Salesforce-native AI agent detects churn risk and delivers explainable mitigation strategies.
Reactive retention efforts are superseded by automated event-driven workflows that deliver structured mitigation strategies directly within the Salesforce ecosystem.
A Salesforce-native agent that continuously monitors customer activity across cases, emails, and conversation transcripts to identify churn risk and deliver actionable mitigation insights. Using Einstein Prompt Templates for reasoning, it delivers structured analysis through Lightning Web Components and Agentforce.
Prompt-orchestrated architecture enables scalable churn detection with full explainability, transforming reactive support into proactive retention.
The Customer Churn Analysis Agent continuously monitors Salesforce activity data, reasons over churn signals using Einstein Prompt Templates, and delivers structured churn insights through Lightning Web Components and Agentforce. Built on Salesforce's Agentforce, Einstein GenAI, Data Cloud, and LWC technologies, the system provides end-to-end churn intelligence within the native platform ecosystem.
Event + Batch Driven
Prompt Orchestrated
Account-Centric
The system processes customer signals through multiple stages of transformation and analysis:
Customer Signals (Cases, Emails, Calls, Notes)
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Trigger Flows (Email / Case / Opportunity / Notes)
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Eligibility Flag on Account
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Batch Apex (Scheduled / On-demand)
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Churn Insight Flows
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├─ Churn Analysis Prompt
├─ Data Formatter Prompt
└─ JSON Extraction Prompt
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Churn Analysis Report / Summary
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LWC Dashboards & Agentforce Access
Architecture Flow Diagram
Collects behavioral and operational signals.
Cases, Emails, Opportunities
Salesloft & Genesys transcripts
Employee-flagged churn indicators
Structured churn analysis using prompts.
Churn category & justification
Sentiment and risk indicators
Mitigation recommendations
Insights delivered within Salesforce.
Account-level churn reports
LWC dashboards & summaries
Agentforce conversational access
Scalable: Batch Apex processes large account volumes.
Explainable: AI outputs are structured and stored.
Proactive: Event-driven churn detection.
Composable: Flows, prompts, and UI evolve independently.
Churn analysis reports are indexed using a retriever-backed RAG pattern, enabling Agentforce to answer churn-related questions with contextual evidence.
User Question │ ▼ Agentforce (Churn Topic) │ ▼ Search Retriever (Churn Reports) │ ▼ Churn Summary RAG Prompt │ ▼ Contextual, Evidence-backed Response
Architecture Flow Diagram
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