What the Microsoft Ads copy adaptation from Google RSA assets prompt does

Act as a Microsoft Advertising copy adaptation and migration specialist for US and UK campaigns.

The prompt will, at minimum:

  • Verify current Microsoft Advertising responsive search ad fields, character limits, editorial policies and import differences from official documentation
  • Audit the source Google RSA assets by headline role, description role, pinning, keyword use, claim source, landing page and market; do not assume Google approval implies Microsoft approval
  • Keep US and UK modules separate for spelling, currency, date, legal source, promotion language and consumer terminology
  • Preserve high-value concepts only when the supplied performance notes are comparable; mark platform-specific performance inference as UNVERIFIED
  • Rebuild headline and description portfolios to achieve role diversity: brand, category, benefit, proof, offer, service, urgency only when evidenced, and CTA

Who it is for

Gökhan Güzel's e-commerce prompt for ChatGPT users: marketers, founders, agencies and consultants who need an auditable, evidence-based deliverable instead of generic advice.

What you get

  • Source Google RSA audit
  • US and UK market modules
  • Source-to-target asset mapping
  • Microsoft Ads headline and description sets
  • Character, editorial and destination QA

Variables

PlaceholderPurpose
{{approved_claims}}Provide the exact value or source for approved claims; include definition, relevant URL or attached file. Use UNKNOWN when unavailable and never substitute an industry average
{{audience_segments}}Target audience, segment, persona, customer/player or industry group
{{brand_name}}Provide the exact value or source for brand name; include definition, relevant URL or attached file. Use UNKNOWN when unavailable and never substitute an industry average
{{brand_voice}}Provide the exact value or source for brand voice; include definition, relevant URL or attached file. Use UNKNOWN when unavailable and never substitute an industry average
{{constraints}}Provide the exact value or source for constraints; include definition, relevant URL or attached file. Use UNKNOWN when unavailable and never substitute an industry average
{{google_rsa_assets}}Provide the exact value or source for google rsa assets; include definition, relevant URL or attached file. Use UNKNOWN when unavailable and never substitute an industry average
{{keyword_themes}}Provide the exact value or source for keyword themes; include definition, relevant URL or attached file. Use UNKNOWN when unavailable and never substitute an industry average
{{landing_pages}}Provide the exact value or source for landing pages; include definition, relevant URL or attached file. Use UNKNOWN when unavailable and never substitute an industry average
{{offer_details}}Provide the exact value or source for offer details; include definition, relevant URL or attached file. Use UNKNOWN when unavailable and never substitute an industry average
{{performance_notes}}Provide the exact value or source for performance notes; include definition, relevant URL or attached file. Use UNKNOWN when unavailable and never substitute an industry average
{{required_variants}}Provide the exact value or source for required variants; include definition, relevant URL or attached file. Use UNKNOWN when unavailable and never substitute an industry average
{{target_market}}Target market; UNKNOWN if unavailable

How to use

Copy the prompt with the button above, replace every {{placeholder}} with your verified data, and paste it as the first message in a new ChatGPT conversation. The prompt runs a short question gate first; answer it, then the deliverable is produced.

Run Microsoft Ads copy adaptation from Google RSA assets in ChatGPT

Open a new ChatGPT chat, paste the filled-in Microsoft Ads copy adaptation from Google RSA assets prompt and answer the short question gate. ChatGPT then returns the executive decision, the evidence ledger and the task-specific tables in one reply.

Source

Original file in the multilingual prompt library on GitHub: