competitor-analysis

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Run competitive analysis. Use when: content, SEO, paid ads, social, AI visibility, pricing, positioning comparison.

AI & Automation 136 stars 37 forks Updated 3 days ago MIT

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Skill Content

# /digital-marketing-pro:competitor-analysis ## Purpose Deliver a comprehensive competitive intelligence report across all major marketing dimensions. Identify competitor strengths, weaknesses, strategies, and gaps the brand can exploit. ## Input Required The user must provide (or will be prompted for): - **Competitors**: 2-5 competitor names and/or URLs - **Analysis scope**: Full analysis or specific dimensions (SEO, content, ads, social, pricing) - **Key battleground keywords**: Terms where the brand competes head-to-head - **Industry/category**: For contextual benchmarking ## Process 1. **Load brand context**: Read `~/.claude-marketing/brands/_active-brand.json` for the active slug, then load `~/.claude-marketing/brands/{slug}/profile.json`. Apply brand voice, compliance rules for target markets (`skills/context-engine/compliance-rules.md`), and industry context. **Also check for guidelines** at `~/.claude-marketing/brands/{slug}/guidelines/_manifest.json` — if present, load restrictions and relevant category files. Check for custom templates at `~/.claude-marketing/brands/{slug}/templates/`. Check for agency SOPs at `~/.claude-marketing/sops/`. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults. 2. **Content analysis**: Content types, publishing frequency, top-performing content, content gaps, topic authority 3. **SEO analysis**: Domain authority, keyword overlap, ranking gaps, backlink comparison, techn...

Details

Author
indranilbanerjee
Repository
indranilbanerjee/digital-marketing-pro
Created
4 months ago
Last Updated
3 days ago
Language
Python
License
MIT

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