amendments to the claims.
Information Disclosure Statement
The information disclosure statement filed 01/01/2026 fails to comply with 37 CFR 1.98(a)(3)(i) because it does not include a concise explanation of the relevance, as it is presently understood by the individual designated in 37 CFR 1.56(c) most knowledgeable about the content of the information, of each reference listed that is not in the English language. It has been placed in the application file, but the information referred to therein has not been considered.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term (e.g. unit) used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use nonce terms such as “unit” and “system” are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the nonce terms “unit” and “system” are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. As such, claims 1-16 in this case are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, and in keeping with paragraphs [0188]-[0190] of the specification.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-13, 15-29, 31, and 32 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 2019/0347668 to Williams et al. in view of U.S. Patent Application Publication No. 20170330195A1 to Lange et al.
With regards to claims 1 and 17, Williams et al. teaches:
a processor; and a memory storing instructions that when executed by said processor (paragraph [0182], “The processing system 300 includes one or more processors that execute computer-readable instructions and non-transitory memory that stores the computer-readable instructions. In implementations having two or more processors, the two or more processors can operate in an individual or distributed manner. In these implementations, the processors may be connected via a bus and/or a network.”; see also paragraphs [0299]-[0304]) create a dynamic display of multiple tickets on a user interface (UI), the tickets representing an incoming event for a supported system supported by said communication system having two-way data access (paragraph [0208], “In the example of FIG. 44, the user has created a workflow action with respect to the new ticket status. The GUI 4000 displays the workflow action with respect to the corresponding new ticket status.”; paragraph [0237], “In a first example, in response to a service specialist taking a call from the contact for a first time regarding a particular ticket, the client-specific service system 1900 may display a ticket history to the specialist that indicates that the user has purchased App Creator, that the contact's issue is with content integration, and that the contact has been sent the Emoji Support article. In another example, an automated workflow process servicing the ticket may retrieve the ticket node to learn that the contact has already been sent the Emoji Support article, so that it may determine a next course of action. In another example, an analytics tool may analyze all the tickets issued with a particular product and the issues relating to those tickets.”; and paragraphs [0254]-[0257]), said communication system comprising:
a repository storing at least pre-defined rules for ticket creation (paragraph [0016], “The system further includes a proprietary database that stores contact records and ticket records, wherein the proprietary database also supports at least one of a sales workflow and a marketing workflow. The system also includes a knowledge graph that stores information relating to the client, the contact, and content that may be referenced during an attempted resolution of a ticket according to the service workflow.”);
a ticket system configured to receive said incoming event and related activities from at least one agent associated with said supported system (paragraph [0005], “The method includes receiving, by the processing system, a set of customization parameters corresponding to the set of service features from the client, wherein the customization parameters include a set of custom ticket attributes and a ticket pipeline definition.”) via at least two different communication channels (paragraph [0272], “For example, the client may opt from one or more of a ticket support, ticket workflow management, multiple ticket workflows, email/chat and ticket integration, customized email templates, knowledge graph support, conversation routing, customer service website that includes recommended content (e.g., articles or videos on solving common problems), a chat bot (text-based and/or audio-based), automated routing to service specialists, live chat, customer service analytics, customized reporting, and the like.”) between said supported system and said at least one agent, said activities having changing levels of interactivity (paragraph [0193], “For example, a client, via a client device 1640, may provide selections of one or more features and capabilities enabled in the platform 1600 as described throughout this disclosure (e.g., automated content generation for communications, automated chat bots, AI-generated follow up emails, communication integration, call routing to service experts, and the like) via a graphical user interface (e.g., drop-down menu, a button, text box, or the like). A client, via a client device 1640, may also use the platform 1600 to find and provide content that may be used to help provide service or support to its contacts (e.g., articles that answer frequency asked questions, “how-to” videos, user manuals, and the like) via a graphical user interface (e.g., an upload portal).”; paragraph [0231], “In embodiments, the additional ticket data 1752 may include or reference the specialist or specialists that have helped service the ticket (e.g., employee IDs), any notes entered by specialists, a number of notes entered by the specialists, a list of materials that have been sent to the contact during attempts to resolve the issue, and the like. In embodiments, the ticket data 1752 may include references to transcripts of conversations with the contact over different mediums. For example, the ticket data 1752 may include or reference conversations had with a bot, over email, in text message, over social media, and/or with a customer service specialist.”; paragraph [0268], “In embodiments, the feedback module 1916 is trained to determine the appropriate communication channel to request feedback (e.g., email, text message, push notification to native application, phone call, and the like).”),
