# Pipedrive Deal Pipeline Tracker

> Turn your Pipedrive pipeline into a structured report with conversion rates, weighted forecasts, and at-risk deal flags.

Source: https://cotera.co/solutions/sales/pipedrive-deal-pipeline-tracker

---

- **Team:** Sales
- **Tools:** Pipedrive
- **Difficulty:** medium
- **Setup time:** 10 min
- **Time saved:** 2-3 hours per report

## How it works
1. **Stage-by-Stage Breakdown** — Deal counts, values, and conversion rates per stage
2. **Weighted Forecast** — Revenue projections based on stage probabilities
3. **At-Risk Deal Flags** — Stale deals and missing data highlighted automatically
4. **Google Sheets Export** — Full report exported to a shareable spreadsheet

## Example requests
- Build a pipeline health report for this quarter
- Which deals have been stuck in the same stage for over 2 weeks?
- Show me weighted revenue forecast across all pipelines

## Prompt

```markdown
## Task

Use @Pipedrive/List Pipelines and @Pipedrive/List Stages to map your full sales process, then @Pipedrive/List Deals and @Pipedrive/Get Deal to pull every active deal. Calculate stage-by-stage conversion rates, weighted pipeline value, and average deal age. Export the results to @Google Sheets/Create Spreadsheet as a formatted pipeline report.

**Example:** Build a pipeline health report showing deals by stage, conversion rates, and projected revenue for this quarter.

## Input

The user will provide either:
1. A pipeline name or ID to analyze
2. A time period to focus on (e.g., "this quarter", "last 30 days")
3. Nothing (analyze all pipelines)

**Example:** "Show me pipeline health for Q1" or "Analyze my Enterprise pipeline"

## Context

### What to Analyze

**Stage-level metrics:**
- Number of deals per stage
- Total and average deal value per stage
- Average time deals spend in each stage
- Deals flagged as "rotten" (stale)

**Pipeline-level metrics:**
- Overall conversion rate (deals won / deals created)
- Weighted pipeline value (deal value x stage probability)
- Average sales cycle length
- Win rate and loss reasons

**Deal-level flags:**
- Deals without expected close dates
- Deals stuck in a stage longer than average
- Deals with no recent activity or notes
- Large deals that need attention

### Analysis Strategy

1. List all pipelines to understand the sales process structure
2. Get stages for each pipeline with their probability settings
3. Pull all open deals and group them by stage
4. Calculate metrics per stage and per pipeline
5. Flag at-risk deals and summarize in Google Sheets

### What Counts as a Valid Result

- Use actual deal values and dates from Pipedrive
- Calculate weighted revenue using stage probabilities
- Flag deals with no activity in the last 14+ days as stale
- Only count deals with status "open" for active pipeline

## Output

**Pipeline Overview:**

| Pipeline | Open Deals | Total Value | Weighted Value | Avg Cycle |
|----------|-----------|-------------|----------------|-----------|
| [Pipeline 1] | X | $Y | $Z | N days |

---

**Stage Breakdown:**

| Stage | Deals | Total Value | Avg Value | Probability | Weighted |
|-------|-------|-------------|-----------|-------------|----------|
| [Stage 1] | X | $Y | $Z | N% | $W |

---

**At-Risk Deals:**

| Deal | Value | Stage | Days in Stage | Issue |
|------|-------|-------|---------------|-------|
| [Deal 1] | $X | [Stage] | N | No activity in 20 days |

---

**Projected Revenue:**
- Best case: $[sum of all open deal values]
- Weighted forecast: $[sum of weighted values]
- Committed (>80% probability): $[high-probability deals]

A Google Sheet has been created with the full report: [link]
```

## Related reading
- [Pipedrive Deal Pipeline Management](https://cotera.co/articles/pipedrive-deal-pipeline-management.md)
- [AI Email Finder Sales Prospecting](https://cotera.co/articles/ai-email-finder-sales-prospecting.md)
- [AI Sales Call Notes Crm](https://cotera.co/articles/ai-sales-call-notes-crm.md)