Marketing AI Skill
Marketing Analytics Attribution
Implement marketing analytics and attribution models including multi-touch attribution, marketing mix modeling, funnel analysis, cohort analysis, campaign ROI tracking, and marketing dashboard design. Use when setting up attribution models, analyzing market...
Marketing Analytics & Attribution
Implement marketing analytics and attribution models including multi-touch attribution, funnel analysis, cohort analysis, and campaign ROI tracking.
Workflow
1. Attribution Models
ATTRIBUTION MODELS
═══════════════════════════════════════
Model How It Works Pros Cons
───────────────────────────────────────────────────────────────────────────────
Last-click 100% to last touch Simple, clear Ignores all upstream
First-click 100% to first touch Values awareness Ignores nurturing
Linear Equal to all touches Fair across journey No weight differentiation
Time-decay More credit to recent Values final touches Arbitrary decay rate
Position-based 40% first, 40% last, Balanced Arbitrary split
20% middle touches
Data-driven Algorithmic (ML) Most accurate Requires volume, complex
Custom Rule-based weights Flexible Manual maintenance
RECOMMENDED APPROACH:
═══════════════════════════════════════
Primary: Data-driven (GA4, when enough data)
Secondary: Position-based (40/20/40) — when data insufficient
Supplemental: Marketing mix modeling (MMM) — for paid media optimization
ATTRIBUTION RESULTS BY MODEL:
═══════════════════════════════════════
Channel Last-click First-click Linear Position-based Data-driven
────────────────────────────────────────────────────────────────────────────────────────
Organic search 15% 45% 30% 35% 32%
Paid search 35% 10% 20% 22% 24%
Social (organic) 5% 20% 12% 14% 13%
Email 10% 5% 15% 16% 15%
Paid social 15% 8% 12% 10% 11%
Content/SEO 5% 12% 11% 10% 12%
Referral 5% 10% 8% 5% 8%
Direct 10% 0% 5% 5% 7%2. Marketing Funnel Analysis
MARKETING FUNNEL
═══════════════════════════════════════
Funnel Stages:
═══════════════════════════════════════
Stage Volume Conversion Drop-off Metric
────────────────────────────────────────────────────────────────────────
Website visits 150,000 — — Traffic
Engaged sessions 75,000 50% 50% Engagement rate
Leads (MQL) 12,000 16% 84% Lead rate
SQLs 3,600 30% 70% SQL rate
Opportunities 1,800 50% 50% Opp rate
Proposals 900 50% 50% Proposal rate
Closed-won 360 40% 60% Win rate
Overall conversion: 150,000 → 360 (0.24%)
MQL to SQL: 30% (target: ≥35%) ⚠️
SQL to Opportunity: 50% (target: ≥55%) ⚠️
Opportunity to Won: 20% (target: ≥25%) ⚠️
Revenue per visitor: $18 (360 deals × $15K / 150,000 visits)
Target revenue per visitor: $25
CONVERSION OPTIMIZATION PRIORITIES:
═══════════════════════════════════════
Stage Issue Action Impact
────────────────────────────────────────────────────────────────────────────────
Engaged → MQL Low form completion Optimize lead magnet +2K MQLs
MQL → SQL Slow lead response Reduce to <5 min +600 SQLs
SQL → Opportunity Poor discovery calls Improve qualification +360 Opps
Opportunity → Won Long sales cycle Accelerate with proof +180 Won3. Cohort Analysis
COHORT ANALYSIS
═══════════════════════════════════════
Customer Retention (by signup month):
═══════════════════════════════════════
Cohort M0 M1 M2 M3 M6 M12 Churn Rate
────────────────────────────────────────────────────────────────────────────
Jan 2024 100% 88% 82% 78% 72% 65% 35%/year
Feb 2024 100% 89% 84% 80% 75% — —
Mar 2024 100% 90% 85% 82% — — —
Apr 2024 100% 91% 87% — — — —
May 2024 100% 90% 86% — — — —
Trend: Retention improving (M1: 88% → 91%)
Revenue by Cohort:
═══════════════════════════════════════
Cohort MTR (M1) MTR (M3) MTR (M6) ARPU LTV LTV:CAC
