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Activating and training Pega Sales Automation 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:

If you installed the Pega Sales Automation sample application, to reset the artificial intelligence sample, use the Tools menu in the Sales Ops portal. This resets the sample data that is related to artificial intelligence features for demonstration purposes.

Activating artificial intelligence

  1. In the App Studio Explorer panel, click Settings > Application Settings.
  2. Click the Features tab.
  3. In the Features section, select the Artificial intelligence insights - opportunity insights, lead ranking, and sales coach check box.
  4. Click Save.
  5. In Dev Studio, open the SA-Artifacts agent schedule.
  6. On the Edit Agent screen, select the Enabled? check box for all scheduled agents.
  7. Click Save.

Verifying Decision Strategy Manager (DSM) nodes

  1. In Dev Studio, click Configure > Decisioning > Infrastructure > Services.
  2. Verify that each of the following services contains a node with a Status of Normal:
    • Decision Data Store
    • Adaptive Decision Manager
    • Data Flow
    • Visual Business Director

Importing historical data

  1. In Dev Studio, click Configure > Application > Distribution > Import.
  2. Click Choose File, browse for and select the HistoricalData file from your distribution media, 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 Dev Studio header search text field, search for and select the pxDecisionResults data set of the Data-Decision-Results class.
  2. ClickActions > Run.
  3. In the Operations field, select Truncate.
  4. Click Execute.
  5. Repeat steps 1 through 4 for the PreviousStages data set of the SA-SR class.

Deleting existing models

  1. In Dev Studio, click Configure > Decisioning > Predictive Analytics > Adaptive Models Management.
  2. Select all of the existing models:
    • PredictWin
    • PredictMoveNextStage
    • PredictCloseDate
    • BaseWinModel
    • LeadRanking
    • PredictEffectiveness
  3. Click Delete Models.

Running the data flows for opportunity insights

  1. In the Dev Studio header search text field, search for and select the StoreOpportunitySnapshots data flow.
  2. Click Actions > Run.
  3. On the Data flow test run form, click Start.
  4. Repeat steps 1 through 3 for the TrainFromHistory data flow.

Running the data flows for sales coach

  1. In the Dev Studio header search text field, search for and select the StoreSalesRepSnapshots data flow.
  2. Click Actions > Run.
  3. On the Data flow test run form, click Start.
  4. Repeat steps 1 through 3 for the CaptureEffectivenessOutcomes data flow.

Running the data flows for lead ranking

  1. In the Dev Studio header search text field, search for and select the StoreLeadSnapshots data flow.
  2. Click Actions > Run.
  3. On the Data flow test run form, click Start.
  4. Repeat steps 1 through 3 for the CaptureLeadOutcomes data flow.
  5. To set up predictors and calculate lead score for already existing leads in application and store it in lead predictor table, run the InitialiseLeadPredictorTable activity.

Enabling preloaded NBAs

  1. Set usePreloadedNBA DSS to true.
  2. Override GenerateNBA job scheduler and set Enable job scheduler toggle to true.
    To see the job scheduler changes instantly, run LoadNBAForAllOpps dataflow.
  3. Optional: If your implementation layer has additional NBAs, add them by overriding LoadNBAForAllOpps_Ext dataflow. Then, create declare triggers to track work item updates.

Published October 24, 2017 — Updated October 25, 2018


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