Data Context Engine

  • Freigeben Version: Australia
  • Aktualisiert 12. März 2026
  • 1 Minute Lesedauer

    • The Data Context Engine breaks down silos by aggregating data from multiple sources—both internal and external—collecting it in one place to enable data-driven, actionable decisions.

    The insights gained from analyzing operational data can be used to deliver proactive service, mitigate risks, trigger configured customer plays, and enhance overall engagement strategies. With the Data Context Engine, you can:
    • Collect Data: Gather information from multiple sources including Performance Analytics (PA) indicators and external systems.
    • Analyze Information: Process and categorize data using customizable breakdowns and associations, and generate insights.
    • Visualize Results: Present findings through comprehensive dashboards and reports.
    Data collected by the Data Context Engine is used to calculate and maintain:
    • Health scores: Calculate health scores for customer engagements.
    • Product usage and adoption scores: Generate scores to measure product usage and adoption.
    • Risk signals: Identify and generate risk signals.
    • Success outcomes: Create success outcomes based on the collected data
    To collect and use data, you must set up a data source and link it to the appropriate context table (engagement, success outcome, or product usage). The Context Engine Data table stores this information and updates health scores, adoption metrics, risk signals, and success outcomes when scheduled jobs run. For more details, see Set up the Data Context Engine.