Definition
inriver supports product data quality through structured attributes, enrichment workflows, workflow automation, and AI-assisted analytics that give visibility into product data performance. The goal is consistent, complete records before content is syndicated to channels and marketplaces.
How quality is supported
- Structure: attributes are structured for complex B2B and B2C catalogs, giving the catalog a consistent shape that makes gaps and inconsistencies visible.
- Enrichment workflows: teams fill and normalize content through governed, collaborative workflows.
- Workflow automation: repetitive steps are automated so records move through enrichment and approval consistently.
- AI-assisted analytics: visibility into product data performance helps teams see where content is weak and improve it over time.
How it relates to catalog intelligence
inriver's quality features live inside the PIM/PXM and focus on completeness, consistency, and channel readiness 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?