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Marketing Analytics Model
Operating System for Growth
Treat analytics as an operating system, not a dashboard project. Build a marketing analytics engine that powers decision making.

Target a 40% reduction in manual reporting hours within two quarters by institutionalising your analytics model.

Data Pipeline Design
- 1
Ingest: Capture platform data via APIs
- 2
Model: Transform into clean reporting layers
- 3
Serve: Deliver to BI tools and notebooks
- 4
Activate: Feed segments back to automation

Reporting Cadences
Daily: Pacing dashboards for spend
Monthly: Executive scorecards + CAC

Analytics Squad Roles
- ✓
Analytics Lead owns roadmap and priorities
- ✓
Data Engineer manages pipelines and schema
- ✓
Marketing Analyst produces insights
- ✓
BI Developer maintains dashboards

Experimentation First
Create a shared backlog with hypotheses, success metrics, and owners. Use ICE or PIE frameworks to prioritise tests.

Success Metrics
100% campaigns with consistent UTMs. 25% increase in test velocity. Forecast accuracy within plus or minus 5% for pipeline and revenue.

Need Analytics Strategy?
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