Inputs
| Field | Your Value |
|---|---|
| Primary Channels | [[Channels - e.g. Organic Search, Paid Social, Email, Direct, Events]] |
| Current Tool Stack | [[Tool Stack - e.g. GA4, HubSpot, Salesforce, Triple Whale]] |
| Primary Business Goal | [[Goal - e.g. Optimize CAC, Prove channel ROI, Feed MMM]] |
| Sales Cycle Length | [[Average Sales Cycle - e.g. 45 days]] |
1. Attribution Model Selection and Rationale
Recommended Primary Model: Position-based (40% first, 40% last, 20% middle) for [[Goal]].
Rationale: Our sales cycle is [[Sales Cycle Length]] with multiple touches. First touch captures awareness drivers. Last touch captures conversion triggers. Middle credit acknowledges the nurturing work that happens in between. This model balances credit fairly while remaining simple to implement and explain to stakeholders.
Alternative models to consider:
- Last-touch only: when proving immediate performance of bottom-funnel paid campaigns.
- First-touch: brand awareness or top-of-funnel budget justification.
- Data-driven (once sufficient conversion volume): after 3-6 months of clean data in GA4 or CRM.
2. Tracked Channels and UTM Taxonomy
Standard UTM Parameters (all campaigns):
| Parameter | Convention | Example |
|-----------|------------|---------|
| utm_source | Platform or referrer | linkedin, google, newsletter |
| utm_medium | Channel type | cpc, email, social, organic |
| utm_campaign | Campaign or initiative | q3-launch, always-on-brand |
| utm_content | Creative or variant | variant-a, carousel-2 |
| utm_term | Keyword or audience | [[keyword or segment]] |
Channel Definitions:
- Paid Search: source=google / bing, medium=cpc
- Paid Social: source=meta / linkedin / tiktok, medium=social-paid
- Email: source=newsletter / lifecycle, medium=email
- Organic: source=google / direct, medium=organic (no utm)
- Direct: no utm or source=(direct)
3. Tooling and Data Flow
Core Stack:
- GA4 for web behavior and last non-direct click modeling
- CRM (e.g. [[CRM]]) for opportunity and revenue attribution
- [[MMM or Additional Tool]] for media mix modeling (future)
- Server-side tagging or enhanced conversions to mitigate cookie loss
Data Flow:
1. Campaign parameters captured at first user interaction.
2. User ID or hashed email passed to CRM on conversion.
3. Revenue and stage data back-synced to analytics via API or native integration.
4. Weekly export to data warehouse for custom reporting.
4. Conversion and Event Definitions
Primary Conversion: [[Qualified Lead / Purchase / Demo Booked]]
Key Events to Track:
- Page view of high-intent pages
- Form submit (all forms with source tagging)
- Demo / trial start
- Purchase / contract signed
- Revenue amount
Micro-conversions (for path analysis):
- Content download
- Webinar registration
- Add to cart / pricing page view
All events must include UTM parameters and user identifiers where consent allows.
5. Known Gaps and Cookieless Considerations
Current Gaps:
- Offline conversions (phone, in-person) - use unique promo codes and call tracking numbers.
- View-through on display/video (not credited in click models).
- Cross-device journeys without logged-in state.
- Privacy-limited identifiers (iOS, consent mode).
Mitigations:
- Increase logged-in / email capture rate to 35%+ of traffic.
- Deploy first-party data audiences and consented identifiers.
- Run periodic brand lift and MMM studies to triangulate.
- Document offline pipeline in CRM with campaign codes.
6. Reporting Cadence and Decision Use-Cases
Weekly: Channel performance snapshot (last 7 / 28 days) using position-based + last-touch comparison.
Monthly: Full path analysis, assisted conversions, and model comparison. Recommend budget shifts.
Quarterly: Model validation + incremental lift studies. Update taxonomy and event definitions.
Decision Use-Cases:
- Shift budget from low-assist channels to high first-touch awareness drivers.
- Credit content team for middle-funnel assists that accelerate pipeline.
- Justify always-on brand campaigns using first + assisted metrics.
7. Numbered Setup Steps
- Audit current UTMs and clean legacy naming.
- Implement consistent parameter taxonomy in ad platforms and links.
- Configure GA4 enhanced measurement + key events with revenue value.
- Connect CRM and analytics via native or Zapier/API.
- Build master dashboard with model toggle.
- Document taxonomy and share with all campaign owners.
- Run 30-day parallel model test before fully switching decision framework.
8. Additional Depth and Best Practices
- Never rely on a single model for all decisions. Compare last-touch (performance) vs position-based (strategy) side by side.
- Revisit taxonomy every 6 months as new channels and creatives are introduced.
- For B2B with long cycles, weight assisted revenue and pipeline velocity over raw last-click.
- Maintain a "source of truth" mapping table between analytics and finance definitions of a "lead" or "sale".
This attribution plan delivers a practical, documented framework ready for immediate implementation.
9. Privacy and Consent Notes
All tracking respects consent mode and regional laws (GDPR, CCPA). Users who decline cookies receive aggregated reporting only. First-party data collection via forms and logins is the long-term mitigation.
Template ready. Fill [[merge fields]] and implement the UTM taxonomy and event tracking before the next planning cycle.
> Framework based on current GA4 + CRM best practices and post-cookieless measurement approaches as of 2026.
Plans, Strategies & Roadmaps
Evidence-led
Prioritised
Decision-ready
