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Checkout Friction Audit

核心功能为分析结账流程,定位流失环节,生成含严重度、原因、优先级的摩擦地图及落地执行方案。适用于加购率高但下单率低、结账弃购激增、支付/物流投诉频发的场景。输入含结账流程笔记、弃购信号等,支持浏览器观测;输出含执行摘要、优先级行动等的专业报告,可对接迭代板跟进修复。

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热度 82.78
最近更新 2026-05-11 17:30:28
分类:营销依赖:联网浏览搜索 / 内部调用大模型应用场景:市场分析 / 报告撰写

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add checkout-friction-audit
Metadata
name
checkout-friction-audit
description
Audit checkout friction points and prioritize fixes that improve completed purchases without increasing risk. Use when the user reports high add-to-cart but low purchase rate, checkout abandonment spikes, or repeated payment/shipping complaints.

Checkout Friction Audit

Skill Card

  • Category: Conversion
  • Core problem: Which checkout steps are leaking intent and killing purchase completion?
  • Best for: Conversion rate recovery projects
  • Expected input: Checkout flow notes, abandonment signals, user complaints, policy constraints
  • Expected output: Friction map with severity, likely cause, and fix priority
  • Creatop handoff: Push fixes into sprint board and rerun after implementation

Browser-first guidance

If the checkout flow is accessible by URL or staging page, prefer OpenClaw managed browser for direct observation before producing recommendations.

Recommended order:

  1. Use any funnel notes, complaints, or screenshots the user already has.
  2. If live checkout pages are available, inspect them in OpenClaw managed browser.
  3. Use Browser Relay only when the user explicitly wants to inspect their current Chrome session.

Workflow

  1. Clarify where the drop appears to happen.
    • cart?
    • shipping step?
    • payment step?
    • mobile-specific issue?
  2. Map checkout path and identify complaint-linked touchpoints.
  3. Score friction by impact on completion and fix complexity.
  4. Separate UX friction from trust/compliance friction.
  5. Output top quick wins and structural fixes.

Output format

Return in this order:

  1. Executive summary (max 5 lines)
  2. Priority actions (P0/P1/P2)
  3. Evidence table (signal, confidence, risk)
  4. 7-day execution plan

Quality and safety rules

  • Tie each recommendation to observed evidence, not guesswork.
  • Prioritize reversible low-risk fixes first.
  • Avoid recommendations that violate platform/payment policies.
  • If the observed flow is partial, state that clearly.

License

Copyright (c) 2026 Razestar.

This skill is provided under CC BY-NC-SA 4.0 for non-commercial use. You may reuse and adapt it with attribution to Razestar, and share derivatives under the same license.

Commercial use requires a separate paid commercial license from Razestar. No trademark rights are granted.