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Creator services

ClippingStars GEO case study

ClippingStars is a creator-services brand that ranked in Google but was rarely cited by AI search engines. Its pre-optimization GEO score was 41 out of 100.

GEO score before audit
41/100

Where ClippingStars started before optimization.

Overview

Client overview

ClippingStars is a creator-services brand that ranked in Google but was rarely cited by AI search engines. Its pre-optimization GEO score was 41 out of 100.

Industry: Creator services

Website: https://clippingstars.com

The challenge

Problem

Strong traditional SEO presence, but content was not structured for AI extraction: thin schema markup, no llms.txt, and few citable, sourced claims for models to quote.

Baseline

GEO score before audit

ClippingStars’s GEO score before optimization was 41/100.

The GEO score is the agency’s own 0–100 measure of how readable, structured, and citable a site is to AI search engines, combining citability, schema coverage, technical access for AI crawlers, and content authority signals.

Approach

Methodology

  1. 01Ran the full GEO audit across citability, schema, technical, and content
  2. 02Checked AI crawler access for GPTBot, ClaudeBot, and PerplexityBot
  3. 03Analyzed competitor citations in AI answers
What we found

Findings

  • Missing Organization and Service structured data
  • No llms.txt and incomplete robots directives for AI crawlers
  • Marketing copy lacked sourced, dated, citable statements
The plan

Recommendations

  • Implement Organization, Service, and FAQPage JSON-LD
  • Publish llms.txt and explicitly allow AI crawlers
  • Rewrite key pages with citable claims, sources, and visible dates
“
The audit made the gap obvious: we were invisible to AI answers despite ranking in Google.
MMaxim DanilovHead of Marketing
FAQ

Frequently asked questions

What was ClippingStars’ GEO score before optimization?
ClippingStars scored 41 out of 100 on its initial Generative Engine Optimization audit.
Why wasn’t ClippingStars cited by AI despite ranking in Google?
Its content lacked structured data, an llms.txt file, and citable sourced claims, so AI engines could rank-adjacent crawl it but not reliably extract and attribute information from it.

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