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Introducing the Keyword Clustering app! ✨

Many folks have been asking for a port of Lee Foot's awesome keyword clustering script to Streamlit. I’ve been working on it in the past weeks, and I'm super chuffed to release it today!


Basically, you’ll have the same goodies as in Lee’s Notebook, it's just faster to use and you won't need to know any Python! 🎈



🎲 Want to jump right in? Try the app here!


So, what do you get with this app


Simply upload your SEMRush, Ahrefs or Google Search Console report and get:

  1. The cluster name

  2. The cluster size (how many keywords are in a cluster)

  3. The estimated search volume per cluster

  4. The median Keyword Difficulty per cluster (from Ahrefs)

  5. The median CPC per cluster

  6. The estimated traffic per cluster


Why cluster your keywords?


Grouping your keywords into topic clusters provides mighty insights for your SEO strategy. Here are just a handful of use cases:

  • Build topic clusters around your parent keyword

  • Find out what the main keyword and secondary keywords your pages should target

  • Find new themes and content ideas

  • Bulk filter-out junk keywords from your keyword lists

  • Find your competitors' most profitable keyword clusters


New in V2!


Lee has already udated its script (the man is fast!), and I've started porting some of these features in our Streamlit app:

  • Accepts .txt and .csv files. Header or headerless! (Excel formats (.xls and .xlsx) are coming soon)

  • Now accepts Adwords Search Terms reports

  • Auto-detects character encoding on CSVs


About the Beta


The tool is still in Beta, with possible rough edges! The limitations are:

  • No Excel import

  • Only the first 10K rows will be reviewed and clustered

I will add more rows once the app is deemed stable, so keep your eyes peeled!


As always, your feedback is welcome. Let me know if you find any bugs or if you have any suggestions!


This app is free. If it's useful to you, you can buy me a coffee to support my work here ▶️ https://buymeacoffee.com/cwar05


Happy clustering! 🙌

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