Case Study: Bringing Structure to Multi-Brand Product Data

One of the UK’s “Big Four” retailers runs a vast catalogue spanning grocery, fashion and home merchandise across supermarkets, convenience stores, e-commerce and mobile apps. It manages more than 960,000 SKUs and over 700 product attributes across four brands and three product domains, each with completely different data requirements: food needs nutritional values and allergen information, clothing needs size guides and variants, and general merchandise needs technical specifications. At that scale, accurate product data is an operational requirement, not a finishing touch. Keeping it consistent across every channel was the problem the retailer set out to solve.

Key Strategic Focus Areas

• Multi-Brand Product Data Orchestration
  The retailer manages dramatically different product data structures across categories. Bluestone PIM enables clear separation between product domains while maintaining central governance and consistent workflows.

• AI-Driven Product Enrichment at Scale
  AI automation generates product descriptions, attributes, and metadata automatically. This reduces manual work for merchandising teams and speeds up catalogue updates during seasonal launches.

• Digital Asset Synchronisation
  A custom DAM-to-PIM integration automatically links product photography, marketing assets, and compliance documents to the correct SKUs across web and mobile channels.

Before Bluestone PIM, product information was spread across multiple internal systems, each maintained by a different department. The fragmentation created friction across the business:

• Inconsistent product information between channels
• Slow supplier onboarding
• Manual product enrichment
• Limited visibility into who owned which data

The scale made it harder still: more than 700 attributes across four brands and three very different domains. When food, fashion and general-merchandise attributes share one environment, category hierarchies quickly become difficult for teams to navigate. The retailer needed a platform that could deliver both scale and structural clarity, without slowing product launches.

The implementation focused on building a composable product data architecture that separates product domains while maintaining a unified governance framework.

Separation of Product Domains

Three Bluestone PIM environments were deployed to support the retailer’s main divisions:

• Grocery products
• Clothing products
• General merchandise products

This separation prevents attribute conflicts and keeps product editing interfaces relevant for each business unit.

Integration Architecture

Bluestone PIM was positioned as the single source of truth for product data.

Supplier systems and PLM platforms send product data through ingestion layers that clean, standardise, and normalise incoming information before it enters the PIM environment. This prevents low-quality data from reaching downstream systems.

Once products are enriched and approved, the data is distributed through APIs to digital commerce platforms, search engines, and other applications supporting the retailer’s online experience.

Implementation Timeline

The implementation forms part of a broader three-year digital transformation programme (2024–2026) focused on modernising the retailer’s product data infrastructure and improving scalability across its omnichannel ecosystem.

Key Highlights

• DAM-to-PIM integration: a custom integration links product photography, marketing assets and compliance documents to the correct SKUs across web and mobile.
• AI attribute identification: image recognition detects colour, category and style, then applies them to product records automatically.
• Custom import plugin: a dedicated extension handles large-scale asset management and bulk manual imports for high-volume content updates.

Operational Efficiency: Retail media asset approvals that previously required one to three weeks can now be completed in approximately 90 seconds through automated validation workflows.

Cost Reduction: AI-powered compliance audits reduced verification costs to roughly £0.01 per audit.

Data Consistency at Scale: The platform maintains consistent product information for more than one million enriched products across web and mobile channels.

The retailer continues to build on Bluestone PIM as part of its longer-term commerce strategy. Two initiatives are already in motion: personalised product discovery, where enriched data and intelligent search power tailored recommendations, and sustainability transparency, which will bring carbon-footprint and packaging-impact data into the product experience. A further phase will expand SKU capacity and fully fold the general-merchandise categories into the digital commerce ecosystem.