KW Clusterized is an open-source tool that groups keyword lists into topical clusters to help organize search intent. It is aimed at SEOs, content strategists, and growth teams. Add keywords by pasting comma-separated or newline-delimited text, or upload a CSV, TXT, or TSV file. The app can handle large keyword sets in one pass, remove duplicate entries, and group the remaining terms. Its clustering method combines word overlap, Jaccard similarity, and greedy single-linkage agglomerative clustering. The results appear as color-coded cluster cards with automatically generated labels, and assignments can be downloaded as CSV with cluster ID, label, and keyword columns. Similarity thresholds are configurable in the clustering engine’s code. The README says analysis happens in the browser, with keywords staying there and no server round-trips or API calls. The repository credits Sean G as the builder and provides the software under the MIT License, with an as-is warranty disclaimer. The README describes running the app locally with Node.js 18.17 or later and npm 9 or later, and says it can be deployed on Vercel. It also links to a live demo.
Who it is for
KW Clusterized suits SEOs, content strategists, and growth teams who need to organize large keyword lists into topical groups. It is useful when keyword input from text or CSV, TXT, or TSV files and CSV cluster exports fit the workflow.
What is good
- Accepts pasted keywords and CSV, TXT, or TSV uploads.
- Handles large keyword sets in one pass and removes duplicates.
- Shows clusters as color-coded cards with automatic labels.
- Exports cluster IDs, labels, and keywords as CSV.
- Analysis runs in the browser, with no API calls.
- Released under the MIT License.
What to know first
- The listed export format is CSV only.
- Local setup requires Node.js 18.17 or later and npm 9 or later.
Verdict
Choose KW Clusterized if you want a free, open-source way to group keyword lists and export the results as CSV. Its browser-based processing keeps keywords in the browser according to the README. Look elsewhere if you need SERP analysis.
Get started with KW Clusterized
- Open the linked live demo or the repository.
- Paste comma-separated or newline-delimited keywords, or upload a CSV, TXT, or TSV file.
- Run the clustering to group and review the color-coded clusters.
- Download cluster assignments as CSV.
- To run it locally, use Node.js 18.17 or later and npm 9 or later.
Limits to know first
The clustering engine’s similarity thresholds can be adjusted in code. The listed export format is CSV.
Questions about KW Clusterized
Is KW Clusterized free?
Yes. It is open source and provided under the MIT License, with an as-is warranty disclaimer.
What input formats does it accept?
You can paste comma-separated or newline-delimited keywords, or upload CSV, TXT, and TSV files.
What can I export?
Cluster assignments can be downloaded as CSV with cluster ID, label, and keyword columns.
Does KW Clusterized make API calls?
The README says analysis runs in the browser, keywords stay there, and the app makes no API calls or server round-trips.
Can I change the similarity threshold?
The clustering engine supports configurable similarity thresholds, which the README says can be adjusted in code.
How can I run or deploy it?
The README describes local setup with Node.js 18.17 or later and npm 9 or later, and says the app can be deployed on Vercel. It also links to a live demo.
Compared on keyword clustering tools
- Clustering method
- semantic
- SERP analysis
- No
- Batch upload
- Yes
- Export formats
- CSV
- API access
- No
