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Product Data Validation

Data management and qualityIntermediate Level

Checking product information against rules for completeness, format and correctness before it goes to a webshop, feed or marketplace.

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What is Product Data Validation?

Product data validation is checking product information against rules before you publish it: are required fields filled, are formats right (GTIN, price, units), and do values make sense? A product data validation tool runs those checks automatically and lists the products that fail. Typical rules check that titles stay within a channel's length limit, that every product has an image and a valid GTIN, that prices are positive and that color or size values come from an agreed list. Validation differs from data cleansing: validation finds the problem, cleansing fixes it. To see how your feed holds up against Google's rules, run it through the free Google Shopping feed checker.

Why Product Data Validation matters for e-commerce

Marketplaces and shopping channels reject or hide products with missing or invalid data, and shoppers notice wrong details. In Salsify's 2025 consumer research, 54% of shoppers said they dropped a purchase because of conflicting information. Validating data before it leaves your system catches these errors once, instead of fixing them channel by channel after a listing is rejected.

Free tool

Check a product against Google Shopping rules

Enter one product's title, description, price, GTIN and image link. The checker lists the errors and warnings Merchant Center's core requirements would raise, before you upload.

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Examples of Product Data Validation

  • 1Rule: GTIN check digit, Field: EAN, Result: 8712345678906 passes, 8712345678900 fails
  • 2Rule: required field, Field: main image, Result: product blocked from the Google Shopping feed until an image is added
  • 3Rule: maximum length, Field: title, Channel: Amazon, Result: a 92-character title is flagged (limit 75)
  • 4Rule: allowed values, Field: color, Result: "navy" passes, "blu" fails
  • 5Rule: range, Field: sale price, Result: flagged when it is higher than the regular price
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How WISEPIM Helps

  • Quality Guard rules check products against your own rules and rule packs, such as the Amazon title limit.
  • Channel Readiness shows which products are ready for each channel and which fields are missing.
  • Review queue collects the products that need attention so you work through them in one place.
  • Bulk editing fixes the same issue on many products at once.
  • AI enrichment fills missing descriptions, attributes and specs that validation flags.

Common mistakes with Product Data Validation

  • Validating only when a marketplace rejects a listing.
  • Using one rule set for every channel, while each channel has its own limits.
  • Checking that a field is filled but not that the value is valid.
  • Letting free-text values ("blue", "Blue", "blu") into fields used for filters.
  • Not re-validating after a bulk import or supplier update.

Tips for Product Data Validation

  • Start with the fields that block publishing: title, price, GTIN, image and category.
  • Write separate rules for each channel's limits instead of one strict global rule.
  • Use pick lists for attributes such as color and size so values stay consistent.
  • Validate GTINs with a check-digit tool such as the EAN/GTIN validator.
  • Read the data validation guide before you write your first rule set.

Trends around Product Data Validation

  • Rule packs per channel that follow marketplace requirements.
  • AI that suggests a fix next to every failed check.
  • Validation at import, so bad supplier data never enters the catalog.
  • Checks for AI shopping assistants that read structured product data.

Tools for Product Data Validation

  • WISEPIM: Quality Guard rules, Channel Readiness and a Review queue for product data checks.
  • Google Merchant Center: shows feed errors and warnings per product after you submit a feed.
  • Akeneo PIM: completeness scores and validation rules per channel and locale.
  • Salsify: content requirements per retailer and channel.
  • OpenRefine: a free tool to explore and clean messy spreadsheet data.

Related Terms

Access Control (PIM)Attribute Dependency ManagementAttribute InheritanceAttribute ManagementAttribute mappingAttribute Scoping

Also Known As

Product data checksData validationProduct data quality checksFeed validationValidation rules

Frequently Asked Questions

It is software that checks product data against rules and lists the products that fail. It can be a feature of a PIM system, a feed tool or a marketplace dashboard such as Google Merchant Center. Good tools let you set rules per channel and fix issues in bulk.

Validation checks data against rules and reports what is wrong. Cleansing changes the data to fix those problems, for example by standardizing units or correcting values. You usually validate first, cleanse next and validate again.

Start with the fields a channel needs to publish a product: title, price, GTIN, main image, availability and category. Then add rules for the attributes shoppers filter on, such as size, color and material.

Validate whenever data changes: after an import, a supplier update or a bulk edit. A PIM system can run rules continuously, so every saved product is checked against the rules for its channels.

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