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Nobody realizes what's happening behind the scenes with large language models. Everybody thinks they get their information from their training data...
Nobody realizes what's happening behind the scenes with large language models. Everybody thinks it gets its information from its training data. When you put in a prompt, it does a search using perplexity.
Here we see the searches.
This is where it goes deeper. It does something called ground and queries based off what it learns from its original search. It will follow up, then do searches into the brands that it learned about.
So if you're asking it to recommend you a product, it will start with a very broad search, then go deeper into the brands that it found.
This is why you need to make sure there are good things floating around about your brand on the internet. Take your reviews, put them on YouTube, put them on Facebook. These are the most clicked websites in Google search: YouTube, Reddit, Facebook, Instagram, TikTok, X.
Put positive stuff out there about your brand using the language that people search with. Review, rating, testimonial. Is your company legit?
Is your company a scam? Is your company real?
When the large language model researches your brand, it will find these positive things, making you more likely to get recommended. And if you want to learn how to do SEO that influences LMS, you get paying customers, users, warm leads calling you up, learn this conversion based SEO at compactkeywords. Com.
Nobody realizes what's happening behind the scenes with large language models.
AI visibility work depends on matching the right model, search surface, or answer format to the business outcome being optimized.
Map each AI/search surface to a task: answer extraction, public copy, citation mining, checkout readiness, media generation, or customer-intent capture.
This source is connected to AI visibility and answer readiness.
Nobody realizes what's happening behind the scenes with large language models.