said ticket system to create and update at least one ticket of said multiple tickets according to said pre-defined rules (paragraph [0274], “The default ticket attributes may be a set of ticket attributes that must remain in the ticket. Examples of default ticket attributes, according to some implementations of the platform 1600, may include (but are not limited to) one or more of a ticket ID or ticket name attribute (e.g., a unique identifier of the ticket), a ticket priority attribute (e.g., high, low, or medium) that indicates a priority of the ticket, a ticket subject attribute (e.g., what is the ticket concerning), a ticket description (e.g., a plain-text description of the issue to which the ticket pertains) attribute, a pipeline ID attribute that indicates a ticket pipeline to which the ticket is assigned, a pipeline stage attribute that indicates a status of the ticket with respect to the ticket pipeline in which it is being processed, a creation date attribute indicating when the ticket was created, a last update attribute indicating a date and/or time when the ticket was last updated (e.g., the last time an action occurred with respect to the ticket), a ticket owner attribute that indicates the contact that initiated the ticket, and the like.”); and
an inbox/feed system to dynamically update a display showing said UI together with a feed of status indicators ()paragraph [0081], “In embodiments, the customer relationship management system 158 may include one or more customer data records 164, such as reflecting data on groups of customers or individual customers, including demographic data, geographic data, psychographic data, data relating to one or more transactions, data indicating topics of interest to the customers, data relating to conversations between agents of the enterprise and the customers, data indicating past purchases, interest in particular products, brands, or categories, and other customer relationship data. The customer data records 164 may be used by the platform 100 to provide additional suggested topics 138, to select among suggested topics 138, to modify suggested topics 138, or the like. In embodiments, the CRM system 158 may support interactions with a customer, such as through a customer chat 184, which in embodiments may be edited in the user interface 152 of the content development and management application 150, such as to allow a writer, such as an inside sales person or marketer who is engaging in the customer chat 184 with the customer to see suggested topics 138 that may be of interest to the customer, such as based on the customer data records 164 and based on relevancy of the topics to the main differentiators of the enterprise.”; paragraph [0213], “For example, a request may be received from a contact request (e.g., a contact fills out a form from the client's website or a website hosted by the platform 1600 on behalf of the client), a chat bot (e.g., when a contact raises a specific issue in a chat with the chat bot), via a customer service specialist (e.g., the client calls a service specialist and the service specialist initiates the request), and the like. In response to receiving a ticket request, the ticket management system 1604 generates a new ticket from a ticket object corresponding to the ticket type. The ticket management system 1604 may include values in the ticket attributes of the ticket based on the request, including the ticket type attribute, the subject attribute, the description attribute, the date/time created attribute (e.g., the current date and/or time), the last update attribute (e.g., the current date and/or time), the owner attribute (e.g., the contact identifier), and the like.”) for said changing levels of interactivity according to content and said at least two different communication channels for said multiple tickets (paragraph [0231], “In embodiments, the additional ticket data 1752 may include or reference the specialist or specialists that have helped service the ticket (e.g., employee IDs), any notes entered by specialists, a number of notes entered by the specialists, a list of materials that have been sent to the contact during attempts to resolve the issue, and the like. In embodiments, the ticket data 1752 may include references to transcripts of conversations with the contact over different mediums.”; paragraph [0232], “The ticket timeline can identify when the ticket was initiated, when different actions define in the workflow occurred (e.g., chat bot conversation, sent link to FAQ, sent article, transferred to customer service specialist, made house call, resolved issue, closed ticket, and the like). The ticket timeline of a ticket record 1740 can be updated each time a contact interacts with a client-specific service system with respect to a particular ticket.”), said inbox/feed system comprising:
