UseCases/Current/PureConnect/CE41 - Revision history

Ed.jamer@genesys.com: Text replacement - "Genesys Cloud" to "Genesys Cloud CX"

2021-11-09T21:27:50Z

Text replacement - "Genesys Cloud" to "Genesys Cloud CX"

Shane.landy@genesys.com at 14:45, June 3, 2021

2021-06-03T14:45:45Z

Shane.landy@genesys.com: UCC: Removed all references to Dialog Engine

2021-03-09T18:24:42Z

UCC: Removed all references to Dialog Engine

Shane.landy@genesys.com: UCC: Updated benefits to align with calculators

2021-02-16T13:46:48Z

UCC: Updated benefits to align with calculators

Ed.jamer@genesys.com: Text replacement - " Altocloud" to " Predictive Engagement"

2020-11-17T15:24:01Z

Text replacement - " Altocloud" to " Predictive Engagement"

Shlandy93 at 09:04, September 23, 2020

2020-09-23T09:04:27Z

WikiSysop at 12:59, July 15, 2020

2020-07-15T12:59:17Z

WikiSysop: Text replacement - "PureEngage" to "Genesys Engage"

2020-07-15T12:03:15Z

Text replacement - "PureEngage" to "Genesys Engage"

Shlandy93 at 15:44, May 22, 2020

2020-05-22T15:44:38Z

Show changes

Shlandy93 at 10:37, April 20, 2020

2020-04-20T10:37:56Z

@@ Line 165: / Line 165: @@
 *Google ASR is connected through a universal UniMRCP connector that supports voicebots through Intelligent Automation, if a customer needs voice-based ASR they require Nuance.
 *There is an extra lead time for cloud deployment for a customer-specific infrastructure plan to be created. Cloud Operations supports many customers and a new deployment enters into the queue with other requests.
-*Dialog Engine is not available for PureConnect. It is only available on Genesys Cloud.<br />
+*Dialog Engine is not available for PureConnect. It is only available on Genesys Cloud CX.<br />
 |CustomerAssumptions=*Voicebot configuration and settings will be quoted as part of a Professional Services engagement to capture requirements and business logic.
 |RequiresAll=CE01
 |DocVersion=1.0.2
 }}

@@ Line 3: / Line 3: @@
 |Title=Genesys Voice Bots
 |Offering=PureConnect
 |SMART_Benefits={{SMART Benefits
-|UCBenefitID=Reduced Volume of Interactions
+|UCBenefitID=Improved Containment Rate
 |UCBenefit=Increase self-service interactions results in reduced agent-assisted interactions for repetitive or common requests.
 }}{{SMART Benefits
@@ Line 16: / Line 27: @@
 |UCBenefit=Reuse of existing assets and the option to use less expensive speech alternatives
 }}
 |UCSummary=Genesys supports a “design once, deploy anywhere” concept for AI-driven bots to enable organizations to provide a seamless customer experience across voice and digital channels. This use case focuses on deploying a bot on the voice channel and can automatically be extended to digital channels by adding the Genesys Chatbots with Blended AI Use Case. The voice bot supports and orchestrates the following capabilities:
@@ Line 145: / Line 145: @@
 |HistoricalReporting=*How many conversations took place over a period
 *Length of time for each conversation: maximum/minimum/average<br />
 |GeneralAssumptions=*Use Case supports voice channel. {{#mintydocs_link:topic=CE31}} supports digital channels.
 *This Use Case is supported by industry templates that contain examples of voicebot applications combining personalization, natural language understanding, AI, and microapps. Voicebot application requirements including required microapps will be confirmed during design. These application templates are created for Financial Services, Telco, and Travel.
@@ Line 168: / Line 167: @@
 *Dialog Engine is not available for PureConnect. It is only available on Genesys Cloud.<br />
 |CustomerAssumptions=*Voicebot configuration and settings will be quoted as part of a Professional Services engagement to capture requirements and business logic.
 |DocVersion=1.0.2
 }}

