tw-ecom-analytics-benchmarks

asgard-ai-platform ｜ 資料與分析 ｜ 原文 ｜ MIT

台灣電商 CVR、ROAS、LTV 等指標的基準區間（內文待補）

---
name: "tw-ecom-analytics-benchmarks"
description: "台灣電商的基準區間：CVR、ROAS、LTV、AOV、回購率、購物車放棄率，依產業類別（3C、美妝、服飾、母嬰、生鮮）和通路（DTC、Shopee、momo）分群。當台灣商家問「我的 CVR / ROAS 算好嗎？」或要評估商業案例的規模時使用。來源紀律：引用產業報告或廠商資料；沒有文件佐證的區間要標示為估計值。STATUS: SKELETON — 內文待補。"
metadata:
  category: "WP-01 電商"
  domain: "ecommerce-tw"
  layer: "analytics"
  related_mcps: []
  related_skills: ["ecom-analytics", "tw-ecom-analytics-ga4", "biz-unit-economics", "biz-cac-ltv"]
  last_verified: "2026-04"
  status: "skeleton"
  tags: ["taiwan", "e-commerce", "benchmarks", "metrics"]
---

# 台灣電商基準

> **STATUS: SKELETON**：內文待補。

## 何時使用這個 skill

- 商家問「我的 CVR / ROAS / LTV 算好嗎？」
- 評估商業案例的規模（營收 / 廣告支出預估）
- 跨產業類別或通路比較表現
- 投資人 / 銀行簡報用的基準

## 何時「不要」使用

- 埋點本身 → `tw-ecom-analytics-ga4`
- 單位經濟模型框架 → `biz-unit-economics`

## 核心概念

TODO: 依產業類別 × 通路的基準表，附帶引用來源的區間。

## 決策樹

TODO: 商家輪廓 → 適用的基準列。

## 實作指引

TODO: 比較範本、異常值標記準則、落在區間外時該怎麼辦。

## 常見陷阱

TODO: 5-6 個陷阱（基準過期、產業類別分錯、通路組合造成扭曲、歸因模型不一致、檔期高峰造成扭曲）。

## IRON LAW

TODO（候選：「所有基準區間都必須標明來源 + 年份。沒有引用的數字比沒有數字更糟。」）。

## 輸出格式

TODO.

## 相關

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

_Last verified: 2026-04_

---
name: "tw-ecom-analytics-benchmarks"
description: "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."
metadata:
  category: "WP-01 電商"
  domain: "ecommerce-tw"
  layer: "analytics"
  related_mcps: []
  related_skills: ["ecom-analytics", "tw-ecom-analytics-ga4", "biz-unit-economics", "biz-cac-ltv"]
  last_verified: "2026-04"
  status: "skeleton"
  tags: ["taiwan", "e-commerce", "benchmarks", "metrics"]
---

# 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_