───────────────────────────────────────────────────────────────────────────────
Jan 2024 $150 $280 $520 $1,800 $5,400 3.2x
Feb 2024 $155 $300 — $1,850 — —
Mar 2024 $160 $310 — $1,900 — —
Trend: MTR increasing ($150 → $160 M1)
LTV:CAC: 3.2x (target: ≥3x) ✓
LTV CALCULATION:
═══════════════════════════════════════
ARPU (Annual Revenue Per User): $1,800
Gross margin: 80%
Monthly churn rate: 2.5%
LTV = ARPU × Gross margin × (1 / Monthly churn)
LTV = $1,800 × 0.80 × (1 / 0.025) = $57,600 × 0.025 = $5,760
CAC (Customer Acquisition Cost): $1,800
LTV:CAC = $5,760 / $1,800 = 3.2x ✓
Payback period: 6 months (target: ≤12 months) ✓4. Campaign ROI Tracking
CAMPAIGN ROI TRACKING
═══════════════════════════════════════
Campaign Performance (Q4 2024):
═══════════════════════════════════════
Campaign Spend Leads SQLs Revenue ROAS CPA
────────────────────────────────────────────────────────────────────────────────
Google Ads — Search $20,000 180 54 $108,000 5.4x $111
Google Ads — PMax $10,000 120 36 $72,000 7.2x $83
LinkedIn Ads $15,000 90 36 $54,000 3.6x $167
Facebook/Instagram $5,000 65 15 $22,500 4.5x $77
Content/SEO $0* 450 90 $135,000 ∞ $0
Email marketing $2,000 85 42 $63,000 31.5x $24
Webinars $3,000 45 22 $33,000 11.0x $67
Referral program $1,000 30 18 $27,000 27.0x $33
*Content cost included in marketing overhead
Total: $56,000 → 1,065 leads → 313 SQLs → $514,500 revenue
Overall ROAS: 9.2x | Avg CPA: $53
UTM TRACKING STANDARD:
═══════════════════════════════════════
UTM Parameters:
→ utm_source: Platform (google, linkedin, facebook, email, webinar)
→ utm_medium: Channel (cpc, cpm, email, organic, referral)
→ utm_campaign: Campaign name (q4-product-launch)
→ utm_content: Ad variant (headline-a, headline-b)
→ utm_term: Keyword (project-management-software)
Naming Convention:
→ {quarter}-{campaign-type}-{campaign-name}
→ Example: q4-content-gate-gatekeeper5. Marketing Dashboard
MARKETING DASHBOARD
═══════════════════════════════════════
Executive View:
═══════════════════════════════════════
Revenue Leads MQLs SQLs CAC LTV:CAC
────────────────────────────────────────────────────────────────────────────────
$514,500 1,065 580 313 $53 3.2x
Traffic by Channel (Monthly):
═══════════════════════════════════════
Channel Sessions Conv. Rate Leads Cost/Lead
────────────────────────────────────────────────────────────────────────
Organic search 45,000 3.2% 1,440 $0
Direct 25,000 4.5% 1,125 $0
Paid search 18,000 5.0% 900 $111
Social (organic) 15,000 2.1% 315 $0
Email 12,000 7.1% 850 $24
Paid social 8,000 3.8% 304 $167
Referral 5,000 6.0% 300 $33
Other 22,000 2.5% 550 —
Total: 150,000 sessions → 5,884 leads → Avg conversion: 3.9%Edge Cases
- B2B long cycles: 6-12 month attribution windows
- Multi-channel: Cross-device, cross-platform tracking
- Privacy: Cookieless tracking, server-side, first-party data
- Enterprise: Complex funnel, multiple touchpoints
- Attribution gaps: Offline conversions, sales calls
Integration Points
- Analytics: GA4, Adobe Analytics, Mixpanel, Amplitude
- Attribution: Bizible, Rockyard, Impact, Triple Whale
- BI: Tableau, Looker, Power BI, Databox
- CRM: Salesforce, HubSpot
- Advertising: Google Ads, Meta, LinkedIn, TikTok
- Marketing automation: HubSpot, Marketo, Pardot
Output
Marketing Analytics Status
MARKETING ANALYTICS — Q4 2024
═══════════════════════════════════════
Total revenue attributed: $514,500
Overall ROAS: 9.2x
CAC: $53 (target: ≤$60) ✓
LTV:CAC: 3.2x (target: ≥3x) ✓
Conversion rate: 3.9% (website → lead)
MQL → SQL: 30% (target: ≥35%) ⚠️
Payback period: 6 months (target: ≤12) ✓
Top channel: Content/SEO ($135K revenue, $0 CPA)
Next priority: Improve MQL→SQL rate (30% → 35%), optimize LinkedIn CPA