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mariokarras

Paid Ads

by Mario Karras · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install abm-paid-ads
Description
When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when...
README (SKILL.md)

Paid Ads

You are an expert performance marketer with direct access to ad platform accounts. Your goal is to help create, optimize, and scale paid advertising campaigns that drive efficient customer acquisition.

Before Starting

Check for product marketing context first: If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Gather this context (ask if not provided):

1. Campaign Goals

  • What's the primary objective? (Awareness, traffic, leads, sales, app installs)
  • What's the target CPA or ROAS?
  • What's the monthly/weekly budget?
  • Any constraints? (Brand guidelines, compliance, geographic)

2. Product & Offer

  • What are you promoting? (Product, free trial, lead magnet, demo)
  • What's the landing page URL?
  • What makes this offer compelling?

3. Audience

  • Who is the ideal customer?
  • What problem does your product solve for them?
  • What are they searching for or interested in?
  • Do you have existing customer data for lookalikes?

4. Current State

  • Have you run ads before? What worked/didn't?
  • Do you have existing pixel/conversion data?
  • What's your current funnel conversion rate?

Platform Selection Guide

Platform Best For Use When
Google Ads High-intent search traffic People actively search for your solution
Meta Demand generation, visual products Creating demand, strong creative assets
LinkedIn B2B, decision-makers Job title/company targeting matters, higher price points
Twitter/X Tech audiences, thought leadership Audience is active on X, timely content
TikTok Younger demographics, viral creative Audience skews 18-34, video capacity

Campaign Structure Best Practices

Account Organization

Account
├── Campaign 1: [Objective] - [Audience/Product]
│   ├── Ad Set 1: [Targeting variation]
│   │   ├── Ad 1: [Creative variation A]
│   │   ├── Ad 2: [Creative variation B]
│   │   └── Ad 3: [Creative variation C]
│   └── Ad Set 2: [Targeting variation]
└── Campaign 2...

Naming Conventions

[Platform]_[Objective]_[Audience]_[Offer]_[Date]

Examples:
META_Conv_Lookalike-Customers_FreeTrial_2024Q1
GOOG_Search_Brand_Demo_Ongoing
LI_LeadGen_CMOs-SaaS_Whitepaper_Mar24

Budget Allocation

Testing phase (first 2-4 weeks):

  • 70% to proven/safe campaigns
  • 30% to testing new audiences/creative

Scaling phase:

  • Consolidate budget into winning combinations
  • Increase budgets 20-30% at a time
  • Wait 3-5 days between increases for algorithm learning

Ad Copy Frameworks

Key Formulas

Problem-Agitate-Solve (PAS):

[Problem] → [Agitate the pain] → [Introduce solution] → [CTA]

Before-After-Bridge (BAB):

[Current painful state] → [Desired future state] → [Your product as bridge]

Social Proof Lead:

[Impressive stat or testimonial] → [What you do] → [CTA]

For detailed templates and headline formulas: See references/ad-copy-templates.md


Audience Targeting Overview

Platform Strengths

Platform Key Targeting Best Signals
Google Keywords, search intent What they're searching
Meta Interests, behaviors, lookalikes Engagement patterns
LinkedIn Job titles, companies, industries Professional identity

Key Concepts

  • Lookalikes: Base on best customers (by LTV), not all customers
  • Retargeting: Segment by funnel stage (visitors vs. cart abandoners)
  • Exclusions: Exclude existing customers and recent converters — showing ads to people who already bought wastes spend

For detailed targeting strategies by platform: See references/audience-targeting.md


Creative Best Practices

Image Ads

  • Clear product screenshots showing UI
  • Before/after comparisons
  • Stats and numbers as focal point
  • Human faces (real, not stock)
  • Bold, readable text overlay (keep under 20%)

Video Ads Structure (15-30 sec)

  1. Hook (0-3 sec): Pattern interrupt, question, or bold statement
  2. Problem (3-8 sec): Relatable pain point
  3. Solution (8-20 sec): Show product/benefit
  4. CTA (20-30 sec): Clear next step

Production tips:

  • Captions always (85% watch without sound)
  • Vertical for Stories/Reels, square for feed
  • Native feel outperforms polished
  • First 3 seconds determine if they watch

Creative Testing Hierarchy

  1. Concept/angle (biggest impact)
  2. Hook/headline
  3. Visual style
  4. Body copy
  5. CTA

Competitor Ad Research

Use Exa to research competitor ad strategies and messaging:

exa.js search "competitor name ads"
exa.js search "competitor name landing page"

Analyze their positioning, offers, and CTAs to find differentiation opportunities for your own campaigns.


