Item-data import can bring your entire product catalog into Analytics, letting you measure user behavior, site traffic, revenue and key events with item-specific data such as size, color, style, or item-scoped custom dimensions make sense for your business.
Importing item data into Analytics simplifies and reduces the amount of ecommerce data you need to send along with events: a single Item ID or SKU sent to Analytics at collection time can be joined with your imported item data to populate ecommerce dimensions and metrics in your reports.
On this page
How item-data import works
To use this feature, you must be collecting recommended events for online sales.
Item-data import maps item-scoped item_ids or item-scoped custom dimensions in historically and ongoing collected events to the item-field values you import, and processes and displays the uploaded values (in audiences, reports, and explorations) instead of the originally collected values. For example, if an item_id is used in a report (individually or in aggregate), Analytics replaces the value that was collected originally with the value that was uploaded and displays the uploaded value in the report. This lets you fix or update collected values in order to restructure your data or make it useful again. In addition, if there are newer uploaded values at query time that haven't been processed yet, Analytics uses those newer values instead of the processed values. With item data import, you have more flexibility in the choice of key and import dimensions.
Start by thinking about what item-scoped reporting you want to add in your reports and explorations. If this information isn't already collected by Analytics and it's not handled by one of the other data import types, you can use the item data type to join this information with your Analytics data. You can then create custom reports to view the imported item-scoped data alongside standard Analytics data.
Before you begin
You must be an Editor (or above) at the property level to import item data.
Item data import requires you to set up item-scoped custom dimensions in your Google Analytics property. Make sure to create these custom dimensions carefully before you begin to import your item data.
Note:
- Item data import only supports item-scoped custom dimensions. Learn more about setting up custom dimensions.
- Query time data, such as imported item data, isn’t available when you're creating audiences in Analytics or when you're creating segments in Explorations. Learn more about the difference between query time and processing time in joining data.
Analyze and take action
The default item dimensions (for example, Item brand, Item category, Item name) appear in the Ecommerce purchases report.
You can use item data in Explorations to explore funnels and segment overlap.
You can also segment your users in Explorations by their shopping behavior based on imported item data.
Upload the data
The general upload procedure is outlined in the About Data Import article.
When you create the data source, select Item data as data type.
After you select the option to upload data from a CSV file or SFTP server, you must map the fields you imported to fields in Google Analytics.
In the Key fields table:
- Click Add fields to add fields in Google Analytics to which you would like to join your imported data. This is also called the schema key.
- In the "Analytics field" column, you’ll see the name of the selected Google Analytics field.
- In the "Analytics item parameter" column, you’ll see the associated Analytics item parameter for the Analytics field.
- Note for standard fields selected, the Analytics item parameter will be set as “N/A (standard)”
In the Import fields table:
- Click Add fields to select the fields you'd like to include in your data via the selected join key. This can be across either:
- Select from standard fields and/or custom dimensions
- Type-in an item parameter that is not assigned to a custom dimension using the “+” button
- In the "Analytics field" column, you’ll see the name of the selected Google Analytics field.
- Note for type-in item parameter creation, the Analytics field column will be set as “N/A”. Please ensure type-in item parameters follow expected event naming conventions. Learn more about event naming rules here.
- In the "Analytics item parameter" column, you’ll see the associated Analytics item parameter for the Analytics field.
- Note for standard fields selected, the Analytics item parameter will be set as “N/A (standard)”
In both tables, you select the matching fields in your import file in the "Import field" column.
After you upload your data, it can take up to 24 hours for Analytics to make that data available in reports, audiences, and explorations.
Since item data import uses the reporting/query time join and does not alter data that has already been processed, you can delete an item data source from the data-upload service to remove custom item data from Analytics reports.
Data-source details
Legend
- Scope: the scope determines which events will be associated with the import-dimension values. There are four levels of scope: user, session, event, and item. Item-data import is used to widen item-scoped metadata within ecommerce events.
- Schema key: lists the key dimensions or metrics. The key is used to join the data you upload with the existing data in your events for this data-source type.
- Imported data: lists the dimensions and metrics available for the data you upload to Analytics.
The dimensions and metrics listed for the schema are for reference only and may not be complete; the actual dimensions and metrics available will appear in the user interface when you create the data source.
| Scope | Item-scoped |
|---|---|
| Schema key |
At least ONE and up to TWO dimensions total, made up of dimensions from categories listed below: Item fields
Custom dimensions
If a custom dimension utilized as a key field in the data source is deleted, the import will fail. |
| Imported data |
Dimensions
Custom dimensions
New item parameters
If a custom dimension utilized as an import field in the data source is deleted, the import will continue to work with said custom dimension no longer available in reporting. |
| Notes |
|
Template
Here is an example CSV template for item data. If you need to create your upload files by hand, use this example as a guide.
| item_id | item_name | item_cat1 | item_cat2 | item_cat3 | item_cat4 | item_cat5 | brand | variant |
|---|---|---|---|---|---|---|---|---|
| p100001 | itemname1 | cat1a | cat2b | cat3c | cat4d | cat5e | brand_foo | variant_small |
| p100002 | itemname2 | cat1s | cat2b | cat3c | cat4d | cat5e | brand_bar | variant_medium |
| p100003 | itemname3 | cat1v | cat2w | cat3x | cat4y | cat5z | brand_bar | variant_large |
Limits of item data import
- Deleting an item data source from the data-upload service does not delete the values stored in the item dimensions for the affected items as those values may have changed.
- Imported item data requires both query time and processing time for reporting. This process can take up to 24 hours. If a data source is deleted before incoming data is fully processed, item dimensions such as item_name may be reported as (not set). Learn more about the value (not set).
- If necessary, and as with all other collection methodologies, you may need to follow up with a data deletion to remove data uploaded via this method.
- No new events can be created with item data import.
- Deleting a custom dimension used in the custom data event import limitations
- If it is set as a key field, deletion will cause the item data import to fail.
- If it is set as an import field, deletion will not cause the item data import to fail. However, the deleted custom dimension will no longer be widened in reporting.
- Type-in item parameters will not be surfaced in reporting as they are not associated with a custom dimension. If a new custom dimension is created against an imported item parameter, Google Analytics replaces historical and future events with the new custom dimension in reporting.
- You can create up to 5 data sources for item data, with a total size limit of 1 GB across all item data sources.
- Cross data source exceptions
- Pre-existing data source import fields can't be remapped as new data source import fields unless the composite key field set is the same.
- Pre-existing data source import fields can't be remapped as new data source key fields.
- Pre-existing data source key fields can't be remapped as new data source import fields.