facebook-ads-analyzer
🥈SilverFacebook Ads Analyzer 是一个专业的广告数据分析系统，基于facebook_ads 的 claude code agent skill ,能够： 自动分析 Facebook Ads Manager 导出的 CSV 数据 根据不同广告目标（互动/转化/流量）智能评估广告表现 识别最佳和最差广告 生成详细的诊断报告和优化建议 提供数据驱动的投放策略方案
2210Updated 2mo ago
Intermediate30min to implementautomation
Saves ~150 min per use
Quick InstallView Source
git clone https://github.com/liangdabiao/facebook-ads-analyzer.gitWorks with:
Claude
Overview
About This Skill
Facebook Ads Analyzer automates performance evaluation of ads exported from Facebook Ads Manager. It applies weighted composite scoring algorithms tailored to your advertising goal—whether interaction, conversion, or traffic—and classifies ads as excellent, medium, or poor based on data-driven thresholds. The system diagnoses performance issues and provides specific optimization suggestions for each ad, from increasing budgets on top performers to identifying problem areas in underperforming campaigns. It generates three detailed outputs: a CSV with individual ad scores and rankings, a markdown analysis report highlighting top and bottom 10 ads with actionable insights, and a strategy proposal document with conservative, balanced, and aggressive investment approaches.
How to Use
Export your ad data as CSV from Facebook Ads Manager. Tell Claude your advertising goal (interaction, conversion, or traffic) and ask it to analyze the file. Claude loads the data, applies the appropriate metric weights, calculates composite scores, classifies ads, diagnoses issues, and generates results.csv, analysis_report.md, and strategy_proposal.md files.
Use Cases
Identify which Facebook ads to scale by analyzing engagement, conversion, or traffic metrics
Diagnose why specific ads underperform and get targeted recommendations for improvement
Generate weekly performance reports to track trends and optimize campaign budgets
Compare ad performance across different goals to align spending with business objectives
Tags
Setup & Installation
Quick Install
No install command available. Check the GitHub repository for manual installation instructions.
Alternative Install (Git Clone)
git clone https://github.com/liangdabiao/facebook-ads-analyzerRequirements
- Claude Code or compatible AI agent
- Works with: Claude
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
Prompt Template
Analyze the following Facebook Ads data for [COMPANY] in the [INDUSTRY] sector. The data is attached as a CSV file. Provide a detailed report that includes: 1) Performance evaluation based on the primary goal of [GOAL: engagement/conversions/traffic], 2) Identification of top and bottom-performing ads, 3) Specific optimization recommendations, and 4) Data-driven suggestions for future ad placements and targeting.
Example Output
# Facebook Ads Performance Analysis for GreenTech Solutions ## Overview The analysis covers GreenTech Solutions' Facebook ad campaigns from January 1, 2023, to March 31, 2023, with a primary focus on conversions. The dataset includes 15 campaigns, 48 ad sets, and 120 individual ads. ## Key Findings ### Top-Performing Ads - **Ad ID: 1234567890** - **CTR**: 4.2% - **Conversion Rate**: 12.5% - **Cost per Conversion**: $18.76 - **Targeting**: Homeowners aged 35-55 interested in solar panels - **Placement**: Instagram Feed - **Ad ID: 0987654321** - **CTR**: 3.8% - **Conversion Rate**: 11.9% - **Cost per Conversion**: $20.12 - **Targeting**: Small business owners interested in energy efficiency - **Placement**: Facebook News Feed ### Underperforming Ads - **Ad ID: 5556667777** - **CTR**: 0.8% - **Conversion Rate**: 2.1% - **Cost per Conversion**: $85.43 - **Targeting**: Broad interest in renewable energy - **Placement**: Facebook Right Column - **Ad ID: 7778889999** - **CTR**: 1.2% - **Conversion Rate**: 1.8% - **Cost per Conversion**: $78.33 - **Targeting**: General audience interested in sustainability - **Placement**: Audience Network ## Recommendations 1. **Increase Budget Allocation**: Shift budget from underperforming ads to top-performing ads, particularly Ad ID 1234567890 and 0987654321. 2. **Refine Targeting**: Narrow the audience for underperforming ads to focus on specific demographics and interests that align with the top-performing ads. 3. **Optimize Placements**: Reduce spend on Facebook Right Column and Audience Network placements, focusing more on Instagram Feed and Facebook News Feed. 4. **A/B Testing**: Create new ad variations based on the successful elements of the top-performing ads, such as ad copy, images, and targeting criteria. 5. **Landing Page Optimization**: Ensure that the landing pages for underperforming ads are optimized for conversions, with clear calls-to-action and relevant content.
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