/google-search-ads-builder

name: google-search-ads-builder
description: >
  End-to-end Google Search Ads campaign builder. Performs deep keyword research
  (competitor SEO, review language mining, Reddit/HN community terminology, site audit),
  builds keyword architecture with funnel mapping and intent classification, creates
  ad group structure, generates headline/description variants, builds negative keyword
  lists, recommends bid strategy, and exports a campaign-ready CSV for Google Ads Editor import.
tags: [ads]

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:

| Bucket | Intent | Examples | |--------|--------|---------| | **Problem-aware** | Searching for solutions to a pain | "how to automate outbound", "fix slow sales pipeline" | | **Solution-aware** | Searching for a category of product | "AI SDR tool", "outbound automation software" | | **Brand/Competitor** | Searching for you or competitors by name | "[your brand]", "[competitor] alternative" |

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 pag