Scrape competitor ads from Meta Ad Library and Google Ads Transparency Center, analyze creative patterns (hooks, formats, CTAs), reverse-engineer landing page funnels, and produce a strategic teardown with vulnerability analysis and counter-play recommendations. Use when you need to understand the competitive ad landscape, find new creative directions, or identify weaknesses in a competitor's paid strategy.
npx gooseworks install --claude # Then in your agent: /gooseworks <prompt> --skill competitor-ad-intelligence
Scrape competitor ads from Meta and Google, analyze creative patterns, reverse-engineer landing page funnels, and produce a full strategic teardown — hooks, formats, positioning bets, vulnerabilities, and counter-plays.
Core principle: A competitor's ad portfolio is a window into their growth strategy. Long-running ads reveal what converts. New ads reveal what they're testing. Landing pages reveal their positioning bets. The best ad creative teams start with evidence from what's already working, then differentiate.
Gather from the user:
apollo.io, clay.run)For each competitor domain, scrape ads from Meta Ad Library.
Use web_search to find competitor ads in the Meta Ad Library (publicly accessible, no API key needed):
web_search: site:facebook.com/ads/library "[competitor_name]"
web_search: "[competitor_name]" Meta Ad Library active ads
web_search: "[competitor_name]" facebook ads examplesYou 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>
Use fetch_webpage on the Ad Library URL to extract ad details if your agent supports it.
Note: Apify actors for Meta Ad Library scraping exist but are unreliable as of April 2026 due to Meta's anti-scraping measures. Use
web_searchas the primary method.
Collect per ad:
For each competitor domain, scrape ads from 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 examplesYou can also visit directly: https://adstransparency.google.com/?search_text=<competitor_name>
Use fetch_webpage on the Transparency Center URL to extract ad details if your agent supports it.
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 | |
|---|---|---|
| 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:
For each unique landing page URL found in ads, fetch and analyze:
fetch_webpage: [landing_page_url]Or use curl if fetch_webpage is unavailable.
Extract per landing page:
Group all ads into logical campaigns by:
For each campaign cluster:
| Dimension | Analysis |
|---|---|
| Strategic intent | What is this campaign trying to achieve? (Awareness / Lead gen / Free trial / Competitive displacement) |
| Target persona | Who is this ad speaking to? (Role, pain, stage) |
| Positioning bet | What market position are they claiming? |
| Hook strategy | Fear / Outcome / Social proof / Contrarian / Product-led |
| Conversion path | Ad → LP → CTA → [Demo call / Free trial / Content download] |
| Longevity signal | How long has this been running? (Longer = likely working) |
| A/B tests detected | Multiple creatives to same LP = active testing |
Based on ad volume and platform distribution, estimate where they're concentrating spend:
| Platform | Ad Count | % of Total | Estimated Focus |
|---|---|---|---|
| Meta (Facebook) | [N] | [X%] | [Awareness / Retargeting] |
| Meta (Instagram) | [N] | [X%] | [Visual / younger audience] |
| Google Search | [N] | [X%] | [Bottom-funnel capture] |
| Google Display | [N] | [X%] | [Awareness / retargeting] |
| YouTube | [N] | [X%] | [Education / awareness] |
Identify across all competitors:
Identify weaknesses in each competitor's ad strategy:
| Vulnerability Type | Description |
|---|---|
| Message-LP mismatch | Ad promises one thing, LP delivers another |
| Single-persona dependency | All ads target the same persona — missing segments |
| Platform concentration | Heavy on one platform, absent from others |
| No social proof | Ads or LPs lack credibility markers |
| Weak CTA | Asking for too much too soon (demo before value) |
| Generic positioning | Claims anyone could make — not differentiated |
| Stale creative | Same ads running unchanged for months — fatigue risk |
If Web Archive data exists for their landing pages:
# Competitor Ad Intelligence Report — [DATE]
## Coverage
- Competitors analyzed: [list]
- Meta ads collected: [N]
- Google ads collected: [N]
- Unique landing pages analyzed: [N]
- Estimated active campaigns: [N]
---
## Executive Summary
[3-5 sentence summary: What is the competitive ad landscape? What's working? Where are the gaps and vulnerabilities?]
