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.

When to Use

• "What ads are my competitors running?"
• "Tear down [competitor]'s ad strategy"
• "Find new creative angles for our paid campaigns"
• "Reverse-engineer [competitor]'s paid funnel"
• "What hooks are working in [our space]?"
• "Audit the ad landscape before we launch"
• "Find weaknesses in [competitor]'s ad strategy"
• "What format — video, image, carousel — is dominant in our category?"

Phase 0: Intake

Gather from the user:

1. Competitor names + domains (e.g., apollo.io, clay.run)
2. Your product/domain — for comparison framing
3. Channels: Meta only, Google only, or both? (default: both)
4. Depth level:
   • Standard: Ad scrape + creative analysis + landing page analysis
   • Deep: Standard + historical comparison + funnel reconstruction + counter-plays
5. Product category — helps frame analysis
6. Known competitor landing pages? — any URLs already spotted in their ads

Phase 1: Scrape Meta Ads

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 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>

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_search as the primary method.

Collect per ad:

• Ad copy (headline + primary text)
• Visual type (image / video / carousel)
• CTA button text
• Landing page URL
• Active duration (first seen, still running or stopped)
• Platforms (Facebook, Instagram, Audience Network)
• Ad variations (A/B tests — same landing page, different creative)

Phase 2: Scrape Google Ads

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 examples

You 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:

• Headline variants (up to 3)
• Description lines
• Ad type (Search / Display / YouTube / Shopping)
• Landing page URL
• Geographic targeting (if visible)

Phase 3: Analyze Creative Patterns

After collecting all ads, perform structured analysis.

Hook Pattern Clustering

Group all ad headlines/openers by hook type:

Count how many ads per competitor use each hook type. This reveals their primary messaging strategy.

Format Distribution

CTA Taxonomy

List all unique CTAs found. Common patterns:

• Urgency: "Start free", "Try now", "Get started today"
• Low-friction: "See how it works", "Watch demo", "Learn more"
• Outcome: "Book a demo", "Get your free audit", "Calculate your ROI"

Phase 4: Landing Page & Funnel Analysis

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:

• Hero headline — Does it match the ad promise?
• Subheadline — Value prop expansion
• Primary CTA — What action are they driving? (Demo / Free trial / Sign up / Download)
• Social proof — Logos, testimonials, case study metrics
• Pricing visibility — Is pricing shown or hidden?
• Form fields — How much info do they ask for?
• Page type — General homepage / dedicated LP / feature page / use-case page
• Message match score — How well does the LP deliver on the ad's promise? (1-10)

Campaign Clustering

Group all ads into logical campaigns by:

• Landing page destination — Ads pointing to the same URL = same campaign
• Messaging theme — Similar copy angles = same strategic bet
• Audience signal — Different copy for different personas

Per-Campaign Funnel Analysis

For each campaign cluster:

Budget Allocation Inference

Based on ad volume and platform distribution, estimate where they're concentrating spend:

Phase 5: Strategic Analysis

Creative Gap Analysis

Identify across all competitors:

1. Angles nobody is running — Hook types absent from competitor ads = white space
2. Overcrowded angles — If everyone leads with "save time", avoid it or be more specific
3. Format opportunities — If no one is running video in your space, it may stand out
4. Underutilized proof — Are competitors avoiding specific proof points you could own?
5. CTA patterns to test — What CTAs do the longest-running ads use?

Vulnerability Analysis

Identify weaknesses in each competitor's ad strategy: