Keyword Intent Classifier
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Keyword Intent Classifier

v1.0 documentation

Classifies keywords into search intent categories: Informational, Navigational, Commercial, Transactional using NLP pattern matching and optional embeddings.

CSV/XLSX inputXLSX export
keyword_intent_classifier.py146 lines5 paramsPython 3.8+
Quick start
1

Install

terminal
pip install -r requirements.txt
2

Run

terminal
python keyword_intent_classifier.py --input keywords.csv --output classified.xlsx
terminal
python keyword_intent_classifier.py --keywords "buy laptop online" "how to fix wifi" "nike official site"
3

Export

Add --output report.xlsx to save results as a spreadsheet.

Parameters
FlagDescription
--inputCSV/XLSX with keywords
--columnColumn name with keywords
--keywordsKeywords to classify. Multiple values allowed
--methodMethod. Options: rules, embeddings, both
--outputSave as XLSX
help
python keyword_intent_classifier.py --help
Use cases
Keyword strategy
Client research
Competitor intelligence

Run before creating content. Use the output to plan which terms to target, group into clusters, and prioritize by difficulty. Export to XLSX and share with your content team.

Deliver keyword research as a paid service. Run the tool on a client's niche, export results, and present clusters as a content roadmap. Charge $100-300 per research package.

Analyze what keywords competitors rank for that you're missing. Feed the output into your content calendar to close gaps systematically.

Works well with

Combine with other tools for a complete workflow:

Brand Serp Auditor

Competitor Analysis

Fetches and analyzes multiple competitor pages using NLP to find content gaps, c

Competitor Strategy Analyzer

Reverse-engineers a competitor's content strategy by analyzing their sitemap or

Content Brief Generator

Generates data-driven content briefs by analyzing top-ranking competitor pages.

Content Gap Mapper

Maps content gaps across topic clusters. Identifies which subtopics are covered

Featured Snippet Optimizer
Dependencies

Requires: numpy, pandas, scikit-learn, sentence-transformers. All included in requirements.txt.

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