Agent skill

Conversion Rate Optimizer

by FerroxLabs in FerroxLabs/wayland

Systematic CRO methodology covering conversion audits, hypothesis generation, A/B and multivariate testing, heatmap and session recording analysis, user research techniques, landing page…

Apache-2.0Auto-check passedMarketing & SEO

Install Conversion Rate Optimizer

skills CLI
$ npx skills add FerroxLabs/wayland --skill conversion-rate-optimizer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install FerroxLabs/wayland conversion-rate-optimizer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/FerroxLabs/wayland.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src/process/resources/skills-library/bodies/skills/marketing-sales/conversion-rate-optimizer .claude/skills/conversion-rate-optimizer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
conversion-rate-optimizer
GitHub stars
608
Token cost
~3.8k tokens
SKILL.md length
577 words
Files
1
Skills in repo
1,194
Repo updated
First seen
Licence
Apache-2.0

At a glance

Systematic CRO methodology covering conversion audits, hypothesis generation, A/B and multivariate testing, heatmap and session recording analysis, user research techniques, landing page…

  • Works in 4 steps: Data Collection and Audit → Hypothesis Generation → Test Design → …
  • The user asks about conversion rate optimizer
  • SKILL.md covers When to Use, Process, Questions to Ask First and The CRO Process, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Conversion Rate Optimizer is an agent skill from FerroxLabs/wayland. Systematic CRO methodology covering conversion audits, hypothesis generation, A/B and multivariate testing, heatmap and session recording analysis, user research techniques, landing page optimization, funnel analysis, and statistical significance for data-driven growth. Use when the user asks about conversion rate optimizer or needs help with related topics. Do NOT use for unrelated domains or when a more specialized skill exists.

Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Conversion rate optimization. The repository describes itself as: Wayland - The AI Agent That Perceives. Reasons. Acts. Evolves. The licence is Apache-2.0.

When your agent uses it

  • The user asks about conversion rate optimizer
  • Needs help with related topics
  • Unrelated domains
  • A more specialized skill exists

Example prompts

  • “/conversion-rate-optimizer”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Data Collection and Audit
  2. Hypothesis Generation
  3. Test Design
  4. Analysis and Learning

What it can do on your machine

Read from SKILL.md and the folder at commit 4c030c7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Conversion Rate Optimizer loads about 3.8k tokens when it runs. Until then it costs about 115 tokens; SKILL.md has 577 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~115
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from FerroxLabs/wayland at commit 4c030c7, republished under its Apache-2.0 licence (© FerroxLabs). 577 words, ~3,809 tokens.

Download SKILL.mdSave it as .claude/skills/conversion-rate-optimizer/SKILL.md (or your agent's skills folder).
name
conversion-rate-optimizer
description
Systematic CRO methodology covering conversion audits, hypothesis generation, A/B and multivariate testing, heatmap and session recording analysis, user research techniques, landing page optimization, funnel analysis, and statistical significance for data-driven growth. Use when the user asks about conversion rate optimizer or needs help with related topics. Do NOT use for unrelated domains or when a more specialized skill exists.
license
Apache-2.0
metadata.author
foundry-skills
metadata.version
1.0.0
metadata.tags
marketing seo analysis
metadata.category
marketing-sales
metadata.subcategory
marketing
metadata.disclaimer
none
metadata.difficulty
intermediate

Conversion Rate Optimizer

When to Use

Process

  1. Gather requirements. Ask the user clarifying questions about their specific context, goals, constraints, and experience level.

  2. Analyze the situation. Review the information provided and identify key factors, challenges, and opportunities relevant to conversion rate optimizer.

  3. Develop the framework. Create a structured approach tailored to the user's needs, incorporating best practices and domain-specific considerations.

  4. Deliver actionable output. Present specific, implementable recommendations with clear rationale, timelines, and success criteria.

  5. Address edge cases. Proactively identify potential issues, alternative approaches, and contingency plans.

Use this skill when:

  • User needs guidance on conversion rate optimizer
  • User asks about conversion rate optimizer best practices or techniques
  • User wants a structured approach to conversion rate optimizer

Do NOT use this skill when:

  • A more specialized skill exists for the specific subtopic
  • The request is outside the scope of conversion rate optimizer

You are a conversion rate optimization specialist who treats CRO as an applied science, not guesswork. Every recommendation is grounded in data, user research, and validated through controlled experiments. You understand that a 1% conversion rate improvement can mean millions in revenue, and you know how to find those improvements systematically.

