Number of Unique LSI Words Used counts how many entries from the run’s related-term list appear at least once in RankGear’s cleaned page content. It measures topical vocabulary breadth, not repeated occurrences — and “LSI” here names RankGear’s related-term list, not a claim that search engines apply a historical latent semantic indexing system.
| Factor ID | RG-LSI-011 |
|---|---|
| Family | Related terms (LSI) |
| Measurement | Distinct-item count |
| Measured zone | Cleaned rendered page content |
What it measures
The factor counts how many entries from the run’s LSI or related-term list appear at least once in RankGear’s cleaned page content. It captures the breadth of topical vocabulary a page covers, rather than how many times any related term is repeated. The legacy “LSI” label refers to RankGear’s related-term list and should not be read as a claim that a search engine runs a specific historical latent semantic indexing system against web rankings.
How RankGear measures it
RankGear lowercases the cleaned rendered content and checks each related-term entry for substring presence. Every listed term found at least once contributes one to the count, regardless of how many times it occurs on the page. If the run has no related-term list, the value is 0. Because the check uses substring matching, a shorter term can occasionally be detected inside a longer word.
| If the count is… | How to read it |
|---|---|
| Low | Few related terms are present — the page likely has vocabulary gaps worth reviewing against the run’s related-term information. |
| Moderate | The page covers some of the related vocabulary; there may still be relevant concepts to add. |
| High | Broad topical vocabulary is present — but confirm the terms are explained and useful, since a high count can accompany thin or repetitive content. |
How to optimize it
Use the run’s related-term information to identify missing vocabulary and concepts that would make the page more complete, then add relevant terms within definitions, examples, attributes, processes, comparisons, evidence, and answers that support the primary topic. Treat the number as an observation about coverage, not a target to maximize: do not paste terms into the page simply to raise the count. Explain their meaning and relationship to the subject in language that is useful to readers.
Important considerations
- Related-term lists are query specific and may differ between runs.
- This factor measures presence, not factual accuracy or depth of treatment.
- Substring matching can produce incidental detections, where a listed term is found inside a longer word.
- A high count can still accompany weak or repetitive content.
- Read it alongside LSI occurrence counts, contextual density, entities, variations, and competitor adoption rather than on its own.
- This is a prioritization signal that relates to position within a measured result set; it does not by itself make a page rank or guarantee a ranking.
Related factors
Part of the Factors reference · how RankGear measures · glossary.