Structured data, entity clarity, and citations that get you cited by ChatGPT and Gemini.
Get Your Free ScanAI models like ChatGPT and Gemini don't crawl your site the way Google does — they answer from a web of structured product data, clear entity signals, and third-party sources they already trust. Most D2C sites were built for human browsing, not machine-readable clarity: no schema markup, no FAQ content answering the exact questions buyers ask, no citations on the sites AI models actually trust. So when someone asks "what's the best [category] brand," the model has nothing solid to point to — and defaults to whoever's competitor already did the structural work.
We map 8–12 buyer queries you should be found for, and your current status on each.
Product, FAQ, and Organization schema implemented across product and key pages.
Rewriting About/product pages so AI systems can confidently describe and recommend the brand.
Getting cited on 2–3 third-party sources AI models trust — review sites, comparisons, relevant directories.
An llms.txt / AI-readability feed for your site — the same setup Yogreet runs on itself.
Before: A skincare D2C brand had strong Instagram engagement but was invisible in AI search — three competitors showed up, they didn't.
What we did: Structured their product data, content, and entity signals so AI systems could confidently cite them as a trusted, specific answer.
After: Now appears as a recommended option in AI-generated answers for their core queries — visibility earned for free, every time someone asks.
Yes — the process is category-agnostic; we tailor the target queries and citations to your specific space.
Traditional SEO targets search-engine rankings; GEO/AEO targets how AI models cite and recommend brands directly in conversational answers.