/revenue-attribution

name: revenue-attribution
description: Analyze marketing and sales touchpoints to attribute revenue credit using multi-touch models and channel contribution analysis
license: MIT
metadata:
  author: ClawFu
  version: 1.0.0
  mcp-server: "@clawfu/mcp-skills"

Revenue Attribution

> Determine which marketing and sales activities drive revenue using multi-touch attribution models, enabling smarter budget allocation and campaign optimization.

When to Use This Skill

• Justifying marketing spend to leadership
• Optimizing channel mix allocation
• Evaluating campaign ROI
• Resolving marketing/sales credit disputes
• Building attribution reports

Methodology Foundation

Based on **Bizible/Marketo Multi-Touch Attribution** and **Google Analytics Attribution Models**, covering:

• First-touch attribution (awareness credit)
• Last-touch attribution (conversion credit)
• Linear attribution (equal credit)
• Time-decay attribution (recency-weighted)
• Position-based (U-shaped, W-shaped)

What Claude Does vs What You Decide

| Claude Does | You Decide | |-------------|------------| | Explains attribution models | Which model fits your business | | Calculates credit distribution | How to act on insights | | Identifies top-performing channels | Budget reallocation amounts | | Shows model comparison | Final attribution policy | | Highlights discrepancies | Exception handling |

What This Skill Does

1. **Model education** - Explain different attribution approaches 2. **Credit calculation** - Apply models to touchpoint data 3. **Channel analysis** - Compare performance by source 4. **Model comparison** - Show how results differ by model 5. **Optimization recommendations** - Where to invest more/less

How to Use

Analyze attribution for this closed-won deal:

Deal: [Company Name]
Value: $[Amount]
Close Date: [Date]
Sales Cycle: [Days]

Touchpoint Journey:
1. [Date] - [Channel] - [Action]
2. [Date] - [Channel] - [Action]
...
[List all touchpoints chronologically]

Questions:
- Which channels deserve credit?
- Compare first-touch vs last-touch
- Recommend budget allocation

Instructions

Step 1: Understand Attribution Models

| Model | Logic | Best For | |-------|-------|----------| | **First-Touch** | 100% to first interaction | Awareness measurement | | **Last-Touch** | 100% to final conversion | Direct response | | **Linear** | Equal split across all | Long consideration cycles | | **Time-Decay** | More credit to recent | Sales-assisted journeys | | **Position-Based** | 40/20/40 (first/middle/last) | Balanced view | | **W-Shaped** | 30/30/30 + 10 remainder | Include MQL moment |

Step 2: Map the Customer Journey

Document all touchpoints with:

• **Timestamp** - When it occurred
• **Channel** - Source (Paid, Organic, Email, Event, etc.)
• **Action** - What happened (visit, download, demo, etc.)
• **Stage** - Awareness, Consideration, Decision

Step 3: Apply Attribution Model

**First-Touch Example:**

Journey: Paid Search → Email → Webinar → Demo → Close
Revenue: $50,000

First-Touch Attribution:
- Paid Search: $50,000 (100%)
- All others: $0

**Linear Example:**

Same journey, 4 touchpoints:
- Paid Search: $12,500 (25%)
- Email: $12,500 (25%)
- Webinar: $12,500 (25%)
- Demo: $12,500 (25%)

**Position-Based (40/20/40):**

- Paid Search: $20,000 (40% - first)
- Email: $5,000 (10% - middle)
- Webinar: $5,000 (10% - middle)
- Demo: $20,000 (40% - last)

Step 4: Aggregate by Channel

Sum attribution across all deals to see total channel contribution:

Channel Performance (Position-Based):
- Paid Search: $500K attributed (35%)
- Events: $300K attributed (21%)
- Organic: $280K attributed (19%)
- Email: $220K attributed (15%)
- Referral: $150K attributed (10%)

Step 5: Calculate ROI by Channel

Channel ROI = Attributed Revenue / Channel Spend

Example:
- Paid Search: $500K revenue / $100K spend = 5x ROI
- Events: $300K revenue / $200K spend = 1.5x ROI

Examples

Example 1: Deal-Level Attribution

**Input:**

Analyze attribution for TechStart Inc:

Deal: TechStart Inc
Value: $75,000 ARR
Close Date: March 15
Sales Cycle: 62 days

Touchpoint Journey:
1. Jan 12 - Google Ads - Clicked ad, visited pricing
2. Jan 15 - Organic Search - Blog post read
3. Jan 22 - LinkedIn Ad - Whitepaper download (MQL)
4. Feb 1 - Email nurture - Opened 3 emails
5. Feb 10 - Webinar - Attended "Product Demo Day"
6. Feb 18 - Direct - Requested demo (SQL)
7. Mar 5 - Sales - Discovery call
8. Mar 12 - Sales - Proposal review
9. Mar 15 - Direct - Signed contract

Compare first-touch, last-touch, and position-based.

**Output:**

## Attribution Analysis: TechStart Inc ($75,000)

### Journey Summary
- **Total Touchpoints**: 9
- **Marketing Touchpoints**: 6 (Jan 12 - Feb 18)
- **Sales Touchpoints**: 3 (Mar 5 - Mar 15)
- **Sales Cycle**: 62 days
- **Key Conversion**: LinkedIn whitepaper (MQL), Demo request (SQL)

### Model Comparison

| Channel | First-Touch | Last-Touch | Position-Based | Linear |
|---------|-------------|------------|----------------|--------|
| Google Ads | $75,000 | $0 | $22,500 | $8,333 |
| Organic Search | $0 | $0 | $3,750 | $8,333 |
| LinkedIn Ads | $0 | $0 | $7,500 | $8,333 |
| Email | $0 | $0 | $3,750 | $8,333 |
| Webinar | $0 | $0 | $3,750 | $8,333 |
| Direct (Demo) | $0 | $0 | $7,500 | $8,333 |
| Sales | $0 | $75,000 | $26,250 | $25,000 |

### Position-Based Breakdown (Recommended)

**First Touch (30%): $22,500**
- Google Ads gets full first-touch credit
- Drove initial awareness and pricing interest

**MQL Touch (30%): $22,500**
- LinkedIn Ads: $15,000 (whitepaper = MQL)
- Webinar: $7,500 (influenced SQL)

**Last Touch (30%): $22,500**
- Demo Request: $7,500
- Sales (Close): $15,000

**Middle Touches (10%): $7,500**
- Organic: $2,500
- Email: $2,500
- Other: $2,500

### Insights

1. **Google Ads** initiated the journey - valuable for awareness
2. **LinkedIn Ads** drove the MQL - critical conversion point
3. **Sa