Use it to detect over-optimisation before publishing
Before publishing any SEO-focused content, paste it into the analyser and check whether your target keyword appears in the red zone (above 4%). If "email marketing" appears 22 times in a 500-word article, that is a 4.4% density that will read unnaturally and may trigger over-optimisation signals. Reduce occurrences to 8–10 for a more natural 1.6–2% density that reads better and tends to perform better in search.
Analyse competitor content to understand their keyword focus
Copy the text of a competitor's top-ranking page (use the browser's "view source" or copy the visible text) and paste it into the analyser. The frequency table reveals exactly which terms they use most, how often, and whether they use multi-word phrases that match common search queries. Cross-reference with the three-word phrase tab to find complete keyword phrases they are targeting that you might be missing.
Check for unintentional keyword cannibalism
If you have multiple pages targeting similar topics, paste both into the analyser in sequence and compare the top 10 words. If both pages have very similar top-word distributions, they may be competing with each other in search rankings — a situation called keyword cannibalism. Differentiate the pages by making each one focus on different specific aspects of the topic, reflected in different top keyword distributions.
Use the 3-word phrase tab for long-tail opportunity
Long-tail keywords — specific 3+ word phrases — often have less competition and more intent than single words. The 3-word phrase analysis shows which specific phrases your content naturally uses. If your article about home insurance uses "home insurance quote" naturally five times, that is a potential long-tail keyword signal you can reinforce in your title and headings. If a valuable long-tail phrase appears zero times, add it naturally.
Aim for semantic richness, not target density
Modern search algorithms use semantic analysis to understand topic coverage, not just keyword repetition. Rather than hitting a specific keyword density, aim for rich coverage of related terms. If you are writing about "coffee brewing", a well-written article will naturally include terms like "extraction", "grind size", "water temperature", "bloom", "pour-over" — these semantic neighbours signal depth of coverage more effectively than repeating "coffee brewing" at a specific percentage.