Questions to Ask First

  1. What is the primary conversion you want to optimize? (Purchase, sign-up, lead form, trial start)
  2. What is your current conversion rate and baseline traffic?
  3. What analytics tools are you using? (GA4, Mixpanel, Amplitude, Heap)
  4. Do you have heatmap/session recording tools? (Hotjar, FullStory, Microsoft Clarity)
  5. What A/B testing platform are you on or considering? (Optimizely, VWO, Google Optimize successor, custom)
  6. What is your average monthly unique visitor count to the pages being optimized?
  7. Have you run A/B tests before? What were the results?
  8. What does your conversion funnel look like? (Steps from landing to conversion)
  9. What is the dollar value of a conversion? (Revenue per conversion, or LTV)
  10. What are your top 3 hypotheses for why visitors are not converting?

The CRO Process

Step 1: Data Collection and Audit
QUANTITATIVE DATA (what is happening):
  Analytics audit:
  - [ ] Funnel visualization: Map every step from entry to conversion
  - [ ] Drop-off analysis: Where do visitors leave? What % at each step?
  - [ ] Device breakdown: Mobile vs desktop conversion rates
  - [ ] Traffic source analysis: Conversion rate by channel
  - [ ] Page speed: Load time per page (target: < 3 seconds)
  - [ ] Error tracking: 404s, JS errors, form errors
  - [ ] Search queries: What are visitors searching for on-site?

  Heatmap and recording analysis:
  - [ ] Click maps: Where do visitors click? (Including rage clicks)
  - [ ] Scroll maps: How far do visitors scroll? (Where do they stop?)
  - [ ] Session recordings: Watch 50+ sessions per key page
  - [ ] Form analytics: Which fields cause abandonment?

QUALITATIVE DATA (why it is happening):
  - [ ] Customer surveys: Post-purchase and exit surveys
  - [ ] User interviews: 5-10 interviews with target customers
  - [ ] Support tickets: Common complaints and confusion points
  - [ ] Review mining: What do customers say in reviews?
  - [ ] Competitor analysis: What are competitors doing differently?
  - [ ] Usability testing: 5 users attempt the key task while narrating

DATA SYNTHESIS TEMPLATE:
  Page: [URL]
  Traffic: [monthly uniques]
  Current conversion rate: [X]%
  Top drop-off point: [step/element]
  Primary friction: [what is blocking conversion]
  User quote: "[actual user feedback]"
  Hypothesis: [what you believe will fix it and why]
Step 2: Hypothesis Generation
HYPOTHESIS FORMAT:
  "Based on [data/observation], I believe that [change]
   will cause [metric] to [increase/decrease] because [reason]."

EXAMPLE:
  "Based on session recordings showing 40% of mobile users abandon
   the checkout at the address form, I believe that adding address
   autocomplete will increase mobile checkout completion by 15%
   because it reduces typing friction on small screens."

PRIORITIZATION FRAMEWORK (PIE):
  Potential: How much improvement is possible? (1-10)
  Importance: How valuable is the traffic to this page? (1-10)
  Ease: How easy is it to implement and test? (1-10)
  PIE Score = (Potential + Importance + Ease) / 3

HYPOTHESIS BACKLOG:
  | # | Hypothesis           | Potential | Importance | Ease | PIE  | Status  |
  |---|----------------------|-----------|------------|------|------|---------|
  | 1 | [hypothesis]         | [1-10]    | [1-10]     | [1-10]| [avg]| Backlog |
  | 2 | [hypothesis]         | [1-10]    | [1-10]     | [1-10]| [avg]| Testing |
  | 3 | [hypothesis]         | [1-10]    | [1-10]     | [1-10]| [avg]| Won     |

Run tests in PIE score order. Always have 2-3 tests in queue.
Step 3: Test Design
A/B TEST DESIGN TEMPLATE:
  Test name: [descriptive name]
  Hypothesis: [from backlog]
  Page(s): [URL(s)]
  Metric: Primary [conversion rate] | Secondary [AOV, bounce rate]
  Variants:
    Control (A): [current experience]
    Variant (B): [proposed change]
  Traffic split: 50/50
  Minimum sample size: [calculated, see below]
  Estimated duration: [days]
  Exclusions: [returning visitors, specific segments, bots]

SAMPLE SIZE CALCULATION:
  Required inputs:
    Baseline conversion rate: [X]%
    Minimum detectable effect (MDE): [X]% relative improvement
    Statistical significance: 95% (standard)
    Statistical power: 80% (standard)

  RULE OF THUMB:
    For a 5% baseline with 10% relative MDE (5.0% -> 5.5%):
    ~30,000 visitors per variant needed.

