ad-campaign-analyzer

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Analyze ad campaign performance data (Google, Meta, LinkedIn) to identify what's working, what's wasting budget, and specific cut/scale/test recommendations. Runs statistical analysis, funnel diagnostics, and multi-channel budget reallocation with specific dollar-amount shift recommendations and scenario modeling.

AI & Automation 1,055 stars 194 forks Updated 3 days ago MIT

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Skill Content

# Ad Campaign Analyzer Take raw campaign performance data and turn it into clear decisions. This skill doesn't just summarize metrics — it diagnoses problems, identifies winners, checks statistical significance, and tells you exactly what to cut, scale, and test next. Then it goes further: it compares channels on equal terms, finds where you're over-spending vs under-spending relative to results, and produces a concrete budget reallocation plan. **Core principle:** Most startup founders check their ad dashboard, see a ROAS number, and either panic or celebrate. This skill gives you the nuanced analysis a paid media specialist would: what's actually significant, what's noise, and where your next dollar should go. It also solves the allocation problem — most startups either spread budget too thin across channels (no channel gets enough to learn) or dump everything into one channel (missing cheaper opportunities elsewhere). ## When to Use - "Analyze my Google Ads performance" - "Which ads should I kill?" - "Is this campaign working?" - "Where am I wasting ad spend?" - "Optimize my Meta Ads" - "How should I split my ad budget?" - "Should I spend more on Google or Meta?" - "Reallocate my ad spend across channels" - "Where am I getting the best return?" - "I have $X/month for ads — how should I distribute it?" ## Phase 0: Intake 1. **Campaign data** — One of: - CSV export from Google Ads / Meta Ads Manager / LinkedIn Campaign Manager - Pasted performance table - Scre...

Details

Author
gooseworks-ai
Repository
gooseworks-ai/goose-skills
Created
4 months ago
Last Updated
3 days ago
Language
Python
License
MIT

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