@@ Line 26: / Line 26: @@
 *Quickly and easily deploy omnichannel bots with Natural Language Understanding (NLU) and pre-built microapps that leverage industry best practice
 *Move to cloud at your own speed and at low risk with cloud, hybrid, and premise options
-*Inclusion of voicebots powered by Natural Language Understanding from Genesys Dialog Engine, Google DialogFlow and Amazon Lex to provide natural and rich conversational experiences for customers who call Customer Service. Spoken phrases from customers are transcribed to text by Google Cloud Speech to Text which is then interpreted by the chosen NLU application to identify the customer’s intent.  For example, book a flight; extract key data for the query such as origin and destination city, date, day, time; and generate an appropriate response and/or further questions to continue the interaction.
+*Inclusion of voicebots powered by Natural Language Understanding from Google DialogFlow and Amazon Lex to provide natural and rich conversational experiences for customers who call Customer Service. Spoken phrases from customers are transcribed to text by Google Cloud Speech to Text which is then interpreted by the chosen NLU application to identify the customer’s intent.  For example, book a flight; extract key data for the query such as origin and destination city, date, day, time; and generate an appropriate response and/or further questions to continue the interaction.
 |UCSummary=Genesys supports a “design once, deploy anywhere” concept for AI-driven bots to enable organizations to provide a seamless customer experience across voice and digital channels. This use case focuses on deploying a bot on the voice channel and can automatically be extended to digital channels by adding the Genesys Chatbots with Blended AI Use Case. The voice bot supports and orchestrates the following capabilities:
@@ Line 55: / Line 55: @@
 |MaturityLevel=Differentiated
 |BusinessImageFlow={{SMART BusinessImageFlow
 |BusinessImage=https://www.lucidchart.com/documents/edit/20930a15-2e99-42c6-948a-364417c1f4ce/0
 |BusinessFlowDescription=#A voice interaction is initiated (reactive or proactive) on the voice channel.
@@ Line 71: / Line 70: @@
 #*The customer speaks to the voicebot in natural language. For example, the customer could say “I missed a bill payment and want to check my balance because I think I'm in arrears”
 #*The voicebot listens to the customer and converts the raw spoken utterance into text.
-#The voicebot then sends the customer's response to the configured NLU engine (for example, Dialog Engine). If intent and entities are returned, the conversation moves to the correct point in the interaction flow, which could be within one of the following subflows:
+#The voicebot then sends the customer's response to the configured NLU engine. If intent and entities are returned, the conversation moves to the correct point in the interaction flow, which could be within one of the following subflows:
 #Identification and Verification (ID&V)
 #*Automated business process (such as Payment Collection microapp)
@@ Line 151: / Line 150: @@
 *Handoff to voice agent is on the same channel.
 *To access a 3rd party NLU, it must be routed through Intelligent Automation.
 *NLU capabilities for non-English languages can be supported through third-party NLU engines such as Google DialogFlow.  Integration to third-party NLU/AI engines is a customization task. Dialogs that do not require NLU can support any language by using personas.
 *Integration to Knowledge Center is a customization task; an example integration code snippet can be provided.
@@ Line 165: / Line 162: @@
 *#German
-* The IVR transcript will not pass.
+*The IVR transcript will not pass.
-* The voicebot is deployed in a Hybrid model, that is, Genesys PureConnect infrastructure on premise with Google components in the cloud.
+*The voicebot is deployed in a Hybrid model, that is, Genesys PureConnect infrastructure on premise with Google components in the cloud.
-* Google ASR is connected through a universal UniMRCP connector that supports voicebots through Intelligent Automation, if a customer needs voice-based ASR they require Nuance.
+*Google ASR is connected through a universal UniMRCP connector that supports voicebots through Intelligent Automation, if a customer needs voice-based ASR they require Nuance.
-* There is an extra lead time for cloud deployment for a customer-specific infrastructure plan to be created. Cloud Operations supports many customers and a new deployment enters into the queue with other requests.<br />
+*There is an extra lead time for cloud deployment for a customer-specific infrastructure plan to be created. Cloud Operations supports many customers and a new deployment enters into the queue with other requests.
 |CustomerAssumptions=*Voicebot configuration and settings will be quoted as part of a Professional Services engagement to capture requirements and business logic.
 |DocVersion=1.0.2
 }}

