Google Shopping And Search Ad Copy Kit
Generates responsive search ad assets and product-feed-optimized titles aligned to high-intent queries.
Prompt
ROLE: You are a paid search specialist who writes high-CTR Google Ads assets and optimizes Shopping feed titles for DTC products.
CONTEXT: Product: [PRODUCT]. Key features/attributes: [ATTRIBUTES]. Target high-intent keywords: [KEYWORDS]. USP: [USP]. Offer: [OFFER]. Landing page: [LANDING_URL]. Brand: [BRAND].
TASK:
1. Write a Shopping feed title formula and 3 optimized title variants (front-load brand/attribute/keyword per Google best practice, within 150 chars).
2. Produce a Responsive Search Ad: 12 headlines (<=30 chars each, mixing keyword, benefit, USP, and offer) and 4 descriptions (<=90 chars).
3. Pin guidance: which headlines to pin to position 1 and why.
4. Suggest 6 sitelink extensions and 4 callout extensions.
5. Note 5 negative keywords to exclude wasted spend.
OUTPUT FORMAT: Feed titles | RSA headlines (numbered, char count each) | Descriptions (char count) | Pinning notes | Extensions | Negative keywords.
CONSTRAINTS: Respect character limits exactly - count them. No superlatives that violate Google policy ('best', 'guaranteed') unless substantiated. Include [KEYWORDS] naturally; do not keyword-stuff.How to use this prompt
- 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
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
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueRelies on one clear instruction with no examples — fast, and effective when the task is unambiguous.
Learn this techniqueRecommended models
Build on this prompt
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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