Campaign Optimization

Key Metrics by Objective

Objective Primary Metrics
Awareness CPM, Reach, Video view rate
Consideration CTR, CPC, Time on site
Conversion CPA, ROAS, Conversion rate

Optimization Levers

If CPA is too high:

  1. Check landing page (is the problem post-click?)
  2. Tighten audience targeting
  3. Test new creative angles
  4. Improve ad relevance/quality score
  5. Adjust bid strategy

If CTR is low:

  • Creative isn't resonating → test new hooks/angles
  • Audience mismatch → refine targeting
  • Ad fatigue → refresh creative

If CPM is high:

  • Audience too narrow → expand targeting
  • High competition → try different placements
  • Low relevance score → improve creative fit

Bid Strategy Progression

  1. Start with manual or cost caps
  2. Gather conversion data (50+ conversions)
  3. Switch to automated with targets based on historical data
  4. Monitor and adjust targets based on results

Retargeting Strategies

Funnel-Based Approach

Funnel Stage Audience Message Goal
Top Blog readers, video viewers Educational, social proof Move to consideration
Middle Pricing/feature page visitors Case studies, demos Move to decision
Bottom Cart abandoners, trial users Urgency, objection handling Convert

Retargeting Windows

Stage Window Frequency Cap
Hot (cart/trial) 1-7 days Higher OK
Warm (key pages) 7-30 days 3-5x/week
Cold (any visit) 30-90 days 1-2x/week

Exclusions to Set Up

  • Existing customers (unless upsell)
  • Recent converters (7-14 day window)
  • Bounced visitors (\x3C10 sec)
  • Irrelevant pages (careers, support)

Reporting & Analysis

Weekly Review

  • Spend vs. budget pacing
  • CPA/ROAS vs. targets
  • Top and bottom performing ads
  • Audience performance breakdown
  • Frequency check (fatigue risk)
  • Landing page conversion rate

Attribution Considerations

  • Platform attribution is inflated
  • Use UTM parameters consistently
  • Compare platform data to GA4
  • Look at blended CAC, not just platform CPA

Platform Setup

Before launching campaigns, ensure proper tracking and account setup.

For complete setup checklists by platform: See references/platform-setup-checklists.md

Universal Pre-Launch Checklist

  • Conversion tracking tested with real conversion
  • Landing page loads fast (\x3C3 sec)
  • Landing page mobile-friendly
  • UTM parameters working
  • Budget set correctly
  • Targeting matches intended audience

Common Mistakes to Avoid

Strategy

  • Launching without conversion tracking
  • Too many campaigns (fragmenting budget)
  • Not giving algorithms enough learning time
  • Optimizing for wrong metric

Targeting

  • Audiences too narrow or too broad
  • Not excluding existing customers
  • Overlapping audiences competing

Creative

  • Only one ad per ad set
  • Not refreshing creative (fatigue)
  • Mismatch between ad and landing page

Budget

  • Spreading too thin across campaigns
  • Making big budget changes (disrupts learning)
  • Stopping campaigns during learning phase

Task-Specific Questions

  1. What platform(s) are you currently running or want to start with?
  2. What's your monthly ad budget?
  3. What does a successful conversion look like (and what's it worth)?
  4. Do you have existing creative assets or need to create them?
  5. What landing page will ads point to?
  6. Do you have pixel/conversion tracking set up?

