Skip to main content


         This documentation site is for previous versions. Visit our new documentation site for current releases.      
 

Activating and training adaptive models for artificial intelligence

Updated on September 14, 2021

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.

Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide Pega Sales Automation Implementation Guide
To configure your application for artificial intelligence, log in to Pega Sales Automation and complete all the procedures in this section.
Note: If you installed the Pega Sales Automation sample application, as an operator with the Sales Ops persona, reset the artificial intelligence sample data to the original form by using the Tools menu.

Activating artificial intelligence

  1. In the navigation pane of App Studio, click SettingsConfigurations.
  2. In the AI Settings configuration set, set the following options to True using the gear icon:
    • Enable AI
    • Enable Lead Ranking
    • Enable Opportunity Insights
    • Enable Sales Coach
  3. Click Submit.

Enabling the job schedulers

  1. In the navigation pane of Admin Studio, click ResourceJobs
  2. Enable the following job schedulers:
    • OpportunityInsights
    • RecommendationsForRep
    • DailySnapshotsForLead
    • DailySnapshotsForAE

Verifying Decision Strategy Manager (DSM) nodes

  1. In the header of Dev Studio, click ConfigureDecisioningInfrastructureServices.
  2. 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

Importing historical data

  1. In the header of Dev Studio, click ConfigureApplicationDistributionImport.
  2. 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.

Truncating data sets

  1. In the navigation pane of Dev Studio, click RecordsData ModelData Set.
  2. Search for and open the pxDecisionResults data set of the Data-Decision-Results class.
  3. Click ActionsRun.
  4. In the Operation field, select Truncate.
  5. Click Run.
  6. Repeat steps 2 to 5 for the PreviousStages data set of the SA-SR class.

Deleting existing models

  1. In the header of Dev Studio, cllick ConfigureDecisioningModel Management.
  2. Select all of the models listed below:
    • PredictWin
    • PredictMoveNextStage
    • PredictCloseDate
    • BaseWinModel
    • LeadRanking
    • PredictEffectiveness
  3. Click Delete Models.

Running the data flows for opportunity insights (B2B selling mode)

Before you begin: Before performing this procedure, perform the "Activating artificial intelligence" procedure.
Run the data flows for opportunity insights to pass the incoming data to the adaptive models so that the system can calculate opportunity insights for B2B opportunities.
  1. In the navigation pane of Dev Studio, click RecordsData ModelData Flow.
  2. Search for and open the StoreOpportunitySnapshots data flow.
  3. Click ActionsRun.
  4. After you see the confirmation message with a successful result, repeat steps 2 and 3 for the TrainFromHistory data flow.
  5. Optional: To set up predictors and calculate win score for already existing opportunities and store them in the opportunity predictor table, run the SnapshotAndUpdatePredictors activity.

Running the data flows for opportunity insights (B2C selling mode)

Before you begin: Before performing this procedure, perform the "Activating artificial intelligence" procedure.
Run the data flows for opportunity insights to pass the incoming data to the adaptive models so that the system can calculate opportunity insights for B2C opportunities.
  1. In the navigation pane of Dev Studio, click RecordsData ModelData Flow.
  2. Search for and open the StoreIndOpportunitySnapshots data flow.
  3. Click ActionsRun.
  4. After you see the confirmation message with a successful result, repeat steps 2 and 3 for the TrainIndvOppFromHistory data flow.
  5. Optional: To set up predictors and calculate win score for already existing opportunities and store them in the opportunity predictor table, run the SnapshotAndUpdatePredictors activity.

Running the data flows for sales coach

Run the data flows for the sales coach to pass the incoming data to the adaptive models so that the system can calculate sales coach suggestions.

Note: Before performing the steps below, make sure that you have the EnableSalesCoach dynamic system setting set to true.

  1. In the navigation pane of Dev Studio, click RecordsData ModelData Flow.
  2. Search for and open the StoreSalesRepSnapshots data flow.
  3. Click ActionsRun.
  4. After you see the confirmation message with a successful result, repeat steps 2 and 3 for the CaptureEffectivenessOutcomes data flow.

Optional: Running the data flows for lead ranking (B2B selling mode)

Run the data flows for lead ranking to pass the incoming data to the adaptive models so that the system can calculate the B2B lead scores.
  1. In the navigation pane of Dev Studio, click RecordsData ModelData Flow.
  2. Search for and open the StoreLeadSnapshots data flow.
  3. Click ActionsRun.
  4. Repeat steps 2 and 3 for the CaptureLeadOutcomes data flow.
  5. 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.

Optional: Running the data flows for lead ranking (B2C selling mode)

Run the data flows for lead ranking to pass the incoming data to the adaptive models so that the system can calculate the B2C lead scores.
  1. In the navigation pane of Dev Studio, click RecordsData ModelData Flow.
  2. Search for and open the StoreIndividualLeadSnapshots data flow.
  3. Click ActionsRun.
  4. Repeat steps 2 and 3 for the CaptureIndividualLeadOutcomes data flow.
  5. 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.

Enabling preloaded next best actions (NBAs)

  1. In the navigation pane of App Studio, click SettingsConfigurations.
  2. In the AI Settings configuration set, set the following options to True using the gear icon:
    • Enable AI
    • Enable Opportunity Insights
  3. Click Submit.
  4. In the Toggle Settings configuration set, set Use Preloaded NBA to True using gear icon and click Submit.
  5. In the navigation pane of Admin Studio, click ResourceJobs.
  6. Search for and enable the GenerateNBA job scheduler.
  7. Optional: To see the job scheduler changes instantly, run the GenerateNextBestActions activity.

Tags

Pega Sales Automation 8.7

Have a question? Get answers now.

Visit the Support Center to ask questions, engage in discussions, share ideas, and help others.

Visit the Support Center

Did you find this content helpful?

Yes
No

Want to help us improve this content?
Suggest an edit

We'd prefer it if you saw us at our best.

Pega.com is not optimized for Internet Explorer. For the optimal experience, please use:

Close Deprecation Notice
Contact us