Buyer questions
Use category questions that do not name your company, then see which products the engine actually recommends.
directree GEO Monitor
GEO Monitor is an LLM SEO tool for teams that want evidence of how ChatGPT, Perplexity, Gemini and AI-search answers mention their product.
GEO Monitor tracks AI engines. It has zero effect on your directree listing or ranking.
Use category questions that do not name your company, then see which products the engine actually recommends.
Open the underlying response, inspect the mention and review the citations rather than trusting an unexplained score.
Use missing sources and inconsistent facts as a concrete research list, not a promise that any one change will make you rank.
What this category means
LLM SEO is often used to describe work that makes a product easier for large language models and AI-search systems to understand or retrieve. A monitoring tool cannot make an LLM recommend a brand. It can test buyer questions consistently, record the answer, and reveal where a brand is absent, misdescribed, or cited from an unexpected source.
Use this view when the question is not simply whether your site ranks in Google. It is whether an AI answer mentions your product when a buyer asks a relevant category question, and what evidence was present in that answer.
How it works
An LLM SEO tool works from real category questions a prospect would ask an AI, kept free of your brand name so the result is a discovery baseline rather than a forced mention.
The same questions run against ChatGPT, Perplexity, Gemini and AI-search answers, because an LLM can recommend different products for the same intent depending on the engine and its sources.
Each response is stored with whether your product was named and which pages were cited, so an LLM SEO change is inspectable rather than an unexplained score.
Absent mentions and shaky citations become a checklist of clearer facts and better third-party coverage. No LLM SEO tool can force a model to recommend you.
LLM SEO describes the work of making a product easier for large language models and AI-search systems to understand, retrieve and cite. An LLM SEO tool sits on the measurement side of that work: it does not rewrite the model, it tests buyer questions consistently and shows where a brand is missing, misdescribed, or cited from an unexpected source. The honest framing is that you are improving the evidence an LLM can draw on, not programming its output.
Traditional rank tracking tells you where a page sits in Google's blue links. An LLM SEO tool answers a different question: when a buyer asks an AI a category question, does the answer mention your product, and what evidence was present? Both surfaces matter, and most teams need both kinds of evidence rather than assuming a strong Google ranking guarantees an AI mention.
AI outputs vary with the prompt, the available web information, the model version and the search context. Any LLM SEO tool that promises a guaranteed ChatGPT mention is overstating what is possible. A trustworthy tool keeps the raw answers and citations so you can judge for yourself whether a mention was a genuine recommendation or noise.
A practical price comparison
| Tool | Published starting price | Prompt coverage | Approach |
|---|---|---|---|
| directree GEO Monitor | $29/mo | 15 buyer questions | Stored answers, citations and evidence gaps |
| OtterlyAI | from $29/mo | 15 prompts on Lite | Daily monitoring, citations and audits |
| Profound | from $99/mo, billed yearly | 50 prompts on Starter | AI-search analytics and broader marketing workflows |
| Peec AI | See current public plan | 3 models on Starter | Daily brand and competitor tracking for marketing teams |
Competitor details are based on public pricing pages and can change. Check each provider's current plan before making a buying decision.
Straightforward plans
$29/mo
or $290/yr
$79/mo
or $790/yr
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Questions, answered honestly
It measures or helps investigate how a product appears in answers generated by large language models and AI-search experiences.
No. AI outputs vary and no responsible tool can guarantee a recommendation. Monitoring makes the observed answers easier to inspect.
Naming a brand in a prompt can force a mention. Brand-free buyer questions give a more honest discovery baseline.