LSI Words in Clean Text counts how many times the run’s related terms appear in RankGear’s cleaned page text. It is a raw occurrence count, so repeated uses of the same listed term add to it — read it alongside coverage factors, not as proof that a search engine uses classic latent semantic indexing.
| Factor ID | RG-LSI-001 |
|---|---|
| Family | Related terms (LSI) |
| Measurement | Occurrence count |
| Measured zone | Cleaned rendered page text |
What it measures
This factor counts occurrences of the related terms supplied for the analysis run within RankGear’s cleaned page text. The legacy “LSI” label refers only to the run’s related-keyword list; it is not evidence that a search engine applies a particular historical latent semantic indexing implementation to web ranking. Because it is an occurrence count, repeated uses of a single listed term can increase the value.
How RankGear measures it
RankGear lowercases the cleaned rendered text and evaluates every term in the run’s LSI or related-keyword list. Matches are case-insensitive and use word boundaries. The occurrence counts for all listed terms are summed to produce the factor value. The measurement follows RankGear’s established match-quoting behavior for compatibility. If the run has no related-term list, the result is 0. A separate factor measures the number of unique related terms, so this value should not be read as a unique-term count.
value = sum over each listed term of ( case-insensitive, word-boundary matches of that term in the lowercased clean text )How to optimize it
Review the related terms associated with the keyword and identify vocabulary that helps explain the subject — its attributes, processes, alternatives, problems, or expected outcomes — then incorporate the appropriate terms into genuinely useful content rather than treating the list as mandatory wording. Use natural language and cover the underlying concepts. Treat this value as an observation, not a target: if the page already meets the competitive goal, do not add repetitions simply to raise the count.
Important considerations
- Related-term lists are specific to the query and to the data available for the run.
- A higher count may reflect repetition rather than broader topical coverage.
- The factor does not determine whether a term is factually or contextually appropriate.
- Compare this measurement with unique-term, entity, variation, and contextual-density factors.
- Avoid keyword stuffing and do not sacrifice readability to reproduce a competitor’s raw count.
- This is a correlational prioritization signal within a measured result set — a higher count does not by itself cause or guarantee a ranking.
Related factors
Part of the Factors reference · how RankGear measures · glossary.