Keyword Cluster Tool
How To Identify Search Intent
Every page has a measurable gap between meta description and keyword intent. Classic keyword matching techniques count the length and frequency of keywords but miss the meaning behind them. Now vector embeddings uncover, cluster, and prioritize keyword intent.
Accomplishing this requires an AI pipeline that translates text into numerical representations, creates an embedding space, and performs calculations. We've set this up and made it free.
Use this tool to see which keyword clusters your page serves well, which it misses, and what to do about each one.
Select Your Google Search Console Data Source
Upload Your Data
Filter Google Search Console to a single page, export the .zip, and upload it below. The tool scrapes your meta description, scores every query against it, and clusters the results.
How to export from GSC
- Open Google Search Console and navigate to Performance > Search Results
- Filter by the page you want to analyze (required)
- Click Export and download the CSV (this produces a .zip)
- Select the downloaded .zip file below
Use Sample Data
Simulate process of scraping, scoring, and clustering using synthetic GSC data for the fictitious SaaS company, LumonHR.
The sample results will load below.
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Privacy: Your data is processed in memory only and never stored.
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