AI Prompts for Ad Copy
Prompts for writing high-converting ad campaigns across search, social, and display channels.
Write three Google Search ad headlines under 30 characters for this product.
Generate a Facebook ad primary text for this offer targeting this audience.
Write a LinkedIn ad copy for this B2B product aimed at senior managers.
Create five ad copy variations to A/B test for this campaign.
Write a retargeting ad for users who visited this page but did not convert.
Rewrite this ad copy to emphasise urgency and scarcity.
Generate display ad copy in three sizes: short, medium, and long.
Write a YouTube pre-roll ad script under 30 seconds for this product.
Create ad copy that addresses the top three objections for this offer.
Write a benefit-focused ad headline and description for this feature.
How to Use These Prompts
You can copy any prompt above and use it with tools like ChatGPT, Claude, or other AI assistants.
- 1Copy the prompt
- 2Paste it into your AI assistant
- 3Replace placeholders with your specific context
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Frequently Asked Questions
What are AI ad copy prompts?
AI ad copy prompts are structured instructions given to AI assistants like ChatGPT or Claude to help with ad copy tasks. You provide relevant context — such as code snippets, error messages, or requirements — so the AI can give targeted, actionable suggestions.
How do I use ChatGPT or Claude for ad copy?
Copy one of the prompts from this page, paste it into ChatGPT or Claude, and include your specific context such as code, error output, or requirements. Providing more detail helps the AI give more accurate and useful responses.
What should I include in a ad copy prompt?
The best ad copy prompts include relevant context such as the programming language or platform, any error messages or expected behaviour, and what you have already tried. This helps the AI assistant understand the problem and give more precise guidance.
Can AI fully automate ad copy?
AI tools can significantly speed up ad copy tasks by generating suggestions, identifying issues, and drafting solutions. However, professionals should review all AI output carefully before applying it, especially in production environments.