Marketing Skills - Claude Code Guidance

This guide covers the 4 production-ready marketing skills and their Python automation tools.

Marketing Skills Overview

Available Skills:

1. content-creator/ - Content creation, brand voice, SEO optimization (2 Python tools)
2. marketing-demand-acquisition/ - Demand generation and customer acquisition (1 Python tool)
3. marketing-strategy-pmm/ - Product marketing and go-to-market strategy
4. campaign-analytics/ - Multi-touch attribution, funnel conversion analysis, campaign ROI calculation (3 Python tools)

Total Tools: 6 Python automation tools, 9+ knowledge bases, 15+ templates

Python Automation Tools

1. Brand Voice Analyzer (content-creator/scripts/brand_voice_analyzer.py)

Purpose: Analyzes text for formality, tone, perspective, and readability

Features:

• Formality analysis (formal vs casual language patterns)
• Tone detection (professional, conversational, technical)
• Perspective analysis (1st person, 2nd person, 3rd person)
• Readability scoring (Flesch Reading Ease formula)
• Output formats: JSON or human-readable

Usage:

# Basic analysis
python content-creator/scripts/brand_voice_analyzer.py content.txt

# JSON output for integrations
python content-creator/scripts/brand_voice_analyzer.py content.txt json

Output Example:

Brand Voice Analysis Results:
- Formality Score: 65/100 (Semi-formal)
- Tone: Professional with conversational elements
- Perspective: 2nd person (you-focused)
- Readability: 72 (College level)

Implementation Notes:

• Pure Python (standard library only)
• No external API calls or ML models
• Fast local processing (<1 second for typical content)
• Works offline

2. SEO Optimizer (content-creator/scripts/seo_optimizer.py)

Purpose: Comprehensive SEO analysis with actionable recommendations

Features:

• Keyword density analysis (primary + secondary keywords)
• Content structure evaluation (headings, paragraphs, lists)
• Meta tag validation (title, description)
• Readability assessment
• SEO score calculation (0-100)
• Actionable improvement recommendations

Usage:

# Basic SEO analysis
python content-creator/scripts/seo_optimizer.py article.md "primary keyword"

# With secondary keywords
python content-creator/scripts/seo_optimizer.py article.md "primary keyword" "secondary,keywords,here"

# JSON output
python content-creator/scripts/seo_optimizer.py article.md "keyword" --json

Output Example:

SEO Analysis Results:
- Overall SEO Score: 78/100
- Primary Keyword Density: 1.8% (target: 1-2%)
- Secondary Keyword Usage: 5/7 keywords present
- Content Structure: Good (H2, H3 hierarchy)
- Meta Description: Present (145 chars)

Recommendations:
1. Add primary keyword to H2 heading
2. Increase secondary keyword "conversion" usage
3. Add alt text to 2 images

Implementation Notes:

• 419 lines of pure algorithmic analysis
• No LLM calls or external APIs
• CLI-first design for automation
• Supports markdown and HTML input

3. Demand Generation Analyzer (marketing-demand-acquisition/scripts/)

Purpose: Analyze demand generation campaigns and acquisition funnels

Features:

• Campaign performance analysis
• Acquisition channel evaluation
• Conversion funnel metrics
• ROI calculation

Usage:

python marketing-demand-acquisition/scripts/demand_gen_analyzer.py campaign-data.csv

Campaign Analytics Tools

4. Attribution Analyzer (campaign-analytics/scripts/attribution_analyzer.py)

Purpose: Multi-touch attribution modeling across marketing channels

Features:

• Five attribution models (first-touch, last-touch, linear, time-decay, position-based)
• Configurable time-decay half-life
• Per-channel credit allocation and revenue attribution
• Conversion and non-conversion journey analysis

Usage:

python campaign-analytics/scripts/attribution_analyzer.py campaign_data.json
python campaign-analytics/scripts/attribution_analyzer.py campaign_data.json --model time-decay --half-life 14
python campaign-analytics/scripts/attribution_analyzer.py campaign_data.json --format json

5. Funnel Analyzer (campaign-analytics/scripts/funnel_analyzer.py)

Purpose: Conversion funnel analysis with bottleneck detection

Features:

• Stage-to-stage conversion rates and drop-off percentages
• Automatic bottleneck identification (largest absolute and relative drops)
• Overall funnel conversion rate
• Segment comparison when multiple segments provided

Usage:

python campaign-analytics/scripts/funnel_analyzer.py funnel_data.json
python campaign-analytics/scripts/funnel_analyzer.py funnel_data.json --format json

6. Campaign ROI Calculator (campaign-analytics/scripts/campaign_roi_calculator.py)

Purpose: Calculate comprehensive campaign ROI metrics with benchmarking

Features:

• ROI, ROAS, CPA, CPL, CAC calculation
• CTR and conversion rate metrics
• Industry benchmark comparison
• Underperformance flagging

Usage:

python campaign-analytics/scripts/campaign_roi_calculator.py campaign_data.json
python campaign-analytics/scripts/campaign_roi_calculator.py campaign_data.json --format json