….; and
a feed constructor to dynamically construct said feed of multiple tickets for display based on said-combined data (paragraph [0245], “The communication integrator 1902 may then transfer the communication session to a different medium. In some embodiments, the sequence by which a communication session is transferred (e.g., escalating from a chat bot to a specialist or escalating from a text-based chat to a phone call) is defined in a custom workflow provided by the client. The communication integrator 1902 may feed the obtained data to the medium. For example, if being transferred to a specialist, the communication integrator 1902 may populate a GUI of the specialist with the ticket information (e.g., ticket ID and current issue), contact information, the ticket status, transcripts of recent conversations with the contact, and/or the like. The communication session may then commence on the new medium without the contact having to provide any additional information to the system 1900.”), and
a dynamic view constructor to construct a view displaying a list of agents and their activity information, said list derived from an analysis of activities associated with said multiple tickets (Fig. 23, paragraph [0254], “In embodiments the service specialist portal may include chat interfaces, visualization tools that display a specialist's open tickets and/or various communication threads, analytics tools, and the like. Upon a contact and/or ticket being routed to a service specialist, the communication integrator 1902 may provide the specialist with all relevant data pertaining to the contact and/or the ticket.”; paragraph [0257], “The GUI 2300 displays a set of open tickets and where the tickets are with respect to the client's ticket pipeline. In this example arrangement, the specialist or supervisor can view tickets that are new, tickets that are awaiting communication from the contact, tickets that have progressed to the email stage, tickets that have been resolved, and tickets that have been closed. Each ticket assigned to the specialist may be displayed in a respective card, whereby the card provides a synopsis of the ticket (e.g., date created, contact name, and general issue).”).
While Williams et al. teaches a communication integrator communication integrator to retrieve or otherwise obtain information that is relevant to the current communication session, including a ticket ID, contact information (e.g., username, location, etc.), the current issue (e.g., the reason for the ticket), and/or other suitable information, including information obtained from the databases and/or knowledge graph, and that the communication integrator may then transfer the communication session to a different medium (or communication channels) such as when a communication session is transferred (e.g., escalating from a chat bot to a specialist or escalating from a text-based chat to a phone call) as defined in a custom workflow provided by the client (see paragraph [0245] et seq.), but fails to explicitly teach combine data collected from said supported system with said ticket information. However Lange et al. teaches:
an information deriver to combine data collected from said supported system with said ticket information (paragraph [0245], “The CoPilot user interface or integrated support interface runs on the front end such as on a browser or the users device and receives input from the end user. This received user input may include collection handling 1334 such as notes, screenshots and object references. The user input also may include virtual assistant and integrated help 1336, chat 1338, user activity tracking 1340 and notification handling 1342.”; paragraph [0246], “The application connector 1320 provides applications 1304-1310 or products all information that is required to start the CoPilot UI for end users who are looking for help. It also allows applications 1304-1310 to provide CoPilot information to the content retrieval and management module 1314. The applications 1304-1310 provide the application context 1324, user context 1326 and system context 1328 that is required for CoPilot to offer dedicated help the user is looking for in the context of her work.”; paragraph [0248], “The support organizations at the customer shall also be enabled to provide help documents and search capabilities for help documents and plug them into CoPilot so that those documents appear in CoPilot's integrated help whenever they fit to the application context 1324, user context 1326 or chat context. For this, the first support integration module 1330 provides a dedicated interface which allows customers to plug in document search and display services.”); and
a feed constructor to dynamically construct said feed of multiple tickets for display based on said-combined data (paragraph [0245], “This information may be stored on the CoPilot backend 1302 and provide input to the support integration module 1312 to populate information for support tickets and to enable mapping of this information through the first support integration module 1316 and the second support integration module 1318.”; paragraph [0246], “The applications 1304-1310 provide the application context 1324, user context 1326 and system context 1328 that is required for CoPilot to offer dedicated help the user is looking for in the context of her work.”; paragraph [0249], “The second support integration module 1318 does the mapping of existing CoPilot chats and collections to support tickets and also allows status updates of CoPilot chats and collections in case of status changes in the external support system 1332 and vice versa.”).