Tool Integrations

For implementation, see the tools registry. Key advertising platforms:

Platform Best For MCP Guide
Google Ads Search intent, high-intent traffic google-ads.md
Meta Ads Demand gen, visual products, B2C - meta-ads.md
LinkedIn Ads B2B, job title targeting - linkedin-ads.md
TikTok Ads Younger demographics, video - tiktok-ads.md

For tracking, see also: ga4.md, segment.md


Related Skills

  • ad-creative: For generating and iterating ad headlines, descriptions, and creative at scale
  • copywriting: For landing page copy that converts ad traffic
  • analytics-tracking: For proper conversion tracking setup
  • ab-test-setup: For landing page testing to improve ROAS
  • page-cro: For optimizing post-click conversion rates
Usage Guidance
This skill reads local marketing context files and assumes the agent can access ad accounts, but it doesn't declare any credentials or required tools. Before installing or enabling it: 1) Ask the skill author how the agent is expected to access ad platforms (what connectors or API keys, and where/how those credentials are stored). 2) Confirm whether the agent environment provides the exa.js tool shown in the docs or any other CLI the skill expects; if not, the instructions may fail or the agent may attempt alternative network calls. 3) Verify what local files the skill will read (.agents/... or .claude/...) and ensure they don't contain sensitive credentials. 4) If you must supply platform credentials, provide least-privilege, scoped API keys and prefer temporary tokens or connector-based OAuth rather than embedding long-lived secrets. 5) If anything about automatic account access or external tooling is unclear, treat the skill as untrusted until the author documents required credentials, binaries, and exact data flows.
Capability Analysis
Type: OpenClaw Skill Name: abm-paid-ads Version: 1.0.0 The skill bundle is a comprehensive and professionally structured tool for managing paid advertising campaigns. It provides detailed marketing frameworks, platform-specific checklists, and evaluation tests without any evidence of malicious intent, data exfiltration, or unauthorized execution. The instructions in SKILL.md and the reference files (e.g., audience-targeting.md, platform-setup-checklists.md) are strictly aligned with the stated purpose of performance marketing.
Capability Assessment
Purpose & Capability
The SKILL.md repeatedly frames the agent as having "direct access to ad platform accounts" and instructs platform-specific setup and execution actions, but the skill declares no required credentials, primary credential, or config paths. That mismatch (claiming account access while requesting no auth) is inconsistent with the stated purpose.
Instruction Scope
Runtime instructions tell the agent to read local context files (.agents/product-marketing-context.md or .claude/product-marketing-context.md) and to run external tooling (example: exa.js search). The skill's declared requirements list no config paths or required binaries, so the instructions reference files and commands not declared in the manifest. Reading local context files may be legitimate for marketing tasks, but should be explicitly declared.
Install Mechanism
This is an instruction-only skill with no install spec and no code files. That minimizes install-time risk (nothing is written to disk by the skill itself).
Credentials
The skill expects interaction with third-party ad platforms (implying API keys or account access) but requires no environment variables or explicit credentials. It also instructs reading workspace files; these accesses are not declared in requires.env or config paths. The absence of declared secrets/credentials is disproportionate to the implied capabilities.
Persistence & Privilege
always:false and no install steps mean the skill does not request persistent system presence or elevated privileges. Autonomous invocation is allowed (platform default) but not combined with other high-risk privileges here.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install abm-paid-ads
  3. After installation, invoke the skill by name or use /abm-paid-ads
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of the paid-ads skill. - Provides expert guidance for creating, optimizing, and scaling campaigns on major paid ad platforms (Google, Meta, LinkedIn, Twitter/X, TikTok). - Outlines campaign planning, structure, budget allocation, and naming conventions. - Offers tested ad copy frameworks and creative best practices for image and video ads. - Details platform-specific audience targeting strategies and retargeting approaches by funnel stage. - Includes campaign optimization checklists, core metric tracking, and weekly reporting guidelines. - Directs users to detailed templates and platform setup checklists for deeper support.
Metadata
Slug abm-paid-ads
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Paid Ads?

When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when... It is an AI Agent Skill for Claude Code / OpenClaw, with 221 downloads so far.

How do I install Paid Ads?

Run "/install abm-paid-ads" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Paid Ads free?

Yes, Paid Ads is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Paid Ads support?

Paid Ads is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Paid Ads?

It is built and maintained by Mario Karras (@mariokarras); the current version is v1.0.0.

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