CE37/Canonical - Revision history

Shane.landy@genesys.com: USC: Updated HLF embed code

2021-03-31T15:27:30Z

USC: Updated HLF embed code

Shane.landy@genesys.com at 17:06, January 28, 2021

2021-01-28T17:06:02Z

Shlandy93 at 16:49, June 22, 2020

2020-06-22T16:49:31Z

Shlandy93 at 17:20, June 17, 2020

2020-06-17T17:20:59Z

Shlandy93 at 13:03, April 15, 2020

2020-04-15T13:03:35Z

Shlandy93 at 13:16, April 8, 2020

2020-04-08T13:16:59Z

Bgrenon: 1 revision imported

2020-03-26T15:34:42Z

1 revision imported

smart_wiki>Shlandy93 at 12:25, March 24, 2020

2020-03-24T12:25:52Z

Shlandy93 at 11:01, July 17, 2019

2019-07-17T11:01:54Z

Shlandy93 at 17:17, January 24, 2019

2019-01-24T17:17:45Z

@@ Line 16: / Line 16: @@
 *Proactively engage with customers via a chatbot if this score drops below a defined threshold while on the website
 *Deflect from live agent contact by proactively displaying additional information or offering the most cost-effective channel
-|HighLevelFlowLucid=https://www.lucidchart.com/documents/edit/e1dbefe6-cdd0-4ea9-9f29-7ef2106bfada/0
+|HighLevelFlowLucid=e1dbefe6-cdd0-4ea9-9f29-7ef2106bfada
 |BuyerPersonas=Chief Digital Officer, Head of Contact Center(s), Head of Customer Experience, Head of Customer Service
 |QualifyingQuestions=# What insights do you have about the behaviors that determine whether someone on your website is lost or unable to complete a service task?

@@ Line 3: / Line 3: @@
 |Solution=Digital
 |Title=Genesys Predictive Engagement
-|Subtitle=Use machine learning powered journey analytics to observe website activity, predict visitor outcomes, and proactively engage with prospects and customers via agent-assisted chat, content offer or chatbot.
+|Subtitle=Use AI powered journey analytics to observe website activity, predict visitor outcomes, and proactively engage with prospects and customers via agent-assisted chat, content offer or chatbot.
 }}
 {{SMART Canonical
 |PlatformChallenge=It’s challenging to identify the right individual, the best moments, and the optimal ways to offer assistance online. Companies want to shape their customers’ journeys and drive them towards desirable outcomes, but it’s hard to utilize all of the available data in a way that is meaningful and actionable. In addition, consumers expect fast answers, but it's expensive to always engage an agent.
 |PlatformSolution=Proactively lead customers to successful journeys on your website. Apply machine learning, dynamic personas, and outcome probabilities to identify the right moments for proactive engagement via a web chat or help content screen-pop.

@@ Line 51: / Line 51: @@
 }}
 {{SMART Benefits
-|CanonicalBenefitID=Reduced Volume of Interactions
+|CanonicalBenefitID=Reduced Handle Time
-|CanonicalBenefit=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.
+|CanonicalBenefit=When the engagement requires escalation from self-service to assisted service, the agent is provided context of the journey.
 }}

@@ Line 6: / Line 6: @@
 }}
 {{SMART Canonical
-|BuyerPersonas=Chief Digital Officer, Head of Contact Center(s), Head of Customer Experience, Head of Customer Service
+|ID=
 |PlatformChallenge=It’s challenging to identify the right individual, the best moments, and the optimal ways to offer assistance online. Companies want to shape their customers’ journeys and drive them towards desirable outcomes, but it’s hard to utilize all of the available data in a way that is meaningful and actionable. In addition, consumers expect fast answers, but it's expensive to always engage an agent.
 |PlatformSolution=Proactively lead customers to successful journeys on your website. Apply machine learning, dynamic personas, and outcome probabilities to identify the right moments for proactive engagement via a web chat or help content screen-pop.
@@ Line 22: / Line 18: @@
 *Deflect from live agent contact by proactively displaying additional information or offering the most cost-effective channel
 |HighLevelFlowLucid=https://www.lucidchart.com/documents/edit/e1dbefe6-cdd0-4ea9-9f29-7ef2106bfada/0
 }}
 {{SMART DataSheetFlow
@@ Line 43: / Line 44: @@
 {{SMART Benefits
 |CanonicalBenefitID=Improved Employee Productivity
-|CanonicalBenefit=Representatives are empowered with real time customer journey data from your website which allows them to personalize and prioritize engagements with prospective and existing customers. Productivity is improved when reps interact when they have the most likely impact on the sale or customer service
+|CanonicalBenefit=Representatives are empowered with real time customer journey data which allows them to personalize and prioritize engagements with prospective and existing customers.
 }}
 {{SMART Benefits
 |CanonicalBenefitID=Increased Revenue
-|CanonicalBenefit=Accelerate sales and conversion rates by engaging online shoppers in real time at the right time as they browse your website. Grow customer lifetime value through more proactive and personalized service and cross-selling and upselling customers on products or services of greatest value to them.
+|CanonicalBenefit=Accelerate sales and conversion rates by engaging online shoppers in real time at the right time as they browse your website. Grow customer lifetime value through more proactive and personalized service.
 }}
 {{SMART Benefits

