UseCases/Current/PureConnect/CE37 - Revision history

Shane.landy@genesys.com: UCC: removed all references to Altocloud and replaced with Predictive Engagement

2021-04-20T15:51:29Z

UCC: removed all references to Altocloud and replaced with Predictive Engagement

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

2021-02-16T13:45:54Z

UCC: Updated benefits to align with calculators

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

2020-12-01T16:55:12Z

UCC: Updated benefits to align with calculators

Ed.jamer@genesys.com: Text replacement - "Altocloud([. ])" to "Predictive Engagement$1"

2020-11-17T15:02:47Z

Text replacement - "Altocloud([. ])" to "Predictive Engagement$1"

Shlandy93 at 15:42, September 29, 2020

2020-09-29T15:42:11Z

Shlandy93 at 18:04, September 23, 2020

2020-09-23T18:04:32Z

Shlandy93 at 12:33, August 11, 2020

2020-08-11T12:33:01Z

Show changes

Bgrenon: Text replacement - "\|SMART_HybridAssumptions={{SMART HybridAssumptions \|Hybrid_Assumption=(.*) }}" to "|DocVersion=$1"

2020-01-20T22:01:26Z

Text replacement - "\|SMART_HybridAssumptions={{SMART HybridAssumptions \|Hybrid_Assumption=(.*) }}" to "|DocVersion=$1"

Bgrenon: 1 revision imported

2019-04-24T12:24:25Z

1 revision imported

Shlandy93: Published

2019-04-24T12:24:24Z

Published

@@ Line 136: / Line 136: @@
 A CX Insights Dashboard that shows the following will be available:
-* Combined total number of chats (native, Altocloud and bots) for a workgroup for an interval.
+*Combined total number of chats (native, Predictive Engagement and bots) for a workgroup for an interval.
-* Total number of native chats for a workgroup for an interval.
+*Total number of native chats for a workgroup for an interval.
-* Total number of Altocloud chats for a workgroup for an interval.
+*Total number of Predictive Engagement chats for a workgroup for an interval.
-* Total number of bot chats for a workgroup for an interval.
+*Total number of bot chats for a workgroup for an interval.
-* Combined total number of chats (native, Altocloud and bots) for an agent for an interval.
+*Combined total number of chats (native, Predictive Engagement and bots) for an agent for an interval.
-* Total number of native chats for an agent for an interval.
+*Total number of native chats for an agent for an interval.
-* Total number of Altocloud chats for an agent for an interval.
+*Total number of Predictive Engagement chats for an agent for an interval.
-* Total number of bot chats an agent for an interval.
+*Total number of bot chats an agent for an interval.
 |RequiresAll=CE18, CE31
 |GeneralAssumptions=*Genesys Widgets 9 must be used
 *General logic for routing of interactions will be using the logic defined within the mandatory use cases
 *Design and configuration of this use should take it into account previous deployment of mandatory use cases
-*Integration of Altocloud desktop gadgets into Interaction Connect.
+*Integration of Predictive Engagement desktop gadgets into Interaction Connect.
-*Genesys Altocloud for On Premises is sold as Subscription only (On Premises Perpetual customers may consume through subscription).
+*Genesys Predictive Engagement for On Premises is sold as Subscription only (On Premises Perpetual customers may consume through subscription).
-|CustomerAssumptions=*Customer must deploy both Altocloud and Widgets code snippets on their website / web pages
+|CustomerAssumptions=*Customer must deploy both Predictive Engagement and Widgets code snippets on their website / web pages
-|DocVersion=1.0.2
+|DocVersion=1.1.2
 }}

