paid-ads-optimize
FeaturedDiagnose wasted paid-ad spend, pacing, and allocation, then propose safe evidence-backed optimizations. Use for waste, negatives, budgets, bid changes, poor CPA or ROAS, underpacing, overspend, or scaling decisions.
AI & Automation 3,349 stars
417 forks Updated 1 weeks ago MIT
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# Paid Ads Optimization
Read `../shared/operating-contract.md` and `../shared/measurement-framework.md`. Review before changing anything.
## Diagnose before cutting
Verify the conversion signal, period completeness, spend volume, attribution model, and recent account changes. Spend with no recorded conversion can indicate broken tracking or immature data; treat it as a hypothesis until the signal and volume support an intervention. Check landing-page or operational failures before blaming targeting.
Classify the bottleneck as query/audience quality, creative fatigue, delivery/rank, budget constraint, landing-page mismatch, tracking, or economics. Use the specialized Google, Meta, X, or LinkedIn skill for live diagnosis. For other platforms, analyze only the supplied or verified data.
## Rank reversible moves
Prefer this order: exclude an irrelevant query, placement, or audience; pause the narrowest losing unit; adjust budget or bid in a measured step; then consider structural change. For a reallocation, show the current and proposed allocations, the same total budget unless the user approves an increase, and the observable hypothesis.
Do not declare a loser from a few clicks. Set a threshold appropriate to the named target CPA, conversion lag, and channel role. Preserve upper-funnel and assisted-conversion context rather than judging all campaigns on last-click CPA alone.
## Approval and follow-up
Present each exact mutation with scope, current value, proposed value,...
Details
- Author
- nowork-studio
- Repository
- nowork-studio/notfair-plugin
- Created
- 4 months ago
- Last Updated
- 1 weeks ago
- Language
- TypeScript
- License
- MIT
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