@@ Line 10: / Line 10: @@
 |UCBenefit=Present a customer experience that is tailored to the individual based on who they are, why they might be interacting, and the status of the contact center.
 }}{{SMART Benefits
-|UCBenefitID=Improved Net Promoter Score
+|UCBenefitID=Improved Customer Experience
 |UCBenefit=Reduce time to serve, which in turn improves Net Promoter Score (NPS).  Improve self-service containment rates, handle time, and overall customer experience by enabling routing to the right self-service application by correctly identifying intent.
 }}{{SMART Benefits
@@ Line 21: / Line 21: @@
 Blending bots technology with voice, self-service and digital applications enables companies to optimize service without incurring costs associated with live customer interactions. Designing customer experiences with voice bots delivers the following:
-*Ability to manage the customer entire journey, automated wherever possible, human touch when needed, for example, chatbots, voicebots, and Predictive Engagement
+*Ability to manage the customer entire journey, automated wherever possible, human touch when needed, for example, chatbots, voicebots, and Altocloud
 *Create personalized bot experiences by sharing context across voice and digital channels and with agents
 *Voicebots in general provide significantly higher benefits than a traditional IVR due to advancements in speech recognition technology and the introduction of Conversational AI which promotes a more natural interaction providing a high-quality customer experience
@@ Line 146: / Line 146: @@
 |HistoricalReporting=*How many conversations took place over a period
 *Length of time for each conversation: maximum/minimum/average<br />
-|DocVersion=1.0.2
+|RequiresAll=CE01
 |GeneralAssumptions=*Use Case supports voice channel. {{#mintydocs_link:topic=CE31}} supports digital channels.
 *This Use Case is supported by industry templates that contain examples of voicebot applications combining personalization, natural language understanding, AI, and microapps. Voicebot application requirements including required microapps will be confirmed during design. These application templates are created for Financial Services, Telco, and Travel.
@@ Line 163: / Line 163: @@
 *#French
 *#Spanish (Mexican)
-*#German<br />
+*#German
 |CustomerAssumptions=*Voicebot configuration and settings will be quoted as part of a Professional Services engagement to capture requirements and business logic.
-|RequiresAll=CE01
+|DocVersion=1.0.2
 }}

@@ Line 21: / Line 21: @@
 Blending bots technology with voice, self-service and digital applications enables companies to optimize service without incurring costs associated with live customer interactions. Designing customer experiences with voice bots delivers the following:
-*Ability to manage the customer entire journey, automated wherever possible, human touch when needed, for example, chatbots, voicebots, and Altocloud
+*Ability to manage the customer entire journey, automated wherever possible, human touch when needed, for example, chatbots, voicebots, and Predictive Engagement
 *Create personalized bot experiences by sharing context across voice and digital channels and with agents
 *Voicebots in general provide significantly higher benefits than a traditional IVR due to advancements in speech recognition technology and the introduction of Conversational AI which promotes a more natural interaction providing a high-quality customer experience

@@ Line 16: / Line 16: @@
 |UCBenefit=Reuse of existing assets and the option to use less expensive speech alternatives
 }}
 |UCOverview=Successful companies strive to provide good experiences for their customers, but doing so becomes challenging and expensive given the multitude of communications channels (voice and digital) that must be offered to interact with customers. It is increasingly expensive to serve customers with live agents and companies need to optimize efficiencies in cases when requests can be fully or partially automated and serve customers faster and more economically.  Customer Service costs are sustainable for self-service channels like in-app, web self-service, and virtual assistant but they begin to increase with web chat and exponentially skyrocket with voice. The challenge to customer service leaders is to provide outstanding experiences for customers by utilizing automation and artificial intelligence blended with human interaction where required.
@@ Line 38: / Line 37: @@
 *Offer a callback - if outside of business hours or long wait time then the voicebot offers a callback from the voice channel
 *Offer a voicebot survey depending on business context
 |PainPoints=*Agents wasting time, capturing routine information
 *Increasing interactions on voice channels
@@ Line 55: / Line 53: @@
 <br />
 |BuyerPersonas=Chief Digital Officer, Head of Customer Experience, Head of Business Units, Head of Customer Service
 |MaturityLevel=Differentiated
 |BusinessImageFlow={{SMART BusinessImageFlow
 |BusinessFlow=
@@ Line 144: / Line 136: @@
 *Based on context from PureConnect, Intelligent Automation, Genesys User Data, or third-party web service
 |DistributionLogic=When the conversation is handed over to a live agent, the interaction moves to one of these use cases, depending on the channel the customer is using -  see the Use Case Interdependencies section for related use cases.
 |CustomerInterfaceRequirements=N/A
@@ Line 156: / Line 147: @@
 *Length of time for each conversation: maximum/minimum/average<br />
 |DocVersion=1.0.2
-|GeneralAssumptions=*Use Case supports voice channel. [[UseCases/Draft/GenesysEngage-onpremises/CE31|Genesys Chatbots with Blended AI (CE31)]] supports digital channels.
+|GeneralAssumptions=*Use Case supports voice channel. {{#mintydocs_link:topic=CE31}} supports digital channels.
 *This Use Case is supported by industry templates that contain examples of voicebot applications combining personalization, natural language understanding, AI, and microapps. Voicebot application requirements including required microapps will be confirmed during design. These application templates are created for Financial Services, Telco, and Travel.
 *Handoff to voice agent is on the same channel.
@@ Line 173: / Line 164: @@
 *#Spanish (Mexican)
 *#German<br />
-|CustomerAssumptions=
+|CustomerAssumptions=*Voicebot configuration and settings will be quoted as part of a Professional Services engagement to capture requirements and business logic.
 |RequiresAll=CE01
 |SMART_PremiseAssumptions={{SMART PremiseAssumptions
@@ Line 182: / Line 173: @@
 |Premise_Assumption=More infrastructure is required to support UniMRCP and Google ASR.
 }}
 |SMART_CloudAssumptions={{SMART CloudAssumptions
 |Cloud_Assumption=Google ASR is connected through a universal UniMRCP connector that supports voicebots through Intelligent Automation, if a customer needs voice-based ASR they require Nuance.
@@ Line 190: / Line 180: @@
 |Cloud_Assumption=More infrastructure is required to support UniMRCP and Google ASR.
 }}
 }}

