Analyze Churn Risk Alert — Sales Intelligence

Sales teams analyze deals and customer data across systems. Manual analysis misses opportunities and risks.

44
Fields Extracted
300s
Max Processing
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What This Template Does

AI-powered extraction using gemini-2.5-flash. Part of 113 production-ready templates.

Capabilities

  • Reporting
  • Risk Assessment
  • Pipeline Analysis
  • Pipeline
  • Reporting

Output Schema

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "title": "Churn Risk Alert Output",
  "description": "Structured output for identifying accounts at risk of churning",
  "type": "object",
  "required": [
    "account_name",
    "revenue_at_risk",
    "risk_level",
    "churn_indicators",
    "document_type"
  ],
  "properties": {
    "account_name": {
      "type": "string",
      "description": "Name of the customer account"
    },
    "account_id": {
      "type": "string",
      "d
...

Quick Start

$ pip install doclayer
$ doclayer process document.pdf --agent sales.churn-risk-alert

See It In Action

Real extraction example showing input document and structured output.

Input Document
ACCOUNT HEALTH REPORT - CHURN RISK ASSESSMENT

Report Generated: January 20, 2025
Analysis Period: October 1, 2024 - December 31, 2024 (Q4 2024)

ACCOUNT INFORMATION
===================
Account Name: Pinnacle Financial Group
Account ID: ACC-45892
Industry: Financial Services
Segment: Enterprise
Customer Since: March 2022
CSM: Amanda Torres

CONTRACT DETAILS
================
Product: DocLayer Enterprise Suite
ARR: $385,000
Contract Start: April 1, 2024
Contract End: March 31, 2025
Days Until Rene
Extracted Data
{
  "account_name": "Pinnacle Financial Group",
  "account_id": "ACC-45892",
  "segment": "Enterprise",
  "revenue_at_risk": "$385,000.00",
  "contract_renewal_date": "2025-03-31",
  "days_until_renewal": 70,
  "usage_metrics": {
    "active_users": {
      "current": 148,
      "previous": 245,
      "change_percentage": "-39.6%"
    },
    "api_calls": {
      "current": "1.8M/month",
      "previous": "3.2M/month",
      "change_percentage": "-43.8%"
    },
    "feature_adoption": "6/15 features",
    "storage_used": "42% of 5TB allocation"
  },
  "nps_score": -25,
  "nps_category": "Detractor",
  "nps_feedback": "The platform has become unreliable. We've experienced three outages in the past two months that disrupted our operations. Support response has been slow and unhelpful. We are actively evaluating alternatives.",
  "csat_score": 2.1,
  "support_metrics": {
    "open_tickets": 2,
    "tickets_last_quarter": 34,
    "escalations": 4,
    "avg_resolution_time": "18.5 hours"
  },
  "engagement_metrics": {
    "days_since_last_login": 3,
    "days_since_csm_contact": 73,
    "executive_sponsor_status": "left_company"
  },
  "billing_status": {
    "status": "current",
    "failed_payments": 0,
    "days_overdue": 0
  },
  "health_score": 28,
  "risk_level": "CRITICAL",
  "churn_indicators": [
    "Usage drop of 39.6% in active users (Q4 vs Q3)",
    "API calls declined 43.8% quarter-over-quarter",
    "NPS score of -25 (strong Detractor)",
    "Executive sponsor (VP Technology) left company",
    "No CSM contact in 73 days",
    "Support ticket volume increased 325%",
    "Average resolution time 18.5 hours vs 4-hour SLA",
    "Actively evaluating competitors (DataVault Pro, CloudDocs Inc)",
    "Feature adoption dropped from 11 to 6 features",
    "Stakeholders reverting to manual processes"
  ],
  "recommended_actions": [
    {
      "action": "Executive escalation - VP/C-level outreach within 48 hours",
      "priority": "immediate",
      "owner": "Executive"
    },
    {
      "action": "Assign dedicated support engineer for open P2 tickets",
      "priority": "immediate",
      "owner": "Support"
    },
    {
      "action": "Schedule QBR with IT leadership and business stakeholders",
      "priority": "high",
      "owner": "CSM"
    },
    {
      "action": "Identify and engage new executive sponsor",
      "priority": "high",
      "owner": "Sales"
    },
    {
      "action": "Offer extended POC of new reliability features",
      "priority": "medium",
      "owner": "CSM"
    },
    {
      "action": "Prepare retention package (discount, extended terms, premium support)",
      "priority": "medium",
      "owner": "Sales"
    }
  ],
  "csm_assigned": "Amanda Torres",
  "document_type": "churn_risk_alert",
  "alert_generated_at": "2025-01-20T09:00:00Z"
}

Example showing identification of high-risk enterprise account with 39% usage decline and negative NPS. Demonstrates extraction of churn indicators including executive sponsor departure and poor support sentiment for risk assessment.

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Frequently Asked Questions

What documents can Churn Risk Alert process?

The Churn Risk Alert template processes sales documents including various formats and layouts. See the instructions for specific document types supported.

How accurate is the Churn Risk Alert extraction?

The Churn Risk Alert template uses Gemini 2.5 Flash for high-accuracy extraction. Results include confidence scores for each field.

Can I customize the Churn Risk Alert template?

Yes, you can modify the extraction schema, add custom fields, or adjust the instructions to match your specific requirements.

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