Claude Skills for Paid Ads: The Cross-Platform Playbook for 2026

Step 01

Audit

Export campaign data from both platforms. Google Ads: download campaign performance reports with all columns for the last 30 days. Meta Ads: export your campaign breakdown by date, ad set, and ad level. Upload both to the same Claude Project. The audit stage answers one question: what happened? Run the Wasted Spend Audit and Search Term Leakage skills on Google data. Run the Audience Overlap Analysis and Creative Fatigue Detection skills on Meta data. Within 5 minutes, you have a complete picture of both platforms.

Step 02

Diagnose

The audit tells you what happened. The diagnosis tells you why. Run the CPA Diagnosis skill with data from both platforms and Claude identifies root causes: Is your Google CPA rising because search term drift is bringing in irrelevant traffic? Is your Meta CPA spiking because your best ad set hit frequency 4.2 and audience saturation? The cross-platform view often reveals insights invisible in single-platform analysis — like discovering your Google and Meta campaigns are competing for the same users, inflating costs on both.

Step 03

Optimize

Apply fixes based on the diagnosis. The Budget Reallocation skill models three scenarios for shifting spend between campaigns and between platforms. The A/B Test Analyzer evaluates running experiments on both Google RSAs and Meta creative variants. Optimization skills output specific, numbered recommendations with projected impact — not generic advice. A typical cross-platform optimization cycle yields 15–30% improvement in blended ROAS.

Step 04

Report

Generate a single unified report covering both platforms. The Executive Summary skill merges Google and Meta metrics into one narrative with platform-level breakdowns, blended KPIs, and trend analysis. The Weekly Digest skill creates a stakeholder-ready document with what changed, what was done, and what comes next. Teams using Claude for unified reporting cut reporting time from 5 hours to 20 minutes per week.

Step 05

Repeat

Run the full cycle weekly. Each iteration builds on the previous one — Claude retains context within the Project, so it tracks trends over time. After 4 weeks, the skills become more accurate because they have historical baselines. After 8 weeks, Claude can predict issues before they become expensive. This compounding improvement is the main advantage of a skill-based approach over ad-hoc prompting.

Skill 01

CPA Diagnosis

Identifies why your cost per acquisition changed on either platform. On Google, it checks bid strategy shifts, Quality Score changes, search term drift, and impression share movement. On Meta, it checks frequency saturation, audience overlap, creative fatigue, and placement performance. Feed it data from both platforms and it produces a ranked diagnosis with severity ratings and specific fixes. The average CPA diagnosis uncovers 2–4 actionable issues per platform.

• Google adaptation — Analyzes Quality Score, auction insights, and search term reports for intent drift
• Meta adaptation — Analyzes frequency caps, audience fatigue curves, and placement-level cost variations
• Cross-platform view — Compares CPA trends between platforms to identify systemic issues vs. platform-specific problems

Skill 02

Budget Reallocation

Models the impact of shifting spend between campaigns and between platforms. Most advertisers allocate budgets based on historical splits, not performance. This skill ranks every campaign across both platforms by cost-per-conversion efficiency, identifies donors (high CPA, low ROAS) and recipients (low CPA, high ROAS with budget constraints), and models three reallocation scenarios: conservative (10%), moderate (20%), and aggressive (35%). It shows projected conversions and blended ROAS for each scenario.

• Google adaptation — Factors in impression share lost to budget as a signal for campaigns that can absorb more spend
• Meta adaptation — Factors in audience saturation curves to predict when increased spend hits diminishing returns
• Cross-platform view — Models shifting budget from Google to Meta (or vice versa) based on marginal CPA curves

Skill 03

Anomaly Detection

Flags statistical outliers in performance data before they become expensive problems. The skill establishes a rolling baseline from your last 30 days, then identifies any metric that deviates more than 2 standard deviations. A 40% click-through-rate drop on a Tuesday that would have taken you until Friday’s review to catch gets flagged immediately. Anomaly detection across 12 Google campaigns and 8 Meta ad sets takes Claude under 90 seconds.

• Google adaptation — Monitors CPC, CTR, conversion rate, impression share, and Quality Score changes
• Meta adaptation — Monitors CPM, CTR, frequency, relevance score, and cost-per-result changes
• Cross-platform view — Correlates anomalies across platforms to detect shared causes (e.g., landing page downtime)

Skill 04

Weekly Digest

Generates a structured weekly performance report covering both platforms in one document. Includes week-over-week and month-over-month comparisons, anomaly flags, action items completed, and next-week priorities. The format is designed to send directly to stakeholders without editing — plain language, not platform jargon. Teams using this skill eliminate 4–6 hours of weekly reporting work while producing higher-quality reports.

• Google section — Campaign-level breakdown with conversion, CPA, ROAS, and impression share trends
• Meta section — Ad-set-level breakdown with reach, frequency, cost-per-result, and creative performance
• Blended section — Combined KPIs, cross-platform spend allocation, and unified recommendations

Skill 05

Executive Summary

Creates a C-suite-ready summary of paid advertising performance across all platforms. Unlike the Weekly Digest (which is for the marketing team), the Executive Summary answers three questions executives care about: How much did we spend? What did we get? What should we change? The output is a one-page document with a top-line KPI dashboard, a narrative summary, and 3 strategic recommendations ranked by revenue impact.

• Format — One page, 3 sections: KPI dashboard, narrative, and recommendations
• Audience — CFOs and CMOs who need ROI justification, not campaign-level details
• Cross-platform — Presents unified ROAS, blended CPA, and total conversion volume across Google and Meta

Skill 06

A/B Test Analyzer

Evaluates running experiments on both platforms using statistical significance testing. On Google, it analyzes RSA headline and description variants, bid strategy experiments, and landing page tests. On Meta, it evaluates creative variants, audience tests, and placement experiments. The skill calculates confidence levels, projects how long to run each test for significance, and recommends winners. It catches the #1 testing mistake: declaring winners too early with insufficient data. Tests need 95% confidence — most advertisers stop at 70%.

• Google adaptation — Analyzes RSA asset reports, Google Experiments data, and ad rotation metrics
• Meta adaptation — Analyzes creative split tests, dynamic creative element performance, and audience segment tests
• Cross-platform — Identifies learnings transferable between platforms (e.g., a headline angle winning on Google may improve Meta ad copy)

Project 01

Master Project: Cross-Platform Command Center

This Project holds your 6 cross-platform skills as custom instructions, your blended KPI targets (target CPA, target ROAS, monthly budget), and data exports from both platforms. Upload your Google Ads campaign report and Meta Ads campaign breakdown to the Project knowledge base. Set the custom instructions to: “You are a cross-platform paid ads analyst. When I provide data from Google Ads and Meta Ads, analyze both in context and provide unified recommendations. Our blended CPA target is $[X]. Our blended ROAS target is [X].”

Project 02

Google Ads Deep-Dive Project

Holds your 15 Google Ads skills, search terms reports, keyword lists, Quality Score data, and Google-specific context like target impression share and bid strategy settings. Use this Project for deep Google-specific work: negative keyword mining, Quality Score optimization, RSA copy generation. Connect MCP for live data access if you manage $50K+/month. See the MCP connector setup guide for step-by-step instructions.

Project 03

Meta Ads Deep-Dive Project

Holds your 15 Meta Ads skills, audience insights, creative performance data, and Meta-specific context like pixel events and custom conversion rules. Use this Project for creative fatigue analysis, audience overlap resolution, placement optimization, and lookalike audience building. The Meta Project benefits from including your brand guidelines and previous ad creative briefs in the knowledge base — Claude generates better creative recommendations when it understands your brand voice.