    For a 2% baseline with 20% relative MDE (2.0% -> 2.4%):
    ~16,000 visitors per variant needed.

  Use an online calculator (Evan Miller, Optimizely) for exact numbers.
  DO NOT end tests early because results "look good."

COMMON TESTING MISTAKES:
  - Ending tests before reaching sample size (false positives)
  - Testing too many variants with too little traffic
  - Not accounting for weekday/weekend differences (run full weeks)
  - Testing cosmetic changes instead of addressing real friction
  - Not segmenting results post-test (mobile vs desktop)
Show full SKILL.md (230 more words)Show less
Step 4: Analysis and Learning
POST-TEST ANALYSIS:
  Test name: [name]
  Duration: [X days]
  Sample size: [per variant]
  Statistical significance: [X]%

  Results:
    Control: [X]% conversion ([confidence interval])
    Variant: [X]% conversion ([confidence interval])
    Relative lift: [+/-X]%
    Revenue impact: $[estimated annual impact]

  Verdict: [Winner / Loser / Inconclusive]

  SEGMENTED ANALYSIS (always check these):
    By device: Did the variant win on mobile AND desktop?
    By traffic source: Did it win across all channels?
    By new vs returning: Did behavior differ?
    By browser: Any technical issues?

  LEARNING:
    What did we learn about our users from this test?
    [Always document the insight, even if the test lost]

  NEXT STEPS:
    If winner: Implement permanently. Design iteration test.
    If loser: Analyze why. Update hypothesis. Design new test.
    If inconclusive: Increase sample size or test a bolder change.

Landing Page Optimization

The Conversion-Focused Landing Page Framework
ABOVE THE FOLD (0-2 seconds):
  1. HEADLINE: Clear value proposition. What do you get?
     Formula: "[Achieve outcome] without [pain point]"
     or "[Number] [audience] use [product] to [result]"
  2. SUBHEADLINE: How does it work? (One sentence)
  3. HERO IMAGE/VIDEO: Show the product in use or the outcome
  4. PRIMARY CTA: One clear action. Button with action verb.
     "Start Free Trial" not "Submit"
     "Get Your Report" not "Download"
  5. TRUST INDICATOR: Logo bar, "Trusted by X companies," or rating

BELOW THE FOLD:
  6. PROBLEM AGITATION: Remind them why they are here
  7. SOLUTION: How your product/service solves the problem
  8. SOCIAL PROOF: Testimonials, case studies, numbers
  9. FEATURES/BENEFITS: 3-4 key benefits with supporting details
  10. OBJECTION HANDLING: FAQ or common concerns addressed
  11. SECONDARY CTA: Repeat the primary CTA
  12. RISK REVERSAL: Guarantee, free trial, money-back promise

CRITICAL RULES:
  - One page, one goal, one CTA (repeated, not multiple different CTAs)
  - Remove navigation on dedicated landing pages
  - Match message to ad copy (scent trail)
  - Mobile-first design (60%+ of traffic is mobile)
  - Page load under 3 seconds (every second costs ~7% conversions)
Form Optimization
FORM FRICTION REDUCTION:
  - Every field you remove increases conversion by ~5-10%
  - Only ask for what you need at THIS stage
  - Use smart defaults and auto-detection (country, state)
  - Inline validation (immediate feedback, not after submit)
  - Progress indicators for multi-step forms
  - Save progress for long forms
  - Explain WHY you need sensitive information

FORM FIELD PRIORITY:
  Essential: Email address (minimum viable capture)
  High value: First name (enables personalization)
  Medium value: Company, role (enables segmentation)
  Low value: Phone (high friction, low completion impact)
  Avoid: Anything you can look up or infer later

MULTI-STEP FORM STRATEGY:
  Step 1: Low-friction question (email, or "What describes you best?")
  Step 2: Medium-friction (name, company)
  Step 3: Higher-friction (phone, budget, timeline)
  Each step shows progress and allows backward navigation.
  Conversion drops at each step, but qualified leads improve.

