How do users typically interact with LLMs differently than search engines?

Users have genuine conversations with LLMs rather than just typing keywords. Key differences include conversational approach where users ask follow-up questions and engage in dialogue, decision-making focus where LLMs are used to help make choices and comparisons, detailed context where users provide more background information in their queries, comparative queries with common patterns like "What is the best X for?" and "Brand X vs Brand Y", and question format where users type complete questions rather than keyword fragments.

What are the best methods to discover questions users ask LLMs about my brand?

Several effective methods help identify LLM queries: Qwairy directly analyzes your brand positioning across multiple LLMs and suggests real user queries, Google Search Console regex using filters like ^(who|what|where|how|why)\s to find question-based queries, Bing Webmaster Tools to monitor search performance since ChatGPT uses Bing for real-time results, Perplexity analysis to check related questions suggested by this AI search engine, and comparative regex using ^(best|better|vs|versus|or)\s to find comparison queries.

How important are brand mentions for LLM visibility?

Brand mentions are crucial for LLM positioning because LLMs determine what terms are likely to follow based on existing mentions in their database through probability calculation. More mentions across authoritative sites increase your chances of being cited for authority building. Brand mentions should be relevant to your industry and expertise for context. The link building evolution shows strategy shifts from just getting backlinks to ensuring contextual brand mentions, and source diversity with mentions across various types of sites (blogs, forums, news) strengthens authority.

What technical SEO optimizations are important for LLMs?

Key technical optimizations for LLM visibility include: IndexNow implementation set up in Bing Webmaster Tools for faster indexing, site speed optimization by converting images to WebP format and reducing file sizes to ~100KB, 404 error management to redirect all broken pages to prevent wasted crawl budget, server optimization using quality hosting to handle traffic spikes from LLM crawlers, log analysis to track when and where LLMs visit your site to optimize crawling, and LLMs.txt file as optional future-proofing file to guide LLM crawlers.

How can I track my brand's performance and traffic from LLMs?

Track LLM performance through multiple methods: Qwairy monitoring provides weekly updates on brand visibility across ChatGPT, Perplexity, Gemini, Claude. Provider-specific tracking monitors performance by individual LLM provider and keyword. Competitor analysis compares your performance with competitors' LLM visibility. Google Analytics dashboards track referral traffic from LLMs and identify top-performing pages. Source analysis discovers which sites LLMs cite most frequently for your industry, and landing page optimization identifies which pages perform best with LLM traffic.

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How to Position Your Brand on LLMs: Complete Guide | Qwairy

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How to Position Yourself on LLMs and Attract More Traffic in 5 Steps

Luca Fancello•April 7, 2025•Updated Dec 21, 2025•19 min read•

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Learn how to improve your visibility on ChatGPT, Perplexity, and other LLMs with our comprehensive guide including tests and concrete examples.

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