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Agent Skill · 研究检索

marketing-spend-analysis(营销支出分析)

marketing-spend-analysis 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

marketing-spend-analysis 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 54,679。

总安装 499周安装 20GitHub Stars 19下载 162核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:marketing-spend-analysis(营销支出分析)
来源仓库:https://github.com/finsilabs/awesome-ecommerce-skills
仓库路径:skills/marketing-spend-analysis
安装命令:
npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill marketing-spend-analysis
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill marketing-spend-analysis

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选营销支出分析相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。通过关键词或任务场景进行信息检索与筛选。marketing-spend-analysis 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

安装前需确认权限范围和维护状态,避免触发联网或文件读写。建议结合原始 README 核验具体用法和功能边界。

来源仓库内路径:skills/marketing-spend-analysis

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill mar…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

marketing-spend-analysis 怎么安装?

在终端执行 npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill marketing-spe…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

marketing-spend-analysis 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

marketing-spend-analysis 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

marketing-spend-analysis 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

marketing-spend-analysis 用的人多吗?

公开数据是累计安装 499 次,近一周安装 20 次,下载 162 次,GitHub 19 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

marketing-spend-analysis 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
marketing-spend-analysis

营销支出分析 · 本页

49919需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Marketing Spend Analysis

Overview

Marketing spend is typically the largest variable cost in a DTC ecommerce business — often 15–40% of revenue. Unlike most costs, marketing spend is directly controllable in near-real-time: you can increase or decrease budgets on paid channels within minutes. This creates both opportunity (scale what works) and risk (waste capital on what does not).

The core goal is to maximize total contribution profit from your marketing investment — not just revenue. A channel with high ROAS but thin margins, high return rates, or low AOV may generate less actual profit than a channel with lower ROAS and stronger unit economics.

This skill guides you through building a unified view of marketing spend and performance across all channels, using tools designed specifically for ecommerce merchants.

When to Use This Skill

  • When managing marketing budgets across multiple platforms (Meta, Google, TikTok, Amazon Ads)
  • When wanting to identify which channels generate the most profitable customers
  • When needing a unified marketing performance dashboard fed by multiple ad platforms
  • When hitting diminishing returns on a key channel and deciding how to reallocate spend
  • When comparing platform-reported ROAS against first-party attributed ROAS
  • When building a marketing efficiency report for a board or investor update

Core Instructions

Step 1: Choose a unified marketing analytics tool

The biggest problem in marketing spend analysis is that each platform (Meta, Google, TikTok) reports its own ROAS using its own attribution window — and they all claim 100% credit. You need a tool that pulls data from all platforms into one view and compares against your actual order data.

PlatformRecommended ToolWhat It Does
ShopifyTriple Whale or Polar AnalyticsConnects Shopify orders + all ad platforms; shows blended ROAS, MER, and channel-level true ROAS side by side
Shopify (budget option)Shopify Analytics + Google Analytics 4Free; last-click attribution only; no cross-platform comparison
WooCommerceMetorik + GA4Metorik adds UTM attribution to WooCommerce orders; GA4 provides channel-level conversion reporting
BigCommerceGlew.io or RockerboxBoth connect BigCommerce orders to ad platform spend data
All platformsNorthbeam or RockerboxPlatform-agnostic; provide first-party multi-touch attribution across all channels with spend pacing

Key metrics to track in your chosen tool:

MetricDefinitionWhy It Matters
Platform ROASRevenue attributed by each platform / spend on that platformWhat the ad platform claims (typically inflated)
First-party ROASRevenue attributed by your own pixel / spendMore accurate; corrects for view-through over-attribution
Blended MERTotal revenue / total marketing spend across all channelsOverall marketing efficiency; harder to game
True ROASGross profit attributed to channel / spendAccounts for COGS; the right metric for profitability decisions
CAC (new customers only)New customer acquisition spend / new customers acquiredSeparate from retargeting/retention spend
ROAS break-even1 / (1 - COGS rate - fulfillment rate)Minimum ROAS needed to not lose money

Step 2: Set up your marketing analytics stack


Shopify

Triple Whale setup (recommended for $50K+/mo ad spend):

