Stop steering on spreadsheets. One warehouse, one source of truth.
A BigQuery warehouse under automated pipelines, a library of eight ecommerce dashboards built around decisions, and AI digests that tell you what changed and why. Numbers your whole team can finally agree on.
Definition
What is a BigQuery-backed reporting stack?
A BigQuery-backed reporting stack is an ecommerce reporting setup where every data source lands in one BigQuery warehouse through automated pipelines, and every dashboard reads from that single modelled source of truth. Shopify orders and refunds, COGS, ad spend from Meta and Google, GA4 behaviour, shipping, and fees are unified into tables that compute numbers no single platform can, like contribution margin per SKU or blended MER against margin instead of revenue. This matters because dashboards wired straight to platform connectors go stale and untrustworthy: each platform uses its own attribution, the numbers never agree, and a silently broken connector keeps rendering old data. Anlyto builds the warehouse, the pipelines, the Looker Studio and Sheets reporting on top, and the definitions doc that makes every number defensible, then maintains it all under the Reporting Partner retainer.
What the service ships
Custom reporting
Data infrastructure first, dashboards second
Anyone can sell you a Looker template on a platform connector. We build the data infrastructure underneath: a warehouse you own, pipelines that keep it current, and definitions the whole team agrees on. Custom reporting builds start from $X.
BigQuery data warehouse
Your own warehouse, in your own Google Cloud project. Shopify orders, refunds, and COGS, ad spend, GA4 behaviour, shipping, and fees, modelled into tables built for decisions. You own it outright.
- Owned by you, not us
- Full history retained
- Modelled for margin, not just revenue
Automated pipelines
Fivetran and managed connectors where they fit, custom connectors where they don't, scheduled queries for the modelling layer. Data lands daily without anyone exporting a CSV.
- Fivetran + custom connectors
- Scheduled query models
- Monitored, not fire-and-forget
Custom Looker Studio and Sheets reporting
Dashboards and operational reports built on the warehouse, not on flaky platform connectors. Looker Studio for the morning view, Sheets where your team actually works.
- Reads from the warehouse only
- Branded and shareable
- Sheets exports for ops teams
Definitions doc
Exactly how every number is computed: what counts as an order, how returns hit margin, which spend is included in MER. When the whole team agrees on definitions, the arguments stop.
- Every metric documented
- One agreed source of truth
- Onboards new hires fast
Validation against actuals
Modelled numbers reconciled against known-good months before anything ships. A dashboard nobody trusts is decoration; validation is what makes it the number the room defers to.
- Reconciled to your store
- Known-good month checks
- Discrepancies explained, not hidden
Maintenance path
Sources change, catalogs grow, questions evolve. The build rolls into the Reporting Partner retainer so pipelines stay monitored and dashboards stay current, or you take the docs and run it in-house.
- Pipeline monitoring
- Dashboard upkeep + extensions
- Monthly insight review
Reporting is only as honest as the tracking feeding it. Fix data quality upstream with a tracking setup.
The dashboard library
Eight dashboards, each built around a decision
Predefined builds on your own warehouse, refreshed daily. Each one exists to answer a question you currently answer on gut feel. Pick one, or stack them: they share the same warehouse, so every dashboard you add gets cheaper to build and richer in context. Each dashboard is priced from $X.
Store Performance
Answers every morning: did we actually make money yesterday, and where?
- Revenue, orders, and AOV vs target
- Contribution margin per order
- Channel-level P&L
Creative
Decides which ads earn the next dollar of budget, before winners fatigue.
- Margin-based ROAS per creative
- Winning-creative detection
- Fatigue and lifecycle signals
Churn, LTV & Retention
Decides which customers and channels deserve acquisition spend.
- LTV:CAC by channel
- Churned customers per month
- Repeat purchase rate by cohort
Subscription & MRR
Shows whether recurring revenue is compounding or quietly leaking.
- MRR movement and net churn
- Subscriber cohort retention
- Failed payment recovery
Funnel & Conversion
Decides which step of the funnel to fix first, with the leak priced in revenue.
- View-to-cart and cart-to-checkout rates
- Checkout completion by device
- Revenue lost per funnel step
Inventory
Decides what to reorder, discount, or drop before it costs you.
- Days of cover per SKU
- Cash sitting in dead stock
- Stock-out risk on best sellers
Supplier & Vendor
Shows which suppliers cost you sales, and what each SKU truly costs landed.
- Lead time and delay rate by supplier
- Landed cost per SKU
- Lost-sales impact of delays
Unified Ads
Decides where the next dollar of spend goes across every platform.
- Blended MER against margin
- Spend and CAC by platform
- Cross-channel contribution
Not sure which one you need first? The reporting audit tells you.
Analytics automation & AI
Your dashboards shouldn't wait for you to open them
A dashboard only helps when someone looks at it. The automation layer pushes what matters to where your team already is: Slack, email, and the tools they work in every day.
AI insight digests
A weekly digest to Slack or email: what changed, why it changed, and what to look at. Written from your warehouse, not from a generic template.
Anomaly and alert automation
ROAS drops, tracking breakage, margin anomalies, and spend spikes flagged the day they happen, not discovered in a weekly meeting.
Data workflow automation
Pipelines, exports, and the n8n glue between tools. Cost feeds ingested, reports delivered, ops sheets updated, all without a human in the loop.
Ask-your-data agents
Plain-language questions against your warehouse: which SKUs lost money last week, how did the promo cohort retain. Answers with the numbers, in Slack.
After the build
Reporting is living software
Sources change, catalogs grow, and the questions never stop. Pipeline monitoring, dashboard maintenance, data hosting, and a monthly insight review roll into the Reporting Partner retainer, so the numbers stay trustworthy long after handoff.
See the Reporting Partner retainerHow we build
From scattered exports to one source of truth
Scope + definitions
Working session on your unit economics, cost structure, and the decisions the reporting must support. Metric definitions agreed before anything is built.
Warehouse + pipelines
BigQuery warehouse in your own project. Shopify, ads, GA4, and cost feeds connected through automated pipelines and modelled into decision-ready tables.
Dashboards
Library dashboards and custom views built on the warehouse. Looker Studio for the morning read, Sheets where your ops team works.
Validate + hand off
Numbers reconciled against known-good months, definitions doc delivered, team walkthrough done. Then the Reporting Partner retainer keeps it all current.
FAQ
Reporting questions
What founders and operators ask before committing to a warehouse-backed build.
Ready for numbers the whole room defers to?
Book a 30-minute call. Tell us the decisions you're making on gut feel, and we'll map the warehouse and dashboards that ground them.
Continue reading
Related services
- Read more
Reporting Audit
Not sure what to build first? The audit maps what you report on today, what you can't answer, and what to fix in which order.
- Read more
Tracking Setup
Every dashboard inherits the quality of the tracking underneath it. Fix data quality upstream before modelling on top of it.
- Read more
Retainers
The Reporting Partner module keeps pipelines monitored, dashboards current, and insight flowing monthly.
- Read more
Ads Management
Once the Unified Ads and Creative dashboards are live, we can run the spend on them: measurement-led ads management.
Published
Last reviewed