Run a section-by-section CRO teardown on a single landing page. Scores hero, value prop, social proof, features, objections, CTA, and footer; audits forms, mobile, and page speed; outputs prioritized fixes (quick wins / strategic / long-term) and A/B test hypotheses to a client-ready markdown report. Activates on phrases like "CRO review", "landing page audit", "improve my conversion rate", "/market landing acme.com/signup".
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Run a section-by-section CRO teardown on a single landing page. Scores hero, value prop, social proof, features, objections, CTA, and footer; audits forms, mobile, and page speed; outputs prioritized fixes (quick wins / strategic / long-term) and A/B test hypotheses to a client-ready markdown report. Activates on phrases like "CRO review", "landing page audit", "improve my conversion rate", "/market landing acme.com/signup".
version
1.0.0
author
Wayland Business Pack (port of zubair-trabzada/ai-marketing-claude)
Standalone CRO teardown for a single landing page. Produces a section-by-section score, prioritized fixes, and A/B test hypotheses. Unlike market-audit, this skill does not fan out - it runs end-to-end in the parent and writes one report.
When to Use
User supplies a landing-page URL and asks for conversion optimization, CRO review, or signup-rate help
Slash: /market-landing <url> or /market landing <url> (via market orchestrator)
After /market-audit if the funnel dimension flagged the landing page as the bottleneck
When NOT to Use
Whole-site audit across many pages - use market-audit
Copy-only rewrite without conversion-mechanic analysis - use market-copy
Full funnel (ad → landing → email → checkout) - use market-funnel
Authoring a fresh sales/squeeze/OTO/landing page from a brief - use /convert <page-type> (business-conversion pack). market-landing audits existing pages; convert-pack authors fresh ones.
Inputs
<url> - required. Bare domains are normalized to https://<url>.
Prefer web_extract for the readable text + visible CTAs. If the analysis needs raw HTML for above-the-fold structure, form field counts, button colors, or <meta> tags, use terminal + curl, then parse with analyze_page.py (shared with market-audit):
curl -L --max-filesize 200000 -A "Wayland-CRO-Bot/1.0" \
-o .wayland/tmp/landing-<slug>.html "<url>"
Pricing transparency (no hidden fees or surprise costs)
Security and privacy indicators where relevant
Comparison with alternatives (if applicable)
Section 6 - Call-to-Action (weight 10%)
CTA button checklist:
CTA text describes the VALUE, not the action ("Get My Free Report" vs "Submit")
CTA button is visually dominant (size, color, whitespace)
CTA appears multiple times on long pages
Secondary CTA exists for visitors not ready to commit
CTA has supporting microcopy (e.g., "No credit card required")
Button text uses first person ("Start MY trial" vs "Start YOUR trial")
CTA is specific to the offer (not generic)
CTA copy scoring:
Weak: "Submit", "Click Here", "Learn More"
Medium: "Sign Up", "Get Started", "Download Now"
Strong: "Start My Free Trial", "Get My Custom Report", "Claim Your Discount"
Section 7 - Footer and Secondary Elements (weight 5%)
Checklist:
Final CTA present at bottom of page
Contact information or support options visible
Privacy policy and terms of service linked
Trust badges repeated near final CTA
No competing links that lead away from conversion
Copyright and legal information present
Social media links (only if they support conversion, not distract)
Step 4 - Copy scoring
Score the overall page copy on 5 dimensions (1-10 each):
Clarity - Can a visitor understand the offer in 5 seconds?
Urgency - Is there a reason to act NOW vs later?
Specificity - Are claims concrete with numbers, timeframes, outcomes?
Proof - Are claims backed by evidence, data, or testimonials?
Action Orientation - Does the copy drive toward a specific next step?
Copy Score = average of the 5 dimensions × 10 (out of 100).
Step 5 - Form optimization audit
If the page has a form:
Element
Best Practice
Field count
Every additional field reduces conversion ~7%. Lead capture: 3-5 fields max.
Labels
Use inline labels or floating labels. Avoid placeholder-only labels.
Button text
Match the value proposition. "Get My Free Guide" > "Submit".
Error handling
Inline validation. Specific error messages. Don't clear the entire form on error.
Multi-step
Break long forms into steps with progress indicator.
