Ai Marketing Claude Suite

AI Marketing Suite for Claude Code

Skill by ara.so — Marketing Skills collection.

This skill enables Claude Code to perform comprehensive marketing analysis, copywriting, competitive intelligence, and automation tasks. It includes 15 specialized marketing skills with parallel subagent execution, automated website analysis, and client-ready PDF report generation.

What This Project Does

AI Marketing Claude is a comprehensive marketing automation suite that:

• Audits websites across 6 marketing dimensions (content, conversion, SEO, competitive, brand, growth)
• Generates marketing copy with before/after optimization examples
• Creates email sequences (welcome, nurture, launch) with full automation
• Builds content calendars for 30-day social media planning
• Analyzes competitors with automated intelligence gathering
• Produces PDF reports suitable for client deliverables
• Scores marketing effectiveness with weighted methodology (0-100)

All functionality is accessible through /market commands in Claude Code.

Installation

One-Command Install

curl -fsSL https://raw.githubusercontent.com/zubair-trabzada/ai-marketing-claude/main/install.sh | bash

Manual Installation

git clone https://github.com/zubair-trabzada/ai-marketing-claude.git
cd ai-marketing-claude
./install.sh

The installer copies skill files to ~/.claude/skills/ and agent definitions to ~/.claude/agents/.

Optional PDF Support

For client-ready PDF reports:

pip install reportlab

Python Dependencies

pip install -r requirements.txt

Required packages:

• requests - HTTP requests for webpage analysis
• beautifulsoup4 - HTML parsing and content extraction
• reportlab - PDF generation (optional)

Core Commands

Usage Patterns

Running a Full Marketing Audit

/market audit https://example.com

This command: 1. Launches 5 parallel subagents (content, conversion, SEO, competitive, strategy) 2. Scores the website across 6 dimensions 3. Generates actionable recommendations 4. Saves output to MARKETING-AUDIT.md

Expected output format:

Launching 5 parallel agents...
✓ Content & Messaging Analysis     — Score: 72/100
✓ Conversion Optimization          — Score: 58/100
✓ SEO & Discoverability            — Score: 81/100
✓ Competitive Positioning          — Score: 64/100
✓ Brand & Trust                    — Score: 76/100
✓ Growth & Strategy                — Score: 61/100

Overall Marketing Score: 69/100

Full report saved to MARKETING-AUDIT.md

Generating Email Sequences

/market emails SaaS product launch

Produces a complete email sequence with:

• Subject lines and preview text
• Email bodies with personalization
• CTAs and timing recommendations
• A/B test variations

Creating Social Media Calendars

/market social AI productivity tools

Generates 30-day content calendar with:

• Daily post ideas
• Platform-specific formatting
• Hashtag recommendations
• Engagement strategies

Competitor Analysis

/market competitors https://example.com

Automated competitive intelligence:

• Identifies top competitors
• Analyzes positioning and messaging
• Extracts pricing strategies
• Maps feature comparisons

Generating Client Proposals

/market proposal "Tech startup needing SEO services"

Creates customized proposal with:

• Executive summary
• Recommended services
• Pricing tiers
• Timeline and deliverables

Python Script Integration

The suite includes Python scripts for automated analysis:

Website Analysis Script

# scripts/analyze_page.py
import requests
from bs4 import BeautifulSoup
import json

def analyze_marketing(url):
    """
    Analyzes a webpage for marketing effectiveness
    Returns structured data for scoring
    """
    response = requests.get(url, headers={
        'User-Agent': 'Mozilla/5.0 (Marketing Analysis Bot)'
    })
    soup = BeautifulSoup(response.content, 'html.parser')
    
    analysis = {
        'headlines': extract_headlines(soup),
        'ctas': extract_ctas(soup),
        'value_props': extract_value_propositions(soup),
        'social_proof': extract_social_proof(soup),
        'seo_elements': extract_seo_elements(soup)
    }
    
    return analysis

Usage from Claude Code:

python scripts/analyze_page.py https://example.com

Competitor Scanner

# scripts/competitor_scanner.py
def scan_competitors(base_url):
    """
    Identifies and analyzes competitor websites
    """
    competitors = discover_competitors(base_url)
    
    reports = []
    for competitor in competitors:
        reports.append({
            'url': competitor,
            'positioning': analyze_positioning(competitor),
            'pricing': extract_pricing(competitor),
            'features': extract_features(competitor)
        })
    
    return reports

Social Calendar Generator

# scripts/social_calendar.py
def generate_calendar(topic, days=30, platforms=['linkedin', 'twitter']):
    """
    Generates social media content calendar
    """
    calendar = []
    
    for day in range(days):
        for platform in platforms:
            post = {
                'day': day + 1,
                'platform': platform,
                'content': generate_post_idea(topic, platform),
                'hashtags': suggest_hashtags(topic, platform),
                'best_time': get_optimal_posting_time(platform)
            }
            calendar.append(post)
    
    return calendar

PDF Report Generator

# scripts/generate_pdf_report.py
from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
from reportlab.lib.styles import getSampleStyleSheet

def generate_pdf(audit_data, output_path='marketing-report.pdf'):
    """
    Generates professional PDF marketing report
    Requires: pip install reportlab
    """
    doc = SimpleDocTemplate(output_path, pagesize=letter)
    story = []
    styles = getSampleStyleSheet()
    