@@ Line 4: / Line 4: @@
 |Offering=PureConnect
 |SMART_Benefits={{SMART Benefits
-|UCBenefitID=Improved Net Promoter Score
+|UCBenefitID=Improved Customer Experience
 |UCBenefit=Offer assistance only as needed to reduce customer annoyance.
 }}{{SMART Benefits
@@ Line 144: / Line 144: @@
 * Total number of Altocloud chats for an agent for an interval.
 * Total number of bot chats an agent for an interval.
-|DocVersion=1.0.2
+|RequiresAll=CE18, CE31
 |GeneralAssumptions=*Genesys Widgets 9 must be used
 *General logic for routing of interactions will be using the logic defined within the mandatory use cases
 *Design and configuration of this use should take it into account previous deployment of mandatory use cases
 |CustomerAssumptions=*Customer must deploy both Altocloud and Widgets code snippets on their website / web pages
-|RequiresAll=CE18, CE31
+|DocVersion=1.0.2
 }}

@@ Line 3: / Line 3: @@
 |Title=Predictive Engagement for Customer Service
 |Offering=PureConnect
 |UCIntro=Please be advised that this use case has been merged with Genesys Predictive Engagement (SL09). SL09 has now been decommissioned and all relevant content is displayed in this use case.
 |UCOverview=One of the biggest challenges for the modern business is learning to work with the data available in a way that is both meaningful and easy to act on. The data generated by a website often goes unexplored, and as a result, the intentions and reactions of individual customers and prospects can be overlooked. Focus is often placed on the broad strokes–key metrics such as the number of conversions per month–and the ability to identify the potential customers who need engagement is lost. As a result, customers who may be on the verge of signing up for a trial, completing a checkout, searching for information regarding service or support, or any other desirable outcome, fall through the cracks. The high volume of website traffic makes it a challenge to identify the right individuals, best moments, and optimal ways to engage in real-time. Expectations for time-to-respond are increasing but growing your staff is costly.
@@ Line 17: / Line 33: @@
 *A customer is planning a trip abroad and needs to notify their credit card company. They go to the company's website and based on a search related to "travel alert," a chatbot is offered to assist to prevent the need to call the contact center.
 *A customer is proactively offered self-help options to assist with a transaction, for example providing a link to a video to help with a Return Merchandise Authorization (RMA).
 |UCSummary=Understanding and using knowledge of online activities and behaviors can provide context to better handle a follow-up digital or voice interaction to help customers who are shopping, buying, using the company's products across the full customer life cycle. This engagement intelligence can also be used for converting service requests to sales opportunities for cross-sell or up-sell. Genesys uses artificial intelligence to observe and analyze the progress of website visitors toward defined outcomes – service requests, pending transactions, application status.  This technology allows the business to engage with customers using dynamic observations and predictions rather than simple static rules- creating happier customers, smarter employees, and better outcomes.
@@ Line 136: / Line 136: @@
 A CX Insights Dashboard that shows the following will be available:
-* Combined total number of chats (native, Predictive Engagement and bots) for a workgroup for an interval.
+* Combined total number of chats (native, Altocloud and bots) for a workgroup for an interval.
 * Total number of native chats for a workgroup for an interval.
-* Total number of Predictive Engagement chats for a workgroup for an interval.
+* Total number of Altocloud chats for a workgroup for an interval.
 * Total number of bot chats for a workgroup for an interval.
-* Combined total number of chats (native, Predictive Engagement and bots) for an agent for an interval.
+* Combined total number of chats (native, Altocloud and bots) for an agent for an interval.
 * Total number of native chats for an agent for an interval.
-* Total number of Predictive Engagement chats for an agent for an interval.
+* Total number of Altocloud chats for an agent for an interval.
 * Total number of bot chats an agent for an interval.
 |GeneralAssumptions=*Genesys Widgets 9 must be used
 *General logic for routing of interactions will be using the logic defined within the mandatory use cases
 *Design and configuration of this use should take it into account previous deployment of mandatory use cases
-|CustomerAssumptions=*Customer must deploy both Predictive Engagement and Widgets code snippets on their website / web pages
+|CustomerAssumptions=*Customer must deploy both Altocloud and Widgets code snippets on their website / web pages
 |RequiresAll=CE18, CE31
 |SMART_PremiseAssumptions={{SMART PremiseAssumptions
-|Premise_Assumption=Integration of Predictive Engagement desktop gadgets into Interaction Connect
+|Premise_Assumption=Integration of Altocloud desktop gadgets into Interaction Connect
 }}{{SMART PremiseAssumptions
-|Premise_Assumption=Genesys Predictive Engagement for On Premises is sold as Subscription only (On Premises Perpetual customers may consume through subscription).
+|Premise_Assumption=Genesys Altocloud for On Premises is sold as Subscription only (On Premises Perpetual customers may consume through subscription).
 }}
 |SMART_CloudAssumptions={{SMART CloudAssumptions
-|Cloud_Assumption=Integration of Predictive Engagement desktop gadgets into Interaction Connect
+|Cloud_Assumption=Integration of Altocloud desktop gadgets into Interaction Connect
 }}
 }}

