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| − | {{SMART UseCase | + | {{SMART Meta |
| − | |ID=CE31 | + | |SolutionCategory=CE |
| − | |Title=Genesys Blended AI Bots | + | |Solution=Self-Service and Automation |
| − | |Offering=GenesysEngage-onpremises | + | |Title=Genesys Chatbots |
| − | |UCOverview=The proliferation of digital channels leads to higher customer expectations and an increased number of interactions that companies deal with when servicing customers. Coupled with increased usage of Artificial Intelligence (AI) for business applications, this change results in organizations implementing chatbots that can interact with customers to automate tasks and assist their queries on digital channels such as web, mobile, social, SMS, and messaging apps. Chatbots can alleviate strain on contact center employees while improving the customer experience and controlling costs. Chatbots are always on and available, and can hand over to a live agent at any time where needed. While chatbots can also be used by employees and for business optimization purposes, the remainder of this document refers to omnichannel bots in the context of customer engagement. The primary benefits of chatbots are to increase self-service success, deflect interactions from the contact center, and improve the customer experience. | + | |Subtitle=Use chatbots to automate customer conversations and seamlessly hand over to a live agent when needed. |
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| − | Genesys chatbots unify and orchestrates self-service experiences using both native and third-party bots – powering exceptional customer and employee experiences. Genesys supports a “design once, deploy anywhere” concept for bots to enable organizations to provide a seamless customer experience across voice and digital channels. This use case focuses on deploying a bot on web chat, mobile chat, Facebook Messenger, Twitter Direct Message, Line Messaging, WhatsApp, or SMS.
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| − | |SMART_Benefits={{SMART Benefits
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| − | |UCBenefitID=Reduced Volume of Interactions
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| − | |UCBenefit=Increase self-service interactions to reduce agent-assisted interactions for repetitive or common requests.
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| − | }}{{SMART Benefits
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| − | |UCBenefitID=Improved First Contact Resolution
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| − | |UCBenefit=Tailor the customer experience to the individual based on who they are, why they could be interacting, and the status of the contact center
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| − | }}{{SMART Benefits
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| − | |UCBenefitID=Improved Customer Experience
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| − | |UCBenefit=Reduce the time required to address the customer request, handle off-hour contacts, offer immediate options, and improve outcomes.
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| − | |UCSummary=Genesys Chatbots supports native platform Dialog Engine Bot Flows and third-party platforms such as Amazon, Google etc. As each chatbot and third party has their own specific capabilities, this use case covers broadly available capabilities, for the most of to date latest references available, visit the [https://help.mypurecloud.com/articles/bring-your-own-technology-services-model/ Resource Center]. | + | {{SMART Canonical |
| | + | |PlatformChallenge=Many customer service, sales or support conversations with customers are repetitive — Frustrating both for customers as well as employees. If these conversations can be automated at the point of contact, it would save agents a lot of time and significantly improve customer experience |
| | + | |PlatformSolution=Chatbots automate natural conversations across digital channels. Chatbots look up customer information and activity to answer questions. They can hand over conversations with context to an agent when needed, or even offer a callback<sup>1</sup> during or after hours. |
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| − | <span>The chatbot supports or orchestrates the following capabilities:</span> | + | <sup>1</sup>''Callback option is available for Genesys Engage only.'' |
| | + | |PainPoints=*Increasing interactions on digital channels |
| | + | *Low first contact resolution rates |
| | + | *Generic customer experience across all customers |
| | + | *High online purchase abandonment or lack of assistance |
| | + | *Increasing repeat contacts |
| | + | *Customer having to queue for a long time for chat agents |
| | + | *No seamless customer experience across channels |
| | + | |DesiredState=*Introduce self-service through chatbot |
| | + | *Pass conversation history when handing over to an agent |
| | + | *Offer callback outside of business hours |
| | + | *Personalized interactions for customers based on natural language understanding |
| | + | *Context-aware chatbot to assist purchase process or service requests |
| | + | *Better user experience based on customer context |
| | + | |HighLevelFlowLucid=0cd99598-9d44-41b7-8891-c768da389418 |
| | + | |BuyerPersonas=Chief Financial Officer, Head of Customer Experience, Head of Customer Service |
| | + | |QualifyingQuestions=1 Do you want to increase NPS while saving on contact center expense? |
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| − | *Personalization – to tailor the experience based on context from the current interaction or from previous interactions
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| − | *Natural Language Understanding – to derive intents and entities
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| − | *Simple bot orchestration enables customers to use the best bot for the job. For example Google Dialogflow has highest alphanumeric recognition rates
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| − | *Genesys Cloud Architect makes it easy to integrate to new bot providers, switch between bot providers or to use multiple bot providers within a single interaction
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| − | *A-B testing with Genesys Cloud Architect helps determine which bot is most effective for a particular business use case
