ShopifyQL Examples for Automated Shopify Reporting

ShopifyQL examples are useful when you want automated Shopify reports without rebuilding the same analytics view by hand every week. UpdateMate can use ShopifyQL metrics inside AI agents so ecommerce teams can track revenue, refunds, products, conversion, and customer trends in recurring reports.

ShopifyQL is Shopify's query language for analytics and reporting. It looks familiar if you know SQL, but it has its own commerce-focused syntax, tables, operators, and reporting rules.

What is ShopifyQL?

ShopifyQL is a query language built by Shopify for analyzing store data. A ShopifyQL query usually starts with a data source, chooses the metrics or dimensions to show, then adds filters, time ranges, grouping, ordering, limits, and visualization options.

A simple pattern looks like this:

FROM sales
SHOW total_sales
SINCE startOfDay(-30d) UNTIL today

That kind of query can become a metric inside UpdateMate, so an AI agent can read it, compare it to previous periods, and explain what changed.

ShopifyQL tables

ShopifyQL queries use FROM to choose the source table or dataset. Common reporting areas include sales, orders, customers, sessions, products, and other Shopify analytics data that Shopify exposes through ShopifyQL.

Examples of report questions that map well to ShopifyQL tables:

• Sales: What was total sales this week, month, or quarter?
• Orders: How many orders were placed and how did average order value change?
• Products: Which products or variants sold the most?
• Customers: Which customer groups bought repeatedly?
• Sessions: Did traffic or conversion rate change?
• Refunds: Which products or channels are causing refund pressure?

When building reports, start with the business question first, then choose the ShopifyQL table, metrics, dimensions, and date range that answer it.

Does ShopifyQL support LIKE or ILIKE?

ShopifyQL is SQL-like, but it is not the same as SQL. In Shopify's current syntax reference, string matching is documented with operators such as STARTS WITH, ENDS WITH, and CONTAINS, not standard SQL LIKE or PostgreSQL-style ILIKE.

So if you are searching for a ShopifyQL LIKE operator, the practical answer is: use ShopifyQL's documented string matching operators instead of assuming LIKE works.

Examples of the intent:

WHERE product_title CONTAINS 'shirt'

WHERE customer_email ENDS WITH '@example.com'

If you need case-insensitive behavior like ILIKE, test the exact query in Shopify's ShopifyQL editor or API for your field and data. Do not assume SQL ILIKE syntax is available just because ShopifyQL looks similar to SQL.

ShopifyQL examples for ecommerce reporting

Here are practical ShopifyQL reporting ideas that work well as automated metrics for an ecommerce team.

Total sales over the last 30 days:

FROM sales
SHOW total_sales
SINCE startOfDay(-30d) UNTIL today

Sales by product title:

FROM sales
SHOW total_sales
GROUP BY product_title
SINCE startOfDay(-30d) UNTIL today
ORDER BY total_sales DESC
LIMIT 10

Sales over time:

FROM sales
SHOW total_sales
TIMESERIES day
SINCE startOfDay(-30d) UNTIL today

These examples are meant as starting points. The exact fields available can depend on the ShopifyQL dataset and analytics access for the store.

Revenue, refunds, and product performance examples

UpdateMate works best when ShopifyQL metrics map to recurring business questions, not isolated charts.

Useful ecommerce report questions include:

• Which products drove the most revenue last week?
• Which products declined fastest compared with the previous period?
• Are refunds increasing for a specific product, vendor, or campaign?
• Did average order value move up or down?
• Which products are growing but still low in absolute revenue?
• Which customer or order segments need attention?

An AI agent can combine ShopifyQL outputs with context from ad platforms, inventory sheets, support tickets, or campaign notes to explain why the numbers changed.

How UpdateMate turns ShopifyQL into recurring reports

UpdateMate can use ShopifyQL to power automated Shopify reporting workflows.

A recurring workflow can:

1. Run ShopifyQL metrics on a schedule.
2. Compare sales, product, refund, and customer metrics with the previous period.
3. Detect meaningful changes, anomalies, and trend breaks.
4. Pull supporting context from other connected tools.
5. Write a weekly ecommerce report in plain language.
6. Send the report to Slack, email, Notion, Google Docs, or another destination.

This turns ShopifyQL from a query you run manually into a repeatable reporting system for ecommerce operators, founders, marketers, and finance teams.