google-ads▌
kostja94/marketing-skills · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Guides Google Ads setup, campaign structure, keyword targeting, and optimization. Google Ads excels at high-intent search traffic; use when people actively search for your solution.
Paid Ads: Google Ads
Guides Google Ads setup, campaign structure, keyword targeting, and optimization. Google Ads excels at high-intent search traffic; use when people actively search for your solution.
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Two Modes: PMF Testing vs Conversion-Driven
| Mode | When | Budget | Landing page | Metrics |
|---|---|---|---|---|
| PMF testing | Pre-PMF; validate idea before building | $47–500; start small | Simple LP: headline, benefits, problem solved, CTA ("Join Waitlist," "Get Early Access") | CTR, sign-up rate, bounce rate; low CTR/high bounce = messaging/positioning issue |
| Conversion-driven | PMF validated; commercialization | Scale; ROAS target | Full funnel; ad-to-page alignment | ROAS, CAC, conversion rate |
PMF testing: No full product needed. Build landing page with Unbounce, Carrd, or Webflow. Run ads to relevant search terms; measure clicks, engagement, signups. Test messaging (e.g., "Fastest App for Freelancers" vs "Simplest Time Tracker for Teams"), pricing (different price points in ads/LP), and audiences (keyword targeting, in-market). Allow 4–6 weeks for PMax learning phase. Use as learning tool, not just marketing channel.
Reference: Marketing Cactus – Using Google Ads to Test Product-Market Fit
Campaign Structure
Account
├── Campaign: Brand (Search)
├── Campaign: Non-Brand (Search)
├── Campaign: Competitor (Search) — optional; bid on competitor brand + "alternative"/"vs"
├── Campaign: Retargeting (Display)
└── Campaign: Performance Max
Competitor Brand Keywords
When: Bid on "[Competitor] alternative," "[Competitor] vs [You]" to intercept high-intent traffic. Google allows competitor terms as keywords; you cannot use competitor names in ad copy without permission.
Landing page: Use a dedicated landing page (comparison/alternatives page), not a blog article. Users searching competitor brands expect direct alternatives—a blog increases bounce; a comparison page matches intent and converts better. See alternatives-page-generator for structure.
Best practices:
- Separate campaign; exact/phrase match; add your brand as negative
- H1 mirrors search intent (e.g., "[Competitor] vs [You]")
- Feature comparison table; one-line differentiator; strong CTA
- Expect lower Quality Score, higher CPC than non-brand; optimize LP relevance
Naming: GOOG_[Objective]_[Audience]_[Offer]_[Date] (e.g., GOOG_Search_Brand_Demo_Ongoing)
Campaign Types
| Type | Best for |
|---|---|
| Search | High-intent queries; keyword-targeted; landing page critical |
| Display | Awareness; retargeting; broader reach |
| YouTube | Video; awareness; consideration |
| Performance Max | Automated; cross-channel; feed + search + display |
Performance Max (PMax) Optimization
Learning period: Run at least 6 weeks for algorithm ramp-up. Works best as complement to Search, not replacement.
Asset groups: Organize by audience intent (e.g., high-intent searchers, cart abandoners, category researchers), not product category alone. Audience signals improve CPA and ROAS vs. no signals.
Asset requirements (per asset group):
- ≥5 images (include 1200×1200)
- ≥5 text assets (4 headlines, 5 descriptions)
- Video when possible
- Refresh creative regularly to maintain performance
Signals: Add remarketing lists and Customer Match to accelerate learning.
Weekly health check: Flag if brand terms >30% of conversions; unexpected geo conversions; any placement >15% of total spend; asset group performance below "Good."
Keyword Strategy
- Brand: Protect brand terms; exclude from non-brand campaigns
- Negative keywords: Build weekly; avoid irrelevant queries. Add support terms (login, forum, pricing, help) from keyword-research—these are existing customers, not prospects.
- Match types: Broad (discovery) → Phrase → Exact (control)
Keyword sources: Use keyword-research for keyword list, clusters, and intent. Map each cluster to a dedicated landing page; relevance improves Quality Score and lowers CPC.
Quality Score Levers
| Factor | Action |
|---|---|
| Expected CTR | Improve ad relevance; test headlines |
| Ad relevance | Align ad copy to keyword intent |
| Landing page | Ad-to-page alignment; fast load; mobile-friendly |
Target: Quality Score ≥6; higher = lower CPC, better ad rank. Benchmark: Improving Quality Score from 5 to 7 can reduce CPC by 30–50%.
Bidding Strategy
| Conversions/month | Strategy |
|---|---|
| <30 | Manual CPC (smart bidding needs volume to optimize) |
| 30–50 | Target CPA; minimum for effective smart bidding |
| 50–100 | Target CPA |
| 100+ | Target ROAS |
Smart bidding: AI-powered bidding (Target CPA, Target ROAS) typically delivers better ROI than manual when conversion volume is sufficient; requires ≥30 conversions in 30 days to work effectively.
Tracking
- Enhanced Conversions: Server-side signals for better attribution
- Offline conversion imports: B2B; CRM → Google Ads
- UTM: Consistent parameters for GA4 cross-check
Paid–Organic Cannibalization
When you rank organically (position 4+) for a keyword and also run PPC, paid ads can absorb clicks that would go to organic. Audit: Cross-reference GSC organic rankings with Search Terms report. If organic ranks well, test pausing PPC on those terms to free budget for higher-impact keywords.
Reference: Backlinko – SEO and PPC: 8 Smart Ways to Align
Pre-Launch Checklist
- Conversion tracking tested with real conversion
- Landing page loads <3s; mobile-friendly
- UTM parameters working
- Negative keyword list built (include support terms from keyword-research)
- Budget set; targeting matches audience
Related Skills
- pmf-strategy: PMF validation framework; when to use PMF testing vs conversion-driven
- paid-ads-strategy: Channel selection; budget allocation; ad-to-page alignment; competitor brand bidding
- alternatives-page-generator: Competitor brand keyword ads → dedicated LP (not blog); comparison page structure
- keyword-research: Keyword list, clusters, intent; support terms for negative keywords; PPC data feeds back SEO priority
- traffic-analysis: UTM for attribution; paid–organic cannibalization audit
- landing-page-generator: LP structure for paid traffic; PAA → FAQ
- analytics-tracking: Conversion tracking; ROAS measurement
How to use google-ads on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add google-ads
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches google-ads from GitHub repository kostja94/marketing-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate google-ads. Access the skill through slash commands (e.g., /google-ads) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★42 reviews- ★★★★★Advait Johnson· Dec 20, 2024
We added google-ads from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Mei Thompson· Nov 23, 2024
I recommend google-ads for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Layla Rahman· Nov 11, 2024
Solid pick for teams standardizing on skills: google-ads is focused, and the summary matches what you get after install.
- ★★★★★Liam Menon· Nov 3, 2024
Useful defaults in google-ads — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Liam Iyer· Oct 22, 2024
I recommend google-ads for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Chinedu Khanna· Oct 14, 2024
Useful defaults in google-ads — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Olivia Khanna· Oct 2, 2024
google-ads has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Piyush G· Sep 25, 2024
google-ads has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Mei Chen· Sep 21, 2024
google-ads reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Chinedu Shah· Sep 9, 2024
google-ads has been reliable in day-to-day use. Documentation quality is above average for community skills.
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