Aggregates account data, analyzes churn risk with AI, alerts teams about high-risk accounts, and provides recommended intervention actions.
This workflow is designed for customer success and retention teams who need to proactively identify accounts at risk of churning before they show explicit signs of leaving. By leveraging AI to analyze multiple data points, teams can prioritize their outreach efforts and intervene with the most vulnerable accounts first.
The process begins by aggregating comprehensive data for each customer account, including product usage metrics, support ticket history, NPS/CSAT scores, billing information, and renewal dates. This data is then processed through an AI model that evaluates patterns and indicators to produce a churn risk score. The model identifies concerning combinations of factors, such as declining usage paired with unresolved support issues or approaching renewal dates.
For accounts that exceed the defined risk threshold, the workflow automatically generates detailed alerts with AI-summarized risk factors and recommended next steps. These alerts are delivered to the appropriate team members via their preferred channels (email, Slack, CRM notification), enabling swift intervention. By identifying at-risk accounts early, teams can implement targeted retention strategies before customers initiate cancellation discussions.
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Use this example as a starting point, not a fixed recipe.
Copy the flow above as a prompt, markdown, skill, or mermaid diagrom. Adjust the steps, tools, agent and human involvement to fit your real workflow. Then test where users actually get value or drop off.
Analyze the following customer account data to determine the churn risk level (Low, Medium, High, or Critical) for {companyName}.
Account Data:
- Usage Trends: {usageTrends}
- Support Tickets: {supportTickets}
- NPS/CSAT Scores: {satisfactionScores}
- Billing Status: {billingStatus}
- Renewal Date: {renewalDate}
- Customer Health Score: {healthScore}
- Last Engagement Date: {lastEngagement}
Please provide:
1. An overall risk score with justification
2. The top 3 risk factors identified
3. 2-3 recommended intervention actions based on the specific risk factors
Format your response in a clear, structured manner suitable for a customer success team to quickly understand the situation and take action.