This part of Lange et al. is applicable to the system of Williams et al. as they both share characteristics and capabilities, namely, they are directed to managing communication sessions for customer service. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Williams et al. to include the system and application context data collection as taught by Lange et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Williams et al. in order to provided contextualized information from each portion of a supported system to a customer facing support agents (see paragraphs [0247]-[0249] of Lange et al.).
With regards to claims 2 and 18, Williams et al. teaches said communication system is integrated with said supported system (paragraph [0032], “FIG. 6 provides a functional block diagram of certain components and elements of a content development platform, including integration of a customer relationship management system with other elements of the platform.”).
With regards to claims 3 and 19, Williams et al. teaches a channel transformer for adapting said user interface of said communication system to communicate with at least one client device belonging to said at least one agent (paragraph [0147], “As is discussed below, the message data 262 may be received from a user via a client device 260 and/or may be generated for the user by the systems described herein.”; paragraph [0197], “In embodiments, the client configuration system 1602 presents a graphical user interface (GUI) to a client user via a client device 1630. In embodiments, the GUI may include one or more drop down menus that allows users to select different service features (e.g., chat bots, automated follow up messages, FAQ pages, communication integration, and the like).”; paragraph [0243], “In embodiments, a communication integrator 1902 integrates communication with a contact over different mediums (e.g., chat bots, specialists, etc.), including the migration of the contact from one medium to another medium (e.g., website to chat bot, chat bot to specialist, website to specialist, etc.)”).
With regards to claims 4 and 20, Williams et al. teaches:
providing data gathering and analysis of ticket information and parameters for said multiple tickets, agent profiles, management data for said creating and updating said at least one ticket and said dynamically updating a display (paragraph [0117], “FIG. 11 illustrates an example of the crawling system 202 and the information extraction system 204 maintaining a knowledge graph 210, whereby the crawling system 202 and the information extraction system 204 may operate to obtain information from one or more information sources 230 and to update the knowledge graph 210 based on the obtained information. In FIG. 11, a set of crawlers 220 obtain (e.g., crawling and/or downloading) information relating to entities and events from various information sources 230.”; paragraph [0195], “Examples of custom ticket attributes are far ranging, as the client may define the custom ticket attributes, and may include a ticket type attributing indicating a type of the ticket (e.g., service request, refund request, lost items, etc.), a contact sentiment attribute indicating whether a sentiment score of a contact (e.g., whether the contact is happy, neutral, frustrated, angry, and the like), a contact frequency attribute indicating a number of times a contact has been contacted, a media asset attribute indicating media assets (e.g., articles or videos) that have been sent to the contact during the ticket's lifetime, and the like.”);
creating and editing knowledge base content for use by said creating and updating said at least one ticket (paragraph [0234], “In embodiments where a knowledge graph 1622 structures the client knowledge base 1624, the knowledge graph 1622 may store relationship data relating to the knowledge base 1624 of a client. In embodiments, the knowledge graph 1622 may be the knowledge graph 210 discussed above. In other embodiments, the knowledge graph 1622 may be a separate knowledge graph. In embodiments, the knowledge graph 1622 includes nodes and edges, where the nodes represent entities and the edges represent relationships between entities.”);
integrating bot agents into the functionality of said at least one agent (paragraph [0213], “or example, a request may be received from a contact request (e.g., a contact fills out a form from the client's website or a website hosted by the platform 1600 on behalf of the client), a chat bot (e.g., when a contact raises a specific issue in a chat with the chat bot), via a customer service specialist (e.g., the client calls a service specialist and the service specialist initiates the request), and the like.”); and
providing rule, artificial intelligence and machine learning support for said creating and updating said at least one ticket, said creating and displaying a one-inbox feed system, providing data gathering and analysis, said creating and editing knowledge base content and said integrating bot agents (paragraph [0132], “Referring back to FIG. 10, the machine learning system 212 is configured to perform machine learning tasks. Learning tasks may include, but are not limited to, training machine learned models to perform specific tasks and reinforcing the trained models based on feedback that is received in connection with the output of a model. Examples of tasks that can be performed by machine learned models can include, but are not limited to, classifying events, classifying entities, classifying relationships, scoring potential recipients of messages, and generating text. Depending on the task, certain types of machine learning may be better suited to a particular task than others.”).
