Google Search Ads Builder

Build a complete Google Search Ads campaign from scratch. This skill handles everything from deep keyword research through community and review language mining, to ad copy generation and campaign structure — outputting files ready to import into Google Ads Editor.

Core principle: Most early-stage teams waste their first $5K on Google Ads because of bad keyword strategy and bad structure. This skill builds the strategic keyword foundation AND a tight, well-organized campaign from day one.

When to Use

• "Set up Google Search Ads for us"
• "Build a Google Ads campaign for [product]"
• "I want to start running search ads — help me set it up"
• "Create a PPC campaign structure"
• "Generate Google Ads copy for our product"
• "Do keyword research for Google Ads"
• "What keywords should we bid on?"
• "Build a keyword strategy for paid search"
• "Find high-intent keywords in our space"

Phase 0: Intake

1. Product name + URL — What are we advertising?
2. One-line value prop — What does it do, for whom?
3. Product category — How would a buyer search for this? (e.g., "sales automation", "AI writing tool")
4. ICP — Who is searching for this? (Role, pain, company stage)
5. Monthly budget — What are you willing to spend? (Affects structure and bid recommendations)
6. Goal — Free trial sign-ups / Demo bookings / Content downloads / Direct purchase
7. Landing pages — URLs you'll send traffic to (or "need to create")
8. Competitor domains — 3-5 competitors (for keyword gap analysis)
9. Geographic targeting — Countries/regions
10. Existing keywords? — Any keywords you already know work or are currently bidding on
11. Known converting keywords? — Any existing performance data

Phase 1: Deep Keyword Research

1A: Seed Keyword Generation

From the product description and ICP, generate 3 keyword buckets:

1B: Competitive Keyword Mining

For each competitor domain, research their organic keyword rankings and ad presence using web_search:

Search: site:<competitor_domain> [product category keywords]
Search: <competitor> SEO keywords ranking
Search: <competitor> top pages organic traffic
Search: "[competitor] site:google.com/ads" OR "[competitor] PPC keywords"
Search: "[competitor]" alternative OR vs OR comparison
Search: best [product category] tools 2026

Use fetch_webpage on competitor landing pages and pricing pages to extract the language and positioning they use — these reveal keyword opportunities.

Extract keywords with buying intent — skip informational-only terms.

1C: Review Language Mining

The exact language buyers use matters more than what marketers think they search. Mine review sites for real buyer vocabulary.

Use web_search to find reviews:

Search: "[product name]" site:g2.com reviews
Search: "[product name]" site:capterra.com reviews
Search: "[competitor name]" site:g2.com reviews
Search: "best [product category]" site:g2.com

Use fetch_webpage on the top review pages to extract phrases like:

• "I was looking for a [term] that could..."
• "We switched from [X] because we needed..."
• "Best [term] for [use case]"

These phrases reveal how real buyers describe the problem and the solution — gold for keyword targeting.

1D: Reddit Community Terminology Mining

Reddit threads contain the unfiltered language your ICP actually uses.

Option A — Apify Reddit Scraper (if APIFY_API_TOKEN is set):

POST https://api.apify.com/v2/acts/trudax~reddit-scraper-lite/runs?token=${APIFY_API_TOKEN}
Content-Type: application/json

{
  "searches": ["best <category> tool OR software OR platform"],
  "maxItems": 30
}

Then poll for results:

GET https://api.apify.com/v2/acts/trudax~reddit-scraper-lite/runs/{RUN_ID}?token=${APIFY_API_TOKEN}

Once status is SUCCEEDED, fetch dataset:

GET https://api.apify.com/v2/datasets/{DATASET_ID}/items?token=${APIFY_API_TOKEN}

Output fields: Each item has dataType ("post" or "comment"), title (posts only), body, communityName, upVotes, url, createdAt.

Option B — Web search fallback:

Search: site:reddit.com "best [product category] tool" OR "recommend [product category]"
Search: site:reddit.com "[competitor name]" alternative
Search: site:reddit.com "[pain point]" solution software

Extract the terminology, slang, and product descriptions real users use in these threads.

1E: Hacker News Terminology Mining

HN discussions reveal how technical buyers describe tools and problems.

Use the free HN Algolia API:

GET https://hn.algolia.com/api/v1/search?query=<product category>&tags=story&hitsPerPage=20
GET https://hn.algolia.com/api/v1/search?query=<competitor name>&tags=story&hitsPerPage=20
GET https://hn.algolia.com/api/v1/search?query=<pain point>&tags=comment&hitsPerPage=30

No API key needed. Extract terminology and product framing from titles and comment text.

1F: Your Site Content Audit

Use fetch_webpage to crawl key pages on the user's own website:

• Homepage
• Product/features pages
• Pricing page
• Blog posts (top 5-10)
• Any existing landing pages

Identify:

• Pages that could serve as ad landing pages
• Keywords the site content already targets (leverage in ads)
• Gaps — search terms the site doesn't cover yet
• Language and positioning already in use

1G: Search Suggest & Related Terms

Search: "[category] tool" → note Google autocomplete suggestions
Search: "[category] software for [ICP role]"
Search: "[pain point] solution"
Search: "how to [problem your product solves]"

1H: Keyword Expansion

For each seed keyword discovered across all sources, expand with:

• Modifiers: best, top, free, cheap, enterprise, for startups, for [role]
• Long-tail: "[category] for [specific use case]"
• Question queries: "how to [solve problem your product addresses]"
• Comparison: "[competitor] vs [your brand]", "[competitor] alternative"

Phase 2: Keyword Architecture

2A: Funnel Stage Mapping

Organize ALL discovered keywords by buyer journey stage:

2B: Intent Classification

2C: Competitive Density Assessment

For the top 30 keywords, estimate competition level: