ServiceNow Otto for Telecommunications, Media, and Technology (TMT) monitor engagement health agentic workflow
Summarize
Summary of ServiceNow Otto for Telecommunications, Media, and Technology (TMT) Monitor Engagement Health Agentic Workflow
The Monitor Engagement Health Agentic Workflow in ServiceNow Otto for TMT enables customer success managers to track the health scores and metric trends of up to 10 active customer engagements. This AI-driven workflow analyzes individual metrics weekly over a 6-week period to detect declining patterns, generating risk signals or risk occurrences when deterioration is identified. The workflow supports proactive management of customer engagement health, helping to identify and address risks early.
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Key Features
- Engagement Monitoring: Tracks health scores for up to 10 engagements per customer success manager where the AI Health Monitor flag is enabled.
- Metric-Level and Overall Health Monitoring: By default, monitors individual metric health scores; can be configured to monitor only overall health scores via a system property adjustment.
- Risk Signal Generation: Automatically creates risk signals labeled as "Health declined" and marked as AI generated when negative trends are detected.
- Scheduled Execution: Runs weekly based on a predefined schedule, with results accessible via the ServiceNow Otto panel and Risk signals page.
- Configurable Color Banding: Allows defining different health score thresholds and color categories per data source context to tailor risk assessment visualization.
- AI Agents Involvement: Utilizes two AI agents:
- Success Trend Analyst: Analyzes metric data to identify patterns and anomalies, providing actionable insights.
- Success Health Monitor: Retrieves engagement data, detects declining trends, and triggers risk signals.
Practical Application for ServiceNow Customers
ServiceNow customers in TMT industries can leverage this workflow to maintain close oversight of customer engagement health, enabling timely intervention through AI-generated risk signals. Activating the workflow and configuring health monitoring settings ensures that customer success teams focus on engagements showing signs of decline. Adjusting the monitoring scope and color banding configurations allows customization to organizational needs and customer-specific contexts, enhancing risk prioritization and remediation strategies.
Monitor engagement health scores and metric trends. The workflow generates risk signals when a decline is detected.
Monitor engagement health agentic workflow overview
Customer success managers can monitor the health score of up to 10 active engagements and summarize the health trend for the past 6 weeks. Each metric used to calculate the health score is monitored. If a declining pattern is detected, a risk signal or a risk occurrence is generated. A summary indicating the number of risk signals created and the health score range is generated. The Monitor engagement health agentic workflow is triggered weekly based on a predefined schedule and the results are displayed in the ServiceNow Otto panel.
- Category: Health declined
- Creation method: AI generated
- To run the agentic workflow as a scheduled job, you must activate the Monitor engagement health flow. See Activate a flow for details.
- The agentic workflow monitors only the engagements for which AI Health Monitor flag has been enabled. Each customer success manager can enable a maximum of 10 engagements. For instructions on enabling this flag, see Create an engagement.
- By default, the health score of each individual metric is monitored. If you want to monitor only the overall health score across all engagements, you must update the
sn_cust_succ_ai_agent_enable_health_monitor_metrics system property by following these steps:
- Navigate to All and enter sys_properties.LIST in the search field.
- Select the sn_cust_succ_ai_agent_enable_health_monitor_metrics property.
- Set the Value field to false. When this property is inactive, the agentic workflow will monitor the overall health score instead of the individual metrics.
- For any new or existing health definitions, you must specify the Context for the Data source to indicate how the color banding range will be applied. Based on the
Context, you can define different color banding ranges that can be used for the health score. For example, you can configure different values for the same Data source
as follows:
- Data source 1
- Data source: Daily collection of NPS
- Context: Health Metric Configuration: Daily collection of NPS (Global)
- Min: 80
- Max: 100
- Color: Green
- Category: Good
- Data source 2
- Data source: Daily collection of NPS
- Context: Daily collection of NPS for (Customer X)
- Min: 0
- Max: 60
- Color: Red
- Category: Poor
- Data source 1
AI agents used in the Monitor engagement health agentic workflow
The Monitor engagement health agentic workflow uses specific AI agents to monitor the engagements, analyze the health trend, and generate a health score.
| AI agent | AI agent role |
|---|---|
| Success trend analyst AI agent | Collects and analyzes metric data, processes large data sets, identifies patterns and anomalies. Provides clear actionable insights enabling AI agents to make informed decisions and take appropriate actions. |
| Success health monitor AI agent | Retrieves data for all active engagements, identifies trends, and creates a risk signal if a declining pattern is detected. |