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Digital commerce / Product information
Bringing structure to a chaotic digital product data landscape
Digital Commerce Architect
Turned unorganized product data into a governed model — structured, optimized, and ready for scalable digital experiences.
PIMProduct DataArchitectureData Governance
Challenge
Product information lived in fragmented, inconsistent forms across systems and teams. Attributes lacked a shared model, enrichment was ad hoc, and downstream channels inherited ambiguity. Scaling catalogs or launching markets meant fighting the data before building experiences.
Approach
- Assessed sources of truth, ownership gaps, and where unstructured or duplicated data blocked delivery.
- Defined a target product information architecture — entities, attributes, relationships, and governance rules.
- Structured and normalized data for reuse across channels; reduced one-off mappings.
- Optimized enrichment and publish flows so cleaner data reached storefront, search, and content systems faster.
- Partnered with business and engineering to make the model operable day-to-day, not just a diagram.
Outcome
Outcomes reflect approximate results in line with industry benchmarks for similar performance and commerce architecture programs — not audited client KPIs.
- ~40–50% faster time-to-publish / enrichment cycle for catalog updates
- ~30–40% fewer data defects reaching storefront and search
- Multi-channel reuse from one structured model across web, search, and merchandising
- Foundation for later AI enrichment and market expansion