How do I install the Tw Ecom Analytics Benchmarks skill?

Run npx skillmds@latest add asgard-ai-platform/tw-ecom-analytics-benchmarks in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Tw Ecom Analytics Benchmarks safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Tw Ecom Analytics Benchmarks?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Tw Ecom Analytics Benchmarks free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Tw Ecom Analytics Benchmarks?

asgard-ai-platform (@asgard-ai-platform) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Tw Ecom Analytics Benchmarks by asgard-ai-platform

Name: Tw Ecom Analytics Benchmarks
Author: asgard-ai-platform

Tw Ecom Analytics Benchmarks

Taiwan e-commerce benchmark ranges for CVR, ROAS, LTV, AOV, repeat rate, cart-abandon — segmented by vertical (3C, 美妝, 服飾, 母嬰, 生鮮) and channel (DTC, Shopee, momo). Use when a TW merchant asks 'is my CVR / ROAS good?' or when sizing a business case. Source discipline: cite industry report or vendor data; mark undocumented ranges as estimates. STATUS: SKELETON — body pending.

File contents

Taiwan E-Commerce Benchmarks

STATUS: SKELETON — body pending.

When to use this skill

A merchant asks "is my CVR / ROAS / LTV good?"
Sizing a business case (revenue / ad-spend projections)
Comparing performance across verticals or channels
Investor / banker deck benchmarks

Do NOT use when

Instrumentation itself → tw-ecom-analytics-ga4
Unit economics framework → biz-unit-economics

Core concepts

TODO: benchmark tables by vertical × channel, sourced ranges with citations.

Decision tree

TODO: merchant profile → applicable benchmark row.

Implementation guidance

TODO: comparison template, outlier-flag criteria, what to do when outside range.

Gotchas

TODO: 5-6 pitfalls (stale benchmarks, vertical misclassification, channel-mix distortion, attribution-model divergence, peak-period distortion).

IRON LAW

TODO (candidate: "All benchmark ranges must cite source + year. An uncited number is worse than no number.").

Output Format

TODO.

ecom-analytics
biz-unit-economics, biz-cac-ltv

Last verified: 2026-04

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