The KeywordGraph Guides: Keyword Research, Topical Authority, Semantic SEO, and LLMO
Start with the step-by-step workflow tutorial, then go deeper with four connected guides — from raw keywords to topic clusters, from topical authority to entity-based optimization, all the way to getting cited by AI search. They cross-reference each other.
The SEO & LLMO Workflow
The recommended starting point: an end-to-end, four-step tutorial that runs the whole method on one topic. Build knowledge graphs of how LLMs and search engines see your domain, map your co-occurrence position, estimate search intent, and fuse it all into a content strategy that ranks in search and gets cited by AI.
Start the Tutorial →Keyword Research
Keyword research is the process of discovering topics, not just keywords. Tools landscape, the five-step graph-based workflow, and the underserved demand the standard tool comparisons miss.
Read the Guide →Topical Authority
Topical authority is a content shape, not a score. How Google and AI engines assess it, how it differs from domain authority, and the four-step framework to build it with knowledge graphs.
Read the Guide →Semantic SEO & Knowledge Graphs
Semantic SEO optimizes content for meaning rather than for keyword strings. The unit is the entity, not the phrase; the unit of organization is the graph, not the page.
Read the Guide →LLMO & Generative Engines
LLMO (also called GEO) structures content for retrieval and citation by AI-powered search engines. The mechanism differs from traditional SEO; the tactics that work are derivable from it.
Read the Guide →Put the guides into practice
Every guide maps back to the same workflow: build a knowledge graph from your keywords or SERP, read the clusters and gaps, and publish into the structure that earns topical authority. Run it on your own topic.
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