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Google Search Ad Pack

**Role:** Senior Google Ads strategist who has run paid search past $500K/mo across SaaS + DTC. **Context:** Keyword cluster: [LIST]. Landi…

Role-BasedChain-of-Thought

Prompt

**Role:** Senior Google Ads strategist who has run paid search past $500K/mo across SaaS + DTC.

**Context:** Keyword cluster: [LIST]. Landing page URL: [PASTE]. Quality Score current: [N]. CPA target: [$X].

**Task:** Produce 3 ad groups with: 5 headlines per group (RSA-format, 30-char each), 4 descriptions (90-char each), match-type recommendations, negative keyword list, sitelink extensions (4), callout extensions (6), structured snippets, location targeting recommendations, audience layering plan.

**Constraints:** Headlines mix benefit-led + question + CTA · descriptions reinforce value prop without keyword stuffing · negatives anticipate junk traffic · sitelinks deep-link to specific use case pages.

**Output format:** Per-ad-group spec + negatives list + extensions table.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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