Funnel Analysis

Funnel Mapping
E-COMMERCE FUNNEL:
  Landing page -> Product page -> Add to cart -> Cart page ->
  Checkout (info) -> Checkout (shipping) -> Checkout (payment) -> Confirmation

  Benchmark drop-offs:
    Landing to product: 40-60% continue
    Product to add-to-cart: 10-20% add
    Add-to-cart to checkout: 30-50% proceed
    Checkout to purchase: 50-70% complete
    Overall: 1-4% of visitors purchase

SAAS FUNNEL:
  Landing page -> Pricing page -> Sign-up -> Onboarding step 1 ->
  Onboarding step 2 -> Activation (key action) -> Conversion (paid)

  Benchmark drop-offs:
    Landing to pricing: 20-40% continue
    Pricing to sign-up: 10-30% sign up
    Sign-up to activation: 20-50% activate
    Activation to paid: 10-30% convert
    Overall: 1-5% of visitors become paying

OPTIMIZATION PRIORITY:
  Fix the biggest drop-off first.
  A 10% improvement at the highest-volume step has more impact
  than a 50% improvement at a low-volume step.

User Research for CRO

Quick-Win Research Methods
METHOD 1: EXIT SURVEY (5 minutes to set up)
  Trigger: When visitor moves mouse to close tab (exit intent)
  Question: "What stopped you from [converting] today?"
  Options:
    - Price is too high
    - Not sure this is right for me
    - Need to compare other options
    - Missing information I need
    - Technical issue
    - Other: [free text]
  Target: 100+ responses for actionable patterns.

METHOD 2: POST-CONVERSION SURVEY
  Trigger: Immediately after purchase/sign-up
  Question: "What almost stopped you from [converting] today?"
  This surfaces objections that ALMOST prevented conversion.
  These are your optimization goldmines.

METHOD 3: FIVE-SECOND TEST
  Show a user your landing page for 5 seconds. Remove it.
  Ask: "What does this company do?"
  Ask: "What is the main action you should take?"
  If they cannot answer, your messaging is unclear.
  Run with 10-20 users. Free tools: UsabilityHub, Maze.

METHOD 4: SESSION RECORDING REVIEW
  Watch 50 sessions on your key conversion page.
  Tally: Rage clicks, scroll-backs, form field hesitation,
  unexpected navigation patterns.
  Pattern with 5+ occurrences = optimization opportunity.

Statistical Rigor

Avoiding False Positives
RULES FOR HONEST TESTING:
  1. Calculate sample size BEFORE starting the test
  2. Set test duration BEFORE starting (minimum 1 full business cycle)
  3. Do not peek at results and stop early if they look good
  4. Use sequential testing methods if you must peek (Bayesian or alpha-spending)
  5. Report confidence intervals, not just p-values
  6. Run winning tests for an additional week to confirm stability
  7. Account for multiple comparisons if testing 3+ variants
  8. Segment results AFTER the test, not to find significance
  9. Check for Sample Ratio Mismatch (SRM) -- if traffic split is not
     close to 50/50, the test infrastructure has a problem
  10. When in doubt, call it inconclusive and run a bigger test

Output Checklist

  • Quantitative data audit completed (analytics, heatmaps, recordings)
  • Qualitative research conducted (surveys, interviews, usability tests)
  • Hypothesis backlog created and prioritized with PIE framework
  • Sample size calculated for primary test
  • Test design documented with variants, metrics, and duration
  • Landing page audited against conversion framework
  • Form fields minimized to essential information only
  • Funnel mapped with drop-off percentages at each step
  • Statistical rigor checklist followed for test analysis
  • Learning documented regardless of test outcome

Output Format

Deliver the response as a structured document with clear headings and actionable content. Use tables for comparisons, numbered lists for sequential steps, and bullet points for options. Include specific examples where applicable.

[Conversion Rate Optimizer deliverable]
1. Context and objectives
2. Analysis or framework
3. Specific recommendations with rationale
4. Action items with timeline

Example

Input: "Help me with conversion rate optimizer for a mid-size project."

Output: A complete conversion rate optimizer framework tailored to the specific context, with actionable steps, relevant considerations, and measurable outcomes.

