← All integrations
E-COMMERCE

Analyze your BigCommerce data in plain English.

BigCommerce store orders, customers, and product performance in plain English.

BigCommerce data analysis questions

  • "What is my BigCommerce repeat purchase rate by acquisition channel?"
  • "Show me top 20 products by gross margin this quarter."
  • "Find checkout abandonment patterns by device and traffic source."
  • "Compare BigCommerce store performance to your Shopify store."
  • "Build me a cohort retention dashboard."

How to connect

  1. Sign in to Tablize and open the Integrations page in your workspace.
  2. Pick BigCommerce and follow the OAuth flow (or paste an API key, depending on the connector).
  3. Run your first sync. Tablize pulls historical data and sets up an incremental cursor so future syncs stay fresh.
  4. Open a new chat and ask your first question. Tablize already knows the schema.

What lands in your workspace

orders BigCommerce orders with totals, status, customer, products.
customers Customer records with order history and lifetime value.

Common workflows

Channel performance brief

Weekly: revenue and CAC per acquisition channel, with recommended budget shifts.

Store data hides the real story across orders, line items, and refunds. With BigCommerce connected, Tablize joins them for you, so “which SKUs actually lost margin after returns” becomes one question instead of an afternoon in spreadsheets.

Once BigCommerce is authorized, tables like orders and customers sync into a dedicated schema in your workspace’s PostgreSQL — incrementally, so only new and changed rows move after the first backfill. Ask something like “What is my BigCommerce repeat purchase rate by acquisition channel?” and Tablize writes the SQL, runs it, draws the chart, and offers to keep the answer as a report, a scheduled script, or a live dashboard.

A setup teams reach for first — Channel performance brief: Weekly: revenue and CAC per acquisition channel, with recommended budget shifts.

Try BigCommerce with Tablize.

Free to try on your own data. Your first answer in under 60 seconds.

Try free with your data