@@ Line 136: / Line 136: @@
 A CX Insights Dashboard that shows the following will be available:
-* Combined total number of chats (native, Altocloud and bots) for a workgroup for an interval.
+* Combined total number of chats (native, Predictive Engagement and bots) for a workgroup for an interval.
 * Total number of native chats for a workgroup for an interval.
-* Total number of Altocloud chats for a workgroup for an interval.
+* Total number of Predictive Engagement chats for a workgroup for an interval.
 * Total number of bot chats for a workgroup for an interval.
-* Combined total number of chats (native, Altocloud and bots) for an agent for an interval.
+* Combined total number of chats (native, Predictive Engagement and bots) for an agent for an interval.
 * Total number of native chats for an agent for an interval.
-* Total number of Altocloud chats for an agent for an interval.
+* Total number of Predictive Engagement chats for an agent for an interval.
 * Total number of bot chats an agent for an interval.
 |GeneralAssumptions=*Genesys Widgets 9 must be used
 *General logic for routing of interactions will be using the logic defined within the mandatory use cases
 *Design and configuration of this use should take it into account previous deployment of mandatory use cases
-|CustomerAssumptions=*Customer must deploy both Altocloud and Widgets code snippets on their website / web pages
+|CustomerAssumptions=*Customer must deploy both Predictive Engagement and Widgets code snippets on their website / web pages
 |RequiresAll=CE18, CE31
 |SMART_PremiseAssumptions={{SMART PremiseAssumptions
-|Premise_Assumption=Integration of Altocloud desktop gadgets into Interaction Connect
+|Premise_Assumption=Integration of Predictive Engagement desktop gadgets into Interaction Connect
 }}{{SMART PremiseAssumptions
-|Premise_Assumption=Genesys Altocloud for On Premises is sold as Subscription only (On Premises Perpetual customers may consume through subscription).
+|Premise_Assumption=Genesys Predictive Engagement for On Premises is sold as Subscription only (On Premises Perpetual customers may consume through subscription).
 }}
 |SMART_CloudAssumptions={{SMART CloudAssumptions
-|Cloud_Assumption=Integration of Altocloud desktop gadgets into Interaction Connect
+|Cloud_Assumption=Integration of Predictive Engagement desktop gadgets into Interaction Connect
 }}
 |DocVersion=1.0.1
 }}

@@ Line 3: / Line 3: @@
 |Title=Predictive Engagement for Customer Service
 |Offering=PureConnect
 |SMART_Benefits={{SMART Benefits
 |UCBenefitID=Improved Net Promoter Score
@@ Line 19: / Line 33: @@
 |UCBenefit=Reduce customer acquisition cost (CAC). Predict which prospects are most likely to buy based on successful outcomes from previous customers. Use these insights to focus marketing efforts and ad spend on a target profiles or sales sales activities.
 }}
 |UCSummary=Understanding and using knowledge of online activities and behaviors can provide context to better handle a follow-up digital or voice interaction to help customers who are shopping, buying, using the company's products across the full customer life cycle. This engagement intelligence can also be used for converting service requests to sales opportunities for cross-sell or up-sell. Genesys uses artificial intelligence to observe and analyze the progress of website visitors toward defined outcomes – service requests, pending transactions, application status.  This technology allows the business to engage with customers using dynamic observations and predictions rather than simple static rules- creating happier customers, smarter employees, and better outcomes.
@@ Line 143: / Line 144: @@
 * Total number of Altocloud chats for an agent for an interval.
 * Total number of bot chats an agent for an interval.
 |GeneralAssumptions=*Genesys Widgets 9 must be used
 *General logic for routing of interactions will be using the logic defined within the mandatory use cases
@@ Line 157: / Line 157: @@
 |Cloud_Assumption=Integration of Altocloud desktop gadgets into Interaction Connect
 }}
 }}

