Overview
Redesigned the content taxonomy and metadata architecture for a global paints and chemicals manufacturer, improving content findability and management across product, solution and market content. Delivered a structured controlled vocabulary, metadata schema, CMS implementation, and governance model for sustained classification quality at scale.
Who This Is For
Global manufacturers, chemicals companies, or B2B enterprises with complex product portfolios requiring structured content taxonomy to improve findability across product, solution, and market content. Typically managing large content estates where inconsistent classification is limiting search effectiveness, personalisation, and AI-readiness.
The Challenge
The organisation manages a large volume of product and solution content across multiple markets and customer segments, but findability is poor. Content is tagged inconsistently, or not tagged at all. Different teams use different terminology for the same products and solutions. The result is content that exists but cannot be surfaced effectively - invisible to search, invisible to AI, and invisible to personalisation engines.
Our Approach
Taxonomy Audit - Assessment of existing content classification, tagging practices, and metadata across product, solution, and market content identifying inconsistencies and findability failures. Taxonomy Design - Structured controlled vocabulary and faceted classification aligned to how customers navigate product and solution content. Metadata Framework - Metadata schema covering mandatory and optional fields, controlled values, and tagging guidelines for each content type. CMS Implementation - Configuration of taxonomy and metadata within the CMS including tagging workflows, quality checks, and governance controls. Governance Model - Taxonomy governance, editorial standards, and review cycles to maintain classification quality as the content estate grows.
Impact
Product findability - Customers and channel partners locate the right product and solution content accurately and efficiently. AI readiness - Structured, tagged product content that AI systems can retrieve, rank, and surface reliably. Personalisation enablement - Metadata that allows the right product content to reach the right audience at the right moment. Consistency across markets - Shared classification standards eliminating duplicate effort and conflicting terminology across global teams.
Delivered while employed at Making Waves (later NoA Ignite). Any public information referenced here is used for identification and does not imply endorsement.
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