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| − | *Graceful escalation to a live Agent at the right time
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| − | |Description=Supported Genesys Chatbot channels for Genesys Cloud are web and mobile chat, <span>Facebook Messenger, WhatsApp, Line Messaging, Twitter Direct Message, and SMS.</span>
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| − | |PainPoints=* Increasing interactions on digital channels
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| − | * Low first contact resolution rates
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| − | * Generic customer experience across all customers
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| − | * High online purchase abandonment or lack of assistance
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| − | * Increasing repeat contacts
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| − | * Customer having to queue for a long time for chat agents
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| − | * No seamless customer experience across channels
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| − | |DesiredState=*Introduce self-service through chatbot
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| − | *Pass conversation history when handing over to an agent
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| − | *Personalized interactions for customers based on natural language understanding
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| − | *Context-aware chatbot to assist purchase process or service requests
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| − | *Better user experience based on customer context
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| − | |BuyerPersonas=Head of Customer Experience, Head of Contact Center(s)
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| − | |MaturityLevel=Differentiated
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| − | |CloudAssumptionsAdditional_Sales=*Channels supported: Web & Mobile Chat, <span>Facebook Messenger, WhatsApp, Twitter Direct Message, Line Messaging, and SMS.</span>
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| − | *Transfer to agent is on same channel.
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| − | *Survey is provided by Bot provider Q&A functionality and needs customisation.
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| − | |BusinessImageFlow={{SMART BusinessImageFlow
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| − | |BusinessFlow=<span>When a customer interacts through a supported Genesys digital channel, a chatbot starts. The chatbot first attempts to use context to anticipate why the customer may be engaging and in turn provides personalized messages to resolve the query. If no personalization options exist, the chatbot asks the customer an open question, such as "How may I help?".</span>
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| − | <span>Once the customer responds, the chatbot tries to interpret the request to determine intent and then decide what to do next. For example, if the customer replies with “I want to check my balance,” the chatbot would first identify and verify them before showing their balance.</span>
| + | 2 Do you think that some customer issues could be effectively resolved without talking to an agent? |
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| − | <span>Once the task finishes, the chatbot asks if the customer needs more help. The customer can respond by asking another question, requesting to chat with an advisor, or replying 'no'. If the customer replies with 'no', the chatbot can offer a survey based on context.</span>
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| | + | 3 Are you having success with automating responses using your teams to analyze the gaps, or could they use some help? |
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| − | <span>If intent is not established or understood, the chatbot passes the customer to an advisor.</span>
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| − | <span>If the customer chooses to speak or chat with an agent and there is a long wait time or it is outside business hours, then the chatbot can present a suitable message.</span>
| + | 4 How are you measuring the success of automation changes? |
| − | | + | |DataSheetImage=SL09 - genesys predictive engagement for sales - header (2).png |
| − | <span>The chatbot continues in this fashion, creating a conversational loop and building context between itself and the customer to better solve their query.</span>
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| − | | + | {{SMART Benefits |
| − | | + | |CanonicalBenefitID=Improved First Contact Resolution |
| − | <span>The following diagram shows the business flow of the use case:</span>
| + | |CanonicalBenefit=Bots identify customers and context, then present choices fitted to expected activity. |
| − | |BusinessImage=92307f69-8aad-4aa1-bcb9-c9848f85e677 | + | }} |
| − | |BusinessFlowDescription=#A chat interaction is initiated (reactive or proactive) across a supported channel.
| + | {{SMART Benefits |
| − | #The customer receives a standard welcome message from the chatbot.
| + | |CanonicalBenefitID=Improved Containment Rate |
| − | #Customer information and/or context is retrieved from:<br />
| + | |CanonicalBenefit=Increase self-service interactions to reduce agent-assisted interactions for repetitive or common requests |
| − | #*Customer profile information in External Contacts
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| − | #*API call to third-party data source
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| − | #The customer receives a personalized message or is handed over to an agent. Examples include:
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| − | #*Custom message or update: "Your next order is due to arrive on Thursday before 12."
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| − | #*Customer is handed over directly to an agent because they owe an outstanding balance.
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| − | #*If the customer is not handed over to an agent, the customer could end their chat, confirm the contact reason, or continue.
