Ask ChatGPT about Shopify data
Load Shopify into your data warehouse first, link orders to ad spend and web analytics with SQL keys, then ask ChatGPT about your shop. ChatGPT reads governed Data Marts through OWOX MCP, not the Shopify Admin API.
ShopifyConnectedAbandoned Checko…Article Metafiel…ArticlesBlog Metafields
ChatGPTIdAband…Compl…Daily 09:00ChatGPT answers Shopify sales questions from whatever export you paste, with refunds and currencies mixed together.
Paste this into your AI assistant. It loads Shopify into a governed Data Mart with OWOX Data Marts and connects ChatGPT through the OWOX MCP server, so sales, discounts and refunds are summed per currency by SQL.
The prompt
Read https://www.owox.com/ai-agent-setup.md and follow it to set up OWOX Data Marts for me, starting from /connectors/shopify-connector-to-chatgpt.md. The task: connect ChatGPT to our Shopify Data Mart and tell me last month's sales, discounts and refunds, separately for each currency, then the order count by shipping country. Tag the links you give me with utm_campaign=ai-task and utm_term=data-foundation. Use what you know about my context and goals
Shopify Endpoints
25 Shopify endpoints you can import. Each lands in its own table in your data warehouse.
Abandoned Checkouts
Checkout sessions that did not complete — customer info, items, and pricing for recovery campaigns.
20 fieldsTime seriesArticle Metafields
Custom metadata attached to articles — namespace, key, value, and type.
9 fieldsArticles
Blog articles — title, author, publication status, and timestamps.
15 fieldsBlog Metafields
Custom metadata attached to blogs — namespace, key, value, and type.
9 fieldsBlogs
Blogs in the store — title, handle, and template settings.
6 fieldsCollection Metafields
Custom metadata attached to collections — namespace, key, value, and type.
9 fieldsCollections
Product collections — title, sort order, product count, and last updated.
10 fieldsCustomer Metafields
Custom metadata attached to customers — namespace, key, value, and type.
9 fieldsCustomers
Customer accounts — contact info, marketing consent, order history, and lifetime spend.
22 fieldsTime seriesDiscount Codes
Discount codes — type, status, usage limits, and validity window.
12 fieldsFulfillment Orders
Fulfillment orders — items to ship, assigned location, delivery method, and status.
11 fieldsInventory Items
Inventory items (SKUs) — tracking status, shipping requirements, and country of origin.
9 fieldsLocation Metafields
Custom metadata attached to locations — namespace, key, value, and type.
9 fieldsLocations
Physical and virtual store locations — activity status, fulfillment capabilities, and address.
19 fieldsOrder Metafields
Custom metadata attached to orders — namespace, key, value, and type.
9 fieldsOrders
Orders placed in the store — financial and fulfillment status, customer info, totals, and timestamps.
96 fieldsTime seriesPage Metafields
Custom metadata attached to pages — namespace, key, value, and type.
9 fieldsPages
Static store pages — title, handle, publication status, and timestamps.
10 fieldsProduct Metafields
Custom metadata attached to products — namespace, key, value, and type.
9 fieldsProduct Variant Metafields
Custom metadata attached to product variants — namespace, key, value, and type.
9 fieldsProduct Variants
Product variants — SKU, price, inventory quantity, and availability.
18 fieldsProducts
Products in the store catalog — vendor, type, status, inventory, and price range.
21 fieldsTime seriesShop
Store settings — domain, currency, timezone, and plan details.
20 fieldsShop Metafields
Custom metadata attached to the shop — namespace, key, value, and type.
9 fieldsTender Transactions
Payment tender transactions — amount, currency, order reference, and processing time.
7 fields
Why ChatGPT needs your data warehouse, not the Shopify account
ChatGPT reading a shop directly sees orders, and does not see how they compare with ad spend and sessions, because those live in different systems. The answer is better when it comes from a warehouse, where the data analyst has already linked orders to ad spend and web analytics by SQL keys.
- Shopify reports what was sold, not what it cost to win the order
- The data analyst links orders, ad spend and sessions by SQL keys and controls the result
- ChatGPT answers from governed Data Marts, with the same definitions every time
ShopifyOrders, customersChatGPT
Data warehouseJoined by idStep 1: Load Shopify into your data warehouse first
Create a Data Mart with Shopify as the source and choose where the data lands. It works with any popular data warehouse.
- 25 endpoints to choose from, each endpoint in its own table
- Authorize with your shop domain and an Admin API access token
- Open the Shopify connector for your data warehouse below
ShopifyData MartGoogle BigQuery
AWS Athena
Snowflake
AWS Redshift
Databricksshopify.ordersStep 2: Link Shopify to ad spend and web analytics
In your data warehouse the model joins Shopify orders to web analytics sessions, and sessions to ad spend by date, source and medium (and campaign in the subscription model). Pick an industry to see the shape of its model.
- Orders sit beside web analytics sessions, and sessions beside ad spend
- Web analytics supplies the session key, so orders and sessions join by SQL keys, not VLOOKUP and gut feeling
- The measures, such as conversion_rate, are defined once
ShopifyOrdersStep 3: Connect ChatGPT to your data with OWOX MCP
In ChatGPT, open Plugins, choose Install plugin, find OWOX Data Marts and sign in. ChatGPT then sees the Data Marts you published, and only those.
- The OWOX MCP server lists the Data Marts it can read
- Only published Data Marts are visible, nothing else in your data warehouse
ChatGPTConnectorsOWOX MCPAddConnectedStep 4: Ask ChatGPT how your shop is performing
Ask in plain words, for example how many orders came in and how the conversion rate moved. ChatGPT finds the Data Mart that answers it, runs the query and answers with measures your data analyst defined.
- The answer reads Orders in your data warehouse, not the Shopify Admin API
- Orders can be read next to ad spend and web sessions
ChatGPTShow orders_count and conversion_rate by dayget_relevant_data_marts_by_promptquery_data_martorders_countconversion_ratecompletion_rateStep 5: Export the answer when you need a file
Optional: in one click, export the answer or its source data to Google Sheets, CSV or XLS to check it or share it.
- The export carries the same governed numbers as the answer
- Share it with a colleague who does not use ChatGPT
Google SheetsCSVXLSOne click
- 0.41.0Rotating a connector key is one change: Sources share reusable Credentials
- 0.39.0Reload a year of history in one backfill, not twelve
- 0.38.0Shopify connector: more orders fields, including line-item discounts
- 0.37.0Clearer connector errors, and custom connectors that handle more APIs
- 0.36.0Start a connector run without expanding the Input Source card
Why OWOX for Shopify in ChatGPT
Letting ChatGPT call the Shopify API gets a number into a chat. OWOX also keeps the data yours, linked and defined once, so the answer is one you can check.
- You own the data. It lands in your own data warehouse, in tables you control.
- Orders tied to sessions. Web analytics supplies the session key, so Shopify orders link to sessions, and sessions to ad spend, and ChatGPT answers about the whole funnel.
- Your whole shop, not one export. 25 Shopify endpoints land in your data warehouse, each in its own table.
- Answers you can trace. You can see which Data Mart an answer came from, and one click exports its source data.
- Maintained for you. Shopify connector upkeep is on OWOX, not on a script you wrote.
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