What formats are the analysis reports provided in?

The skill generates comprehensive Markdown summaries, organized screenshot folders, and CSV files containing ad copy, CTAs, and identified themes.

Does this skill provide private performance metrics?

No, it uses public data. It infers performance by analyzing ad frequency, duration, and messaging patterns to identify what competitors are likely finding successful.

Which platforms does this skill support for ad extraction?

The skill is designed to work with major public repositories including the Facebook Ad Library and LinkedIn, but it can be adapted for other web-based ad galleries.

Can it save visual copies of the advertisements?

Yes, the skill captures screenshots of the ads it finds and organizes them into structured directories alongside the text analysis.

Competitive Ads Extractor

Name: Competitive Ads Extractor
Author: hameed0342j

byhameed0342j

0•

웹 스크래핑 및 데이터 수집

Scrapes and analyzes competitor advertisements from major ad libraries to uncover winning messaging, creative patterns, and market positioning.

The Competitive Ads Extractor skill empowers Claude to perform deep-dive market research by automatically retrieving ad data from platforms like the Facebook Ad Library and LinkedIn. It moves beyond simple scraping to provide comprehensive analysis of competitor pain points, audience targeting, and creative patterns. By synthesizing visual screenshots with copy analysis, it helps marketing and product teams identify high-performing trends and messaging gaps in the market to inform and optimize their own advertising campaigns.

주요 기능

01Structured reporting in Markdown, CSV, and pattern libraries

02Deep messaging analysis of problems, use cases, and value props

030 GitHub stars

04Audience targeting and competitive positioning insights

05Visual creative pattern recognition and screenshot capture

06Automated ad extraction from Facebook and LinkedIn Ad Libraries

사용 사례

01Identifying underserved market pain points for better brand positioning

02Benchmarking competitor messaging during new product launches

03Finding visual and copy inspiration for ad creative design

주요 기능

01Structured reporting in Markdown, CSV, and pattern libraries

02Deep messaging analysis of problems, use cases, and value props

030 GitHub stars

04Audience targeting and competitive positioning insights

05Visual creative pattern recognition and screenshot capture

06Automated ad extraction from Facebook and LinkedIn Ad Libraries

사용 사례

01Identifying underserved market pain points for better brand positioning

02Benchmarking competitor messaging during new product launches

03Finding visual and copy inspiration for ad creative design