What is the typical AI citation rate for B2B brands in 2026?

92% of tracked brands have a citation rate of 0% — meaning ChatGPT, Perplexity, Claude, and Gemini never cite them when buyers ask category-relevant questions. The remaining 8% capture nearly all AI-driven consideration in their categories.

What's the difference between GEO, AEO, and LLMO?

They all describe the same practice — optimizing content so generative AI assistants cite you as a source. GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), and LLMO (Large Language Model Optimization) are interchangeable labels. Pick whichever your team uses.

How is citation rate measured?

Each tracked prompt runs three times per provider per scan. Citation rate is the share of those runs where your domain appears in the assistant's source ledger, expressed 0–100% per prompt per provider.

What counts as a mention if there's no citation?

Monroya classifies every response into four mention classes: cited (linked source), named (mentioned by brand name without a link), category (your category mentioned, you aren't), and absent (no mention at any level).

How often should AI visibility be scanned?

Weekly automated scans establish trend lines. Manual scans are used to measure the lift from a specific change — such as publishing a comparison page or earning a Reddit citation — without waiting for the next weekly cycle.

How is AI-driven sentiment analysis different from classical NLP sentiment scoring?

Classical sentiment scoring uses lexicon or bag-of-words models and reports a scalar polarity. AI-driven sentiment analysis uses an LLM to read the surrounding context, resolve the entity being discussed, and classify the sentiment toward that entity — not toward the document as a whole. The output is a structured record per entity, not per document.

What is entity normalization and why does it matter?

Entity normalization is the step where varied surface forms ("Monroya", "monroya.ai", "the Monroya tool") get collapsed to a single canonical entity ID before sentiment is computed. Without it, the same brand looks like three different things and aggregate scores are wrong.

Can sentiment be tracked inside LLM responses themselves?

Yes. Run a prompt set against ChatGPT, Claude, Gemini, and Perplexity on a schedule; extract every brand mention from the responses; then classify sentiment toward each brand per response. That gives a per-assistant sentiment score for the answers buyers actually see.

How often should sentiment be re-scored?

Weekly is enough for a stable brand; daily is justified during a launch or incident. Single-shot sentiment readings are noisy — aggregate at least 20–30 mentions per entity before reporting a trend.

What's the relationship between sentiment and AI citation rate?

Citation rate measures whether you get named; sentiment measures how you get named. A brand can have high citation rate and negative sentiment (mentioned often but unfavorably). The two metrics belong on the same dashboard.

Glossary

AI search terms, defined.

In 2026, 92% of tracked B2B brands have an AI citation rate of 0% — ChatGPT, Perplexity, Claude, and Gemini never surface them when buyers ask category-relevant questions. The vocabulary for fixing that hasn't settled yet. Here's a plain-English reference for the terms that come up in evaluation and team discussions.

AEO: Answer Engine Optimization.; Practice of making your content show up as the cited source when an AI answer engine (ChatGPT, Perplexity, Claude, Gemini) answers a buyer's question. Distinct from SEO because the optimization target is the assistant's response, not a search results page.; Also seeGEO How it works
AI visibility: Whether AI assistants surface your brand when buyers ask category-relevant questions.; The umbrella metric for AEO/GEO/LLMO programs. Usually tracked as citation rate plus mention quality across a defined prompt set and competitor set.; Also seeTracking AI visibility
Buyer journey matrix: Grid of buyer stages × competitors that maps where AI assistants cite you vs others.; Monroya's home view. Rows are Discovery / Evaluation / Decision; columns are you and your competitor set. Each cell carries a score (0–100) and a list of the prompts driving it. Every cell with a gap is an actionable opportunity.; Also seeBuyer Journey Intelligence
Citation: An AI assistant linking to a specific URL as the source for a claim in its answer.; Citations are extracted from the provider's native citation payload (Perplexity citations, Gemini grounding, ChatGPT browsing) plus a fallback URL parse. Citations are the strongest mention class — they drive click-through and rank-of-trust.
Citation rate: Share of runs in which your domain appears in an assistant's source ledger for a given prompt.; Measured 0–100% per prompt per provider. Each prompt runs three times per scan; citation rate is the share of those runs that cite your domain. The headline AI visibility metric.; Also seeMethodology
GEO: Generative Engine Optimization.; Often used interchangeably with AEO. Same idea: optimize for generative answers, not blue links. The 'engine' framing emphasizes that ChatGPT and Perplexity now function as search engines for a meaningful slice of B2B buyer journeys.; Also seeAEO LLMO
Grounding: The provider-side process of attaching real web sources to a generated answer.; Google's term for the citation pipeline in Gemini. The structured groundingMetadata payload is the most reliable source extraction signal Gemini exposes.
LLMO: Large Language Model Optimization.; Yet another label for the same category as AEO and GEO. The category hasn't settled on one name. Pick whichever your team uses and move on — the work is the same.; Also seeAEO GEO
Mention class: How an assistant references your brand: cited, named, category, or absent.; Classifier output per prompt per provider. Cited = linked source. Named = mentioned by name without a link. Category = your category mentioned, you aren't. Absent = no mention at any level. Used alongside citation rate to score visibility.
Opportunity: A specific, ranked action that closes a measured visibility gap.; Generated per buyer-journey matrix cell where your score trails the competitor set. Carries an estimated lift, an effort estimate, and a draft asset ready to ship.
Prompt: A query you want to track AI assistant behavior on.; Mix of discovery, evaluation, and decision-stage questions your buyers ask. Generated during onboarding, edited by you, then run three times per provider per scan.
Scan: One full pass of every tracked prompt × every provider.; Either weekly (automated, no quota impact) or manual (counts against your monthly limit, used to measure the lift from a specific change).
Source ledger: Per-prompt list of every URL the providers cited, normalized and deduped.; The raw evidence behind every visibility score. Use it to find which competitor pages, Reddit threads, or third-party sources are doing the work.

FAQ

AI search, in five questions.

What is the typical AI citation rate for B2B brands in 2026?: 92% of tracked brands have a citation rate of 0% — meaning ChatGPT, Perplexity, Claude, and Gemini never cite them when buyers ask category-relevant questions. The remaining 8% capture nearly all AI-driven consideration in their categories.
What's the difference between GEO, AEO, and LLMO?: They all describe the same practice — optimizing content so generative AI assistants cite you as a source. GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), and LLMO (Large Language Model Optimization) are interchangeable labels. Pick whichever your team uses.
How is citation rate measured?: Each tracked prompt runs three times per provider per scan. Citation rate is the share of those runs where your domain appears in the assistant's source ledger, expressed 0–100% per prompt per provider.
What counts as a mention if there's no citation?: Monroya classifies every response into four mention classes: cited (linked source), named (mentioned by brand name without a link), category (your category mentioned, you aren't), and absent (no mention at any level).
How often should AI visibility be scanned?: Weekly automated scans establish trend lines. Manual scans are used to measure the lift from a specific change — such as publishing a comparison page or earning a Reddit citation — without waiting for the next weekly cycle.