@@ Line 12: / Line 12: @@
 |UCBenefitID=Reduced Administration Costs
 |UCBenefit=Improve self-service rates by providing customers with the right information at the right time or proactively offering a chatbot to automate the conversation and prevent contact with an agent.
 }}
 |UCOverview=One of the biggest challenges for the modern business is learning to work with the data available in a way that is both meaningful and easy to act on. The data generated by a website often goes unexplored, and as a result, the intentions and reactions of individual customers and prospects can be overlooked. Focus is often placed on the broad strokes–key metrics such as the number of conversions per month–and the ability to identify the potential customers who need engagement is lost. As a result, customers who may be on the verge of signing up for a trial, completing a checkout, searching for information regarding service or support, or any other desirable outcome, fall through the cracks. The high volume of website traffic makes it a challenge to identify the right individuals, best moments, and optimal ways to engage in real-time. Expectations for time-to-respond are increasing but growing your staff is costly.
@@ Line 28: / Line 34: @@
 |UCSummary=Understanding and using knowledge of online activities and behaviors can provide context to better handle a follow-up digital or voice interaction to help customers who are shopping, buying, using the company's products across the full customer life cycle. This engagement intelligence can also be used for converting service requests to sales opportunities for cross-sell or up-sell. Genesys uses artificial intelligence to observe and analyze the progress of website visitors toward defined outcomes – service requests, pending transactions, application status.  This technology allows the business to engage with customers using dynamic observations and predictions rather than simple static rules- creating happier customers, smarter employees, and better outcomes.
-Companies have vast amounts of data within their CRM, marketing automation, contact centers and websites, and Genesys enables companies to unlock that data in real time to engage customers proactively,  eliminating the need for a voice call or contact without context. Genesys Predictive Engagement observes individual customer journeys on your company website and applies machine learning, dynamic (or audience) segmentation, and real-time outcome scoring to identify the right moments for proactive engagement with the right customer via chat, chatbot, or content offer.
+Companies have vast amounts of data within their CRM, marketing automation, contact centers and websites, and Genesys enables companies to unlock that data in real time to engage customers proactively,  eliminating the need for a voice call or contact without context. Genesys Predictive Engagement observes individual customer journeys on your company website and applies machine learning, dynamic (or audience) segmentation, and real-time outcome scoring to identify the right moments for proactive engagement with the right customer via chat, chatbot, or content offer. When the visitor interacts, the sales rep has the customer journey information at their fingertips.
 Predictive Engagement's real-time engagement sophistication increases customer satisfaction, improves conversion rate, and optimizes the use of agent resources for the highest value customers.  Predictive Engagement leads to improvement of key performance indicators such as call deflection, average order value (AOV), first contact resolution, and conversion rates.
@@ Line 74: / Line 80: @@
 }}
 |BusinessLogic=====BL1 – Customer Identification====
-The system can use cookies to detect returning visitors and associate them with previous site visits. Identity information provided during the journey (such as email address or phone number) is captured after it is explicitly submitted from the web page and can identify the visitor even across devices. After the customer is identified, all tracking data collected is associated to that specific customer. All customer information collected is done in a GDPR compliant fashion.