Knowledge Bases

Content Creator References

Location: content-creator/references/

1. brand_guidelines.md - Brand voice framework
   • 5 personality archetypes (Expert, Friend, Innovator, Guide, Motivator)
   • Voice characteristics matrix
   • Brand consistency checklist
   • Industry-specific adaptations
2. content_frameworks.md - 15+ content templates
   • Blog post structures (how-to, listicle, case study)
   • Email campaign frameworks
   • Social media content patterns
   • Video script templates
   • Landing page copy structure
3. social_media_optimization.md - Platform-specific best practices
   • LinkedIn: Professional tone, 1,300 chars, hashtag strategy
   • Twitter/X: Concise, 280 chars, thread patterns
   • Instagram: Visual-first, captions, hashtag limits
   • Facebook: Conversational, engagement tactics
   • TikTok: Short-form video, trending sounds

Campaign Analytics References

Location: campaign-analytics/references/

1. attribution-models-guide.md - Deep dive into 5 attribution models with formulas, pros/cons, selection criteria
2. campaign-metrics-benchmarks.md - Industry benchmarks by channel and vertical for CTR, CPC, CPM, CPA, ROAS
3. funnel-optimization-framework.md - Stage-by-stage optimization strategies, common bottlenecks, best practices

User Templates

Content Creator Assets

Location: content-creator/assets/

• Content calendar template
• SEO checklist
• Social media posting schedule
• Content brief template
• Campaign planning worksheet

Usage: Copy template and customize for your needs

Integration Patterns

Pattern 1: Content Quality Workflow

# 1. Create draft content
vim blog-post.md

# 2. Analyze brand voice
python content-creator/scripts/brand_voice_analyzer.py blog-post.md

# 3. Optimize for SEO
python content-creator/scripts/seo_optimizer.py blog-post.md "target keyword"

# 4. Refine based on feedback

# 5. Publish

Pattern 2: Campaign Planning

# 1. Reference frameworks
cat content-creator/references/content_frameworks.md

# 2. Draft campaign content

# 3. Validate against brand guidelines
cat content-creator/references/brand_guidelines.md

# 4. Analyze performance
python marketing-demand-acquisition/scripts/demand_gen_analyzer.py campaign-results.csv

Pattern 3: Campaign Performance Analysis

# 1. Analyze multi-touch attribution
python campaign-analytics/scripts/attribution_analyzer.py journey_data.json

# 2. Identify funnel bottlenecks
python campaign-analytics/scripts/funnel_analyzer.py funnel_data.json

# 3. Calculate campaign ROI
python campaign-analytics/scripts/campaign_roi_calculator.py campaign_data.json

# 4. Document findings using templates
# Reference: campaign-analytics/assets/campaign_report_template.md

Development Commands

# Content analysis
python content-creator/scripts/brand_voice_analyzer.py content.txt
python content-creator/scripts/brand_voice_analyzer.py content.txt json

# SEO optimization
python content-creator/scripts/seo_optimizer.py article.md "main keyword"
python content-creator/scripts/seo_optimizer.py article.md "main keyword" "secondary,keywords"

# Demand generation
python marketing-demand-acquisition/scripts/demand_gen_analyzer.py data.csv

# Campaign analytics
python campaign-analytics/scripts/attribution_analyzer.py campaign_data.json
python campaign-analytics/scripts/funnel_analyzer.py funnel_data.json
python campaign-analytics/scripts/campaign_roi_calculator.py campaign_data.json

Quality Standards

All marketing Python tools must:

• Use standard library only (no external dependencies)
• Support both JSON and human-readable output
• Provide clear error messages
• Return appropriate exit codes
• Process files locally (no API calls)

Roadmap

Current (Phase 1-2): 4 skills deployed

• ✅ Content creator (brand voice + SEO)
• ✅ Demand generation & acquisition
• ✅ Product marketing strategy
• ✅ Campaign analytics (attribution, funnel, ROI)

Phase 3 (Q2 2026): Marketing expansion

• SEO content optimizer (advanced)
• Social media manager (multi-platform)
• Email marketing automation

Phase 4 (Q3 2026): Growth marketing

• Growth hacking frameworks
• Viral content analyzer
• Influencer collaboration tools

See marketing_skills_roadmap.md for detailed expansion plans.

Related Skills

• Product Team: User research, persona generation → ../product-team/
• Engineering: Web analytics integration → ../engineering-team/
• C-Level: Strategic marketing planning → ../c-level-advisor/

Best Practices

1. Brand Consistency - Always reference brand_guidelines.md before creating content
2. SEO-First - Run seo_optimizer.py on all published content
3. Data-Driven - Use analytics to inform content strategy
4. Platform-Specific - Adapt content using social_media_optimization.md guidelines
5. Iterative - Analyze, optimize, republish

Additional Resources

• Marketing Roadmap: marketing_skills_roadmap.md
• Team Overview: README.md
• Main Documentation: ../CLAUDE.md

Last Updated: February 2026 Skills Deployed: 4/4 marketing skills production-ready Total Tools: 6 Python automation tools