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tw-ecom-analytics-benchmarks

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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.

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How to use this skill

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Source SKILL.md: https://github.com/asgard-ai-platform/skills/blob/HEAD/tw-ecom-analytics-benchmarks/SKILL.md

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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.

Related

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

Last verified: 2026-04