Pipeline Health Investigation
Discover why your sales pipeline changed and what to do about it
Pipeline Health Investigation
Investigate why your sales pipeline changed and get actionable recommendations.
The Question
"Why did pipeline shrink this quarter?"
Or variations:
- "Why is our pipeline down?"
- "What happened to our Q3 pipeline?"
- "Investigate pipeline health"
What Scoop Investigates
When you ask about pipeline health, Scoop runs a multi-probe investigation:
Investigation Plan:
├── Probe 1: Quantify the change
│ └── How much did pipeline change? ($ and %)
├── Probe 2: Analyze by stage
│ └── Which stages lost the most value?
├── Probe 3: Analyze by segment
│ └── Which customer segments are affected?
├── Probe 4: Investigate timing
│ └── When did the decline start?
├── Probe 5: Find root causes
│ └── What factors correlate with lost pipeline?
└── Synthesis: Actionable summary
Example Output
Investigation Results: Pipeline Decline Analysis
FINDING 1: Pipeline Value
├── Current quarter: $4.2M
├── Previous quarter: $5.8M
└── Change: -$1.6M (-28%)
FINDING 2: Stage Analysis
├── Discovery: -$300K (leads not converting to qualified)
├── Qualified: -$450K (stuck deals timing out)
├── Proposal: -$850K (largest loss - deals going dark)
└── Negotiation: No significant change
FINDING 3: Segment Breakdown
├── Enterprise: -$1.2M (75% of total loss)
├── Mid-Market: -$250K
└── SMB: -$150K
FINDING 4: Root Cause Analysis
├── Enterprise deals averaging 45+ days in Proposal stage
├── 8 enterprise deals lost to competitor X (new entrant)
├── Average response time to RFPs increased from 5 to 12 days
└── 3 reps carried 80% of lost pipeline (team capacity issue)
RECOMMENDED ACTIONS:
1. Implement 48-hour RFP response SLA
2. Create competitive battle card for competitor X
3. Review rep workload distribution
4. Add proposal stage follow-up automation
Sample Prompts
Basic Investigation
"Why did pipeline shrink?"
With Time Context
"Why did pipeline drop in Q3 compared to Q2?"
With Segment Focus
"Why is enterprise pipeline down this quarter?"
With Stage Focus
"Why are deals getting stuck in proposal stage?"
Follow-Up Questions
After the initial investigation, dig deeper:
| Follow-Up | What It Reveals |
|---|---|
| "What predicts deals getting stuck in proposal?" | ML analysis of stuck deal patterns |
| "Compare won vs lost enterprise deals" | Key differentiators for winning |
| "Show me the deals lost to competitor X" | Specific competitive losses |
| "What changed about our win rate over time?" | Trend analysis |
Data Requirements
For best results, your pipeline data should include:
| Field | Purpose |
|---|---|
| Deal/Opportunity ID | Unique identifier for tracking |
| Deal Name | Human-readable reference |
| Amount | Pipeline value |
| Stage | Current deal stage |
| Owner | Sales rep assignment |
| Created Date | When deal entered pipeline |
| Close Date | Expected close |
| Last Activity | Engagement tracking |
| Segment/Industry | For segmentation analysis |
| Loss Reason | For root cause analysis |
Tips for Better Results
- Include historical data - Scoop needs comparison points
- Track stage changes - Snapshot data enables stage transition analysis
- Capture loss reasons - Helps identify patterns in lost deals
- Add competitor field - Enables competitive analysis
Related Patterns
- Win/Loss Analysis - What predicts deal success
- Revenue Changes - Investigate closed revenue
- Period Comparison - General before/after analysis
Updated about 23 hours ago