Quick overview
Intent Labeler reads Google’s top 10 for a keyword and answers three questions before you write: which search intents the results serve, in what form each one is answered, and how long the winning pages are.
Who it’s built for
SEO and content teams, agencies and developers who want intent analysis in a browser, a terminal or their own panel.
Workflow breakdown
- Give it a keyword, language and location, or a list of URLs.
- DataForSEO SERP API delivers the live top 10 for any country and language.
- Each page is read as text: via DataForSEO OnPage content parsing in the playground and n8n templates, over plain HTTP in the Python CLI.
- DataForSEO Labs adds search volume, seasonality and traffic per URL.
- A language model only groups the results into intents. Every number (share of results and traffic per intent, reference length, seasonality) is computed by code.
- When the sample is too small, it returns no length and the reason instead of a guess.
What you get
- An HTML report with charts and JSON for your own tools.
- A browser playground that runs on your own keys and shows the real cost of every DataForSEO call. A full run costs about $0.03.
- A Python library, CLI and HTTP API (MIT licence), 16 live examples in 6 markets, and n8n templates.
What you need to get started
- A DataForSEO account with API access.
- A key for any OpenAI-compatible LLM endpoint, for example OpenRouter.
- A browser for the playground, or Python for the library and CLI.
Playground: https://romek-rozen.github.io/intent-labeler/