Required vs optional
Mark optional fields, not required ones.
Auto-fill
Enable browser auto-fill for standard fields.
Field types
Use appropriate input types (email, tel, url) for mobile keyboards.
Step 6 - Mobile responsiveness audit
Mobile is 60%+ of web traffic. Check:
CTA is thumb-reachable (bottom half of screen)
Text is readable without zooming (16px minimum body text)
Forms are usable on mobile (large tap targets, appropriate keyboards)
Images resize properly and don't break layout
No horizontal scrolling required
Page loads under 3 seconds on 4G
Click-to-call for phone numbers
Sticky CTA bar on scroll (if applicable)
Step 7 - Page speed impact
Conversion impact benchmarks:
Load Time
Conversion Impact
0-2 seconds
Baseline (optimal)
2-3 seconds
-7% conversion rate
3-5 seconds
-20% conversion rate
5-8 seconds
-35% conversion rate
8+ seconds
-50%+ conversion rate
Common speed issues to flag: unoptimized images (use WebP, lazy loading), render-blocking JavaScript, missing browser caching, no CDN, excessive third-party scripts, unminified CSS/JS.
Step 8 - A/B test hypotheses
Format each test as: "If we [CHANGE], then [METRIC] will [IMPROVE/INCREASE] because [REASON]."
Candidate tests: headline variations (benefit vs outcome), CTA color and text, social-proof placement (above vs below fold), form field count (-1/-2 fields), hero image vs hero video, long-form vs short-form, urgency elements (countdown, limited spots), price anchoring, testimonial format (text vs video), chatbot/live chat.
Step 9 - Heat-map interpretation guidance (no real data required)
Expected attention zones based on page layout
F-pattern vs Z-pattern reading based on content density
Scroll-depth predictions based on page length and content breaks
Click-probability zones based on visual hierarchy
Rage-click indicators (elements that look clickable but aren't)
Dead zones where content may be ignored
Output
Write to out_path (default .wayland/business-marketing/<ts>-landing-<slug>.md). Required sections, in order:
Header - URL, date, page type, Overall CRO Score: X/100, estimated current CR range, realistic target CR range
Executive summary (3-5 sentences: score, biggest strength, biggest gap, top 3 fixes by impact-to-effort)
Section-by-section analysis - one block per Step-3 section with [Score: X/10, Weight: N%], Findings, and Fixes (HIGH/MEDIUM/LOW)
Page speed (observed indicators + bucket from Step-7 table)
A/B test recommendations (3+ hypotheses in the "If…then…because" template)
Prioritized fix list - Quick Wins (this week), Medium-Term (this month), Strategic (this quarter), each with expected impact
Before/after wireframe notes (text wireframe of current vs recommended above-the-fold layout)
Footer: *Generated by Wayland market-landing. Source: zubair-trabzada/ai-marketing-claude (MIT).*
Key Principles
Tie recommendations to revenue impact. Don't just say "change the button color" - say "changing the CTA to a contrasting color typically increases clicks 15-30%, which at your current traffic could mean X more conversions per month." Only attach dollar figures the user supplies; never fabricate.
Prioritize by effort-to-impact ratio. Quick wins first.
Be specific. "Improve your headline" is useless. "Change 'Welcome to Our Platform' to 'Cut Your Reporting Time by 75% - Automated Analytics for Growth Teams' because it adds specificity, a quantified benefit, and targets a specific audience" is actionable.
Reference industry benchmarks so the client knows where they stand against the page-type table above.
If /market-audit already ran for this domain, read its MARKETING-AUDIT.md and incorporate the funnel-dimension findings - don't duplicate work.
Pitfalls
web_extract summarizes pages > 5000 chars. For above-the-fold checks, button colors, form field counts, or meta-tag analysis, use terminal + curl + analyze_page.py instead.
Don't invent CR numbers. The page-type table is for benchmarking; estimate the user's current CR only as a range, and only when the page signals (form length, friction, social proof depth) clearly bracket it.
Don't fabricate revenue lift. Express impact qualitatively (high/medium/low) unless the user supplies traffic + AOV.
Auth-gated pages: if signin is required, note the gap and audit only the public hero/CTA.
Single-page scope: do not crawl beyond the supplied URL. Multi-page audits belong to market-audit.
