What problem does it solve? Running paid ads without a disciplined operating system leads to wasted budget, junk leads, and emotional kill/scale decisions. This Skill gives an AI agent the playbooks, thresholds, and frameworks of an expert performance marketer so campaigns are structured, measured, and optimized against real unit economics. ## Core Features & Use Cases - Platform Strategy & Selection: Choose between Google Ads, Meta, LinkedIn, TikTok, and Twitter/X based on audience, intent, and budget, with modern guidance like Meta's Andromeda-era broad targeting and creative-first approach. - Operational Playbooks: Deep reference playbooks cover B2B demand lifecycle budgeting, kill rules (2-3x target CPL), LinkedIn bidding progression and penetration-based scaling, Google Search intent ladders and match-type gates, and ABM account targeting. - Tracking & Measurement: Conversion pixel and server-side (CAPI) setup guidance, offline conversion imports, lead quality scoring (Urgency/Budget/Fit), and breakeven CPL/CPC math derived from deal economics. - Use Case: A B2B SaaS founder with $15k/month asks where to advertise. The Skill checks product marketing context, recommends LinkedIn plus high-intent Google Search, structures campaigns with naming conventions and independent budgets, and sets kill rules tied to breakeven CPL. ## Quick Start Ask the agent to plan a paid ads strategy for your product, including platform choice, budget allocation, campaign structure, and optimization rules.