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campaign-analyzer活动分析器

Agent Skill

campaign-analyzer 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。

总安装

8,649

周安装

415

GitHub Stars

公开资料未说明

下载量

4,039
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

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:campaign-analyzer(活动分析器)
来源仓库:https://github.com/eddiebe147/claude-settings
仓库路径:skills/campaign-analyzer
安装命令:
npx skills add https://github.com/eddiebe147/claude-settings --skill 'Campaign Analyzer'
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/eddiebe147/claude-settings --skill 'Campaign Analyzer'

简介

campaign-analyzer 将营销数据转化为可执行的洞察报告。

  • 支持跨平台活动分析、效果诊断与行业基准对比。
  • 帮助制定数据驱动的优化策略,提升广告投放效率。
  • 输出结果需结合业务背景解读,不可仅依赖指标数值决策。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Campaign Analyzer

Turn marketing data into actionable insights that improve campaign performance. This skill helps you systematically analyze campaigns across channels, identify what's working, diagnose what's not, and make data-driven optimization decisions.

Raw metrics don't tell stories - this skill helps you find the narrative in your data. From awareness campaigns to lead generation to e-commerce, learn to measure what matters, benchmark against industry standards, and present findings that drive better marketing decisions.

Built for marketing managers, performance marketers, analysts, and anyone responsible for demonstrating marketing impact and improving results.

Core Workflows

Workflow 1: Campaign Performance Review

  1. Goal Alignment - Compare results to objectives
  2. KPI Dashboard - Track primary and secondary metrics
  3. Funnel Analysis - Identify conversion bottlenecks
  4. Channel Attribution - Understand contribution by source
  5. Spend Efficiency - Calculate cost metrics (CPM, CPC, CPA, ROAS)
  6. Audience Performance - Segment by demographic/behavior
  7. Creative Analysis - Identify top-performing assets
  8. Recommendation Synthesis - Actionable next steps

Workflow 2: Multi-Channel Analysis

  1. Channel Mapping - All touchpoints in customer journey
  2. Attribution Modeling - First touch, last touch, multi-touch
  3. Cross-Channel Synergies - How channels work together
  4. Budget Allocation Review - Spend vs performance by channel
  5. Audience Overlap - Reach and frequency across channels
  6. Journey Mapping - Path to conversion analysis
  7. Optimization Recommendations - Reallocation suggestions

Workflow 3: Creative Performance Analysis

  1. Asset Inventory - All creative variations tested
  2. Performance Ranking - Best to worst performers
  3. Element Analysis - What elements drive performance
  4. Format Comparison - Static vs video vs carousel
  5. Message Testing - Which value props resonate
  6. Creative Fatigue - Performance over time
  7. Learning Documentation - Insights for future creative

Workflow 4: ROI & Attribution Analysis

  1. Revenue Attribution - Connect marketing to revenue
  2. Customer Acquisition Cost - Fully-loaded CAC calculation
  3. Lifetime Value Analysis - LTV by acquisition channel
  4. ROAS Calculation - Return on ad spend by campaign
  5. Payback Period - Time to recoup acquisition cost
  6. Incrementality Testing - True marketing impact
  7. Budget Optimization Model - Optimal allocation recommendations

Quick Reference

ActionCommand/Trigger
Campaign review"Analyze performance of [campaign name]"
Channel comparison"Compare performance across [channels]"
ROI calculation"Calculate ROI for [marketing initiative]"
Creative analysis"Identify top performing creative"
Funnel analysis"Find conversion bottlenecks"
Spend optimization"Recommend budget reallocation"
Attribution review"Analyze attribution for [campaign]"
Executive summary"Create executive summary of [campaign results]"

Best Practices

  • Start with goals - Analysis serves objectives, not vanity
  • Define success upfront - Benchmarks before launch
  • Segment everything - Aggregate data hides insights
  • Compare apples to apples - Normalize for meaningful comparison
  • Look for patterns - Single data points mislead
  • Context matters - Seasonality, competition, market conditions
  • Attribution is imperfect - Acknowledge model limitations
  • Focus on actionable - Insights must lead to actions
  • Trend over point-in-time - Direction matters more than absolute
  • Test before scaling - Validate before major spend shifts
  • Document learnings - Build institutional knowledge
  • Automate reporting - Spend time on analysis, not data pulling
  • Visualize effectively - Charts that tell stories
  • Executive vs detailed - Right depth for right audience
  • Lead with recommendations - What should we do differently?

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

26.89%
按下载量换算1,086

OpenCode

21.52%
按下载量换算869

Gemini CLI

18.08%
按下载量换算730

Antigravity

13.75%
按下载量换算555

Cursor

7.05%
按下载量换算285

windsurf

3.31%
按下载量换算134

安全审计

Gen Agent Trust Hub

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。来源字段存在多来源差异,先按来源优先级自动处理,无法消解时进入异常复核队列。

来源信息

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