@@ Line 10: / Line 10: @@
 |UCBenefit=Present a customer experience that is tailored to the individual based on who they are, why they might be interacting, and the status of the contact center
 }}{{SMART Benefits
-|UCBenefitID=Improved Customer Experience
+|UCBenefitID=Improved Net Promoter Score
 |UCBenefit=Reduce time to serve, which in turn improves Net Promoter Score (NPS).  Improve self service containment rates, handle time and overall customer experience by enabling routing to the right self service application by correctly identifying intent
 }}{{SMART Benefits
@@ Line 16: / Line 16: @@
 |UCBenefit=Reuse of existing assets and the option to use less expensive speech alternatives
 }}
 |UCOverview=Successful companies strive to provide good experiences for their customers, but this becomes challenging and expensive given the multitude of communications channels (voice and digital) that must be offered to interact with customers. It is increasingly expensive to serve customers with live agents and companies need to optimize efficiencies in cases when requests can be fully or partially automated and serve customers faster and more economically.  Customer Service costs are sustainable for self-service channels like in-app, web self-service and virtual assistant but they begin to increase with web chat and exponentially skyrocket with voice. The challenge to customer service leaders is to provide outstanding experiences for customers by utilizing automation and artificial intelligence blended with human interaction where required.
 Blending bots technology with voice, self-service and digital applications enables companies to optimize service without incurring costs associated with live customer interactions. Designing customer experiences with voice bots delivers the following:
 * Ability to manage the customer entire journey, automated wherever possible, human touch when needed, e.g. chatbots, voicebots, and Altocloud
-* Create personalized bot experiences by sharing context across voice and digital channels and with agents
+*Ability to manage the customer entire journey, automated wherever possible, human touch when needed, e.g. chatbots, voicebots, and Altocloud
-* Voicebots in general provide significantly higher benefits than a traditional IVR due to advancements in speech recognition technology and the introduction of Conversational AI which promotes a more natural interaction providing a high-quality customer experience
+*Create personalized bot experiences by sharing context across voice and digital channels and with agents
-* Quickly and easily deploy omnichannel bots with Natural Language Understanding (NLU) and pre-built microapps that leverage industry best practice
+*Voicebots in general provide significantly higher benefits than a traditional IVR due to advancements in speech recognition technology and the introduction of Conversational AI which promotes a more natural interaction providing a high-quality customer experience
-* Move to cloud at your own speed and at low risk with cloud, hybrid and premise options
+*Quickly and easily deploy omnichannel bots with Natural Language Understanding (NLU) and pre-built microapps that leverage industry best practice
-* Inclusion of voicebots powered by Natural Language Understanding from Genesys Dialog Engine, Google DialogFlow and Amazon Lex to provide natural and rich conversational experiences for customers who call Customer Service. Spoken phrases from customers are transcribed to text by Google Cloud Speech to Text which is then interpreted by the chosen NLU application to identify the customer’s intent, e.g. book a flight; extract key data for the query such as origin and destination city, date, day, time; and generate an appropriate response and/or further questions to continue the interaction.
+*Move to cloud at your own speed and at low risk with cloud, hybrid and premise options
