Ivx Ams Conversion Ops

Cursor install notes

• Skill root: this folder (scripts + references live here).
• Vendor source: ~/.cursor/skills/_vendor/ai-marketing-skills/ (git pull to update).
• Telemetry is optional; skip telemetry/*.py unless you opt in.
• Run Python from this skill directory so relative paths resolve.
• Prefer python on Windows if python3 is missing.

AI Conversion Ops

Working directory

cd ~/.cursor/skills/ams-conversion-ops
# Windows: cd $env:USERPROFILE\.cursor\skills\ams-conversion-ops

AI-powered conversion rate optimization: landing page audits, CRO scoring, survey segmentation, and lead magnet generation.

When to Use

• User asks for a landing page audit or CRO analysis
• User wants to score a page across conversion dimensions
• User needs to identify conversion bottlenecks on a URL
• User has survey data and wants to segment respondents by pain point
• User wants lead magnet ideas generated from survey responses
• User needs batch CRO analysis across multiple URLs

Tools

CRO Audit (cro_audit.py)

Fetches a landing page and scores it across 8 conversion dimensions. No headless browser needed.

# Single URL audit
python cro_audit.py --url https://example.com/landing-page

# Batch mode — multiple URLs
python cro_audit.py --urls https://example.com/page1 https://example.com/page2

# URLs from a file (one per line)
python cro_audit.py --file urls.txt

# Specify industry for benchmark comparison
python cro_audit.py --url https://example.com --industry saas

# JSON output
python cro_audit.py --url https://example.com --json

# Save report to file
python cro_audit.py --url https://example.com --output report.json

Scoring dimensions (each 0–100):

1. Headline Clarity — Is the value prop obvious in <5 seconds?
2. CTA Visibility — Are CTAs prominent, contrasting, above the fold?
3. Social Proof — Testimonials, logos, case studies, numbers?
4. Urgency — Scarcity, deadlines, limited offers?
5. Trust Signals — Security badges, guarantees, privacy, certifications?
6. Form Friction — How many fields? Is the form intimidating?
7. Mobile Responsiveness — Viewport meta, responsive patterns, touch targets?
8. Page Speed Indicators — Image optimization, script count, resource size?

Overall CRO Score = Weighted average across all 8 dimensions.

Output includes:

• Per-dimension score with specific findings
• Priority fixes ranked by impact
• Before/after suggestions for each issue
• Industry benchmark comparison
• Overall letter grade (A+ through F)

Supported industries: saas, ecommerce, agency, finance, healthcare, education, b2b, general

Survey-to-Lead-Magnet Engine (survey_lead_magnet.py)

Ingests survey CSV data, clusters respondents by pain point, and generates lead magnet briefs for each segment.

# Basic usage — analyze survey CSV
python survey_lead_magnet.py --csv survey_responses.csv

# Specify which columns contain pain points / challenges
python survey_lead_magnet.py --csv survey.csv --pain-columns "biggest_challenge" "top_frustration"

# Limit number of segments
python survey_lead_magnet.py --csv survey.csv --top-segments 5

# JSON output
python survey_lead_magnet.py --csv survey.csv --json

# Save output
python survey_lead_magnet.py --csv survey.csv --output lead_magnets.json

What it produces:

• Pain point clusters with respondent counts
• Segments ranked by size and commercial potential
• For each top segment, a lead magnet brief:
  • Title, format (guide/checklist/template/calculator), hook
  • Content outline (5–7 sections)
  • Target CTA and distribution channel
  • Viral potential score + conversion potential score
• Prioritized implementation roadmap

CSV format: Questions as column headers, one respondent per row. Works with any survey tool export (Typeform, Google Forms, SurveyMonkey, etc.)

Configuration

No API keys required. Both tools work with local analysis only.

Optional environment variables:

Recommended Workflow

1. Weekly: Run cro_audit.py on your top landing pages to track CRO scores over time
2. Post-survey: Run survey_lead_magnet.py to turn survey data into content strategy
3. Pre-launch: Audit new landing pages before driving paid traffic
4. Monthly: Batch audit competitor landing pages to benchmark against

Dependencies

pip install -r requirements.txt