Agent skill · marketing growth · sickn33
ad-campaign-analyzer
Analyze cross-channel campaign data, quantify uncertainty, and propose evidence-labeled budget tests without overstating causality.
Why this skill is useful
Provides domain-specific knowledge on analyzing ad campaign data and proposing budget reallocations that the AI wouldn't reliably generate on its own.
What it needs
About 11k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
Ad Campaign Analyzer Overview Take raw campaign performance data and turn it into testable decisions. Normalize the inputs, distinguish descriptive results from causal evidence, quantify uncertainty when the data supports it, and propose bounded budget experiments. Core principle: Use verified measurements and explicit uncertainty to prioritize tests. This guide supports analysis, not a guarantee of optimal allocation or specialist performance. When to Use This Skill "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 Screenshots of dashboard (we'll extract the data) 2. Platform(s) — Google / Meta / LinkedIn / All 3. Time period — What date range does this cover? 4. Monthly budget — Total ad spend in this period 5. Primary goal — What conversion are you optimizing for? (Demos / Trials / Purchases / Leads) 6. Target metrics — Do you have target CPA or ROAS? If not, ask for an approved, dated benchmark source; never invent one. 7. Any known changes? — Did you change creative, budget, or targeting during this period? 8. Channels currently running — Google Ads, Meta Ads, LinkedIn Ads, Twitter/X Ads, TikTok Ads, other 9. Funnel data (if available): Lead → MQL rate MQL → SQL rate SQL → Close rate Average deal size 10. Channels you're considering but haven't tried — Want to test new channels? 11. Constraints — Minimum spend on any channel? Platform you must stay on? Before analysis, remove or mask customer names, email addresses, user IDs, and other unnecessary personal data. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/ad-campaign-analyzer--2d7179