 |UCSummary=Genesys supports a “design once, deploy anywhere” concept for AI-driven bots to enable organizations to provide a seamless customer experience across voice and digital channels. This use case focuses on deploying a bot on the voice channel and can automatically be extended to digital channels by adding the Genesys Chatbots with Blended AI Use Case. The voice bot supports and orchestrates the following capabilities:
 * Personalization – to tailor the experience based on context from the current interaction or from previous interactions Natural Language Understanding (NLU) – to derive intents and entities
-* Intent classification utilizes NLU to classify the customer's intent with high accuracy, and connect the customer to the correct self service process or agent. Additionally NLU derives entities, which are pieces of relevant information from customer utterances such as: account numbers, amounts and other parameters that are returned to complete a process corresponding to the intent thus enabling a conversational experience.
+*Personalization – to tailor the experience based on context from the current interaction or from previous interactions Natural Language Understanding (NLU) – to derive intents and entities
-* Identification & Verification (ID&V) – to identify and verify the customer if required
+*Intent classification utilizes NLU to classify the customer's intent with high accuracy, and connect the customer to the correct self service process or agent. Additionally NLU derives entities, which are pieces of relevant information from customer utterances such as: account numbers, amounts and other parameters that are returned to complete a process corresponding to the intent thus enabling a conversational experience.
-* Directed Dialog – to automate relevant and structured business processes or provide information
+*Identification & Verification (ID&V) – to identify and verify the customer if required
-* Involve another NLU/AI platform – if it specializes in a particular topic
+*Directed Dialog – to automate relevant and structured business processes or provide information
-* Hand off to a voice agent – to connect the customer to a live person with the full context of the interaction
+*Involve another NLU/AI platform – if it specializes in a particular topic
-* Offer a callback - if outside of business hours or long wait time then the voicebot offers a callback from the voice channel
+*Hand off to a voice agent – to connect the customer to a live person with the full context of the interaction
-* Offer a voicebot survey depending on business context
+*Offer a callback - if outside of business hours or long wait time then the voicebot offers a callback from the voice channel
 |PainPoints=*Agents wasting time, capturing routine information
 *Increasing interactions on voice channels
@@ Line 51: / Line 55: @@
 <br />
 |BuyerPersonas=Chief Digital Officer, Head of Customer Experience, Head of Business Units, Head of Customer Service
 |MaturityLevel=Differentiated
 |BusinessImageFlow={{SMART BusinessImageFlow
 |BusinessImage=https://www.lucidchart.com/documents/edit/20930a15-2e99-42c6-948a-364417c1f4ce/0
@@ Line 129: / Line 139: @@
 Survey
 * Based on context from PureConnect, Intelligent Automation, Genesys User Data, or third-party web service
 |DistributionLogic=When the conversation is handed over to a live agent, the interaction moves to one of these use cases, depending on the channel the customer is using - please see the Use Case Interdependencies section for related use cases.
 |CustomerInterfaceRequirements=N/A
@@ Line 155: / Line 166: @@
 *# Spanish (Mexican)
 *# German<br />
 |RequiresAll=CE01
 |SMART_PremiseAssumptions={{SMART PremiseAssumptions
 |Premise_Assumption=The IVR transcript will not be passed.
@@ Line 163: / Line 178: @@
 |Premise_Assumption=Additional infrastructure will be required to support UniMRCP and Google ASR
 }}
 |SMART_CloudAssumptions={{SMART CloudAssumptions
 |Cloud_Assumption=Google ASR will be connected through a universal UniMRCP connector, this will support voicebots through Intelligent Automation, if a customer needs voice based ASR they will require Nuance.
@@ Line 170: / Line 186: @@
 |Cloud_Assumption=Additional infrastructure will be required to support UniMRCP and Google ASR.
 }}
 |DocVersion=1.0.1
 }}