    # Title
    story.append(Paragraph(f"Marketing Audit: {audit_data['url']}", styles['Title']))
    story.append(Spacer(1, 12))
    
    # Overall score
    story.append(Paragraph(f"Overall Score: {audit_data['overall_score']}/100", styles['Heading1']))
    
    # Category scores
    for category, score in audit_data['categories'].items():
        story.append(Paragraph(f"{category}: {score}/100", styles['Heading2']))
        story.append(Paragraph(audit_data['recommendations'][category], styles['BodyText']))
        story.append(Spacer(1, 12))
    
    doc.build(story)
    return output_path

Architecture Overview

Skill Hierarchy

market/SKILL.md                     # Main orchestrator (routes all commands)
├── skills/market-audit/SKILL.md    # Full audit coordination
├── skills/market-copy/SKILL.md     # Copywriting generation
├── skills/market-emails/SKILL.md   # Email sequences
├── skills/market-social/SKILL.md   # Social calendars
└── [11 more specialized skills]

Parallel Subagents

The audit command spawns 5 parallel agents:

1. market-content.md - Analyzes messaging, headlines, value propositions, CTAs 2. market-conversion.md - Reviews funnels, forms, friction points, urgency 3. market-competitive.md - Assesses positioning, differentiation, market awareness 4. market-technical.md - Evaluates SEO, tracking, technical performance 5. market-strategy.md - Examines brand, pricing, growth channels

Each agent returns a structured score and recommendations.

Scoring Methodology

Marketing effectiveness is scored across 6 weighted dimensions:

Overall Score = Weighted average (0-100 scale)

Configuration

Environment Setup

No API keys required — all analysis runs locally or via public web scraping.

For custom configurations, edit skill files:

~/.claude/skills/market/SKILL.md

Custom Templates

Modify marketing templates in the templates/ directory:

templates/
├── email-welcome.md        # Welcome sequence template
├── email-nurture.md        # Lead nurture template
├── email-launch.md         # Product launch template
├── proposal-template.md    # Client proposal structure
├── content-calendar.md     # Content calendar format
└── launch-checklist.md     # Launch playbook structure

Common Workflows

Agency Sales Flow

# 1. Audit prospect's website
/market audit https://prospect.com

# 2. Generate competitive analysis
/market competitors https://prospect.com

# 3. Create proposal
/market proposal "B2B SaaS company needing content marketing"

# 4. Generate PDF report for presentation
/market report-pdf https://prospect.com

Product Launch

# 1. Create launch playbook
/market launch "AI-powered email assistant"

# 2. Generate email sequence
/market emails "Product launch for email assistant"

# 3. Build social calendar
/market social "AI email assistant launch"

# 4. Create ad campaigns
/market ads https://product-landing-page.com

Website Optimization

# 1. Run full audit
/market audit https://mysite.com

# 2. Analyze landing pages
/market landing https://mysite.com/pricing

# 3. Optimize copy
/market copy https://mysite.com

# 4. Check SEO
/market seo https://mysite.com

Troubleshooting

PDF Generation Fails

Problem: /market report-pdf command fails

Solution: Install reportlab

pip install reportlab

Website Analysis Timeout

Problem: Analysis hangs on large websites

Solution: Use /market quick for faster analysis or break into specific commands:

/market seo https://example.com
/market copy https://example.com

Skills Not Found

Problem: Claude doesn't recognize /market commands

Solution: Verify installation

ls -la ~/.claude/skills/market*
ls -la ~/.claude/agents/market-*

Re-run installer if needed:

./install.sh

Python Script Errors

Problem: Python scripts fail with import errors

Solution: Install all dependencies

pip install -r requirements.txt

For specific scripts:

pip install requests beautifulsoup4 reportlab

Competitor Analysis Returns Empty

Problem: No competitors found

Solution: Manually specify competitor URLs:

# Edit scripts/competitor_scanner.py
MANUAL_COMPETITORS = [
    'https://competitor1.com',
    'https://competitor2.com'
]

Uninstallation

Remove all marketing skills:

./uninstall.sh

Or manually:

rm -rf ~/.claude/skills/market*
rm -f ~/.claude/agents/market-*.md

Best Practices

For Accurate Audits

• Use full URLs including https://
• Ensure target website is publicly accessible
• Run audits on primary landing pages, not deep subpages

For Email Sequences

• Be specific with topic (e.g., "SaaS trial to paid conversion" not "emails")
• Specify audience segment when possible
• Request specific sequence length (5, 7, or 10 emails)

For Client Deliverables

• Always generate PDF reports for professional presentation
• Combine multiple analyses (audit + competitors + proposal)
• Customize templates before generation

For Best Results

• Run multiple specific commands rather than one generic command
• Use /market quick first, then deep-dive with specific skills
• Save all outputs before re-running analyses