Analyze Pipeline Health Check — Sales Intelligence
Sales teams analyze deals and customer data across systems. Manual analysis misses opportunities and risks.
53
Fields Extracted
300s
Max Processing
Common Pain Points
- Deals fall through cracks without proper tracking
- Churn signals missed until too late
- Pipeline forecasts are inaccurate
- RFP responses take days instead of hours
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": "Pipeline Health Check Output",
"description": "Structured output for sales pipeline analysis and health metrics",
"type": "object",
"required": [
"total_pipeline",
"coverage_ratio",
"win_rate",
"health_status",
"document_type"
],
"properties": {
"report_period": {
"type": "string",
"description": "Reporting period (e.g., Q1 2025, January 2025)"
},
"report_date": {
"ty
...Quick Start
$ pip install doclayer
$ doclayer process document.pdf --agent sales.pipeline-health
See It In Action
Real extraction example showing input document and structured output.
Input Document
PIPELINE HEALTH REPORT ====================== Period: Q1 2025 (January 1 - March 31) Report Date: January 20, 2025 Scope: North America Sales Team EXECUTIVE SUMMARY ----------------- The North America sales team enters Q1 with a solid pipeline foundation, though coverage in the Mid-Market segment requires attention. Overall pipeline health is HEALTHY with some areas to monitor. QUOTA & COVERAGE ---------------- Q1 Quota: $8.5M Total Open Pipeline: $28.7M Coverage Ratio: 3.38x Pipeline by Segm
Extracted Data
{
"report_period": "Q1 2025",
"report_date": "2025-01-20",
"scope": {
"level": "team",
"name": "North America Sales Team"
},
"total_pipeline": "$28.7M",
"weighted_pipeline": "$12.4M",
"quota": "$8.5M",
"coverage_ratio": "3.38x",
"pipeline_by_stage": [
{
"stage_name": "Discovery",
"deal_count": 45,
"value": "$8.2M",
"percentage_of_pipeline": "28.6%",
"avg_days_in_stage": 12,
"conversion_rate": "65.0%"
},
{
"stage_name": "Qualification",
"deal_count": 38,
"value": "$7.8M",
"percentage_of_pipeline": "27.2%",
"avg_days_in_stage": 18,
"conversion_rate": "58.0%"
},
{
"stage_name": "Proposal",
"deal_count": 28,
"value": "$6.5M",
"percentage_of_pipeline": "22.6%",
"avg_days_in_stage": 15,
"conversion_rate": "45.0%"
},
{
"stage_name": "Negotiation",
"deal_count": 18,
"value": "$4.2M",
"percentage_of_pipeline": "14.6%",
"avg_days_in_stage": 22,
"conversion_rate": "72.0%"
},
{
"stage_name": "Contract Review",
"deal_count": 8,
"value": "$2.0M",
"percentage_of_pipeline": "7.0%",
"avg_days_in_stage": 8,
"conversion_rate": "90.0%"
}
],
"win_rate": "30.1%",
"loss_rate": "69.9%",
"avg_deal_size": "$302K",
"sales_cycle_days": 68,
"deal_velocity": {
"avg_days_to_close": 68,
"median_days_to_close": 54,
"deals_progressed_this_period": 42
},
"slipping_deals": {
"count": 12,
"value": "$2.8M",
"percentage_of_pipeline": "9.8%"
},
"stale_deals": {
"count": 8,
"value": "$1.4M"
},
"new_pipeline": {
"deal_count": 24,
"value": "$5.8M",
"vs_previous_period": "+18.0%"
},
"closed_this_period": {
"won_count": 6,
"won_value": "$1.65M",
"lost_count": 4,
"lost_value": "$920K"
},
"forecast": {
"commit": "$2.8M",
"best_case": "$4.2M",
"upside": "$1.8M",
"accuracy_last_period": "87.0%"
},
"health_status": "HEALTHY",
"health_indicators": [
{
"metric": "Coverage Ratio",
"status": "healthy",
"observation": "3.38x coverage exceeds 3x target"
},
{
"metric": "Win Rate",
"status": "healthy",
"observation": "30.1% win rate exceeds 25% target"
},
{
"metric": "Mid-Market Coverage",
"status": "warning",
"observation": "2.3x coverage below 3x target - needs additional pipeline"
},
{
"metric": "Slipping Deals",
"status": "healthy",
"observation": "9.8% slipping rate within 10% target"
},
{
"metric": "Pipeline Generation",
"status": "healthy",
"observation": "+18% MoM growth in new pipeline"
},
{
"metric": "Stale Deals",
"status": "warning",
"observation": "8 deals with no activity in 30+ days need attention"
}
],
"recommendations": [
"Focus pipeline generation efforts on Mid-Market segment to improve coverage from 2.3x to 3x",
"Review and re-engage 8 stale opportunities with outreach campaign",
"Accelerate legal review for GlobalTech Industries deal ($850K slipping)",
"Schedule executive alignment calls for top 5 slipping deals",
"Analyze 'No Decision' losses (28%) for qualification process improvements"
],
"document_type": "pipeline_health_report",
"generated_at": "2025-01-20T09:00:00Z"
}Example demonstrating extraction of sales pipeline metrics including stage distribution, forecast accuracy, and deal aging analysis. Generates health report identifying bottlenecks and opportunities for acceleration.
Related Templates
Frequently Asked Questions
What documents can Pipeline Health Check process?
The Pipeline Health Check template processes sales documents including various formats and layouts. See the instructions for specific document types supported.
How accurate is the Pipeline Health Check extraction?
The Pipeline Health Check template uses Gemini 2.5 Flash for high-accuracy extraction. Results include confidence scores for each field.
Can I customize the Pipeline Health Check template?
Yes, you can modify the extraction schema, add custom fields, or adjust the instructions to match your specific requirements.
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