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KW Clusterized review

Free#25 of 27 in Keyword Clustering Tools

A focused open-source tool for private keyword grouping and CSV export.

6.7/10Editor score
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KW Clusterized6.7 Visit KW Clusterized

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

KW Clusterized is a browser-based, open-source keyword clustering tool for SEOs, content strategists, and growth teams. It accepts pasted keyword lists along with CSV, TXT, and TSV uploads, then groups terms using word overlap, Jaccard similarity, and greedy agglomerative single-linkage clustering. The tool is available on the web and can also be self-hosted. Its MIT license and client-side processing make it suited to teams that want a private way to organize keyword data without server round-trips.

Its main strength is a focused clustering workflow rather than a broad SEO platform. Users can process batches, remove duplicates, adjust the similarity threshold in the clustering engine, and review color-coded cluster cards with generated labels. Results can be exported as CSV with cluster ID, label, and keyword columns. The project is built with Next.js and TypeScript and can be deployed locally or through Vercel, giving technically capable teams a clear self-hosting path.

KW Clusterized fits buyers who already have keyword lists and need lexical grouping with control over processing and output. It is less suitable for teams that need SERP analysis, integrations, API access, or AI features as part of the clustering workflow. Choose it for private, open-source clustering based on word overlap and Jaccard similarity; choose an alternative when search-result evidence, connected systems, or broader automated analysis is central to the process.

KW Clusterized pros and cons

  • Where it wins
    • Client-side processing keeps keyword lists in the browser.
    • Supports CSV, TXT, TSV, pasted, and newline-delimited inputs.
    • Configurable thresholds, deduplication, batch processing, and CSV export.
  • Where it doesn't
    • No SERP analysis for search-result-based clustering.
    • No integrations or API access for connected workflows.
    • No AI features for AI-assisted keyword interpretation.

KW Clusterized fact sheet, pricing and score →

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