Ads Performance Analytics
Skill Verified ActiveHow to read paid media dashboards without fooling yourself. Attribution models, platform reporting quirks, multi-platform reconciliation, ROAS vs LTV horizon traps, statistical noise in performance metrics, incrementality testing, and the failure modes that produce expensive lessons. Triggers on read paid media dashboard, attribution analysis, ROAS vs LTV, multi-platform reconciliation, ad incrementality, geo holdout, conversion lift study, ghost bidding, paid media reporting, board-deck paid media metrics, blended CAC, MMM, MTA, last-click attribution. Also triggers when a marketer is about to scale, kill, or rebudget a campaign based on platform metrics, or when reconciling platform reports against warehouse revenue.
To equip marketers and analysts with the knowledge and framework to accurately interpret paid media performance data, enabling sounder strategic decisions and preventing wasted budget due to misinterpretation.
Features
- In-depth analysis of attribution models and their biases
- Guidance on reconciling platform data with warehouse truth
- Frameworks for understanding ROAS vs. LTV trade-offs
- Methodologies for incrementality testing (geo holdout, lift studies)
- Identification and analysis of common reporting failures and pitfalls
Use Cases
- Interpreting paid media dashboard reports without self-deception
- Reconciling conflicting data between advertising platforms and internal warehouses
- Evaluating the true incremental value of paid media campaigns
- Making strategic budget allocation decisions based on reliable LTV and CAC insights
Non-Goals
- Developing paid media strategy or campaign planning
- Producing creative assets or ad copy
- Operating platform-specific tooling or MCPs directly
- Providing real-time campaign optimization; focuses on analytical interpretation
Installation
npx skills add rampstackco/claude-skillsRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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