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Bringing Structure to Multi-Brand Product Data

One of the UK's "Big Four" retailers runs a sprawling catalogue spanning grocery, fashion, and home merchandise across supermarkets, convenience stores, e-commerce, and mobile apps. There are more than 960,000 SKUs and 700+ product attributes across four brands and three product domains, each with its own data requirements, from nutritional values to size guides to technical specs. At that scale, accurate product data isn't a finishing touch, it's an operational requirement. Keeping it consistent across every channel was the problem the retailer set out to solve.

sainsburry

SNAPSHOT

The Company At a Glance

Company

Leading UK Retailer
Industry

Retail
Sector

Grocery, Clothing, General Merchandise
Region

United Kingdom London (Headquarters)
Sales channel

Omnichannel (Supermarkets, Convenience Stores, E-commerce, Mobile Apps)
Scale

960,000+ SKU’s
Implementation partner

DEPT

FEATURES (EXTENSIONS)

3 separate PIM instances under unified governance

3 separate PIM instances under unified governance

EH__0051_AIENRICH

AI-driven enrichment
DAM-to-PIM integration for assets

DAM-to-PIM integration for assets

MACH/headless architecture

MACH/headless architecture

Automated supplier data ingestion

Automated supplier data ingestion

The Impact

Top Results

Faster Asset Approvals

Retail media asset approval time cut from 1–3 weeks to roughly 90 seconds via automated validation workflows.

Lower Audit Costs

AI-powered compliance audits reduced verification costs to approximately £0.01 per audit.

Consistent Data at Scale

Consistent product information maintained for over one million enriched products across web and mobile channels.

Single Source of Truth

Bluestone PIM became the central source of truth across the retailer's grocery, clothing, and general merchandise divisions.

AI-Driven Enrichment

Automated generation of product descriptions, attributes, and metadata cut manual work for merchandising teams.

Domain Separation at Scale

Three dedicated PIM instances let each product domain run independently while staying under one unified governance framework.

THE CHALLENGE

A Legacy System on Borrowed Time

Product information was spread across multiple internal systems, each maintained by a different department, with no shared structure connecting them.

Pain points:

  • Inconsistent product information between channels.

  • Slow, manual supplier onboarding.

  • Manual product enrichment workflows eating into merchandising teams' time.

  • Limited visibility across product data ownership.

  • Needed: a platform able to handle 700+ attributes across 4 brands without losing structural clarity or slowing down launches.

legacy

OUR APPROACH

The Retailer's Central Product-data Hub

Bluestone PIM was positioned as the retailer's central product-data hub, a single source of truth feeding structured, enriched product data out to every digital channel.

  • Product data flows in from supplier systems and PLM platforms through ingestion layers that clean, standardise, and normalise it before it enters the PIM, keeping low-quality data out of downstream systems.

  • Three separate PIM environments structure and enrich data by domain (grocery, clothing, and general merchandise) each with its own attribute sets and editing interfaces, avoiding conflicts between category types.

  • A custom DAM integration automatically links product photography, marketing assets, and compliance documents to the correct SKUs.

  • Once enriched and approved, data is distributed via APIs to e-commerce platforms, search platforms, and other digital touchpoints across web and mobile channels.

  • A custom plugin supports large-scale asset management and manual product imports, giving teams direct control over high-volume content updates.

How the Product Data Flows

Supplier & PLM Systems

Product data enters through ingestion layers that clean, standardise, and normalise it.

Bluestone PIM

Structures data across three domain-specific instances under one governance model.

AI-Driven Enrichment

Auto-generates descriptions, attributes, and metadata; image recognition tags.

Digital Commerce & Search

Enriched data is published via API to e-commerce, search platforms, and mobile apps.

The Solution

Capabilities Now in Place

Multi-Instance Domain Separation

Runs three dedicated PIM instances, each optimised for its category's data needs, under one unified governance model.

AI-Driven Product Enrichment

Automatically generates product descriptions, attributes, and metadata, reducing manual work for merchandising teams.

AI-Based Attribute Identification

Uses image recognition to detect attributes like colour, category, and style, and applies them to product records automatically.

Digital Asset Synchronisation

Custom DAM-to-PIM integration links product photography, marketing assets, and compliance documents to the correct SKUs across channels.

Custom PIM Extensions

A purpose built plugin supports large scale asset management and manual product imports for high volume content updates.

WHAT'S NEXT

Looking Ahead

The retailer plans to build AI-driven product recommendations and add sustainability data like carbon footprint and packaging impact to product pages. Bluestone PIM's enriched, structured data lays the groundwork for both, alongside expanding SKU capacity as general merchandise is fully integrated.

looking-ahead
contact-viktor

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See How It Could Work For Your Team

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