Relevance

Theoretical Foundations
Relevance
Relevance is the primary criterion in attribute filtering that measures how strongly an attribute relates to the Central Search Intent in semantic SEO.

Relevance is the first criterion for attribute filtering, measuring how strongly an attribute relates to the website's Central Search Intent. An attribute may rank prominently in SERPs with high search volume, but if it doesn't align with your CSI, exclude it from your content.

For example, a pool manufacturer should reject the attribute 'swimming lessons' because it serves swimming instructors and schools, not equipment manufacturers — it's outside their business model and customer journey. During the clustering pipeline, Relevance is one of three filters (alongside Prominence and Popularity) determining whether an attribute creates a separate node in the Topical Map. Relevance is closely tied to Source Context — the same attribute can have high Relevance for one SC and low for another.

When building a Topical Map, attributes with low Relevance should be excluded from content strategy, regardless of search volume. Writing about low-relevance attributes weakens your Site Focus Score and dilutes topical authority, reducing your ability to rank for your core business terms.

Source: AI Semantic SEO Expert, Robert Niechciał (sensai.io)