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Four Guiding Questions

The MakeMeRank methodology is based on four core questions:

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1. Are the foundations in place?

Check: Is your website technically readable for AI models? Do models find you in brand searches? This includes:
  • llms.txt
  • robots.txt configuration for AI bots
  • Structured data (Schema.org)
  • Clear, crawl-friendly content
The most honest visibility test: Do models mention you in general topics too, without explicitly searching for you? This corresponds to the Visibility score.

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3. What are the next steps?

From the analysis we derive prioritized actions – sorted by impact and effort.

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4. What content is missing?

Report gaps are turned into concrete content suggestions – LinkedIn and blog – aligned with your analysis.

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Research Foundation

MakeMeRank is based on:
  • Princeton / IIT Delhi – GEO: Generative Engine Optimization (2023): Strategies like citability, statistics, source citations can increase visibility in LLM answers by up to 40%.
  • Microsoft – From Discovery to Influence: A Guide to AEO and GEO (2025): Snippability patterns, content structure, robots.txt.
  • Vercel – How We’re Adapting SEO for LLMs and AI Search (2025): Passage quality, llms.txt, structured answer blocks.
Details and links: GEO Wiki – Research & Sources.

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Snippability Patterns

Answers must be “liftable” – individually understandable and citable. Proven patterns:
  • Short Answer Block – H2/H3 as question, 1–2 sentence answer, then details
  • Q&A Block – Clear question-answer pairs
  • Comparison tables – e.g. Model A vs. Model B
  • Step-by-step How-To – Numbered guides
  • Glossary entries – Definition + short explanation
Hidden content in tabs/accordions: Microsoft warns that AI systems often don’t reliably use hidden content. Core theses should be directly visible.