---
## Meta Ad Analysis
### Hook Distribution
| Hook Type | [Comp1] | [Comp2] | [Comp3] |
|-----------|---------|---------|---------|
| Fear/Loss | 40% | 10% | 0% |
| Outcome | 30% | 50% | 60% |
...
### Top Performing Ads (Longest Running)
**[Competitor] — [Ad Title/Hook]**
> [Ad copy excerpt]
- Format: [type]
- CTA: [text]
- Running since: [date]
- Why it likely works: [analysis]
---
## Google Ad Analysis
### Headline Patterns
[Top headline structures with examples]
### Most Common CTAs
[ranked list]
---
## Campaign Breakdown
### Campaign 1: [Inferred Campaign Name]
- **Competitor:** [name]
- **Ads in cluster:** [N]
- **Platform(s):** [Meta / Google / Both]
- **Strategic intent:** [Awareness / Lead gen / Competitive displacement / etc.]
- **Target persona:** [Description]
- **Hook strategy:** [Type]
- **Landing page:** [URL]
- Hero: "[Headline text]"
- CTA: "[Button text]"
- Message match: [Score/10]
- **Longevity:** [First seen date → status]
- **A/B tests detected:** [Yes/No — what they're testing]
**Sample ad:**
> **Headline:** [text]
> **Body:** [text]
> **CTA:** [button]
> **Format:** [Image/Video/Carousel]
**Assessment:** [1-2 sentences — is this working? Why/why not?]
### Campaign 2: ...
---
## Funnel Map
[Ad: Hook/Angle] → [LP: /landing-page-url] → [CTA: Book Demo] ↓ [Ad: Different angle] → [LP: /same-or-different] → [CTA: Free Trial]
---
## Budget Allocation Estimate
| Platform | Share | Focus Area |
|----------|-------|-----------|
| [Platform] | [X%] | [Intent] |
---
## Creative Gap Analysis
### Angles Nobody Is Running
1. [Angle] — Why it could work for you: [reasoning]
2. [Angle] — ...
### Overcrowded Angles (Avoid or Differentiate)
- [Angle] — [N] of [N] competitors use this
### Format White Space
- [Format] is not being used by competitors on [platform]
---
## Vulnerability Report
### 1. [Vulnerability]
**Competitor:** [name]
**Evidence:** [What we observed]
**Your opportunity:** [How to exploit this gap]
### 2. ...
---
## Recommended Counter-Plays
### Counter-Play 1: [Name]
- **Target their weakness:** [Which vulnerability]
- **Your ad angle:** [Hook]
- **Platform:** [Where to run]
- **Proposed headline:** "[headline]"
- **Proposed body:** "[copy]"
- **LP strategy:** [What your landing page should emphasize]
- **Why test this:** [rationale]
### Counter-Play 2: ...| Component | Cost |
|---|---|
| Ad library research (web_search) | Free |
| Landing page fetching | Free |
| Web Archive lookup (deep mode) | Free |
| Analysis | Free (LLM reasoning) |
| Total | Free |
web_search — query Meta Ad Library and Google Ads Transparency Centerfetch_webpage or curl — fetch and analyze landing pagesDiagnose Meta Ads campaign performance using Meta's actual system mechanics — Breakdown Effect, Learning Phase, Auction Overlap, Pacing, and Creative Fatigue — and produce structured, testable recommendations that avoid judging segments by average CPA instead of marginal efficiency.
Pre-flight policy check for Meta ads. Takes ad copy plus advertiser context, resolves and fetches the relevant Meta transparency-center policy pages at runtime, and returns a Pass / Fix Required / Block verdict with cited findings and rewrites.
For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.