Difference between revisions of "UseCases/Current/PureConnect/SL09"
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|UCSummary=Genesys Predictive Engagement monitors individual customer journeys on your company website and applies machine learning, dynamic segmentation, and real-time outcome scoring to identify the right moments for proactive engagement with the right customer via chat or content offer. When the visitor interacts, the sales rep has the customer journey information at their fingertips. | |UCSummary=Genesys Predictive Engagement monitors individual customer journeys on your company website and applies machine learning, dynamic segmentation, and real-time outcome scoring to identify the right moments for proactive engagement with the right customer via chat or content offer. When the visitor interacts, the sales rep has the customer journey information at their fingertips. | ||
|Description=Reporting, Callback, Content Offer and third-party integration capabilities with Predictive Engagement are awaiting common architecture direction, for further details please contact your respective Product Manager. Customer Service applications of this use case are covered by a use case, CE37. | |Description=Reporting, Callback, Content Offer and third-party integration capabilities with Predictive Engagement are awaiting common architecture direction, for further details please contact your respective Product Manager. Customer Service applications of this use case are covered by a use case, CE37. | ||
| − | |PainPoints=* Inability to see, understand and engage in real time with customers and prospects across channels | + | |PainPoints=* Inability to see, understand and engage in real time with customers and prospects across channels. |
| − | * Low conversion rate on website | + | * Low conversion rate on website. |
| − | * | + | * Poorly utilized inside sales staff. |
| − | * | + | * Difficulty in creating and converting qualified online sales opportunities. |
| − | + | * Low optimization of website user journeys of efficient engagement through self- and assisted- service. | |
| − | * | + | |DesiredState=* Use journey analytics to detect where customers or prospects struggle on a website. Use this information to improve their purchasing journeys. |
| − | |DesiredState=* Use journey analytics to detect where customers or prospects struggle on a website | + | * Identify the visitor's segmentation, monitor their web behavior, and predict their outcome score related to the online purchasing process. |
| − | * Identify the visitor's segmentation, monitor their web behavior, and predict their outcome score related to the online purchasing process | + | * Use machine learning to profile behavior, predict outcomes, and allow organizations to define rules on when intervention is necessary. |
| − | * Use machine learning to profile behavior, predict outcomes and allow organizations to define rules on when | + | * Proactively engage with prospects via chat or content offer if this score drops below a defined threshold while on the website. |
| − | * Proactively engage with prospects via chat or content offer if this score drops below a defined | + | * Engage a sales rep at the critical point in the sales process to increase likelihood of closing the sale, while improving customer experience. |
| − | * Engage a sales rep at the critical point in the sales process to increase likelihood of closing the sale, while improving customer | + | * Identify hot leads on the website via customer browsing behavior and predict customer likelihood to perform a specific action. |
| − | * Provide sales rep with context from the customer journey on the website | + | * Provide sales rep with context from the customer journey on the website. |
| − | * Deflect from live agent contact by proactively displaying additional information or offering the most cost-effective channel for the specific customer segment | + | * Deflect from live agent contact by proactively displaying additional information or offering the most cost-effective channel for the specific customer segment. |
|BuyerPersonas=Chief Digital Officer, Head of Sales, Head of Ecommerce | |BuyerPersonas=Chief Digital Officer, Head of Sales, Head of Ecommerce | ||
|MaturityLevel=Differentiated | |MaturityLevel=Differentiated | ||
Revision as of 16:49, March 10, 2020
No results
Important
Customer Service applications of this use case is addressed by Genesys Predictive Chatbots (CE37).No results
Contents
Use Case Overview
Story and Business Context
Info needed.
Use Case Benefits*
The following benefits are based on benchmark information captured from Genesys customers and may vary based on industry, lines of business or Genesys product line: Info needed.
*You can sort all use cases according to their stated benefits here: Sort by benefits
Summary
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Use Case Definition
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Business and Distribution Logic
Business Logic
Info needed.
Customer-facing Considerations
Interdependencies
All required, alternate, and optional use cases are listed here, as well as any exceptions.
| All of the following required: | At least one of the following required: | Optional | Exceptions |
|---|---|---|---|
| None | None | None | None |
Document Version
Needs info.