paid-ads

Create, optimize, and scale paid advertising campaigns across Google Ads, Meta, LinkedIn, Twitter/X, and TikTok.

Updated Mar 27, 2026
One-click install
npx skills add https://github.com/CenredJun/openclaw-claudecode-setup-kit --skill paid-ads-cenredjun
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: paid-ads
Source: https://github.com/CenredJun/openclaw-claudecode-setup-kit/tree/main/skills/paid-ads
Command: npx skills add https://github.com/CenredJun/openclaw-claudecode-setup-kit --skill paid-ads-cenredjun

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Paid advertising is complex and fragmented across platforms, budgets, and audiences, making it hard to launch effective campaigns, control spend, and consistently acquire customers at an efficient cost. This Skill gives tactical guidance to set measurable goals, pick the right platforms, structure campaigns, and apply optimization levers so ads drive predictable acquisition outcomes.

Core Features & Use Cases

  • Platform selection & strategy: Recommend the best mix of Google Ads, Meta, LinkedIn, Twitter/X, TikTok and others based on intent, audience, and budget.
  • Campaign structure & naming: Provide templates for account organization, ad group/ad splits, and naming conventions for reliable scaling and reporting.
  • Audience & retargeting: Define targeting, lookalike strategies, exclusion rules, and funnel-based retargeting windows and messaging.
  • Creative & testing frameworks: Offer ad copy formulas, video/image best practices, and a testing hierarchy to iterate quickly.
  • Optimization & reporting: Diagnostic checklist for CPA/ROAS issues, bid progression guidance, frequency controls, and weekly reporting cadence.
  • Use Case: Plan and scale a B2B lead-gen campaign on LinkedIn + Google Search with retargeting on Meta, including budget splits, KPI targets, and a 4-week testing plan.

Quick Start

Tell the assistant your campaign goal, monthly ad budget, primary offer and landing page, and ask for a recommended platform mix, initial structure, and a 4-week testing plan.

Frequently Asked Questions about paid-ads

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I structure ad campaigns to improve ROAS across Google Ads and Meta?

To improve ROAS, structure campaigns using clear naming conventions, distinct ad groups for audience splits, and funnel-based retargeting windows. This organization ensures reliable scaling, accurate reporting, and efficient customer acquisition across Google Ads and Meta.

What's the best way to allocate budget for B2B lead-gen campaigns on LinkedIn?

For B2B lead-gen campaigns on LinkedIn, allocate budget by defining KPI targets and using a 4-week testing plan. Split spend between LinkedIn and Google Search based on audience intent, then apply diagnostic checklists to control CPA.

How does retargeting work for paid ads across different platforms like TikTok and Twitter/X?

Retargeting works by defining exclusion rules, lookalike strategies, and specific retargeting windows based on funnel stages. It applies across TikTok, Twitter/X, Meta, and Google Ads to re-engage audiences with tailored messaging for better conversion.

Do I need conversion tracking pixels to optimize paid advertising campaigns?

Yes, you need conversion tracking pixels or conversion data to optimize paid advertising campaigns. Tracking pixels are required to measure results, apply optimization levers, calculate CPA/ROAS, and execute bid progression guidance.

Why does my CPA spike during paid ad scaling and how can I fix it?

Your CPA spikes during paid ad scaling due to frequency fatigue or incorrect bid progression. Fix it using a diagnostic checklist for CPA/ROAS issues, applying frequency controls, and following a structured weekly reporting cadence for optimization.

Can I use the same ad creative testing framework for both LinkedIn and Meta?

Yes, you can use the same creative testing framework for LinkedIn and Meta. It provides ad copy formulas, video and image best practices, and a structured testing hierarchy to iterate quickly across different ad platforms.