PE-GPR/HIW - Revision history

Peter.chaplin@genesys.com: Published

2021-08-31T09:37:29Z

Published

WikiSysop: Text replacement - "\|Platform=([^\|])GenesysEngage-onpremises([\|])" to "|Platform=$1GenesysEngage-cloud$2"

2020-07-25T02:32:09Z

Text replacement - "\|Platform=([^\|]*)GenesysEngage-onpremises([\|]*)" to "|Platform=$1GenesysEngage-cloud$2"

WikiSysop: Text replacement - "\|Platforms?=([^\|])PureEngage([\|])" to "|Platform=$1GenesysEngage-onpremises$2"

2020-07-15T11:44:22Z

Text replacement - "\|Platforms?=([^\|]*)PureEngage([\|]*)" to "|Platform=$1GenesysEngage-onpremises$2"

Vivian: Published

2020-06-18T15:58:18Z

Published

Bgrenon: Published

2020-06-08T16:39:29Z

Published

New page

{{HIW
|product=
|Standalone=
|DisplayName=How Predictive Routing works
|Application=GPR Core Platform
|TocName=How Predictive Routing works
|Platform=PureEngage
|ComingSoon=No
|Context=Learn how Predictive Routing scores agents to find the best match between agent and interaction for the KPI you want to optimize.
|featurename=Predictive Routing
|ShortDescription=Predictive Routing uses Machine Learning to match agents and interactions so as to optimize your most important KPIs.
|overviewtext=Your environment provides a rich source of historical data about your agents, customers, interactions, and interaction outcomes. Predictive Routing (GPR) ingests this data in a systematic way, then uses it to score your agents for each interaction. Agent scores indicate how well each agent should be able to resolve the customer's need in a way that optimizes whichever metric you are trying to improve. The machine learning component ensures that GPR continuously improves scoring accuracy based on outcome data from previous interaction-agent matchups.
|featureoverview=Predictive Routing (GPR) consists of three components, Data Loader, the GPR Core Platform, and the URS Strategy Subroutines. Data Loader uploads your data to the Core Platform. The Core Platform enables you to create view your data, create and maintain Predictors and Models, and scores agents. The URS strategy Subroutines integrate into your routing solution, where they submit interaction details to the Core Platform, which scores your agents for their predicted level of success with that interaction, and then route the interaction based on the scoring response.
|FeatureSection=
|HIWSection=
}}

@@ Line 1: / Line 1: @@
 {{HIW
 |DisplayName=How Predictive Routing works
 |TocName=How Predictive Routing works
@@ Line 10: / Line 8: @@
 |featurename=Predictive Routing
 |ShortDescription=Predictive Routing uses Machine Learning to match agents and interactions so as to optimize your most important KPIs.
-|overviewtext=Your environment provides a rich source of historical data about your agents, customers, interactions, and interaction outcomes. Predictive Routing (GPR) ingests this data in a systematic way, then uses it to score your agents for each interaction. Agent scores indicate how well each agent should be able to resolve the customer's need in a way that optimizes whichever metric you are trying to improve. The machine learning component ensures that GPR continuously improves scoring accuracy based on outcome data from previous interaction-agent matchups.
+|overviewtext=Your environment provides a rich source of historical data about your agents, customers, interactions, and interaction outcomes. Predictive Routing (GPR) ingests this data in a systematic way, then uses it to score your agents for each interaction. Agent scores indicate how well each agent should be able to resolve the customer's need in a way that optimizes whichever metric you are trying to improve. The machine learning component ensures that GPR continuously improves scoring accuracy based on outcome data from previous interaction-agent matchups.  For a high-level view, take a look at the following overview video:
-|featureoverview=Predictive Routing (GPR) consists of three components: the GPR Core Platform (deployed in Pure Engage cloud), Data Loader, and the URS Strategy Subroutines. Data Loader uploads your data to the Core Platform. The Core Platform enables you to create view your data, create and maintain predictors and models, and score agents. It also provides the GPR web application and the GPR API. The URS Strategy Subroutines integrate into your routing solution, where they submit interaction details to the Core Platform for agent scoring in relation to that interaction, and then route the interaction based on the scoring response.
-|FeatureSection=
+{{Video|id=312195823|Description=Predictive Routing overview}}
-|HIWSection=
 }}

@@ Line 6: / Line 6: @@
 |Context=Learn how Predictive Routing scores agents to find the best match between agent and interaction for the KPI you want to optimize.
 |ComingSoon=No
-|Platform=GenesysEngage-onpremises
+|Platform=GenesysEngage-cloud
 |Application=GPR Core Platform
 |featurename=Predictive Routing

PE-GPR/HIW - Revision history

Peter.chaplin@genesys.com: Published

WikiSysop: Text replacement - "\|Platform=([^\|]*)GenesysEngage-onpremises([\|]*)" to "|Platform=$1GenesysEngage-cloud$2"

WikiSysop: Text replacement - "\|Platforms?=([^\|]*)PureEngage([\|]*)" to "|Platform=$1GenesysEngage-onpremises$2"

Vivian: Published

Bgrenon: Published

WikiSysop: Text replacement - "\|Platform=([^\|])GenesysEngage-onpremises([\|])" to "|Platform=$1GenesysEngage-cloud$2"

WikiSysop: Text replacement - "\|Platforms?=([^\|])PureEngage([\|])" to "|Platform=$1GenesysEngage-onpremises$2"