ONGOING ยท SEO / CONTENT OPERATIONS
Turning Content Into a Search System
Treating a large website's content as an interconnected system of topics, products, pages, intent, and internal links, rather than a collection of isolated posts.
- Capability
- SEO & content intelligence
- Lifecycle status
- Ongoing
- Role & ownership boundary
- Leads the content-system design and analysis: audits, taxonomy, topic clusters, product and content mapping, internal-linking and consolidation recommendations, redirect planning, and search-performance analysis. Led, not directed: no people-management implication.
- Collaborators
- Marketing team, Product, SEO stakeholders
- Tools
- Google Search Console, GA4, SEMrush, SurferSEO, WordPress, Obsidian
Overview
This work treats website content as an interconnected system of topics, products, pages, search intent, internal links, and evidence, rather than as a pile of individual articles. The goal is a repeatable basis for content decisions, search prioritization, product alignment, and internal-linking improvements.
Problem
A large content library accumulates overlap: duplicate topics, outdated articles, inconsistent taxonomy, weak internal linking, irrelevant outbound links, orphaned pages, and gaps between content and the products it should support. Each post gets optimized in isolation, which does not fix the structure.
My role
I led the analysis and the system design: content and website audits; evaluating posts for consolidation, refresh, redirect, internal-link updates, product alignment, and canonical ownership; developing topic clusters and product mappings; and planning reporting for internal links, orphans, canonical targets, and content performance.
Approach
Map the library as a system first. Define a taxonomy and the umbrella relationships between topics. Decide consolidation, redirect, and canonical ownership at the cluster level. Connect informational content to the relevant product pages. Audit outbound links for relevance. Then analyze search performance against that structure instead of post by post.
What I built and did
- Content and website audits across the library
- A topic taxonomy with defined umbrella and supporting relationships
- Topic clusters and product / content mappings
- Consolidation, refresh, redirect, and canonical-ownership recommendations
- Internal-linking recommendations connecting content to product pages
- An audit of suspicious and irrelevant outbound links
- A plan for reporting on internal links, orphans, canonical targets, and performance
Selected artifacts
Artifact to add: a visual topic-cluster and product map, a sanitized content audit, or a redacted internal-linking or consolidation decision framework.Outcome
The content library now has a defined taxonomy, cluster-level consolidation and canonical decisions, and an internal-linking model tied to product mapping. It is being used to guide consolidation, internal linking, product alignment, and content prioritization. Search-performance measurement against the new structure is ongoing.
Tools
Google Search Console, GA4, SEMrush, SurferSEO, WordPress, Obsidian, and AI-assisted analysis with custom workflows and scripts.
Reflection / key takeaway
Optimizing pages one at a time does not fix a content library. Structure does: a taxonomy, cluster-level decisions, and internal links that reflect how the topics and products actually relate.