Learn to use the Insight data checker to identify issues in your insight data.
Overview
Each type of product recommendation has different data dependencies, and the Insight data checker can identify issues in your data. This tool appears in the sidebar when you create a new product recommendation. As a side note, for products to be available for selection in a product block, they need to be added to an account's AccountInsight in a collection name that's prefixed with 'catalog_'.
The checks identify two categories of problem:
- Warnings
You can still create the recommendation, but the results will not be optimal. - Errors
The state of the data prevents us from creating a recommendation.
The Insight data checks on two levels: catalog and product. The catalog level will let you know that your schema is wrong, whereas the product level will zoom in on the specific product that's causing the problem.
Validation types
The below table details the Insight data checks that we perform.
Type | Description | Status |
Schema validation |
Checks whether the dependent Insight data collections use a valid schema (i.e. they have the correct fields). |
Error |
SKU validation | Checks whether each product has a unique SKU. This field should be unique, otherwise, your best sellers may wrongly attribute sales. | Warning |
URL validation | Checks whether your products have valid links. Without a valid link, contacts will not be able to click through to view the product. Links should be full URLs pointing to your live website. | Warning |