  1. Install Triple Whale from the Shopify App Store
  2. Connect all ad accounts under Settings → Integrations: Meta, Google, TikTok, Pinterest, Snapchat
  3. Triple Whale installs a first-party pixel on your store that tracks the full customer journey
  4. Go to Triple Whale → Summary Dashboard — view daily spend, attributed revenue, ROAS, MER, new customer CAC, and gross profit by channel in one dashboard
  5. Go to Triple Whale → Attribution → Channel to see revenue under different attribution models side by side (first-click, last-click, Triple Whale's blended model)
  6. Set up Morning Digest emails — Triple Whale sends a daily performance summary automatically
  7. Set Budget Alerts under Settings → Alerts — get Slack/email notifications when ROAS drops below threshold or spend is pacing to overshoot monthly budget

Polar Analytics setup (mid-market, more affordable):

  1. Install Polar Analytics from the Shopify App Store
  2. Connect ad accounts under Integrations
  3. Go to Polar → Channels — view spend, attributed revenue, ROAS, and gross profit by channel
  4. Go to Polar → Blended Dashboard — view overall MER and blended spend vs. revenue trend
  5. Use Polar → AI Insights for automated anomaly detection and spend recommendations

WooCommerce

Metorik + GA4 setup:

  1. Install Metorik and connect to your WooCommerce store
  2. Metorik captures UTM parameters on every order — go to Metorik → Reports → UTM to see orders and revenue by utm_source, utm_medium, utm_campaign
  3. Install Google Analytics 4 via the Site Kit or MonsterInsights plugin
  4. In GA4, go to Advertising → Attribution → Model comparison — select Google, Paid Social, Email as your channels and compare last-click vs. data-driven attribution
  5. For ad spend data from non-Google platforms (Meta, TikTok), manually import spend CSVs into a Google Sheet and connect to Looker Studio alongside GA4 data for a unified view

Alternative: Northbeam or Rockerbox

  • Both support WooCommerce via JavaScript pixel + order API integration
  • Provide the same cross-platform attribution capabilities as Triple Whale but with WooCommerce compatibility

BigCommerce
  1. Install Glew.io from the BigCommerce App Marketplace
  2. Connect ad accounts (Meta, Google, Amazon) in Glew under Integrations
  3. Glew shows spend, attributed revenue, ROAS, and blended MER by channel
  4. For more advanced first-party attribution: install Rockerbox via script injection (BigCommerce → Storefront → Script Manager)

Step 3: Define your ROAS break-even and targets

Before analyzing whether a channel is performing well, calculate your minimum viable ROAS.

ROAS break-even formula:

Break-even ROAS = 1 / (1 - COGS rate - variable cost rate)

Example:
  COGS rate: 45% of revenue
  Fulfillment + payment fees: 12% of revenue
  Break-even ROAS = 1 / (1 - 0.45 - 0.12) = 1 / 0.43 = 2.33x

Any channel with true ROAS below 2.33x is losing money on every sale.

Target ROAS by channel type:

Channel TypeTarget ROAS Multiplier Above Break-EvenWhy
Prospecting (new customers)1.5–2x break-evenAcquiring new customers has higher long-term value than single-order ROAS suggests
Retargeting (existing visitors)2–3x break-evenLower cost; higher conversion rate; but be careful of incrementality
Brand search (Google Branded)5x+High ROAS but low incrementality; customers were coming anyway
Non-brand search (Google Generic)1.5–2x break-evenTrue incremental; valuable for new customer acquisition
Email/SMS10x+Low cost per send; high ROAS but measures existing customer retention, not acquisition

Step 4: Build a weekly channel performance scorecard

Set up a weekly review with this structure. Pull data from your analytics tool (Triple Whale, Glew, GA4):

