This factor counts how many times the run’s related-term (LSI) list appears in a page’s H2 headings. It’s a count of occurrences within H2 text, not a quality score — a higher count relates to how thoroughly your subheadings echo the topic’s supporting vocabulary, but it never guarantees a ranking on its own.
| Factor ID | RG-LSI-003 |
|---|---|
| Family | Related Terms (LSI) |
| Measurement | Related-term occurrence count |
| Measured zone | H2 text |
What it measures
RankGear counts occurrences of the run’s LSI term list inside the page’s H2 headings. The LSI list is the set of related terms derived for a given keyword and result set; this factor tallies how many of those terms surface in your second-level subheadings. It measures presence and frequency in H2 text specifically — not H1s, body copy, or other zones.
How RankGear measures it
RankGear parses the text of every H2 on the page and, for each item in the LSI list, sums case-insensitive, word-aware matches. Matching is word-aware rather than raw substring, so a term counts only where it appears as a whole word (or, for multiword items, as a whole phrase). If the LSI list for the run is empty, the factor returns 0.
How to read it
| If the value is… | What it suggests |
|---|---|
| 0 | No LSI terms appear in any H2 — or the run produced no LSI list. Your subheadings may not reflect the topic’s supporting vocabulary. |
| Low | A few related terms surface in headings. Room to fold more supporting subtopics into the outline where they fit. |
| Higher | Related terminology recurs across your H2s. Read this as coverage of the topic’s subtopics, not as a target to inflate. |
How to optimize it
Use related terminology in H2 headings where it accurately names a major subtopic and genuinely improves the outline. Because the factor counts occurrences rather than unique terms, the aim is a set of subheadings that map the topic honestly — not headings padded with keywords. Treat the number as an observation about your outline’s coverage, not a quota to hit.
Important considerations
- It counts occurrences, not unique terms — the same term in several H2s adds to the total.
- Multiword items are matched as phrases, so a two-word LSI term counts only where both words appear together in that order.
- The LSI list is derived per run and can vary by SERP, so the same page can score differently for different keywords.
- Do not force every related term into headings; write subheadings that read naturally and describe the section beneath them.
- Correlation is not causation. This is a prioritization signal that relates to position within a measured result set; a higher count does not by itself make a page rank.
Related factors
Part of the Factors reference · how RankGear measures · glossary.