conversion-ops
ericosiu/ai-marketing-skills/conversion-ops/SKILL.md
Privacy: This skill logs usage locally to ~/.ai-marketing-skills/analytics/. Remote telemetry is opt-in only. No code, file paths, or repo content is ever collected. See telemetry/README.md. AI-powered conversion rate optimization: landing page audits, CRO scoring, survey segmentation, and lead magnet generation. Fetches a landing page and scores it across 8 conversion dimensions. No headless browser needed. Scoring dimensions (each 0–100): 1. Headline Clarity — Is the value prop obvious in <5 seconds? 2. CTA Visibility — Are CTAs prominent, contrasting, above…
- Installs packages
What's in it
- AI Conversion Ops
- Preamble (runs on skill start)
- When to Use
- Tools
- CRO Audit (croaudit.py)
- Survey-to-Lead-Magnet Engine (surveyleadmagnet.py)
- Configuration
- Recommended Workflow
- Dependencies
# AI Conversion Ops ## Preamble (runs on skill start) ```bash # Version check (silent if up to date) python3 telemetry/version_check.py 2>/dev/null || true # Telemetry opt-in (first run only, then remembers your choice) python3 telemetry/telemetry_init.py 2>/dev/null || true ``` > **Privacy:** This skill logs usage locally to `~/.ai-marketing-skills/analytics/`. Remote telemetry is opt-in only. No code, file paths, or repo content is ever collected. See `telemetry/README.md`. --- 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. ```bash # 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. ```bash # 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: | Variable | Required | Description | |----------|----------|-------------| | `USER_AGENT` | No | Custom user agent for page fetching (default provided) | | `REQUEST_TIMEOUT` | No | HTTP timeout in seconds (default: 15) | ## 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 ```bash pip install -r requirements.txt ```
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