Prepare fields by checking the type of each metaobject definition you plan to group by, whether values are present, and which fields you will group by before opening a report. Shopify's September 28, 2026 changelog says metaobject fields attached through a metafield can now group and filter Analytics reports, and category metafields such as Color or Material are now available as dimensions. Missing values and mixed types can affect how a report groups data.
What changed in Shopify Analytics on September 28, 2026?
Shopify's changelog says that if you attach a metaobject to a product, variant, customer, or order through a metafield, those fields can now be used in Analytics. A designer country, a warranty term, or a loyalty tier can group and filter a report the same way a custom metafield can (Shopify changelog, September 28, 2026).
The same changelog says merchant-owned metaobjects are already enabled, and you can turn a definition off if you do not want it in reports. Metaobjects created by an app stay off until you or the app turn Analytics on for that definition. Custom metafields and category metafields stay in the picker in their own groups.
A second changelog entry the same day says category metafields are now available in Analytics as dimensions and filters. If you already categorized products, there is nothing to turn on. You can group a sales report by Color, Material, Fit, Fabric, Size, Activity, or any other category metafield on your products (Shopify changelog, September 28, 2026).
Why prepare fields before building the report?
Because the report inherits whatever state your fields are in. If many products have no Material value, a grouped report may show a blank or unassigned row. If a product has more than one value for an attribute, Shopify says Analytics keeps those values together on one row so sales are not counted twice.
Preparation is a short audit, not a data project. You are checking three things: the type of each field, whether values are present, and whether the values mean the same thing across your catalog.
Which field types should you check first?
Start with the fields you plan to group by, not every field you own. A practical order is:
- Category metafields (Color, Material, Fit, Fabric, Size, Activity). These come from how you categorize products, so they are usually the fastest to verify.
- Merchant-owned metaobject definitions you created yourself, such as Designer, Collection theme, or Warranty band.
- App-created metaobject definitions. These stay off in Analytics until you or the app enable them, so confirm the setting before you expect them in the picker.
For each one, note the type: single-line text, list, number, or reference. A field typed as a list behaves differently from a single-value field when you group. If you are unsure how a definition is typed, open it in Settings > Metafields and metaobjects and read the definition rather than guessing from the label.
How do you find missing values before they distort a report?
Use a simple worksheet. This is a hypothetical example, not a real store's numbers.
| Field | Products with a value | Products missing a value | Action |
|---|---|---|---|
| Material | 180 of 240 | 60 | Fill or exclude |
| Designer | 95 of 240 | 145 | Decide if blank is meaningful |
| Loyalty tier (customers) | 410 of 500 | 90 | Check signup flow |
Two rules keep this honest. First, a blank is not the same as "other" or "unknown" unless you decide it is. Second, if a field is missing on most records, grouping by it will produce a large unassigned row that dominates the report. Either fill the values or leave that field out of the first version.
To check coverage without exporting everything, filter a report to the field and review the results.
How do you keep values comparable across products?
Comparability is about wording, not technology. "Cotton", "cotton", "100% cotton", and "Organic Cotton" may be four values where you intended two. Before grouping, decide the canonical values and apply them consistently.
A short protocol:
- List the distinct values you actually use for one field.
- Mark duplicates that mean the same thing.
- Choose one spelling and case for each meaning.
- Update the products that differ.
- Re-check the distinct list.
This matters most for materials and fits, where suppliers describe the same thing differently. It also matters for metaobject fields such as Designer country, where "UK", "United Kingdom", and "GB" should be one value if you want a clean filter.
What should you decide before opening the report?
Write down four things: the question, the grouping field, the filter, and the metric. For example: "Which material sells best in the last 90 days, filtered to full-price orders, grouped by Material." That sentence tells you which fields must be clean and which can wait.
If you are also preparing for a seasonal push, the same discipline applies to planning your product selection and messages, as in our guide to preparing year-end sales for clothing stores. And if you use an AI assistant to draft the analysis, run the checks in Before Trusting an AI Answer before you act on it.
What mistakes should you avoid?
- Turning everything on at once. Enable the definitions you will actually use. You can turn a definition off in Settings > Metafields and metaobjects.
- Assuming app metaobjects are ready. They stay off until enabled.
- Treating a blank as a category. It is missing data.
- Comparing a list field to a single-value field. They group differently.
- Changing values mid-period. If you rename values during the period you are analyzing, the report may mix old and new labels.
- Expecting one product with two values to split. Shopify keeps them on one row.
A short pre-report checklist
- Field type confirmed for each grouping field.
- Coverage checked; unassigned row is small or understood.
- Values normalized to one spelling per meaning.
- App-created definitions enabled only if needed.
- Question, grouping, filter, and metric written down.
- No value renames inside the comparison period.
Follow-up questions
Do I need to turn anything on for category metafields?
No. Shopify's changelog says that if you already categorized products, there is nothing to turn on; the attributes your products use are already there. Metaobjects you created yourself are already enabled, while app-created metaobjects stay off until you or the app enable Analytics for that definition.
Can I use these fields in the query editor?
Yes. The metaobject changelog says you can use the same fields in the query editor, and the category metafield changelog says category metafields work in Reports, Explore, and the query editor. The preparation work is the same: clean types, present values, comparable wording.