With regards to claims 5 and 21, Williams et al. teaches said creating and updating said at least one ticket comprises: creating a ticket for said incoming event (paragraph [0104], “For example, in embodiments, tickets or tasks may be opened in a CRM system 158, such as prompting creation of content, such as based on customer-relevant suggestions, via the content development and management application 150, such as content for a conversation or chat with a customer (including one that may be managed by a conversational agent 182 or bot), content for a marketing message or offer to the customer, content to drive customer interest in a web page, or the like.”);
updating said ticket for said incoming event according to changing interactivity and said activities (paragraph [0193], “In embodiments, a client, via a client device 1640, may customize its customer service solution, such that the customer-service solution is tailored to the needs of the client and its customers. In embodiments, a client may select one or more customer service-related service features (or “service features”) and may provide one or more customization parameters corresponding to one or more of the service features. Customization parameters can include customized ticket attributes, service-related content (or “content”) to be used in the course of customer service, root URLs for populating a knowledge graph 1622, customer service workflows (or “workflows”), and the like.”);
remotely accessing a device of said at least one client and to interact with secondary devices connected to said device (paragraph [0149], “In such cases, a user may optionally input a recipient profile 264 and message data 262 into the system 200 via a client device 260. In additional or alternative embodiments, a recipient profile 264 may be generated by machine learned models based on, for example, outcomes relating to personalized messages previously generated by the system 200 and/or the objective of the message.”);
handling communications related to at least one of software installations, upgrades and changing configurations to said device (paragraph [0191], “As used herein, the term “service” should be understood to encompass, except where context indicates otherwise, any of a wide range of activities involved in providing services to customers and others, such as via various workflows of a business, including providing services for value, servicing goods, updating software, upgrading software, providing customer support, answering questions, providing instructions of use, issuing refunds or returns, and many others.”);
gathering and filling said ticket with related information (paragraph [0193], “In embodiments, a client, via a client device 1640, may customize its customer service solution, such that the customer-service solution is tailored to the needs of the client and its customers. In embodiments, a client may select one or more customer service-related service features (or “service features”) and may provide one or more customization parameters corresponding to one or more of the service features. Customization parameters can include customized ticket attributes, service-related content (or “content”) to be used in the course of customer service, root URLs for populating a knowledge graph 1622, customer service workflows (or “workflows”), and the like.”);
preparing a representation of multiple parallel activities and interactions of said ticket for display (paragraph [0193], “For example, a client, via a client device 1640, may provide selections of one or more features and capabilities enabled in the platform 1600 as described throughout this disclosure (e.g., automated content generation for communications, automated chat bots, AI-generated follow up emails, communication integration, call routing to service experts, and the like) via a graphical user interface (e.g., drop-down menu, a button, text box, or the like).”); and
handling associations between said ticket, said at least one client and said at least one agent (paragraph [0005], “The method includes receiving, by a processing system of a multi-client service platform, a set of service features selected by a client of the multi-client service platform. The method includes receiving, by the processing system, a set of customization parameters corresponding to the set of service features from the client, wherein the customization parameters include a set of custom ticket attributes and a ticket pipeline definition.”).
