TF-IDF Tool
Compare your draft against the pages that already rank, and see term by term what they cover and you do not.
Paste both texts above and click Analyze
Missing terms, shared terms, and unique terms with TF-IDF scores
No missing terms found.
| Term | Competitor Score | Priority |
|---|---|---|
No shared terms found.
| Term | Your Score | Their Score | Gap |
|---|---|---|---|
No unique terms found.
| Term | Your Score |
|---|---|
What is TF-IDF?
TF-IDF (Term Frequency-Inverse Document Frequency) measures how important a word is within a document relative to a collection of documents. In SEO, it helps you understand which terms competitors use that you're missing, and which unique terms give your content its distinctive value.
Find content gaps
Discover keywords and topics your competitors cover that you're missing. Fill these gaps to improve your rankings.
Avoid over-optimization
See if you're using certain terms too frequently compared to natural content. Balance is key for modern SEO.
Improve topical depth
TF-IDF reveals related terms and concepts that add depth to your content, signaling expertise to search engines.
Data-driven content
Stop guessing which keywords to include. Use TF-IDF analysis to make evidence-based content decisions.
Frequently asked questions
What is TF-IDF in SEO?
TF-IDF stands for term frequency–inverse document frequency. It weighs a term by how often it appears in your document against how rare it is across a set of documents. A word used everywhere scores low; a word your competitors use repeatedly and you never mention scores high. In SEO it is used to surface the vocabulary a topic requires.
How do I use a TF-IDF tool for content?
Paste your draft, add the pages currently ranking for your target query, and read the terms that score high for them and zero for you. Those are your gaps. The point is not to sprinkle the missing words in — it is to notice the subtopics you forgot to write about, which is what the missing words usually represent.
Is TF-IDF still relevant now that Google uses AI?
As a ranking factor, no — Google has not weighted TF-IDF directly for a long time. As a diagnostic it remains useful and cheap: it is a fast, explainable way to find the concepts a thorough page on your topic covers. Treat the output as a research brief, not an optimisation target.
What is the difference between TF-IDF and keyword density?
Keyword density counts repetition inside one text and tells you nothing about the topic. TF-IDF compares your text against others and tells you what is missing. Density is a guard against over-use; TF-IDF is a guide to coverage.
Advanced competitive analysis with Tonaily
Tonaily analyzes up to 3 competitors simultaneously and tells you exactly which keywords to add to outrank them.