Variations in Figure Tags counts how many of the run’s keyword-variation terms appear inside the page’s HTML figure elements — the captions and text that accompany self-contained visuals. It is a raw occurrence count taken from the captured figure contents, not a quality score: it says nothing about whether the image itself is good or relevant, so read it against the content rather than treating it as a number to maximize.
| Factor ID | RG-KWD-054 |
|---|---|
| Family | Keyword Usage & Density |
| Measurement | Variation occurrence count |
| Measured zone | Raw captured figure contents |
What it measures
This factor counts keyword variations within recognized figure elements. The figure element groups a self-contained visual — an image, diagram, chart, or code sample — together with its caption and related text, so this factor reports how much query-related wording lives specifically inside those figure blocks. The measurement is occurrence based: more than one variation term can contribute, and repeated qualifying occurrences can raise the value. It reflects the descriptive text you attach to visuals, not the visuals themselves.
How RankGear measures it
RankGear extracts the captured contents of paired figure tags from the script-free body without extra HTML cleaning, and sums case-insensitive whole-word variation matches across that raw capture. Because the markup is not stripped first, any nested tags, attribute values, or figcaption text present inside the capture are part of what is scanned. The variation set is specific to the analyzed keyword and to any variation controls applied to the run. If the page has no figure element, or none of the run’s terms appears in the captured contents, the result is 0.
What RankGear looks for
<figure>
<img src="cold-weather-roofing.jpg" alt="Winter roof installation">
<figcaption>Snow-load shingles and ice-dam prevention on a
completed winter roof installation.</figcaption>
</figure>How to read the count
| If the count is… | What to consider |
|---|---|
| 0 | Either the page has no figure element, or its captions and figure text do not use the query’s variation terms. Check whether your visuals are wrapped in figure and whether their captions describe the subject in searchers’ wording. |
| Below the competitive target | Ranking pages tend to attach more query-related terminology to their figures than yours does. Accurate, descriptive captions may add relevant context. |
| At or near the competitive target | Your figures carry query-related wording at a practical level. Prioritize caption accuracy and reader value over adding more terms. |
| Well above the target | May reflect genuinely descriptive captions — or padded, keyword-stuffed figure text. Confirm the captions still read naturally and describe the visual honestly. |
How to optimize it
Use figure for self-contained visuals or examples, and provide accurate captions or related text that explains their topical value. When the caption genuinely describes what the visual shows in natural language, query-related variations tend to appear on their own. Treat this count as an observation about how well your figure text supports the content, not as a quota to fill. Do not add figure wrappers, or stuff variation terms into captions, solely to move this number — use semantic markup because it fits the content.
Important considerations
- The contents are captured raw, without extra HTML cleaning, so nested markup and attributes can influence what is counted.
- This factor can overlap conceptually with
figcaptionand alt-text metrics, which look at closely related text. - It counts wording only — it does not judge image quality or relevance.
- Use semantic markup because it fits the content, not to influence this factor.
- This factor relates to position within a measured result set; it does not by itself make a page rank. Interpret the count alongside content depth, competitor adoption, correlation, and search intent.
Related factors
Part of the Factors reference · how RankGear measures · glossary.