With regards to claims 6 and 22, Williams et al. teaches said handling associations is one of: assigning rules and privileges to said at least one agent for said communication system (paragraph [0066], “From the content clusters 130 a suggestion generator 134 may generate one or more suggested topics 138, which may be presented in a user interface 152 of a content development management application 150 within which an agent of an enterprise, such as a marketer, a sales person, or the like may view the suggested topic 138 and relevant information about it (such as indicators of its similarity or relevancy as described elsewhere herein) and create content, such as web pages, emails, customer chats, and other online presence content 160 on behalf of the enterprise.”); and
handling associations of said at least one agent with said at least one ticket (paragraph [0254], “In embodiments the service specialist portal may include chat interfaces, visualization tools that display a specialist's open tickets and/or various communication threads, analytics tools, and the like. Upon a contact and/or ticket being routed to a service specialist, the communication integrator 1902 may provide the specialist with all relevant data pertaining to the contact and/or the ticket.”).
With regards to claims 7 and 23, Williams et al. teaches generating and updating a feed of said multiple tickets for said at least one agent; and dynamically generating a user interface (UI) element to display said feed (Fig. 23, paragraph [0254], “In embodiments the service specialist portal may include chat interfaces, visualization tools that display a specialist's open tickets and/or various communication threads, analytics tools, and the like. Upon a contact and/or ticket being routed to a service specialist, the communication integrator 1902 may provide the specialist with all relevant data pertaining to the contact and/or the ticket.”).
With regards to claims 8 and 24, Williams et al. teaches generating and updating a feed comprises: updating said feed according to activity information and requirements of said at least one agent; managing multiple feeds; and instructing said constructing said feed according to results of a query placed by said at least one agent; (paragraph [0193], “Customization parameters can include customized ticket attributes, service-related content (or “content”) to be used in the course of customer service, root URLs for populating a knowledge graph 1622, customer service workflows (or “workflows”), and the like. For example, a client, via a client device 1640, may provide selections of one or more features and capabilities enabled in the platform 1600 as described throughout this disclosure (e.g., automated content generation for communications, automated chat bots, AI-generated follow up emails, communication integration, call routing to service experts, and the like) via a graphical user interface (e.g., drop-down menu, a button, text box, or the like).”; paragraph [0245], “The communication integrator 1902 may feed the obtained data to the medium. For example, if being transferred to a specialist, the communication integrator 1902 may populate a GUI of the specialist with the ticket information (e.g., ticket ID and current issue), contact information, the ticket status, transcripts of recent conversations with the contact, and/or the like. The communication session may then commence on the new medium without the contact having to provide any additional information to the system 1900.”).
With regards to claims 9 and 25, Williams et al. teaches providing data gathering and analysis comprises (at least one of in claim 25):
gathering and recording information associated with said multiple tickets, their interactions and their associated activities with said at least one agent (paragraph [0081], “The customer data records 164 may be used by the platform 100 to provide additional suggested topics 138, to select among suggested topics 138, to modify suggested topics 138, or the like. In embodiments, the CRM system 158 may support interactions with a customer, such as through a customer chat 184, which in embodiments may be edited in the user interface 152 of the content development and management application 150, such as to allow a writer, such as an inside sales person or marketer who is engaging in the customer chat 184 with the customer to see suggested topics 138 that may be of interest to the customer, such as based on the customer data records 164 and based on relevancy of the topics to the main differentiators of the enterprise.”); and
analyzing said information and generating automated actions accordingly for said creating and updating said multiple tickets and said dynamically generating an updated UI (paragraph [0081], “In embodiments, a conversational agent 182 may be provided within or integrated with the platform 100, such as for automating one or more conversations between the enterprise and a customer. The conversational agent 182 may take suggested topics from the suggestion generator 134 to facilitate initiation of conversations with customers around topics that differentiate the enterprise, such as topics that are semantically relevant to key phrases found in the primary online content object 102.”).
