Loading page
A practical three-way breakdown of SEO, answer engine optimization, and generative engine optimization: what each one means, where they overlap, and how to run them as a single AI visibility program.
A full breakdown of Qwairy's MCP server: what each tool does, how it compares to Visiblie, Omnia, and Foglift, and why native MCP matters for GEO strategy.
SEO/GEO consultant Thibaut Huertas shares how he tripled Bluecoders' brand mentions and source citations across AI models in under 3 months, using Qwairy to identify high-value prompts and authority backlink targets.
Not all AI crawlers do the same job. Learn which bots to allow or block in robots.txt - GPTBot, ClaudeBot, PerplexityBot and more - without accidentally deleting yourself from AI answers.
Two structural reasons a single AI visibility check misleads, both visible in Google's numbers. (1) Google is not one AI surface but two - AI Overview and AI Mode - which behave like opposites: AI Mode is ~4x longer, names 2x more competitors, cites 1.7x more sources. (2) Neither surface is deterministic: ask the same question again and the brand-mention verdict flips on ~1 in 4 questions, and ~2 in 3 of the questions where the brand appears at all. Same instability on ChatGPT and Perplexity.
Comment Meilleurtaux, leader de la comparaison de crédits immobiliers en France, a utilisé Qwairy pour mesurer et améliorer sa visibilité dans les moteurs IA.
A qualitative study on 150 French unbranded prompts across 9 intent typologies. Why brand-owned editorial dominates 76% of AI citations, how negative framing wipes out official sources (×18), and what GEO teams should do about it.
Most AI crawlers read raw HTML and never run your JavaScript, so client-side content is invisible to them. Learn how to test for it and fix it with SSR, SSG, or prerendering.
A data-backed breakdown of the factors that actually get your pages cited by AI answer engines like ChatGPT and Perplexity - and what matters far less than most checklists claim.
A complete, data-backed guide to Generative Engine Optimization (GEO) for SEOs. Covers how LLMs consume and select content, semantic optimization, E-E-A-T signals, page typology, and content maintenance — with primary sources throughout.
A practical, honest look at what llms.txt is, who actually supports it, and whether adding one helps your AI visibility. Includes a step-by-step guide and realistic expectations.
The technical foundation for getting cited by AI engines: crawler access, rendering, HTML quality, structured data, and discovery. A prioritized, run-anywhere checklist for any site.