Good NumbersA BigQuery data warehouse for your Shopify brand, reconciled and kept up to date.
We pull Shopify, your ad platforms and your attribution tools into BigQuery on a schedule, backfill the history, check every source against the others and model it into tables your whole team can use.
- Built in your own cloud account
- Every source reconciled against Shopify
- Fixed quote before work starts
Your numbers live in five tools that disagree.
Shopify, Meta, Google Ads, your attribution tool and your email platform each keep their own version of the truth. Someone rebuilds the weekly report by hand, and every meeting starts with which number is right.
- Manual reporting
- Hours a week spent exporting, pasting and fixing spreadsheets that break when a column moves.
- Different definitions
- Revenue, orders and ROAS mean something different in every tool, so totals never match.
- Limited history
- Platform interfaces and APIs limit how far back and how detailed you can go. Data you never stored is gone.
- No single place to ask
- Questions that span stores, channels and ads need an analyst and a day of work.
What's included
Source audit and definitions
Every source, field and metric definition agreed up front: what counts as revenue, an order, a new customer and a conversion.
Historical backfill
Full order history from Shopify and as much ad and attribution history as each API allows, loaded once and kept.
Scheduled pipelines
Automatic syncs, from hourly to daily, with retries, re-pulls of recent days that platforms restate, and failure alerts.
Reconciliation models
Spend, orders and revenue cross-checked between sources every day, with known issues flagged instead of hidden.
Modeled tables
Clean daily tables for the business, channels, campaigns, ads, orders and customers, ready for reporting.
Your account, your data
Built in a Google Cloud project you own, with a small monthly cloud bill and no lock-in to us or a SaaS tool.
Outputs your team uses
Google Sheets, Looker Studio or a custom dashboard on top, plus read-only access for AI tools if you want it.
Documentation and handover
Every pipeline, table and definition documented, so your team or any engineer can maintain it.
How it works
- 1
Scope
You tell us your sources and the decisions the data should drive. We reply with questions and a proposed architecture.
- 2
Fixed quote
A written plan with milestones, running costs and a fixed price before anything is built.
- 3
Build and reconcile
Pipelines, backfill and models, with a reconciliation report showing how every source compares.
- 4
Handover and support
Documentation and access handed over, with optional monthly support to monitor and extend it.
Common questions
Anything else, ask in the free check form or email hello@goodnumbers.io.
Why BigQuery?
It handles large ecommerce datasets cheaply, connects natively to Google Ads, GA4 and Looker Studio, and charges for what you use. Many brands pay a few dollars to a few tens of dollars a month for storage and queries at typical volumes.
Which data sources can you connect?
Shopify and WooCommerce, Meta, Google Ads, TikTok, attribution tools, Klaviyo, GA4, Amazon, CRMs and most tools with an API. We confirm each source and its limits during scoping.
Do we own the warehouse?
Yes. It is built in your own Google Cloud project and billing account. We work with the access you give us, and you can remove it at any time.
How long does a build take?
Most builds take two to four weeks depending on the number of sources and how much history needs reconciling.
Do we need a data team to use it?
No. The modeled tables feed Sheets or dashboards your team already understands, and optional monthly support covers monitoring and changes.
Related guides
How to find your true ROAS across Meta, Google and Shopify
Platform ROAS, blended ROAS, MER and break-even ROAS explained with worked numbers, plus a weekly scorecard that shows what ad spend really returns.
TrackingWhy GA4 and Shopify revenue don't match (and how to fix it)
The 8 reasons GA4 shows different revenue than Shopify, how much of a gap is normal, and a step-by-step way to find exactly which orders GA4 is missing.
AttributionWhy Meta Ads revenue doesn't match Shopify (and which number to trust)
Meta almost always reports more purchase value than Shopify. The 8 reasons why, how to measure the real gap, and which number to use for which decision.
Other services: Server-side tracking setupGA4 audit for ShopifyMeta CAPI setupCustom dashboards and AI
Plan your data build.
Tell us which sources you use and which decisions you want the data to drive. We'll reply within one business day with questions, a proposed architecture and a fixed quote. No call needed to start.
Plan a custom data build