Keyword Density: Why Calculate It Today
Keyword density is the share of repetitions of a word or phrase relative to the volume of text. This metric is old and overrated: there is no 'correct percentage', but it clearly shows distortions. You can calculate it using density analysis — it counts individual words, pairs, and triples.
Why Look at It Today
- Find overstuffing. If a phrase appears in every paragraph, the text reads like a machine.
- Check if the text is relevant. Sometimes, unrelated words end up at the top of the frequency list.
- Compare with the top. More useful than any norms: you can see what formulations are actually used by ranked pages.
- Find missing forms. The text may not contain how people phrase the query at all.
How to Read the Result
| Observation | Conclusion |
|---|---|
| Keyword phrase in the top frequency next to prepositions | Clear overstuffing, needs to be diluted |
| Phrase is completely absent | Page does not literally answer the query — add a natural mention |
| Many root words, few synonyms | Text is poor: add variations of formulations |
| Top frequency consists of function words | Normal picture, see Zipf's law |
Where to Look at Frequencies Smartly
Individual words say little: pairs and triples are more useful. This is where you can see how the page formulates the topic — 'indexing check', 'check page indexing', 'page not in index'. If your triples do not match any formulations used by people, the text is written in the company's internal language, not in the query language.
What to Do Instead of Adjusting Percentages
Expand the topic: answer related questions, add specifics and examples. This way, the necessary formulations appear naturally, and the text remains human. How to choose the formulations themselves — keyword selection, how to distribute them across pages — semantic core.