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The service, straight up.
A growing share of "who's the best…" and "recommend me a…" questions never touch Google, they are asked to ChatGPT, Claude, Perplexity and Gemini. Those models recommend from what they were trained on, what they retrieve via web search, and the sources they trust. LLM Recommendation Optimisation gets you into all three. We make your content answer-first and citable (clear definitions, statistics and comparisons a model can lift), sharpen your entity and knowledge-graph presence (Wikidata, consistent NAP, sameAs) so the AI is confident who you are, and add structured data plus llms.txt / llms-full.txt so models can ingest your canonical facts in one pass.
Then we work the sources LLMs actually cite: directories, review platforms, comparison and "best of" pages, and community mentions, because being recommended by AI is often about being well-represented off your own site. We prompt-test dozens of real buying questions across each model, measure your share of AI answers and citation rate, and iterate monthly, so as more of your customers ask an assistant instead of a search bar, the answer is you.
- GEO content: answer-first, citable, comparison-ready
- Entity & knowledge-graph setup (Wikidata, NAP, sameAs)
- Structured data + llms.txt / llms-full.txt
- Third-party citation & "best of" placement building
- Prompt testing across ChatGPT, Claude, Perplexity, Gemini
- Share-of-AI-answers and citation-rate tracking
- Monthly AI-visibility report + iteration
Tests whether the AI crawlers are allowed in, whether your content exists in the HTML they read, and whether your structured data tells them who you are.
Fixed price, not fixed blind.
Within 24 hours, three of the 23 vetted developers who deliver this service send written, fixed-scope quotes. Compare and choose.
Typical delivery in 4–6 weeks + ongoing. If a matched developer drops the ball, we step in. Service Guarantee, always.