skills/competitor-ad-intelligence/SKILL.md
Research public competitor ads, analyze creative patterns and landing pages, and produce an evidence-labeled strategic teardown.
npx skillsauth add ranbot-ai/awesome-skills competitor-ad-intelligenceInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Research competitor ads from Meta and Google, analyze creative patterns, map observable landing-page funnels, and produce a strategic teardown — hooks, formats, positioning bets, vulnerabilities, and counter-plays.
Core principle: A competitor's public ad portfolio is partial evidence about its growth strategy. Long-running ads can indicate continued investment, but public libraries do not expose conversion performance or spend. Separate observations from hypotheses, cite every observed ad or page, and label all performance and budget inferences explicitly.
Gather from the user:
apollo.io, clay.run)For each competitor domain, research ads visible in Meta Ad Library and public search results.
Use web_search only to discover first-party library pages and candidate references:
web_search: site:facebook.com/ads/library "[competitor_name]"
web_search: "[competitor_name]" Meta Ad Library active ads
web_search: "[competitor_name]" facebook ads examples
You can also visit the Meta Ad Library directly: https://www.facebook.com/ads/library/?active_status=active&ad_type=all&country=US&q=<competitor_name>
Prefer manual browser research. Use automated collection only when the platform expressly permits it and the user has authorized it; comply with current terms, robots directives, and rate limits. If the page is blocked, incomplete, dynamic-only, or requires authentication, report the coverage gap; do not bypass the control or invent missing ads or attributes.
Collect per ad:
For each competitor domain, research ads visible in Google Ads Transparency Center.
Use web_search to find competitor ads in Google Ads Transparency Center (publicly accessible):
web_search: site:adstransparency.google.com "[competitor_name]"
web_search: "[competitor_name]" Google Ads transparency
web_search: "[competitor_name]" google search ads examples
You can also visit directly: https://adstransparency.google.com/?search_text=<competitor_name>
Prefer manual browser research. Treat search snippets and third-party examples as secondary evidence and identify them as such. Use automated fetching only when permitted and authorized.
Collect per ad:
After collecting all ads, perform structured analysis.
Group all ad headlines/openers by hook type:
| Hook Type | Pattern | Example | |-----------|---------|---------| | Fear/Loss | Risk of missing out or falling behind | "Your competitors are already using AI SDRs" | | Outcome | Direct result promise | "10x your pipeline in 30 days" | | Question | Challenges current assumption | "Still doing outbound manually?" | | Social proof | Names customers or numbers | "Join 500+ B2B teams using [product]" | | Contrarian | Challenges conventional wisdom | "Cold email isn't dead. Your copy is." | | Empathy | Validates their pain | "We know SDR ramp time is brutal" | | Product-led | Feature as hook | "[Feature] is live — see what's new" |
Count how many ads per competitor use each hook type. This reveals their primary messaging strategy.
| Format | Meta | Google | |--------|------|--------| | Static image | [N] | N/A | | Video | [N] | [N] | | Carousel | [N] | N/A | | Search text | N/A | [N] | | Display banner | N/A | [N] |
List all unique CTAs found. Common patterns:
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