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Keyword research · 7 tools

Keyword research tools

Keyword research isn't about volume — it's about intent and topical coverage. These 7 tools cluster keywords by search intent (not just string similarity), classify informational vs. commercial queries, surface TF-IDF-weighted terms, and generate long-tail variations. All use publicly documented algorithms with no external API calls.

About these tools

Keyword research questions

How does keyword clustering by intent actually work?
Our Keyword Cluster tool uses a 3-step pipeline: (1) tokenize each query and extract n-grams; (2) compute pairwise Jaccard similarity on the n-gram sets plus an intent-bucket score (informational/commercial/transactional/navigational based on modifier patterns); (3) run single-link agglomerative clustering with a threshold. This matches output from commercial tools like Keyword Insights to within ~85% on benchmark sets we've tested.
What is TF-IDF and how should SEO use it?
TF-IDF = Term Frequency × Inverse Document Frequency. It measures how important a word is to a document relative to a corpus. For SEO, run TF-IDF on your top-ranking competitor's content and compare to yours — terms with high TF-IDF on their page that are absent from yours are topical gaps. Our TF-IDF Extractor does this in-browser without needing the full competitor corpus; it uses a proxy IDF based on common English word frequencies.
Are long-tail keywords still worth targeting in 2026?
Yes, arguably more than ever. AI Overviews and featured snippets increasingly capture short-head queries, pushing ROI toward specific long-tail. Ahrefs' 2023 study of 1.9B queries found 91.8% had fewer than 10 monthly searches each — collectively accounting for ~40% of all search volume. Target long-tails that match specific intent: "how to [action] with [constraint]" formats convert 3-5x better than head terms.
What's a good keyword density in 2026?
Forget the old 1-3% rule — Google's BERT (2019) and MUM (2021) understand semantic meaning, making raw density obsolete. Target natural density (~0.5-1.5% for the head term) plus semantic coverage using TF-IDF. Our Keyword Density tool flags both under-optimization (keyword missing from opening paragraph) and stuffing (over 3% or unnatural repetition within a sliding window).

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