LLM SEO: the guide written from measurement

LLM SEO is the practice of making a brand visible inside the answers of AI engines such as ChatGPT, Perplexity and Google AI when buyers ask what to choose. Botanik measures that visibility in three states, Absent, Mentioned and Recommended, with a published, versioned method: Méthode Oracle v2.3, updated July 2026, reusable under CC BY 4.0.

Ask ChatGPT which online bank to choose, and it answers with a shortlist. Your brand is in it, or it is not. Botanik scores that outcome in three states: Absent (cited in fewer than 5% of a prompt's runs), Mentioned (cited in at least 5% of runs without being the first recommendation), and Recommended (the first recommendation in at least 25% of runs). One prompt, one engine, one run proves nothing. The states are computed across repeated runs, and that is the point.

This guide takes one position: measurement before opinion. Every number on this page comes from a published Botanik page: chiefly Méthode Oracle v2.3 (July 2026) and the Baromètre GEO France, edition T3 2026, collected on August 1, 2026, both reusable under CC BY 4.0, plus the public price grid and the buying guide updated July 2026. Nothing here is a screenshot, an anecdote, or a vibe.

One conviction frames the work, stated in Botanik's manifesto: visibility is cultivated, it is not hacked. There is no trick that flips an engine's answer overnight. There is a measurable state, a set of levers, and a re-measurement that tells you whether the levers worked. That loop is what the rest of this page describes.

AI engines do not share one ranking. ChatGPT leans on its corpus and on Bing search, while Gemini draws on the Google index and its SEO signals. In Botanik's Baromètre GEO France, the 3 engines tested named a different number 1 in 2 of the 4 published markets.

Buyers question engines with four intents, and Botanik's Oracle corpus mirrors them: discovery ("how do I choose…"), comparison ("which is the best…"), local ("… near me") and validation ("reviews of…"). The prompts are extracted from real demand data, search plus conversational, reformulated as natural questions, then weighted by demand volume: a heavily asked prompt weighs more than a niche one.

Each engine assembles its answers from different raw material. ChatGPT relies heavily on its corpus and on Bing search. Gemini draws on the Google index and its SEO signals. The same brand can be Recommended on one engine and Absent on another, which is why serious measurement queries each engine separately, with the same prompts, under the same conditions, via API.

Answers also move between runs of the same prompt. That variability is not a bug you can wish away. It is a property you measure. The findings below quantify it.

Citability is earned in two places: on your own pages and in the sources engines read. Botanik's implementation work targets three recurring technical barriers, heavy JavaScript, a missing llms.txt file and incomplete Schema.org markup, then builds presence in the sources engines cite, from comparison sites to Wikipedia and Reddit.

On the page, two things matter in Botanik's implementation work: content designed to be cited, and the removal of three recurring technical barriers: heavy JavaScript, a missing llms.txt file, and incomplete Schema.org markup. Adoption of llms.txt is still marginal: 3.2% of sites have deployed one. The field is early, which means most of your competitors have not moved yet.

Off the page, engines cite sources. Botanik places clients in the sources engines actually draw from: comparison sites, press and regional dailies, authority directories, Wikipedia, Reddit and LinkedIn. This is slower work than publishing on your own domain, and it is where a large part of citation is decided: an engine cannot recommend what its sources never mention.

Which sources matter most depends on the engine where you are losing. ChatGPT leans on Bing and its corpus. Gemini leans on the Google index and its SEO signals. A per-engine verdict tells you where to put the effort first.

First citations in LLM SEO move in 6 to 10 weeks. A durable shift from Mentioned to Recommended plays out over 4 to 6 months, because engines, classic and AI alike, take 3 to 4 months to re-crawl, re-cite and re-rank. Botanik's Pousse plan (Pousse, the sprout) carries a 6-month engagement for that reason.

Botanik's buying guide sets a hard rule for any provider: 30 days is the deadline by which you must have a deliverable in hand, not a discovery phase. Botanik's own calendar runs on that clock. At 30 days: a score per engine (Absent, Mentioned or Recommended), a baseline signed and measured by a third-party tool, and a prioritized roadmap. At 60 days: content and structured data published, placement under way in the sources engines cite, and a first dated competitive comparison. At 90 days: a per-engine report against the baseline, your movement versus 3 competitors, and a decision: continue, adjust, or stop.

The 6-month engagement on Pousse follows from engine behavior, not from sales preference. Engines, classic and AI alike, take 3 to 4 months to re-crawl, re-cite and re-rank a market. Below 6 months, you pay to sow without ever harvesting.

Botanik's free scan answers one question in 60 seconds: do AI engines recommend you? It needs no account and no card, returns a verdict per engine, Absent, Mentioned or Recommended, and runs on the Oracle methodology, which is published in full and reusable under a CC BY 4.0 license.

The scan queries ChatGPT with and without web search, Gemini and Perplexity: the four surfaces it tests. Pick your sector, get your verdict per engine. It is the fastest honest answer to "where do I stand", and it costs you one minute.

If you would rather measure yourself, the full specification is public. Corpus: up to 5,000 prompts per market, built from real demand data, search plus conversational, weighted by demand volume, across the four intents. Protocol: each prompt runs 5 times per engine, via API, under the same conditions, and the median is reported with a ± stability band (the interquartile range). Scoring: Reciprocal Rank Fusion with k = 60, where score(brand) = Σ 1 / (k + rank), and an absence contributes zero.

Two rules keep the numbers honest. Thresholds: Absent means cited in fewer than 5% of a prompt's runs, Mentioned means at least 5% without being the first recommendation, Recommended means the first recommendation in at least 25% of runs. Significance: a variation from one edition to the next counts only if it exceeds the sum of the two stability bands. Below that, it is noise, and it is written as noise in the reports.

Cite it or rebuild it: both are allowed. "Méthode Oracle v2.3", Botanik, juillet 2026, botanik.ai/methode-oracle, free reuse with attribution, CC BY 4.0. The Baromètre keeps every collected line as JSON: exact prompt, verbatim response, model actually served, timestamp, attempts, tokens consumed. The full trace set is available on request, exactly as written, unedited.

Honest LLM SEO states its limits. Botanik prints 4 in every report: 5 runs reduce noise but never cancel it; an engine can cite a stale state of a market; French prompts dominate the corpus, so multilingual coverage is partial; engines evolve without notice, so comparisons hold only when the methodology stays constant.

A visibility score is also silent on the things that matter most to your P&L. The Baromètre states it plainly: it says nothing about your revenue, your market share, or what an AI will answer to a prompt outside the measured list. A real user's answer also depends on their account, their history and their country, none of which a panel fully reproduces.

Honesty is operational, not rhetorical. When Perplexity's API key was not active in the Baromètre's collection environment, the engine was not queried and no value was extrapolated in its place: the gap is published as a gap. The protocol was frozen on August 1, 2026 at 08:03 UTC, before the first call, with a published SHA-256 fingerprint. Hold every provider, Botanik included, to that standard.

The same discipline applies to guarantees. A "+30% guaranteed" with no contractual indicator, no signed baseline and no measurement window is a commercial promise, not a guarantee. Botanik's own local guarantee (+30% local visibility on your zone, or the variable share of its fees is not due) stands on three written conditions: a contractual indicator, measurement by a third-party tool, and a 1-month measurement window. As Botanik's manifesto puts it: a number without a method is an opinion.