CONNECT SHOPIFY TO MUSE
Set up Shopify reporting in Muse
Adzviser retrieves the source data through its MCP reporting tools. Muse uses those results to answer your questions. Connect the source in Adzviser, then authorize Muse to use that connection.
Connect Shopify in Adzviser
Enter the first part of your myshopify.com store URL, sign in to Shopify, and allow Adzviser to read its reporting data. Add the source to the workspace you want to use in Muse.
Open Adzviser setup →Authorize Adzviser in Muse
Open Muse.ai and send: “Can you connect to custom Adzviser MCP at https://mcp.adzviser.com/http?” Select Connect on the Adzviser card, sign in to Adzviser, and select Complete Authorization via MCP. Return to Muse.
https://mcp.adzviser.com/httpVerify the first result
Ask Muse to list your Adzviser workspaces and their sources. Choose the workspace and confirm the store. Request a small report for a known period before expanding the analysis.
The Adzviser reporting connection is read-only. It can retrieve data for analysis; it cannot edit source records or campaigns.
A USEFUL FIRST SHOPIFY REPORT
Explain a sales change before choosing a promotion
Build a report you can check
Compare the last 30 complete days with the previous 30 days for one store. Start with gross sales, discounts, returns, net sales and orders at store level. Then request product-level sales separately and rank products by the absolute change in net sales. Keep stable product identifiers beside names so renamed products do not look like unrelated items.
Match the sales definition before reconciling totals
The Adzviser catalog currently labels the adjustment field Returns. Shopify has introduced Sales reversals terminology for a broader set of negative adjustments. Ask which definition the returned report uses before matching it to Shopify Analytics. Net sales, total sales and payments are different measures; a sales report is not a payout reconciliation.
Distinguish demand from discounting
For products with higher gross sales but weaker net sales, inspect discounts and adjustments before concluding demand improved. Ask Muse for a short review list: the product, the observed change, a possible explanation and the additional evidence needed to decide whether to repeat the promotion.
Metrics for this report: Gross sales; Discounts; Returns; Net sales; Orders.
Relevant breakdowns: Product title; Product SKU.
These are starting fields, not a promise that every combination belongs in one report. Use separate requests for different reporting levels and check the full field catalog for additional coverage.
COPY INTO MUSE
Run your first Shopify analysis
Paste this after connecting. Change the period or research subject to match your question, and let Muse confirm the selection before retrieving results.
Use Adzviser to analyze Shopify. List my workspaces and ask which connected store to use. Compare the last 30 complete days with the previous 30 days for one store. Start with gross sales, discounts, returns, net sales and orders at store level. Then request product-level sales separately and rank products by the absolute change in net sales. Keep stable product identifiers beside names so renamed products do not look like unrelated items. Use these metrics in compatible reports: Gross sales, Discounts, Returns, Net sales, Orders. Relevant breakdowns: Product title, Product SKU. Check field compatibility and use separate tables for different reporting levels. State the actual reporting dates or observation window. Show the supporting rows, then give a short conclusion and one next investigation. Label missing data and separate observed changes from possible explanations.
