PlaybookPrompts

Write RSA headline and description sets from a campaign brief

Marketing & SEO paid-searchgoogle-adscopywriting

Google's Responsive Search Ads require 15 headlines and 4 descriptions that pin cleanly against each other. Writing enough variants without repeating the same idea is tedious — this prompt does the inventory work for you.

Prompt
You are a paid search copywriter. Using the campaign brief below, generate a complete RSA asset set for Google Ads.

1. Write exactly 15 unique headlines (max 30 characters each). After each headline, add a character count in parentheses.
2. Write exactly 4 descriptions (max 90 characters each). Add character counts.
3. Group the 15 headlines into these buckets and label them: [Value prop], [Feature], [CTA], [Urgency/Social proof], [Keyword inclusion].
4. Flag any headline or description that contains a superlative claim (e.g., 'best', 'fastest') — note that these require substantiation.
5. Do not repeat the same core idea across more than two headlines. Point out any near-duplicates before finalizing.

Edge cases: If {{LANDING_PAGE_OFFER}} is vague, state what additional information you need before writing. Character limits are hard — do not suggest edits that exceed them.

Product/service: {{PRODUCT_OR_SERVICE}}
Target audience: {{TARGET_AUDIENCE}}
Landing page offer: {{LANDING_PAGE_OFFER}}
Top 3 keywords to include: {{TOP_KEYWORDS}}
Variables to fill in
  • {{PRODUCT_OR_SERVICE}}
  • {{TARGET_AUDIENCE}}
  • {{LANDING_PAGE_OFFER}}
  • {{TOP_KEYWORDS}}

How to use this prompt

  1. Copy the prompt above (Copy button on the top-right).
  2. Replace each {{VAR}} with your own value. Variables: {{PRODUCT_OR_SERVICE}}{{TARGET_AUDIENCE}}{{LANDING_PAGE_OFFER}}{{TOP_KEYWORDS}}.
  3. Paste it into one of the recommended tools below.
  4. Iterate: tighten constraints in the prompt if the output is generic.

Why this prompt is structured this way

The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.

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