Definition
Akeneo supports product data quality through structured attributes, completeness scoring, and enrichment workflows — and, in the Product Cloud, AI-driven data-quality insights and cleanup automation. The goal is consistent, complete records before content is syndicated to channels.
How quality is supported
- Structure: attributes, families, and variations give the catalog a consistent shape that makes gaps and inconsistencies visible.
- Completeness scoring: records are measured against required fields so teams can prioritize what needs enrichment.
- Enrichment workflows: teams fill and normalize content at scale within governed, role-based processes.
- AI assistance (Product Cloud): generative AI and product data intelligence provide quality insights, enrichment guidance, and automation of repetitive cleanup across large assortments.
How it relates to catalog intelligence
Akeneo's quality features live inside the PIM and focus on completeness and consistency for its own workflows. Catalog intelligence is a complementary layer that measures data against broader search- and AI-readiness standards and drives continuous improvement — the two reinforce each other. See how do you measure catalog quality?