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Product data validation rules

Data management and qualityIntermediate Level

Product data validation rules are automated checks that test product records for missing, wrong or badly formatted data before they are published to a channel.

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What is Product data validation rules?

Product data validation rules are automated checks that test each product record against fixed conditions before it is published, such as a required GTIN with a valid check digit, a title within a channel's length limit, a price above zero or a minimum image size, and flag or block products that fail. Rules come in a few types: required fields (completeness), format rules (pattern, length, unit), allowed values (a color from a fixed list), cross-field logic (a sale price lower than the regular price) and channel rules (what a marketplace or Google Shopping demands, such as a title of at most 150 characters). Validation differs from enrichment: validation finds what is wrong or missing, enrichment fills it. A PIM runs these rules on save or import, so errors are caught before a feed is rejected. Test your feed with the free Google Shopping feed checker.

Why Product data validation rules matters for e-commerce

Every error that reaches a channel costs something: a rejected feed, a product missing from filters, a wrong price or a return. Akeneo's 2025 Consumer Returns Report found that about 60% of shoppers have returned a product because of inaccurate or misleading descriptions. Validation rules catch most of these problems before publishing. They also make quality measurable: instead of a feeling that the catalog is messy, you see how many products fail which rule on which channel, and you can fix the biggest gaps first.

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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 rules

  • 1Rule: required field, Field: GTIN, Check: present and valid check digit, Channel: Google Shopping
  • 2Rule: length, Field: title, Check: at most 150 characters, Channel: Google Shopping
  • 3Rule: allowed values, Field: color, Check: value from the color list, Channel: all
  • 4Rule: cross-field, Fields: sale price and price, Check: sale price lower than price, Channel: webshop
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How WISEPIM Helps

  • Quality Guard rules: WISEPIM lets you define rules for required fields, formats and allowed values, and flags products that fail them.
  • Channel Readiness: see per channel which products are not yet complete for that channel's requirements.
  • Review queue: work through flagged products in one list instead of searching the catalog.
  • AI enrichment: fill the gaps that validation finds, such as missing descriptions or attributes, and review the result.

Common mistakes with Product data validation rules

  • Writing so many strict rules at once that the team cannot save any product.
  • Keeping rules unchanged while channels change their requirements.
  • Setting rules without the people who enter the data, so the rules ignore how they work.
  • Allowing overrides so often that the rules stop meaning anything.

Tips for Product data validation rules

  • Start with the rules that block sales: required channel fields, valid GTINs and prices.
  • Document each rule with what it checks and why, so the team understands a failure.
  • Review rules when a channel changes its requirements or you add a product type.

Trends around Product data validation rules

  • AI-suggested rules: systems propose rules based on patterns and common errors in your data.
  • Channel rule packs: ready-made rule sets that mirror a marketplace's requirements.
  • Validation plus enrichment: products that fail a rule are sent straight to AI enrichment and review.
  • Compliance data: more rules for safety, sustainability and labeling information.

Tools for Product data validation rules

  • WISEPIM: PIM with Quality Guard rules, Channel Readiness and a review queue for flagged products.
  • Google Merchant Center: shows feed errors and warnings after you submit products.
  • Akeneo: PIM with completeness per channel and data quality insights.
  • Stibo Systems: enterprise master data management with rule-based data quality.

Related Terms

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

Also Known As

Data quality rulesValidation criteriaData integrity checksProduct data validation

Frequently Asked Questions

A PIM checks each product against rules you define: required fields, formats, allowed values and channel requirements. It runs the checks when a product is saved or imported and shows which products fail and why, so you fix them before export.

Yes. Once rules are set up, the PIM checks every new and changed product without manual review. Most systems also give each product a completeness or quality score per channel, so you see where to start.

At minimum: required fields per channel, valid GTINs, titles and descriptions within length limits, prices and units in the right format, allowed values for attributes like color and size, and image presence and size.

Validation checks existing data and reports what is wrong or missing. Enrichment adds or improves content, such as descriptions, attributes or translations. Validation rules tell you where enrichment is needed.

Yes, and they usually should. Google Shopping, marketplaces and your own webshop each require different fields and limits, so a product can be complete for one channel and incomplete for another.

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