How does it improve ad copywriting?

It utilizes proven marketing frameworks such as Problem-Agitate-Solve (PAS) and Before-After-Bridge (BAB) to create compelling, conversion-oriented copy.

Which advertising platforms are supported by this skill?

The skill provides specific strategies and best practices for Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, and TikTok.

Does it integrate with my existing marketing context?

The skill is designed to automatically read your product-marketing-context.md file to ensure all ad strategies align with your specific brand and product goals.

Can it help with audience targeting?

Yes, it provides guidance on interest-based targeting, creating lookalike audiences from LTV data, and setting up funnel-based retargeting windows.

How does it handle campaign optimization?

It provides a systematic approach to troubleshooting high CPA or low CTR, including creative refreshes, audience refinement, and landing page optimization.

Paid Ads Campaign Specialist

Name: Paid Ads Campaign Specialist
Author: fianchettogianni

byfianchettogianni

0•

Marketing Automation

Architects, manages, and optimizes multi-platform paid advertising campaigns to maximize ROAS and customer acquisition.

The Paid Ads skill empowers Claude to act as a senior performance marketer, providing expert guidance for Google Ads, Meta, LinkedIn, TikTok, and X. It facilitates the entire campaign lifecycle, from initial strategy and audience targeting to ad copy creation using high-conversion frameworks like Problem-Agitate-Solve (PAS). By implementing standardized naming conventions, budget allocation strategies, and rigorous creative testing hierarchies, this skill helps users scale their paid media efforts efficiently while maintaining a focus on key performance indicators like CPA and ROAS.

Key Features

010 GitHub stars

02Scaling guidelines for budget allocation and algorithm learning

03Ad copy generation using PAS and BAB psychological frameworks

04Multi-platform strategy for Google, Meta, LinkedIn, and TikTok

05Creative best practices for high-performing image and video assets

06Audience targeting logic for lookalikes, retargeting, and exclusions

Use Cases

01Optimizing underperforming campaigns by diagnosing high CPA or low CTR

02Creating a retargeting funnel based on specific user behavior and intent

03Launching a structured PPC campaign from scratch with proper naming and tracking

Key Features

010 GitHub stars

02Scaling guidelines for budget allocation and algorithm learning

03Ad copy generation using PAS and BAB psychological frameworks

04Multi-platform strategy for Google, Meta, LinkedIn, and TikTok

05Creative best practices for high-performing image and video assets

06Audience targeting logic for lookalikes, retargeting, and exclusions

Use Cases

01Optimizing underperforming campaigns by diagnosing high CPA or low CTR

02Creating a retargeting funnel based on specific user behavior and intent

03Launching a structured PPC campaign from scratch with proper naming and tracking