+The system can use cookies to detect returning visitors and associate them with previous site visits. Identity information provided during the journey (such as email address or phone number) is captured after it is explicitly submitted from the web page and can identify the visitor even across devices. After the customer is identified, all tracking data collected is associated to that specific customer. All customer information collected is done in a GDPR compliant fashion. When visitor identity cannot be determined, the customer is handled as an anonymous user and all tracked data attached to them.
 ====BL2 – Segment and Outcome Configuration====
 Segments are a way to categorize visitors on the website based on common behavior and attributes. Segments are configured upfront during system provisioning. A segment can be made up of one or both of these components:
@@ Line 110: / Line 116: @@
 Predictive Engagement can automatically create leads in Salesforce and any CRM that uses Rest APIs through Action Map orchestration.
-|AgentDeskRequirements=*Integration of Genesys Predictive Engagement desktop gadgets into Interaction Connect (if chatbot conversation requires escalation to an agent)<br />
+|AgentDeskRequirements=*Integration of Genesys Predictive Engagement desktop gadgets into Interaction Connect (if chatbot conversation requires escalation to an agent)
 |RealTimeReporting=An admin can see the Live Now view of current visitors and live tracking information on the site. The views allow admins to make real-time operational decisions. For example, when a marketing campaign has gone live and drill into individual customer journeys.
 |HistoricalReporting=Interaction reporter and scheduled reporting are available in Pure Connect to evaluate webchat agent, queue, and customer handling performance.
@@ Line 120: / Line 127: @@
 <span style="background-color: rgb(255, 255, 255);" data-mce-style="background-color: #ffffff;">Action map performance of action types; webchat, content offers and architect flow. It allows a funnel drill-down performance of the key stages which can identify resourcing requirements, queue issues,</span>
-* <span style="background-color: rgb(255, 255, 255);" data-mce-style="background-color: #ffffff;">Qualification</span>
+*<span style="background-color: rgb(255, 255, 255);" data-mce-style="background-color: #ffffff;">Qualification</span>
-* <span style="background-color: rgb(255, 255, 255);" data-mce-style="background-color: #ffffff;">Offer</span>
+*<span style="background-color: rgb(255, 255, 255);" data-mce-style="background-color: #ffffff;">Offer</span>
-* <span style="background-color: rgb(255, 255, 255);" data-mce-style="background-color: #ffffff;">Acceptance</span>
+*<span style="background-color: rgb(255, 255, 255);" data-mce-style="background-color: #ffffff;">Acceptance</span>
-* <span style="background-color: rgb(255, 255, 255);" data-mce-style="background-color: #ffffff;">Engagement</span>
+*<span style="background-color: rgb(255, 255, 255);" data-mce-style="background-color: #ffffff;">Engagement</span>
 |GeneralAssumptions=* Genesys Widgets 9 must be used
 * General logic for routing of interactions will be using the logic defined within the mandatory use cases
-* Design and configuration of this use should take it into account previous deployment of mandatory use cases
+A CX Insights Dashboard that shows the following will be available:
 |CustomerAssumptions=* Customer must deploy both Altocloud and Widgets code snippets on their website / web pages
-|RequiresAll=CE31, CE18
+* Combined total number of chats (native, Altocloud and bots) for a workgroup for an interval.
 |SMART_PremiseAssumptions={{SMART PremiseAssumptions
 |Premise_Assumption=Integration of Altocloud desktop gadgets into Interaction Connect
 }}
 |SMART_CloudAssumptions={{SMART CloudAssumptions
 |Cloud_Assumption=Integration of Altocloud desktop gadgets into Interaction Connect
 }}
 }}

@@ Line 78: / Line 78: @@
 * Visits, Segments and Outcomes
 |HistoricalReporting=<span style="background-color: rgb(255, 255, 255);" data-mce-style="background-color: #ffffff;">Web Journey reporting from Altocloud will not be accessible via Infomart / CX Insights</span>
-|SMART_HybridAssumptions={{SMART HybridAssumptions
+|DocVersion=1.0.1
 |GeneralAssumptions=* Genesys Widgets 9 must be used
 * General logic for routing of interactions will be using the logic defined within the mandatory use cases

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