CHANNEL PERFORMANCE SCORECARD (Last 7 Days vs. Prior 7 Days)
─────────────────────────────────────────────────────────────
Channel    | Spend  | 1P Revenue | 1P ROAS | vs LW | Status
Meta Ads   | $12,400| $38,400    | 3.1x    | +0.3x | OK ✓
Google Ads | $8,200 | $31,100    | 3.8x    | -0.2x | OK ✓
TikTok Ads | $3,100 | $5,700     | 1.8x    | -0.8x | REVIEW ⚠
Amazon Ads | $4,500 | $19,800    | 4.4x    | +0.1x | OK ✓
Email/SMS  | $800   | $22,000    | 27.5x   | +2.0x | OK ✓
─────────────────────────────────────────────────────────────
Total      | $29,000| $117,000   | 4.0x    |       | MER: 4.0x
Break-even ROAS: 2.33x | Monthly Budget: $125,000 | Paced to spend: $126,500 (+$1,500)

TikTok is flagged: ROAS dropped from 2.6x to 1.8x (below 2.33x break-even). Action: Investigate creative fatigue; pause underperforming ad sets; hold budget before cutting entirely.

Step 5: Make budget reallocation decisions

Use this decision framework when channels are over/under-performing:

When to reduce spend on a channel:

  • True ROAS has been below break-even for 2+ consecutive weeks
  • First-party ROAS has declined more than 30% with no operational explanation
  • Creative has not been refreshed in 30+ days and ROAS is declining (creative fatigue)

When to increase spend on a channel:

  • True ROAS is 2x or more above break-even
  • First-party ROAS has been stable or increasing for 3+ weeks
  • Marginal ROAS at current spend level is still above break-even (not in diminishing returns territory)

Before cutting spend, investigate:

  1. Is a top SKU out of stock? Ads running for out-of-stock products waste spend with no ability to convert
  2. Did a creative rotation happen? Performance often dips temporarily during algorithm learning phases (50+ optimization events needed)
  3. Did a competitor run a major promotion? Temporary CPM/CPC spikes are not structural channel problems
  4. Is the tracking pixel firing correctly? A sudden ROAS drop can be a tracking issue, not a performance issue

Best Practices

  • Track true ROAS (profit-based), not platform-reported ROAS — platform ROAS using view-through attribution is almost always higher than reality; compute ROAS from your own first-party data
  • Monitor MER (Marketing Efficiency Ratio) as a holistic metric — blended MER (total revenue / total marketing spend) is harder to game than individual channel ROAS; a healthy ecommerce MER is typically 3–6x
  • Separate new customer acquisition from retention spending — remarketing and email/SMS to existing customers have very different economics than prospecting; track CAC and ROAS separately for new vs. returning customer campaigns
  • Build a weekly spend pacing report — track cumulative spend vs. monthly budget by day; a channel at 80% of monthly budget by day 15 will either overspend or dramatically under-deliver in the second half
  • Track creative performance, not just campaign performance — one creative often drives 70% of a campaign's ROAS; surface creative-level performance and prioritize winning formats
  • Test incrementality before doubling down — high retargeting ROAS may be capturing sales that would have happened anyway; run holdout tests to measure true incremental impact

Common Pitfalls

ProblemSolution
Each platform claims credit for the same orderUse a first-party attribution tool (Triple Whale, Northbeam) to de-duplicate; platform-reported ROAS always double-counts
Cutting spend during a temporary ROAS dipInvestigate root cause before cutting; algorithmic learning phases (post-creative refresh) look like performance drops but recover; allow 50+ optimization events before evaluating
Not separating branded from non-branded search ROASGoogle Branded campaigns have very high ROAS but low incrementality; analyze separately or you will overestimate Google's true contribution
Running ads for out-of-stock productsConnect inventory status to your ad platforms; use rules-based automation in Meta/Google to pause campaigns when SKUs hit 0 stock
Ignoring email and SMS in ROAS calculationsEmail/SMS spend is very low relative to revenue attributed; their MER looks incredible but remember they largely serve existing customers — they are retention tools, not acquisition tools

Related Skills

  • @attribution-modeling
  • @cost-allocation-analysis
  • @unit-economics-tracking
  • @ecommerce-budgeting-forecasting
  • @financial-analytics-dashboard

平台分布

Codex

36.73%
按下载量换算60

Claude

29.98%
按下载量换算49

Cursor

16.17%
按下载量换算26

Gemini CLI

9.64%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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