Context
A global retail enterprise managing thousands of sellers and millions of SKUs struggled with inconsistent, incomplete, and non-compliant item data flowing into its Stibo PIM system. Sellers submitted product information with varying formats, missing attributes, wrong classifications, and category-level inconsistencies—leading to poor searchability, slow onboarding, and operational inefficiencies across the value chain.
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Athena Impact
- Connected Athena’s quality engine with Stibo PIM to validate every incoming SKU across global, category, supply chain, and compliance rules.
- Applied AI/ML-based checks for completeness, standardization, taxonomy accuracy, duplicate detection, and attribute normalization.
- Implemented a real-time feedback loop to sellers, flagging issues instantly (missing attributes, incorrect formats, compliance gaps, classification errors).
- Enabled continuous quality scoring for categories, brands, and seller feeds, ensuring data is clean before it enters downstream eCommerce and supply chain systems.
Results
- 45% improvement in attribute completeness across priority categories.
- 80% reduction in manual item data correction for internal teams.
- Faster seller onboarding and significantly fewer listing rejections.
- Improved search, filter accuracy, and customer experience across digital platforms
