Activating and training adaptive models for artificial intelligence
Artificial intelligence in Pega Sales Automation helps you to proactively assess risks on deals in the pipeline, coach newly recruited sales representatives, and identify leads that have a high probability to be converted to opportunities. Before using artificial intelligence insights with Pega Sales Automation, activate the feature for your implementation and then configure the application to train Pega’s adaptive models for artificial intelligence.
To configure your application for artificial intelligence, log in to Pega Sales Automation and complete the following steps:- Activating artificial intelligence
- Verifying Decision Strategy Manager (DSM) nodes
- Importing historical data
- Truncating data sets
- Deleting existing models
- Running the data flows for opportunity insights
- Running the data flows for sales coach
- Optional: Running the data flows for lead ranking (B2B selling mode)
- Optional: Running the data flows for lead ranking (B2C selling mode)
- Enabling preloaded next best actions (NBAs)
- In the navigation pane of App Studio, click .
- On the Features tab, select the Artificial intelligence insights - opportunity insights, lead ranking, and sales coach check box to see all of the AI capabilities.
- Enable any of the listed AI capabilities by selecting the individual check box.
- Click Save.
- Switch to Dev Studio.
- In the navigation pane of Dev Studio, click .
- Search for an open the SA-Artifacts agent schedule.
- On the Edit Agent Schedule page, select the Enable this agent check box.
- Click Save.
- In the header of Dev Studio, click .
- Verify that each of the following services on the list contains a node with
a status of Normal:
- Decision Data Store
- Adaptive Decision Manager
- Data Flow
- Visual Business Director
- In the header of Dev Studio, click .
- Click Choose File, browse for and select the
HistoricalData file from your distribution
media, and then follow the wizard instructions.
Pega-provided historical data consists of a snapshot of data from a production environment for various models.
- In the navigation pane of Dev Studio, click .
- Search for and open the pxDecisionResults data set of the Data-Decision-Results class.
- Click .
- In the Operation field, select Truncate.
- Click Run.
- Repeat steps 2 to 5 for the PreviousStages data set of the SA-SR class.
- In the header of Dev Studio, cllick .
- Select all of the models listed below:
- PredictWin
- PredictMoveNextStage
- PredictCloseDate
- BaseWinModel
- LeadRanking
- PredictEffectiveness
- Click Delete Models.
- In the navigation pane of Dev Studio, click .
- Search for and open the StoreOpportunitySnapshots data flow.
- Click .
- After you see the confirmation message with a successful result, repeat steps 2 and 3 for the TrainFromHistory data flow.
- In the navigation pane of Dev Studio, click .
- Search for and open the StoreSalesRepSnapshots data flow.
- Click .
- After you see the confirmation message with a successful result, repeat steps 2 and 3 for the CaptureEffectivenessOutcomes data flow.
- In the navigation pane of Dev Studio, click .
- Search for and open the StoreLeadSnapshots data flow.
- Click .
- Repeat steps 2 and 3 for the CaptureLeadOutcomes data flow.
- Optional: To set up predictors and calculate lead score for already existing leads and store them in the lead predictor table, run the InitialiseLeadPredictorTable activity.
- In the navigation pane of Dev Studio, click .
- Search for and open the StoreIndividualLeadSnapshots data flow.
- Click .
- Repeat steps 2 and 3 for the CaptureIndividualLeadOutcomes data flow.
- Optional: To set up predictors and calculate lead score for already existing leads and store them in the lead predictor table, run the InitialiseLeadPredictorTable activity.
- In the navigation pane of Dev Studio, click .
- Search for and open the usePreloadedNBA dynamic system setting.
- In the Value field, set the value true.
- In the navigation pane of Dev Studio, click .
- Search for and open the GenerateNBA job scheduler.
- Turn on the Enable Job Scheduler switch.
- Optional: If your implementation layer has additional next best actions, add them by overriding the LoadNBAForAllOpps_Ext data flow. Then, create declare triggers to track work item updates.
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