Ecommerce & Subscription BigQuery-first Verifiable metrics

Shopify to BigQuery, analytics-ready

Sync Shopify data into BigQuery with a standardized schema, documented metrics, and verifiable attribution.

Warehouse-first: your Shopify data lands in BigQuery tables your team can query directly.

Book a walkthrough View docs

Warehouse path

Shopify

Raw commerce events

modeled and standardized

BigQuery analytics tables

Looking for the general connector page? View Shopify integration.

When Shopify reporting needs a maintained warehouse

The problems teams are usually trying to solve.

Numbers don't reconcile

Shopify reports often conflict with ad platform reporting, slowing channel decisions.

CSV workflows break

Manual exports become brittle as order volume and reporting complexity increase.

Need queryable warehouse data

Teams need warehouse tables they can query instead of fixed dashboard abstractions.

Auditability matters

Black-box logic makes it harder to defend decisions in budget and performance reviews.

What you get

A governed Shopify data foundation that is ready for analysis and activation.

Analytics-ready tables

Orders, customers, products, and transaction context are modeled for BI use, not raw-dump cleanup work.

Standardized ecommerce schema

Consistent naming and stable join keys across SourceMedium integrations reduce ad-hoc reconciliation work.

Documented metrics

Metric definitions and lineage are documented so teams can verify numbers in BigQuery, not trust opaque calculations.

Attribution-ready joins

Shopify revenue joins with session and spend context for channel analysis. See the marketing attribution use case.

What is different vs. standard connectors?

Connector-only

Moves raw rows from source to destination. Modeling, definitions, and reconciliation are left to your team.

SourceMedium foundation

Delivers a modeled warehouse layer with documentation, standardized definitions, and attribution-ready joins your team can verify directly.

Managed BigQuery usage with clear terms

Your proposal specifies compute allowances, overage rates, and usage notification terms for the selected plan. External AI-client subscriptions and charges are separate.

Learn more about the underlying warehouse model on the BigQuery page.

Deployment

SourceMedium runs and maintains the BigQuery warehouse behind your AI and reporting tools. Pro adds direct warehouse access. Deployment in your own Google Cloud project is scoped separately.

Example Shopify models in BigQuery

Representative tables from the existing Shopify integration model.

obt_orders

Order-level facts with standardized revenue, source, and order status context.
obt_order_lines

Product-level line items with SKU, quantity, and price context.
obt_customers

Customer-level records with stable identifiers and order history context.
dim_orders

Order dimension table with durable keys for repeatable joins.
dim_product_variants

Product variant dimension with SKU and attribute normalization.

Example query

-- revenue and new-customer rate by channel (last 30 days)
SELECT
  sm_channel,
  SUM(order_net_revenue) AS revenue,
  AVG(CASE WHEN is_first_order THEN 1 ELSE 0 END) AS new_customer_rate
FROM dataset.obt_orders
WHERE order_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)
GROUP BY 1
ORDER BY revenue DESC;

Joins with

Use Shopify models with your core paid and lifecycle channels.

Meta Ads Google Ads GA4 Klaviyo

How it works

A simple three-step implementation flow.

Step 1

Connect Shopify

Authorize read-only access to Shopify so SourceMedium can ingest orders, customers, products, and transactions.

Step 2

Backfill and incremental sync

Historical data is reconciled first, then incremental Shopify updates run approximately every 15 minutes.

Step 3

Query in BigQuery or ask AI

Use SQL directly in BigQuery with Pro or ask questions in natural language through SourceMedium Agent.

FAQ

Answers to the most common implementation and ownership questions.

Do we keep the data if we leave?

If you leave, you keep your copied dashboards, delivered documentation, and, on Pro, customer-built SQL and models, and you can request an export of your modeled data for 30 days after termination. SourceMedium-managed refreshes stop at offboarding, and hosted data may be deleted once the 30-day export window closes.

Is this just a raw export?

No. SourceMedium provides modeled schema, documented metrics, and consistent joins for analysis.

How do I export Shopify data to BigQuery?

SourceMedium syncs Shopify into modeled BigQuery tables, so your team queries analytics-ready schema directly instead of managing manual CSV exports.

How does billing work?

Before signing, agree the plan, monthly fee, brands and stores, sources, access rights, compute and AI usage, support hours, and any additional charges. Your proposal specifies compute allowances, overage rates, and usage notification terms for the selected plan. External AI-client subscriptions and charges are separate. View pricing.

Is AI included?

Yes. SourceMedium Agent delivers answers in Slack. Included access and usage are documented in your proposal. Analytical answers can expose the underlying SQL. Documentation and methodology answers cite the governing sources.

How fresh is the data?

Incremental Shopify syncs run approximately every 15 minutes. The maintained platform baseline remains complete through the prior day.

Get Shopify data you can actually trust

Use SourceMedium to unify Shopify data with the rest of your ecommerce stack on a BigQuery foundation your team can verify.