Agent Skillsmohitagw15856/pm-claude-skills › conversion-rate-optimization

conversion-rate-optimization

GitHub

审计落地页或转化漏斗,诊断摩擦点,生成基于ICE优先级的CRO测试计划。包含启发式审计、假设设计、样本量计算及测量护栏,确保数据驱动的转化优化。

exports/openclaw/conversion-rate-optimization/SKILL.md mohitagw15856/pm-claude-skills

Trigger Scenarios

改进转化率 审计落地页/注册页/结账页 减少漏斗流失 规划页面A/B测试

Install

npx skills add mohitagw15856/pm-claude-skills --skill conversion-rate-optimization -g -y
More Options

Non-standard path

npx skills add https://github.com/mohitagw15856/pm-claude-skills/tree/main/exports/openclaw/conversion-rate-optimization -g -y

Use without installing

npx skills use mohitagw15856/pm-claude-skills@conversion-rate-optimization

指定 Agent (Claude Code)

npx skills add mohitagw15856/pm-claude-skills --skill conversion-rate-optimization -a claude-code -g -y

安装 repo 全部 skill

npx skills add mohitagw15856/pm-claude-skills --all -g -y

预览 repo 内 skill

npx skills add mohitagw15856/pm-claude-skills --list

SKILL.md

Frontmatter
{
    "name": "conversion-rate-optimization",
    "homepage": "https:\/\/mohitagw15856.github.io\/pm-claude-skills\/skill\/conversion-rate-optimization.html",
    "metadata": {
        "openclaw": {
            "emoji": "📈"
        }
    },
    "description": "Audit a landing page or funnel step and produce a prioritised CRO test plan. Use when asked to improve conversion rate, audit a landing\/signup\/checkout page, reduce funnel drop-off, or plan A\/B tests for a page. Produces a CRO plan — a heuristic conversion audit, the diagnosed friction, prioritised test hypotheses (ICE), test designs with sample-size math, and the measurement guardrails."
}

Conversion Rate Optimization Skill

CRO is not "make the button green" — it's systematically removing the friction and doubt between a visitor and the action. This skill audits a page against conversion heuristics, diagnoses the biggest blockers, and turns them into prioritised, properly-powered tests — so you change conversion on purpose, with evidence, not by redesign-by-opinion.

Required Inputs

Ask for these only if they aren't already provided:

  • The page/step & its one goal — the single action it should drive (signup, purchase, demo).
  • Current performance — conversion rate and traffic volume (volume decides whether A/B testing is even viable).
  • The audience & their intent — where they come from and how warm they are.
  • Known data — analytics, session recordings, or survey signals on where people drop or hesitate.

Output Format

CRO Plan: [page/step]

1. Conversion audit — score the page against the core heuristics, each with the specific issue found:

  • Clarity — is the value proposition and next action instantly obvious?
  • Relevance — does it match the source/ad/intent that brought them?
  • Motivation — are benefits and proof (social proof, results) present at the decision point?
  • Friction — form length, steps, load speed, cognitive load.
  • Anxiety — trust signals, risk reversal (guarantee, "no card needed"), privacy.
  • Distraction — competing CTAs and links pulling away from the one goal.

2. Diagnosis — the top 2–3 conversion blockers, ranked by likely impact (grounded in the data, not taste).

3. Test backlog — each blocker as a hypothesis, scored (ICE):

Hypothesis ("If we ___, conversion will ___ because ___") Heuristic Impact Confidence Ease ICE

4. Test designs (top 2–3) — the variant, primary metric + guardrails (e.g. don't lift signups while tanking paid conversion), and the sample size & duration needed to detect the expected lift. If traffic is too low for A/B significance, say so and recommend sequential/qualitative methods instead.

5. Measurement — how it's tracked, the significance threshold set before running, and the decision rule (ship / iterate / revert).

Quality Checks

  • The audit cites a specific issue per heuristic, not a generic checklist tick
  • Test ideas are hypotheses tied to a diagnosed blocker, prioritised by ICE
  • Each test states the sample size/duration to detect the expected lift
  • Low-traffic reality is acknowledged — A/B testing is only recommended when volume supports it
  • Guardrail metrics prevent a local conversion win that harms downstream value

Anti-Patterns

  • Do not test trivial cosmetics (button colour) before fixing clarity, friction, and anxiety — the big levers
  • Do not A/B test on traffic too low to ever reach significance — use qualitative research or sequential changes instead
  • Do not optimise the step in isolation — a signup lift that lowers paid conversion is a loss; watch the downstream metric
  • Do not call a test on day two because it looks good — set the threshold and sample size before you start
  • Do not redesign by opinion — every change should trace to a diagnosed blocker and a hypothesis

Based On

Conversion-optimization heuristics (clarity / relevance / motivation / friction / anxiety / distraction — LIFT-style) and properly-powered A/B testing.

Version History

  • 54fad50 Current 2026-07-19 12:14

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Metadata

Files
0
Version
471c606
Hash
005c5172
Indexed
2026-07-19 12:14

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