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| − | #Assuming the customer has moved on from the Personalization stage, the interaction is sent to a chatbot (for example Genesys Dialog Engine) which asks an open-ended question like: “How may I help you?” to determine intent and capture the customer'<span></span>s response.'''[BL1]'''<br />
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| − | #*If intent and slots are returned, the conversation moves to the correct point in the interaction flow, for example;
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| − | #**Automated notification task (such as display balance)
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| − | #**Handoff to live agent
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| − | #*If intent and slots are not returned, the conversation returns to the interaction flow and the customer is handed off to an agent.
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| − | #Upon completion of a task,<span></span><span>the interaction is sent to a chatbot (for example Genesys Dialog Engine)</span><span></span> <span>which asks</span> a follow-up question like: "Is there anything else I can help you with?"
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| − | #*If the customer responds “yes,” they return to Step 5: "How may I help you?”
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| − | #*If the customer responds “no,” then the conversation returns to the interaction flow
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| − | #*If the customer responds with a more advanced answer, then determine intent and entities for further processing.
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| − | #Customer information and/or context is retrieved to determine whether to offer a survey.<span></span>'''[BL2]'''<br />
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| − | #*If a survey is offered, the interactions <span>is sent to a chatbot.</span>
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| − | #*If no survey is offered, the interaction flow shows a goodbye message and ends
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| − | #The survey is executed. The survey questions are configurable by <span></span>the customer on a business-as-usual basis in the chatbot and therefore no dialog flow is defined here.
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| − | #<span>The interaction flow </span>presents a goodbye message and ends the chat
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| | }} | | }} |
| − | |BusinessLogic='''NLU:''' | + | {{SMART Benefits |
| − | | + | |CanonicalBenefitID=Improved Customer Experience |
| − | *Intents: The goal of the interaction. For example, a "switch flight" intent returned by the NLU indicates that the customer receives a payment business process.
| + | |CanonicalBenefit=Reduce the time required to address the customer request, handle off-hour requests, offer immediate options, and improve outcomes |
| − | *Slots: Additional pieces of key information returned by the NLU. These pieces can accelerate the conversation by prepopulating answers to subsequent questions.
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| − | '''BL1: Agent Handoff:''' The customer can ask to connect to an available agent. At that point, the chatbot disconnects and the chat transcript (excluding sensitive data) appears in the agent desktop.
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| − | '''BL2: Survey:''' The customer can determine whether to address a survey or not. This survey can be based on:
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| − | *Customer profile information in External Contacts
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| − | *Customer journey data
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| − | *API call to third-party data source
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| − | |DistributionLogic=There is no applicable content for this section.
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| − | |CustomerInterfaceRequirements=This use case expects the utilization of Genesys Cloud Widget to display the chats. | |
| − | |AgentDeskRequirements=Chat transcript between customer and chatbot is populated in the chat interaction window in the agent desktop.
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| − | |RealTimeReporting=With Genesys Cloud, you can do flow reporting and use flow outcomes to report on chatbot intents.
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| − | See the [https://help.mypurecloud.com/articles/flows-performance-summary-view/ Flows Performance Summary view] and use [https://help.mypurecloud.com/?p=185383 flow outcomes] statistics to help you determine performance issues for specific chatbot flows, and gather data about self-service success. Use the chatbot flow data to improve outcomes.
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| − | Use the [https://help.mypurecloud.com/articles/flow-performance-detail-view Flows Performance Detail view] to see a breakdown of metrics by interval for a specific chatbot flow, and to see how chatbot interactions enter and leave a chat flow.
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| − | The [https://help.mypurecloud.com/articles/flow-outcomes-summary-view Flow Outcomes Summary view] displays statistics related to chats that enter Architect flows. These statistics can help you determine how well your chatbot flows serve customers and gather data about self-service success.
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| − | |HistoricalReporting=<span><span>We are working on providing more chatbot reporting in the future, including building your own chatbot reports.</span></span>
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| − | |GeneralAssumptions=*Handoff to agent is on the same channel.
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| − | *The customer is responsible for the build of the natural language bot model and providing the bot training of utterances, intents, or slots. Professional Service may be engaged to develop the model.
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| − | *Survey capabilities are provided by chatbot provider QA functionality (for example, Amazon Lex) and need customization.
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| − | *Chatbot integration is not HIPAA-compliant.
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| − | *Third-Party Chatbots are enabled via the Integrations Registry and informational through AppFoundry.
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| − | *Customers use their own third-party Chatbot accounts for Integration Services.
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| − | |RequiresOr=CE18, CE29, CE34
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| − | |DocVersion=1.4.0
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| − | |Video=398264777
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