What reporting stack should we use?
The standard marketing reporting stack has three layers: an ETL tool to pull platform data automatically (Supermetrics, Funnel — roughly $100–$1,000+/month), a data warehouse to store it (BigQuery — often under $100/month at marketing data volumes), and a BI layer to visualize it (Looker Studio — free, or Power BI/Tableau). Teams under ~$50k/month in spend can start with just Looker Studio and native connectors; the full stack becomes worthwhile when manual reporting consumes more hours than the tools cost.
Key facts
- Typical stack costs: ETL $100–$1,000+/month, BigQuery usually <$100/month at marketing volumes, Looker Studio free.
- Manual reporting commonly consumes 5–10 hours per person per week — usually a higher monthly cost than the entire automated stack.
- The goal: automate 100% of data pulling so analyst time goes to analysis, not extraction.
Why platform-direct reporting fails at scale
Pulling numbers from each platform's dashboard is slow, error-prone, and makes cross-channel comparison manual. All-in-one reporting tools fix speed but often lack the flexibility for custom client metrics, blended CAC calculations, or CRM joins — which is exactly what stakeholders end up asking for.
The three-layer standard
ETL layer: automatically extracts from every ad platform and analytics source on schedule. Warehouse: one queryable home for all of it, joined with CRM and revenue data. BI layer: dashboards stakeholders actually open. Each layer is replaceable independently — that modularity is the point.
The right stack by team size
Under ~$50k/month spend: Looker Studio with native and community connectors — free to cheap, adequate. $50k–$250k/month: add an ETL tool for reliability and history retention. Above that, or with multiple data consumers: add the warehouse layer so reporting, finance, and data science share one source of truth.
Build order
Start with the BI layer for immediate visibility, then add ETL to kill manual pulls, then the warehouse when joins and history matter. External support is most useful architecting the pipeline and building the initial master templates — after which the stack largely runs itself.
Frequently asked questions
What is the standard marketing reporting stack?
Three layers: an ETL tool (Supermetrics/Funnel, $100–$1,000+/month) to pull platform data, a warehouse (BigQuery, often <$100/month) to store it, and a BI tool (Looker Studio, free) to visualize it.
When do we need more than Looker Studio?
When spend passes roughly $50k/month, when you need reliable history beyond platform retention windows, or when reporting requires joins with CRM/revenue data — that's when ETL and a warehouse pay off.
What does a reporting stack cost versus manual reporting?
A full small-team stack runs a few hundred dollars a month. Manual reporting at 5–10 hours per person per week typically costs more than that in salary alone — before counting copy-paste errors.