TF-IDF Calculator
Compare keyword importance across multiple documents. Paste 2–6 pages and instantly see which terms actually differentiate each page — the core signal behind topical SEO and content gap analysis.
Paste text into at least two documents to see which terms are distinctive to each.
How to Use the TF-IDF Calculator
TF-IDF is the single most useful term-weighting formula for SEO content analysis. Here's how to turn scores into content decisions.
Paste your page, plus 2+ competitors
Put your own page in Document A. Paste the top-ranking Australian competitors into B, C, D. Aim for 3–4 docs — that's the sweet spot for meaningful IDF.
Compare top terms across docs
Look for terms that rank high in competitor docs but are missing from yours. Those are your content gaps — add them (in context, not stuffed).
Watch for terms unique to one doc
Terms with DF = 1 only appear in one document. If that's your doc, that's a distinctive signal. If it's a competitor's, it's an angle worth investigating.
Rewrite and re-run
Update your draft and paste it back into Document A. The goal isn't to match every competitor word — it's to cover the shared semantic space while keeping your unique angle.
How TF-IDF Is Calculated
Three simple numbers combine into the score that underpins every search engine's early ranking model.
Term Frequency (TF)
How often a term appears in a single document, normalised by the document length. Higher TF means the term matters within this page.
Document Frequency (DF)
How many of your documents mention the term. Common terms (high DF) are less distinctive — every doc has them.
Inverse Doc Frequency (IDF)
The logarithmic inverse of DF. Terms found in every document get IDF = 0; terms found in only one get a big boost.
TF-IDF Score
Combining both: how important is this term to this document, relative to the whole corpus? The higher the score, the more distinctive the term.
Why TF-IDF Still Matters in 2026
Modern Google uses deep learning — but TF-IDF concepts still underpin how entity coverage, topical depth, and semantic relevance are measured.
Content strategy
On-page optimisation
AI & semantic search
Quality signals
TF-IDF FAQ
How many documents should I compare?
Three to four is ideal for SEO work. Too few and IDF is meaningless; too many and the tool gets noisy. Two is the minimum for any useful comparison.
Is TF-IDF still used by Google?
Not as a direct ranking factor today, but the concept — distinctive terms that prove topical depth — still drives how modern semantic search models evaluate content.
Does the tool send my text anywhere?
No. Every calculation runs locally in your browser. Nothing is uploaded or stored.
Why do short docs return weird scores?
TF-IDF needs enough text per document to stabilise. Paste at least 150–200 words per doc — otherwise a single mention skews TF dramatically.
Want a Full Topical & Content-Gap Audit?
Our Australian SEO team benchmarks your pages against the top-ranking competitors — then hands you a prioritised list of terms and sub-topics to add.
- TF-IDF + semantic gap review
- Prioritised term list
- No lock-in commitment
No long-term commitment. Cancel anytime. 100% satisfaction guaranteed.