With regards to claims 10 and 26, Williams et al. teaches said analyzing said information and generating automated actions comprises at least one of: analyzing and rating agent activity of said at least one agent; making ticket assignment recommendations for managers of said at least one agent; recognizing and highlighting best practices for said at least one agent; generating insights according to patterns or trend analysis for said multiple ticket information; generating alerts and notifications for pre-defined situations; generating configuration changes for said communication system; generating content for said KB creator and editor; providing priority and tag information for said multiple tickets; integrating business information from said supported system; and activating automation actions according to pre-defined rules (at least recognizing and highlighting best practices, paragraph [0252], “For example, if the chat bot 1908, based on the contact's ticket history asks the contact if he is having an issue with content integration and the contact responds by typing “Yes, I can't get emoji to show up in my app,” the chat bot 1908 may rely on a rule that states: if no content has been sent to the contact, then send relevant content. In this example, the chat bot 1908 may retrieve an article describing how to integrate emoji into an application and may send a link to the article to the contact (e.g., via a messaging interface or via email). In another example, the chat bot 1908 may provide a ticket timeline to the machine learning module 1912, which in turn may leverage a neural network to determine that the best action at a given point is to send a particular article to the contact.”).
With regards to claims 11 and 27, Williams et al. teaches creating and editing knowledge base content comprises:
providing authoring and design tools for creation of embedded training material and courseware for said at least one agent and said at least one client (paragraph [0237], “The knowledge graph 1622 is a powerful mechanism that can support many features of a client-specific service system. In a first example, in response to a service specialist taking a call from the contact for a first time regarding a particular ticket, the client-specific service system 1900 may display a ticket history to the specialist that indicates that the user has purchased App Creator, that the contact's issue is with content integration, and that the contact has been sent the Emoji Support article. In another example, an automated workflow process servicing the ticket may retrieve the ticket node to learn that the contact has already been sent the Emoji Support article, so that it may determine a next course of action. In another example, an analytics tool may analyze all the tickets issued with a particular product and the issues relating to those tickets. The analytics tool, having knowledge of the client workflow, may drill down deeper to determine whether a particular article was helpful in resolving an issue.”);
creating a collection of knowledge base articles for use by users of said supported system (paragraph [0252], “Having the topic/type of issue, the chat bot 1908 can identify articles or content that are related to the product to which the ticket corresponds that are relevant to the topic/type of issue. The chat bot 1908 can then provide the content to the contact (e.g., email a link or provide the link in a chat interface). In some embodiments, a chat bot 1908 can also use the knowledge graph 1622 to formulate responses to the contact. For example, if the user asks about a particular product, the chat bot 1908 can retrieve relevant information relating to the product from the knowledge graph 1622 (e.g., articles or FAQs relating to the product).”);
creating a widget embedded in a website to present knowledge base articles (paragraph [0252], “Having the topic/type of issue, the chat bot 1908 can identify articles or content that are related to the product to which the ticket corresponds that are relevant to the topic/type of issue. The chat bot 1908 can then provide the content to the contact (e.g., email a link or provide the link in a chat interface). In some embodiments, a chat bot 1908 can also use the knowledge graph 1622 to formulate responses to the contact. For example, if the user asks about a particular product, the chat bot 1908 can retrieve relevant information relating to the product from the knowledge graph 1622 (e.g., articles or FAQs relating to the product).”); and
automatically selecting, recommending, creating, modifying or adapting knowledge-based content according to said at least ticket information and parameters, agent profiles, management data (paragraph [0159], “In embodiments, where data in the knowledge graph 210 may not be of sufficient structure or confidence, a generative model may be used to generate tokens (e.g., words and phrases) from the content (e.g., information from news articles, job postings, website content, etc.) in the knowledge graph 210 associated with an organization or individual, whereby the model can be trained (e.g., using a training set of input-output pairs) to generate content, such as headlines, phrases, sentences, or longer content that can be inserted into a message.”).
