EE24/Canonical - Revision history

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

2021-04-01T11:21:13Z

USC: Updated HLF embed code

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

2021-02-15T16:45:37Z

USC: Updated benefits to align with calculators

Shlandy93 at 14:16, April 1, 2020

2020-04-01T14:16:44Z

Bgrenon: 1 revision imported

2020-03-26T15:34:40Z

1 revision imported

smart_wiki>Shlandy93 at 14:20, March 24, 2020

2020-03-24T14:20:20Z

Shlandy93 at 16:58, January 15, 2020

2020-01-15T16:58:32Z

Bgrenon: 1 revision imported

2018-08-22T18:18:24Z

1 revision imported

Shlandy93 at 18:19, July 19, 2018

2018-07-19T18:19:01Z

New page

{{SMART Meta
|SolutionCategory=EE
|Solution=Workforce Engagement
|Title=Genesys Text and Speech Analytics for Customer Service
|Subtitle=Mine call recordings for insights to improve agent and customer experiences
}}
{{SMART Canonical
|PlatformChallenge=Most customer requests and issues follow consistent patterns, but you still need people to make sense of their language to respond. Teams can still miss emerging changes in customer requests until they become bigger issues. Finally, how can you identify better issue handling to adopt for training?
|PlatformSolution=AI transcription of voice, combined with text interactions in all channels, identifies keywords and phrases along with customer context to improve responses. Detect changes in the occurrence of words and phrases over time and across interactions to unlock valuable insights into call outcomes.
|HighLevelFlowLucid=https://www.lucidchart.com/documents/edit/74ad401d-942d-422f-8b38-bb8668ab6a4b/0
|BuyerPersonas=Chief Data Officer, Head of Customer Experience, Head of Customer Service
|QualifyingQuestions=1 How are you identifying patterns of requests and issues on your current channels?

2 Do you think your teams are finding new or changing customer issues fast enough to respond proactively (before they snowball)?

3 How do you find the best practices that your teams are naturally developing so they can be shared or used for training?
}}
{{SMART DataSheetFlow
|Flow=Focus areas and campaigns are identified
}}
{{SMART DataSheetFlow
|Flow=A list of topics, phrases and words is created
}}
{{SMART DataSheetFlow
|Flow=Calls are classified based on their sales outcome
}}
{{SMART DataSheetFlow
|Flow=Agent performance is classified
}}
{{SMART DataSheetFlow
|Flow=Focused training is provided bases on performance
}}
{{SMART DataSheetFlow
|Flow=Sales outcomes are in turn improved
}}
{{SMART Benefits
|CanonicalBenefitID=Improved Customer Experience
|CanonicalBenefit=Identify and understand what makes a great experience for each type of contact.
}}
{{SMART Benefits
|CanonicalBenefitID=Increased Revenue
|CanonicalBenefit=Improve attribution, including online to offline engagement, through call analysis.
}}
{{SMART Benefits
|CanonicalBenefitID=Reduced Customer Churn
|CanonicalBenefit=Identify new issues as they emerge from the noise with frequency and new terms monitoring.
}}

@@ Line 17: / Line 17: @@
 *Rapid iteration of customer engagement strategies to be more effective
 *Objective quantification of benefits in using Interaction Analytics for service improvement
-|HighLevelFlowLucid=https://www.lucidchart.com/documents/edit/74ad401d-942d-422f-8b38-bb8668ab6a4b/0
+|HighLevelFlowLucid=74ad401d-942d-422f-8b38-bb8668ab6a4b
 |BuyerPersonas=Chief Data Officer, Head of Customer Experience, Head of Customer Service
 |QualifyingQuestions=1 How are you identifying patterns of requests and issues on your current channels?

@@ Line 8: / Line 8: @@
 |PlatformChallenge=Most customer requests and issues follow consistent patterns, but you still need people to make sense of their language to respond. Teams can still miss emerging changes in customer requests until they become bigger issues. Finally, how can you identify better issue handling to adopt for training?
 |PlatformSolution=AI transcription of voice, combined with text interactions in all channels, identifies keywords and phrases along with customer context to improve responses. Detect changes in the occurrence of words and phrases over time and across interactions to unlock valuable insights into call outcomes.
-|PainPoints=* Poor, disappointing or ineffective customer service or customer service experiences
+|PainPoints=*Poor, disappointing or ineffective customer service or customer service experiences
-* Inability to distinguish between performance of agents and effectiveness of Customer Service strategies
+*Inability to distinguish between performance of agents and effectiveness of Customer Service strategies
-* Reliance on anecdotal feedback about Customer Service effectiveness
+*Reliance on anecdotal feedback about Customer Service effectiveness
-* Contention/ disagreement/ conflicting opinions on what is or is not effective either in terms of CX or Customer Service strategies or agent behavior
+*Contention/ disagreement/ conflicting opinions on what is or is not effective either in terms of CX or Customer Service strategies or agent behavior
-* Wide variation in agent performance or effectiveness
+*Wide variation in agent performance or effectiveness
-|DesiredState=* Improved service performance
+|DesiredState=*Improved service performance
-* A/B testing of Customer Service strategies and agent behavior used to determine most effective approaches
+*A/B testing of Customer Service strategies and agent behavior used to determine most effective approaches
-* Rapid iteration of customer engagement strategies to be more effective
+*Rapid iteration of customer engagement strategies to be more effective
-* Objective quantification of benefits in using Interaction Analytics for service improvement
+*Objective quantification of benefits in using Interaction Analytics for service improvement
 |HighLevelFlowLucid=https://www.lucidchart.com/documents/edit/74ad401d-942d-422f-8b38-bb8668ab6a4b/0
 |BuyerPersonas=Chief Data Officer, Head of Customer Experience, Head of Customer Service
@@ Line 47: / Line 47: @@
 }}
 {{SMART Benefits
-|CanonicalBenefitID=Improved Customer Experience
+|CanonicalBenefitID=Improved Net Promoter Score
 |CanonicalBenefit=Identify and understand what makes a great experience for each type of contact.
 }}

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

@@ Line 6: / Line 6: @@
 }}
 {{SMART Canonical
 |BuyerPersonas=Chief Data Officer, Head of Customer Experience, Head of Customer Service
 |QualifyingQuestions=1 How are you identifying patterns of requests and issues on your current channels?
@@ Line 15: / Line 27: @@
 How do you find the best practices that your teams are naturally developing so they can be shared or used for training?
 |DataSheetImage=CE09 - genesys ivr personalization - header (2).png
 }}
 {{SMART DataSheetFlow

← Older revision	Revision as of 18:18, August 22, 2018
(No difference)