Marketing Analytics
Transform data into actionable marketing insights.
1. Analytics Framework
| Layer | Focus | Tools |
|---|---|---|
| Collection | Tracking, tagging | GA4, GTM, Segment |
| Storage | Data warehouse | BigQuery, Snowflake |
| Analysis | Insights, patterns | Looker, Tableau |
| Action | Optimization | A/B tools, personalization |
2. Key Marketing Metrics
Acquisition Metrics
| Metric | Formula | Benchmark |
|---|---|---|
| CAC | Total acquisition cost / New customers | Industry varies |
| CPL | Ad spend / Leads generated | $5-$50 B2B |
| CPC | Ad spend / Clicks | $1-$5 avg |
| CPM | (Ad spend / Impressions) × 1000 | $5-$15 avg |
Engagement Metrics
| Metric | Formula | Good |
|---|---|---|
| Bounce rate | Single-page sessions / Total sessions | < 40% |
| Pages/session | Pageviews / Sessions | > 2 |
| Avg session duration | Total duration / Sessions | > 2 min |
| Engagement rate | Engaged sessions / Total sessions | > 50% |
Conversion Metrics
| Metric | Formula | Good |
|---|---|---|
| Conversion rate | Conversions / Visitors | 2-5% |
| Lead-to-customer | Customers / Leads | 10-20% |
| Cart abandonment | Abandonments / Carts created | < 70% |
| Checkout abandonment | Abandonments / Checkouts started | < 50% |
Revenue Metrics
| Metric | Formula |
|---|---|
| LTV | ARPU × Customer lifetime |
| LTV:CAC | LTV / CAC (target > 3:1) |
| ROAS | Revenue / Ad spend |
| MER | Revenue / Total marketing spend |
3. Attribution Models
Common Models
| Model | How It Works | Best For |
|---|---|---|
| Last click | 100% to final touchpoint | Direct response |
| First click | 100% to first touchpoint | Awareness |
| Linear | Equal across all touchpoints | Long cycles |
| Time decay | More weight to recent | B2B |
| Position-based | 40-20-40 first/mid/last | Balanced |
| Data-driven | ML-based allocation | High volume |
Multi-Touch Attribution
| Stage | Touchpoint Credit |
|---|---|
| Awareness | First-touch heavy |
| Consideration | Mid-touch matters |
| Decision | Last-touch heavy |
4. Google Analytics 4 (GA4)
Key Differences from UA
| UA | GA4 |
|---|---|
| Sessions | Events |
| Bounce rate | Engagement rate |
| Goals | Conversions |
| Views | Data streams |
Essential Events
| Event | Purpose |
|---|---|
| page_view | Page tracking |
| purchase | Revenue tracking |
| generate_lead | Lead capture |
| sign_up | Registration |
| begin_checkout | Funnel start |
| add_to_cart | E-commerce |
Custom Dimensions
| Dimension | Use Case |
|---|---|
| user_id | Cross-device |
| membership_tier | Segmentation |
| content_group | Content analysis |
| experiment_id | A/B testing |
5. Dashboard Design
Marketing Dashboard Structure
| Section | Metrics |
|---|---|
| Overview | Revenue, sessions, conversions |
| Acquisition | Traffic sources, CAC, new users |
| Engagement | Bounce rate, time on site |
| Conversion | Conversion rate, funnel |
| Revenue | ROAS, LTV, AOV |
Visualization Best Practices
| Metric Type | Best Visual |
|---|---|
| Trend over time | Line chart |
| Comparison | Bar chart |
| Composition | Pie/stacked bar |
| Distribution | Histogram |
| Relationship | Scatter plot |
| KPIs | Big numbers |
6. Funnel Analysis
Standard Marketing Funnel
| Stage | Metrics |
|---|---|
| Awareness | Impressions, reach |
| Interest | Clicks, site visits |
| Consideration | Lead form starts, cart adds |
| Intent | Form completions, checkouts |
| Purchase | Transactions, revenue |
| Loyalty | Repeat purchases, referrals |
Funnel Metrics
| Metric | Formula |
|---|---|
| Stage conversion | Next stage / Current stage |
| Overall conversion | Final stage / First stage |
| Drop-off rate | 1 - Stage conversion |
| Funnel velocity | Avg time between stages |
7. Cohort Analysis
Cohort Types
| Type | Example |
|---|---|
| Acquisition | Users by signup month |
| Behavioral | Users by first action |
| Demographic | Users by segment |
Retention Cohort Table
| Cohort | Week 0 | Week 1 | Week 2 | Week 3 |
|---|---|---|---|---|
| Jan W1 | 100% | 45% | 30% | 25% |
| Jan W2 | 100% | 42% | 28% | 22% |
| Jan W3 | 100% | 48% | 32% | 27% |
8. Marketing Mix Modeling (MMM)
Purpose
- Measure channel effectiveness
- Optimize budget allocation
- Account for external factors
Variables
| Type | Examples |
|---|---|
| Media | TV, digital, OOH |
| Base | Brand, distribution |
| External | Seasonality, economy |
| Competition | Competitor activity |
9. A/B Test Analysis
Statistical Significance
| Sample | Min Detectable Effect |
|---|---|
| 1,000 | 20%+ |
| 10,000 | 5-10% |
| 100,000 | 2-5% |
Test Metrics
| Metric | Purpose |
|---|---|
| Conversion rate | Primary metric |
| Revenue/user | Revenue impact |
| Confidence | Statistical validity |
| P-value | < 0.05 for significance |
10. Reporting Cadence
Report Types
| Report | Frequency | Audience |
|---|---|---|
| Real-time | Live | Operations |
| Daily | Every day | Marketing team |
| Weekly | Every week | Marketing leads |
| Monthly | Every month | Leadership |
| Quarterly | Every quarter | Executive |
Report Structure
| Section | Content |
|---|---|
| Summary | Key highlights, changes |
| Performance | Metrics vs goals |
| Insights | Why it happened |
| Actions | What to do next |
Remember: Data without action is just noise. Always tie analytics to decisions and outcomes.