Metafields and Metaobjects in Shopify Analytics: how to segment reports

Shopify Analytics reports become more useful when they can answer questions beyond “how much did we sell?”. For example: which materials generate the most net sales, how orders vary by customer segment, or which attributes the best-selling products have in common.

As of September 28, 2026, Shopify Analytics can also use category metafields and metaobject fields as reporting dimensions and filters. These capabilities extend existing support for selected custom metafields on products, variants, customers and orders.

The benefit is not simply more charts. It is the ability to analyze data that reflects the store's actual business model, provided the underlying fields are structured and populated consistently.

What changed in Shopify Analytics

Shopify distinguishes three families of custom data that reports can use:

• Category metafields: attributes tied to Shopify's standard product taxonomy, such as material, colour, fit or fabric type.
• Custom metafields: merchant-defined fields for products, variants, customers and orders, such as loyalty tier, commercial season or order type.
• Metaobject fields: properties in a reusable structure, such as a designer's country, the duration of a commercial warranty or a collection family.

Enabled metafields appear in the reports interface as dimensions or filters. Metaobject fields become available when the metaobject is connected to a product, variant, customer or order through a reference metafield.

Shopify Analytics' principal features are available on the Basic, Grow and Advanced plans. That does not mean every custom data type is supported or that every report can be edited without restrictions.

Dimensions, filters and metrics are not interchangeable

A metric is a measured value, such as net sales, orders or units sold. A dimension describes how that value is broken down. A filter restricts which records the report includes.

If “net sales” is the metric and “material” is the dimension, the report can break down sales across cotton, linen and wool. If “linen” is the filter, it includes only records with that value.

The distinction matters because creating a metafield does not create a new metric. It gives the merchant another way to segment metrics that Shopify already provides.

When to use a category metafield

Category metafields are suited to standard product attributes. They are derived from the Shopify Standard Product Taxonomy and depend on the category assigned to each product.

In an apparel catalogue they might describe material, colour, fit, size or sleeve type. Since September 28, 2026, such attributes have been available directly in Reports, Explore and the query editor.

According to Shopify, when products are already categorised and their attributes are populated, there is no additional switch to enable. Available category metafields appear alongside custom metafields.

Category metafields are the more coherent choice when the information matches a standard attribute. Creating a separate custom “material” field when the category already provides one can introduce two competing sources with inconsistent values.

When to use a custom metafield

A custom metafield is better for store-specific information that does not belong in the standard product taxonomy. Examples include:

• a customer's loyalty segment;
• a product's internal commercial line;
• a request type associated with an order;
• a true/false flag for an operational feature;
• the date of a campaign or internal initiative.

Shopify supports only selected metafield types in reports, and only for products, variants, customers and orders. Supported types include certain text, number, date, true/false, colour, rating and URL fields, as well as some lists.

The metafield definition must enable Filter or group data in Analytics. Otherwise, the field may exist and contain values but still be absent from report dimensions and filters.

When a metaobject is the better data model

A metaobject is useful when a single value is not enough. Imagine a catalogue where each product references a designer. That designer may have a name, country, region and type of collaboration. Duplicating those values on every product would be fragile and difficult to maintain.

With a “Designer” metaobject, each product stores a reference to the appropriate entry. Analytics can then group or filter a report by a field such as the designer's “Country”.

To make those fields available:

1. The metaobject must be connected through a single-reference or list-of-references metafield.
2. That reference metafield must belong to a product, variant, customer or order.
3. The metaobject definition must enable the option to filter or group data in Analytics.

Mixed references are not supported for this purpose. Shopify's changelog also states that merchant-created metaobjects are enabled by default, whereas app-created metaobjects stay disabled until the merchant or app explicitly enables the feature.

For the underlying modelling choices, see the IFG guide to Shopify metaobjects and structured content.

A practical way to prepare the data

Before building a report, check the information model. Francesco Guiducci follows a straightforward principle: every field should have a stable meaning, a clear owner and a manageable set of values.

1. Start with the question: define which decision the report should help make.
2. Choose the right resource: decide whether the information belongs to a product, variant, customer or order.
3. Reuse standards: prefer a category metafield when Shopify's taxonomy already covers the attribute.
4. Avoid uncontrolled free text: “Made in Italy”, “made-in-italy” and “Italia” may become separate segments even when they describe the same thing.
5. Populate a sample: check the field's behaviour on a limited set of records.
6. Enable Analytics: activate the appropriate option in the metafield or metaobject definition.
7. Check missing values: a segmented report is incomplete if a significant part of the catalogue has no value for the relevant field.

In complex catalogues, the distinction between variants, metafields and metaobjects is crucial. The IFG guide to complex Shopify catalogues explains where each kind of information belongs.

Three reports that can become more useful

Sales by material or product attribute

A merchant can add “Material” as a dimension in a sales report and compare net sales, orders or units across catalogue values. The result can inform assortment decisions, but it does not by itself prove that the material caused a particular sales performance.

Sales by a metaobject property

If products reference a “Designer” metaobject, a report can group sales by the designer's country or region. The same pattern can work for editorial collections, internal certifications or commercial programmes, as long as the data is real, consistent and relevant.

Customers or orders by custom segment

A customer metafield can represent a loyalty tier; an order metafield can represent an operational classification. These fields make it possible to filter reports without immediately moving data to another system. It is still essential to verify when and how values are assigned: inconsistently updated segments produce unreliable analysis.

Limitations to understand before making decisions

• Not every metafield type or metaobject field is supported.
• Metaobject links must use the supported resource and reference types.
• When a category attribute has multiple values, Shopify keeps them together on the same row to avoid double-counting sales.
• A report table displays at most 1,000 rows. Shopify notes that totals can include all rows; exporting the report may be necessary to obtain the full breakdown.
• Missing values, duplicates and inconsistent naming fragment the analysis.
• Segmentation reveals associations in the data; it does not automatically establish causation.

When a merchant needs to combine advertising costs, margins, logistics data or external sources, Shopify Analytics may not be sufficient on its own. In that case, a broader flow using CSV, Google Sheets, APIs or business intelligence tools may be appropriate, as discussed in the IFG guide to Shopify KPI dashboards.

The useful rule: design the data before the chart

Using metafields and metaobjects in reports brings catalogue data, operations and analysis closer together. It does not remove the need for sound information architecture. If two fields describe the same concept, values change without a rule, or a field is attached to the wrong resource, the report will expose the confusion rather than solve it.

For a store on Basic, Grow or Advanced, the sustainable approach is to start with native features, model a small number of genuinely useful attributes and verify data quality. An app or external dashboard makes sense when the native reports cannot meet a specific requirement, not as a substitute for coherent data.

Official sources

• Shopify Changelog: Category metafields are now available in Analytics, September 28, 2026.
• Shopify Changelog: Use metaobject fields in Analytics reports, September 28, 2026.
• Shopify Help Center: Filtering and editing your reports, accessed September 29, 2026.
• Shopify Help Center: Options for custom data, accessed September 29, 2026.
• Shopify Help Center: Analytics data points reference, accessed September 29, 2026.