@@ Line 6: / Line 6: @@
 }}
 {{SMART Canonical
 |PlatformChallenge=It’s challenging to identify the right individual, the best moments, and the optimal ways to offer assistance online. Companies want to shape their customers’ journeys and drive them towards desirable outcomes, but it’s hard to utilize all of the available data in a way that is meaningful and actionable. In addition, consumers expect fast answers, but it's expensive to always engage an agent.
 |PlatformSolution=Proactively lead customers to successful journeys on your website. Apply machine learning, dynamic personas, and outcome probabilities to identify the right moments for proactive engagement via a web chat or help content screen-pop.
@@ Line 17: / Line 22: @@
 *Deflect from live agent contact by proactively displaying additional information or offering the most cost-effective channel
 |HighLevelFlowLucid=https://www.lucidchart.com/documents/edit/e1dbefe6-cdd0-4ea9-9f29-7ef2106bfada/0
 }}
 {{SMART DataSheetFlow

@@ Line 8: / Line 8: @@
 |PlatformChallenge=It’s challenging to identify the right individual, the best moments, and the optimal ways to offer assistance online. Companies want to shape their customers’ journeys and drive them towards desirable outcomes, but it’s hard to utilize all of the available data in a way that is meaningful and actionable. In addition, consumers expect fast answers, but it's expensive to always engage an agent.
 |PlatformSolution=Proactively lead customers to successful journeys on your website. Apply machine learning, dynamic personas, and outcome probabilities to identify the right moments for proactive engagement via a web chat or help content screen-pop.
-|PainPoints=* Low self-service rate on website leading to high number of contacts into contact center
+|PainPoints=*Low self-service rate on website leading to high number of contacts into contact center
-* Inability to see, understand and engage with customers during service journeys across channels in real time
+*Inability to see, understand and engage with customers during service journeys across channels in real time
-* Website user journeys not optimized for efficient engagement through self-service
+*Website user journeys not optimized for efficient engagement through self-service
-|DesiredState=* Use journey analytics to detect where customers struggle on a website and use this information to improve their service journeys
+|DesiredState=*Use journey analytics to detect where customers struggle on a website and use this information to improve their service journeys
-* Identify the user’s persona, monitor their web behavior, and predict their outcome score related to the customer service process
+*Identify the user’s persona, monitor their web behavior, and predict their outcome score related to the customer service process
-* Use machine learning to profile behavior, predict outcomes and allow organizations to define rules on when to intervene
+*Use machine learning to profile behavior, predict outcomes and allow organizations to define rules on when to intervene
-* Proactively engage with customers via a chatbot if this score drops below a defined threshold while on the website
+*Proactively engage with customers via a chatbot if this score drops below a defined threshold while on the website
-* Deflect from live agent contact by proactively displaying additional information or offering the most cost-effective channel
+*Deflect from live agent contact by proactively displaying additional information or offering the most cost-effective channel
 |HighLevelFlowLucid=https://www.lucidchart.com/documents/edit/e1dbefe6-cdd0-4ea9-9f29-7ef2106bfada/0
 |BuyerPersonas=Chief Digital Officer, Head of Contact Center(s), Head of Customer Experience, Head of Customer Service
@@ Line 42: / Line 42: @@
 }}
 {{SMART Benefits
 |CanonicalBenefit=Representatives are empowered with real time customer journey data from your website which allows them to personalize and prioritize engagements with prospective and existing customers. Productivity is improved when reps interact when they have the most likely impact on the sale or customer service
 }}

← Older revision	Revision as of 15:34, March 26, 2020
(No difference)

@@ Line 7: / Line 7: @@
 {{SMART Canonical
 |PlatformChallenge=It’s challenging to identify the right individual, the best moments, and the optimal ways to offer assistance online. Companies want to shape their customers’ journeys and drive them towards desirable outcomes, but it’s hard to utilize all of the available data in a way that is meaningful and actionable. In addition, consumers expect fast answers, but it's expensive to always engage an agent.
-|PlatformSolution=Proactively offer assistance to those needing help on your website. Apply machine learning, dynamic personas, and outcome probabilities to identify the right moments for proactive engagement via a chat or callback.
+|PlatformSolution=Proactively offer assistance to those needing help on your website. Apply machine learning, dynamic personas, and outcome probabilities to identify the right moments for proactive engagement via a chat or help content screen-pop.
 |HighLevelFlowLucid=https://www.lucidchart.com/documents/edit/179b3474-b65b-4ed4-97cc-bf202ad85747/0
 |BuyerPersonas=Chief Digital Officer, Head of Contact Center(s), Head of Customer Experience, Head of Customer Service
@@ Line 13: / Line 13: @@
 How do you know when to engage with online customers to provide support and assistance?
 Which channels of engagement can you use today to proactively to engage customers on your website?
 }}
 {{SMART Benefits

@@ Line 2: / Line 2: @@
 |SolutionCategory=CE
 |Solution=Digital
-|Title=Predictive Engagement for Customer Service
+|Title=Genesys Predictive Chatbots
-|Subtitle=Use machine learning powered journey analytics to monitor website activity, predict visitor outcomes, and proactively engage with customers
+|Subtitle=Use machine learning powered journey analytics to monitor website activity in real time, predict visitor outcomes, and use chatbots to proactively engage with customers.
 }}
 {{SMART Canonical