Edge Cases

  • Incomplete information: Ask clarifying questions before proceeding rather than making assumptions
  • Conflicting requirements: Identify trade-offs explicitly and present options with pros and cons
  • Scale mismatch: Adapt recommendations to match the user's context (individual vs. team vs. organization)
  • Domain crossover: When the request overlaps with other skill domains, address what falls within scope and reference specialized skills for the rest

© FerroxLabs, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in src/process/resources/skills-library/bodies/skills/marketing-sales/conversion-rate-optimizer of FerroxLabs/wayland.

Open the folder on GitHubat commit 4c030c7

Compare with similar skills

Conversion Rate Optimizer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Conversion Rate Optimizer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Conversion Rate Optimizer this skillFerroxLabs/wayland608—~3.8kAutomated safety check: PassApache-2.0
FLOW SEO FrameworkAgriciDaniel/claude-seo18k2 repos~1.4kAutomated safety check: PassMIT
Onboarding Crofreekmurze/dotfiles1k15 repos~1.6kAutomated safety check: PassNone
Google Analyticsthatrebeccarae/claude-marketing1624 repos~1.3kAutomated safety check: NotesMIT
Paywall Upgrade Crofreekmurze/dotfiles1k14 repos~1.4kAutomated safety check: PassNone
Revenue Centric Designheliocosta-dev/revenue-centric-design740—~1.6kAutomated safety check: PassCustom licence

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Categories

Questions about Conversion Rate Optimizer

What does Conversion Rate Optimizer do?

Systematic CRO methodology covering conversion audits, hypothesis generation, A/B and multivariate testing, heatmap and session recording analysis, user research techniques, landing page…. Conversion Rate Optimizer is an agent skill from FerroxLabs/wayland. Systematic CRO methodology covering conversion audits, hypothesis generation, A/B and multivariate testing, heatmap and session recording analysis, user research techniques, landing page optimization, funnel analysis, and statistical significance for data-driven growth.

When should I use Conversion Rate Optimizer?

Conversion Rate Optimizer fits situations like: the user asks about conversion rate optimizer; needs help with related topics; unrelated domains; A more specialized skill exists.

How do I install Conversion Rate Optimizer in Claude Code?

Run `npx skills add FerroxLabs/wayland --skill conversion-rate-optimizer -a claude-code`. Or copy the skill folder (src/process/resources/skills-library/bodies/skills/marketing-sales/conversion-rate-optimizer in FerroxLabs/wayland) into .claude/skills/conversion-rate-optimizer in your project. Claude Code loads it when a task matches its description.

How do I install Conversion Rate Optimizer in Codex?

Run `npx skills add FerroxLabs/wayland --skill conversion-rate-optimizer -a codex`. Or copy the skill folder (src/process/resources/skills-library/bodies/skills/marketing-sales/conversion-rate-optimizer in FerroxLabs/wayland) into .agents/skills/conversion-rate-optimizer in your project. Codex loads it when a task matches its description.

Can I use Conversion Rate Optimizer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add FerroxLabs/wayland --skill conversion-rate-optimizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/conversion-rate-optimizer, .gemini/skills/conversion-rate-optimizer, .github/skills/conversion-rate-optimizer and .opencode/skills/conversion-rate-optimizer in your project.

What does Conversion Rate Optimizer need to run?

SKILL.md names no scripts, command-line tools or credentials: Conversion Rate Optimizer is instructions for the agent only.

Does Conversion Rate Optimizer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Conversion Rate Optimizer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Conversion Rate Optimizer use?

Conversion Rate Optimizer is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Conversion Rate Optimizer use?

About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Conversion Rate Optimizer?

Skills that share tags, products or a category with Conversion Rate Optimizer: FLOW SEO Framework (AgriciDaniel/claude-seo, 18k stars), Onboarding Cro (freekmurze/dotfiles, 1k stars), Google Analytics (thatrebeccarae/claude-marketing, 162 stars) and Paywall Upgrade Cro (freekmurze/dotfiles, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Conversion Rate Optimizer?

FerroxLabs (a GitHub user) maintains it in FerroxLabs/wayland, which has 608 GitHub stars. The repository holds 1,194 skills in this directory. The repository was last updated on October 6, 2026.

Source: FerroxLabs/wayland on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.