With regards to claims 12 and 28, Williams et al. teaches said multiples ticket comprise information on at least one of: the status of interactions between at least one agent and said at least one client, opening events, closing events, display forms and questionnaires, notes of said at least one agent, ticket meta data, links to related tickets, knowledge base content, ticket association information (paragraph [0231], “In embodiments, the additional ticket data 1752 may include or reference the specialist or specialists that have helped service the ticket (e.g., employee IDs), any notes entered by specialists, a number of notes entered by the specialists, a list of materials that have been sent to the contact during attempts to resolve the issue, and the like.”).
With regards to claims 13 and 29, Williams et al. teaches one of said at least two communication channels is: a social network, email, a shared virtual space, a web service, an organized communication system, an online forum, an online chat room and a messaging system (paragraph [0066], “From the content clusters 130 a suggestion generator 134 may generate one or more suggested topics 138, which may be presented in a user interface 152 of a content development management application 150 within which an agent of an enterprise, such as a marketer, a sales person, or the like may view the suggested topic 138 and relevant information about it (such as indicators of its similarity or relevancy as described elsewhere herein) and create content, such as web pages, emails, customer chats, and other online presence content 160 on behalf of the enterprise.”; paragraph [0245], “In some embodiments, the sequence by which a communication session is transferred (e.g., escalating from a chat bot to a specialist or escalating from a text-based chat to a phone call) is defined in a custom workflow provided by the client. The communication integrator 1902 may feed the obtained data to the medium. For example, if being transferred to a specialist, the communication integrator 1902 may populate a GUI of the specialist with the ticket information (e.g., ticket ID and current issue), contact information, the ticket status, transcripts of recent conversations with the contact, and/or the like.”).
With regards to claims 15 and 31, Williams et al. teaches said preparing a representation displays a single ticket display representing said activities and said changing levels of interactivity (paragraph [0208], “FIG. 42, the GUI 4000 presents a menu with additional options that are organized based on the action type, whereby the user can select an action from a set of actions presented in the menu. The example menu of actions include creating a new task, sending a ticket notification, adding a delay, creating a task, sending an internal email, sending an internal SMS, sending an internal SMS message, and the like. In the example of FIG. 43, the user has selected the ticket notification action. In response to the selection, the GUI 4000 presents the user with the option to draft an email template. In the example, the user provides the email template, including template fields such as “Ticket ID” that may be populated with the ticket ID of the newly generated ticket.”; paragraph [0245], “In some embodiments, the sequence by which a communication session is transferred (e.g., escalating from a chat bot to a specialist or escalating from a text-based chat to a phone call) is defined in a custom workflow provided by the client. The communication integrator 1902 may feed the obtained data to the medium. For example, if being transferred to a specialist, the communication integrator 1902 may populate a GUI of the specialist with the ticket information (e.g., ticket ID and current issue), contact information, the ticket status, transcripts of recent conversations with the contact, and/or the like.”).
With regards to claims 16 and 32, Williams et al. teaches said preparing a representation displays a summarized version of said different levels of interactivity according to an analysis of stored communication data by said providing rule, artificial intelligence and machine learning support (paragraph [0132], “configured to perform machine learning tasks. Learning tasks may include, but are not limited to, training machine learned models to perform specific tasks and reinforcing the trained models based on feedback that is received in connection with the output of a model.”; paragraph [0158], “The content generation system 216 may use statistical models of language, including but not limited to automatic summarization of textual information to generate directed content based on the information about the recipient and/or the recipient's organization. In embodiments, the content generation system 216 may merge the directed content into a message template to obtain the personalized message for a recipient.”; paragraph [0245], “In some embodiments, the sequence by which a communication session is transferred (e.g., escalating from a chat bot to a specialist or escalating from a text-based chat to a phone call) is defined in a custom workflow provided by the client. The communication integrator 1902 may feed the obtained data to the medium. For example, if being transferred to a specialist, the communication integrator 1902 may populate a GUI of the specialist with the ticket information (e.g., ticket ID and current issue), contact information, the ticket status, transcripts of recent conversations with the contact, and/or the like.”).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/J.D.S./Examiner, Art Unit 3626
/JESSICA LEMIEUX/Supervisory Patent Examiner, Art Unit 3626
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