| name | creative-research |
| description | Use when researching competitor ad creatives: find competitors, brand IDs, evergreen winners, breakout winners, pattern analysis. |
Creative Competitor Research Protocol
Discover new creative concepts by analyzing competitor ads. Find validated winning concepts and adapt them for your brand.
Prerequisites
Before exploring competitors, identify your current winning ads and their patterns (angles, formats, hooks). This gives you a baseline to compare competitor insights against. Use your primary conversion metric: Purchase ROAS (ecommerce) or Cost Per Result (leadgen).
Step 1: Find Competitors
AI-Powered Discovery
Tool: ads_library_find_competitors
Parameters:
website_url: "www.yourcompany.com" # Preferred
OR brand: "Your Brand Name"
Returns: competitor brands (up to 5) with names + URLs, product keywords, niche category, market target (B2B/B2C), suggested search queries.
Competitor Selection Rules
- Match competitors by: same product category, similar AOV/price point, similar market size
- A small DTC brand can't replicate a $100M+ brand's approach — scale matters
- Search "[category]" and see which brands appear in results
- DO NOT use generic/wide search terms (e.g., "shopify apps"). Use specific category descriptors (e.g., "sale countdown shopify apps")
When AI Discovery Returns Zero Ads
- Define 2–3 parallel categories (NOT wider, but adjacent). Example: "sale countdown shopify apps" → try "conversion boost shopify apps", "sale announcement shopify apps"
- For each parallel category, find the biggest brands first
- Try
ads_library_search_brands with those brands BEFORE using keyword search
- Only use
ads_library_discover_ads keyword search as last resort
- NEVER go generic. Search terms must be relevant to the specific product function.
Step 2: Get Brand IDs
Tool: ads_library_search_brands
Parameters:
domain: "competitor.com" # More accurate than name
OR name: "Competitor Brand"
limit: 10
Returns: brand_id (needed for fetching ads), brand name, category/niches. Save brand_ids for Steps 3A/3B.
Step 3A: Evergreen Winners (Proven Concepts)
Goal: Find ads running 30+ days — longevity implies profitability.
Tool: ads_library_get_ads_by_brand_id
Parameters:
brand_ids: ["brand_id_1", "brand_id_2"]
live: "true"
order: "longest_running"
limit: 50
running_duration_min_days: 30 # Optional filter
Analysis Process
- Filter: remove ads tagged "low impression count". Focus on top 10–15 longest runners, prioritize 60+ days.
- Deep analyze with
ads_library_analyze_ad: pass top ad IDs with include_duplicates: true.
- Document patterns across winners:
| Element | What to Look For |
|---|
| Angle | What selling points repeat across winners? (Authority? Results? Price?) |
| Concept | How is the angle executed? (Testimonial? Before/after? Expert?) |
| Visual Style | Professional vs lo-fi? UGC? Product-focused? |
| Script | Common structure? (Problem → Solution → CTA) Length patterns? |
| Hook | Visual patterns? Text overlay? Audio approach? (first 3–5 seconds) |
| Format | Dominant format? (Testimonial, demo, lifestyle) |
- For each winner, suggest adaptation: their approach → your version with rationale.
Step 3B: Breakout Winners (Recent Scaling Signals)
Goal: Find concepts launched recently and repeated aggressively — indicates active scaling.
Tool: ads_library_get_ads_by_brand_id
Parameters:
brand_ids: ["brand_id_1", "brand_id_2"]
live: "true"
start_date: "[30 days ago, YYYY-MM-DD]"
order: "newest"
limit: 100
Identifying Breakout Winners
Group ads by similarity (same copy/format/visual style). A Breakout Winner is a concept that:
- Launched within 30 days
- Has been repeated/varied multiple times
- Variations launched across different dates (not just one batch)
Scaling signal levels:
- HIGH (4+ variations across multiple dates): Competitor actively scaling this concept
- MEDIUM (2–3 variations): Worth monitoring
- LOW (< 2): Testing phase
Deep analyze with ads_library_analyze_ad using include_duplicates: true.
Step 4: Alternative Discovery
By Keyword/Product
Tool: ads_library_discover_ads
Parameters:
search_query: "protein shake" # Max 6 words, specific not generic
order: "longest_running"
niches: ["health/wellness"]
display_format: ["video"]
live: true
limit: 50
Use when researching a category broadly rather than specific brands.
Brand Analytics
Tool: ads_library_get_brand_analytics
Parameters:
brand_ids: ["brand_id_1"]
Returns: total active ads, format distribution, platform breakdown. Use to decide which competitors are most active and worth deep analysis.
Key Principles
- Scale matters — compare similar-sized competitors
- Patterns > individual ads — look for what repeats across winners
- Recent > old — breakout winners (30 days) often more valuable than 180-day evergreens
- Variations = validation — multiple versions = strong signal
- Adaptation not copying — translate concepts authentically to your brand
- Speed matters — if competitor is scaling NOW, test quickly before saturation
