Co-Sell Analytics¶
Track campaign performance, pipeline influence, and partner ROI.
Dashboard Overview¶
The Co-Sell Analytics dashboard provides:
- Campaign Performance — Engagement metrics by campaign
- Pipeline Attribution — Content influence on deals
- Partner ROI — Contribution breakdown by partner
- Trend Analysis — Performance over time
Campaign Metrics¶
Engagement Metrics¶
| Metric | Description | Good Benchmark |
|---|---|---|
| Impressions | Total views across channels | 10K+ per campaign |
| Clicks | Link clicks to content | 2-5% CTR |
| Shares | Social shares and forwards | 1-2% share rate |
| Engagement Rate | (Clicks + Shares) / Impressions | 3-7% |
Channel Performance¶
Track performance by distribution channel:
LinkedIn (Partner A):
- Impressions: 5,234
- Clicks: 312 (6.0% CTR)
- Shares: 45
- Comments: 23
LinkedIn (Partner B):
- Impressions: 4,891
- Clicks: 245 (5.0% CTR)
- Shares: 38
- Comments: 19
Email (Partner A):
- Sent: 2,500
- Opens: 875 (35% open rate)
- Clicks: 156 (6.2% CTR)
Email (Partner B):
- Sent: 3,200
- Opens: 1,024 (32% open rate)
- Clicks: 198 (6.2% CTR)
Content Performance¶
Identify top-performing assets:
| Asset | Type | Impressions | Clicks | CTR |
|---|---|---|---|---|
| Launch Announcement | Blog | 3,456 | 234 | 6.8% |
| Feature Deep-Dive | Blog | 2,891 | 189 | 6.5% |
| Teaser Post | 5,234 | 312 | 6.0% | |
| Customer Quote | 4,123 | 287 | 7.0% |
Pipeline Attribution¶
Attribution Models¶
Vellocity supports multiple attribution models:
| Model | Description | Best For |
|---|---|---|
| First Touch | Credit to first content interaction | Awareness campaigns |
| Last Touch | Credit to last content before conversion | Direct response |
| Linear | Equal credit across all touches | General analysis |
| Time Decay | More credit to recent touches | Long sales cycles |
Pipeline Influence Report¶
Track how co-sell content influences deals:
Campaign: Partner Launch Q1 2025
Influenced Opportunities:
- Total Opportunities: 23
- Total Pipeline Value: $1,245,000
- Average Deal Size: $54,130
Attribution Breakdown:
- Partner A Sourced: 12 opps ($678,000)
- Partner B Sourced: 8 opps ($423,000)
- Joint Sourced: 3 opps ($144,000)
Content Attribution:
- Blog Posts: 45% of touches
- LinkedIn Posts: 35% of touches
- Email Campaigns: 20% of touches
Deal Velocity Impact¶
Measure content impact on sales cycle:
| Metric | With Co-Sell Content | Without | Improvement |
|---|---|---|---|
| Sales Cycle | 45 days | 62 days | -27% |
| Win Rate | 34% | 28% | +21% |
| Deal Size | $52K | $48K | +8% |
Partner ROI¶
Contribution Analysis¶
Track each partner's contribution:
Partner A Contribution:
- Content Created: 8 pieces
- Distribution Reach: 12,500
- Leads Generated: 45
- Pipeline Influenced: $678,000
- Investment: $5,000 (time + resources)
- ROI: 135x
Partner B Contribution:
- Content Created: 6 pieces
- Distribution Reach: 9,800
- Leads Generated: 38
- Pipeline Influenced: $423,000
- Investment: $4,000 (time + resources)
- ROI: 106x
Partnership Health Score¶
Overall relationship health (1-10):
| Factor | Score | Weight |
|---|---|---|
| Campaign Execution | 8/10 | 25% |
| Content Quality | 9/10 | 20% |
| Response Time | 7/10 | 15% |
| Pipeline Contribution | 8/10 | 25% |
| Engagement Level | 9/10 | 15% |
| Overall | 8.2/10 | 100% |
AWS CleanRooms Integration¶
Securely analyze account overlap without exposing customer data.
How It Works¶
graph LR
A[Partner A Data] --> B[AWS CleanRooms]
C[Partner B Data] --> B
B --> D[Privacy-Preserving Analysis]
D --> E[Overlap Insights]Analysis Types¶
Account Overlap:
Query: Find mutual customers
Results:
- Total Overlap: 47 accounts
- Overlap Rate: 12% of Partner A customers
- Segments:
- Enterprise: 15 accounts
- Mid-Market: 28 accounts
- SMB: 4 accounts
ICP Validation:
Query: Validate shared ICP alignment
Results:
- ICP Match Rate: 78%
- Top Matching Segments:
- FinTech Mid-Market: 89% match
- SaaS Enterprise: 82% match
- E-commerce SMB: 65% match
Opportunity Identification:
Query: Find co-sell opportunities
Results:
- Partner A customers who could benefit from Partner B: 156
- Partner B customers who could benefit from Partner A: 134
- Cross-sell potential: $2.3M pipeline
Privacy Controls¶
Data Protection
AWS CleanRooms ensures no raw customer data is ever shared between partners.
What's Analyzed: - Hashed account identifiers - Aggregated segment data - Statistical overlap counts
What's NOT Shared: - Individual customer names - Contact information - Revenue data - Contract details
Reports & Exports¶
Scheduled Reports¶
Configure automated reports:
| Report | Frequency | Recipients |
|---|---|---|
| Campaign Performance | Weekly | Marketing team |
| Pipeline Attribution | Monthly | Sales + Marketing |
| Partner ROI | Quarterly | Leadership |
| Executive Summary | Monthly | C-suite |
Export Options¶
Export data in multiple formats:
- CSV — Raw data for analysis
- PDF — Formatted reports
- Slides — Presentation-ready charts
API Access¶
Programmatic access to analytics:
# Get campaign metrics
GET /api/cosell/campaigns/{id}/metrics
# Get pipeline attribution
GET /api/cosell/campaigns/{id}/attribution
# Get partner ROI
GET /api/cosell/partners/{id}/roi
Best Practices¶
1. Set Baselines Early¶
Before launching campaigns, establish baseline metrics:
- Current pipeline velocity
- Typical content engagement rates
- Historical win rates
2. Use Consistent UTM Parameters¶
Standardize tracking parameters:
utm_source: channel (linkedin, email, blog)
utm_medium: type (social, email, organic)
utm_campaign: campaign-name-quarter
utm_partner: partner-identifier
utm_content: asset-identifier
3. Review Weekly¶
Schedule weekly analytics reviews:
- What's working? Double down.
- What's not? Adjust or stop.
- What's missing? Fill gaps.
4. Share Results with Partners¶
Transparency builds trust:
- Share performance dashboards
- Discuss attribution jointly
- Celebrate wins together
- Address underperformance collaboratively
5. Iterate Based on Data¶
Use insights to improve:
- Top-performing content types → Create more
- Low-engagement channels → Reduce investment
- High-converting assets → Replicate approach
Troubleshooting¶
Missing Attribution Data¶
Symptoms: Deals not showing content attribution
Solutions: 1. Verify UTM parameters on all links 2. Check CRM integration status 3. Confirm cookie consent for tracking 4. Review attribution model settings
Inaccurate Metrics¶
Symptoms: Numbers don't match expectations
Solutions: 1. Check date range filters 2. Verify channel integrations 3. Review bot traffic filtering 4. Cross-reference with native analytics