competitor-ad-intelligence

# 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:

| 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 Distribution

| 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] |

### 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:

| Dimension | Analysis |
|-----------|----------|
| **Strategic intent** | What is this campaign trying to achie