Keyword Cannibalization
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Keyword Cannibalization Detector

v1.0 documentation

Detects when multiple pages on the same site target the same keywords, causing them to compete against each other in search results.

URL inputFile inputXLSX export
keyword_cannibalization.py136 lines4 paramsPython 3.8+
Quick start
1

Install

terminal
pip install -r requirements.txt
2

Run

terminal
python keyword_cannibalization.py --urls https://site.com/page1 https://site.com/page2 --output cannibalization.xlsx
terminal
python keyword_cannibalization.py --files page1.html page2.html page3.html --threshold 0.6
3

Export

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

Parameters
FlagDescription
--urlsPage URLs from same site. Multiple values allowed
--filesLocal HTML files. Multiple values allowed
--thresholdThreshold. Default: 0.5 (decimal)
--outputSave as XLSX
help
python keyword_cannibalization.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: beautifulsoup4, numpy, pandas, requests, scikit-learn. All included in requirements.txt.

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