Buyers now ask an assistant before they open a search engine. Citeloop shows how often ChatGPT, Gemini and Perplexity recommend your business, who wins instead, and why.
No setup. We identify your industry, competitors and the queries customers actually ask.
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Assistants recommend brands they can read clearly, that other trusted sources talk about, and that they can crawl. Because their answers shift between sessions, visibility has to be sampled repeatedly and tracked as mentions, citations, sentiment and share of voice — not as a rank.
Most teams only measure one of them. Citeloop separates the two, because they are earned in different ways and pay out differently.
The assistant names your brand inside the answer. Won mostly through reputation signals across the wider web — reviews, forums, press. Drives preference, not clicks.
The assistant links one of your pages as a source. Won through definitive, data-rich, crawlable pages. Drives preference and direct traffic.
Every scan ends with a prioritised action plan: what to change, on which page, why the assistant needs it, and what it should move. Ranked by impact against effort, so you can start on Monday.
Assistants answer “alternatives to X” from third-party lists today. An honest, table-driven comparison page gives them something of yours to cite.
Your homepage opens with a slogan. Lead with one plain sentence stating what you do and for whom — that sentence is what gets lifted into answers.
Three of the five answers cited the same review site. You are not listed there. Getting listed is the shortest path into those answers.
Every recommendation Citeloop generates maps back to one of these. No tricks — assistants reward clarity, corroboration and access.
Lead each section with a one-sentence definition, keep a clean H2/H3 hierarchy and add FAQs that mirror how people actually prompt.
One post never wins. Pillar page plus supporting articles across the full funnel, ideally with original data only you have.
Reddit threads, review sites, industry press and Wikipedia are cited constantly in “what do people recommend” answers.
Concrete numbers, pricing, comparison tables and descriptive URLs give an assistant a reason to link you, not just name you.
A large share of prompts are comparative — “best X”, “X vs Y”, “alternatives to Z”. Publish honest ones before someone else does.
Outdated pricing and stale examples quietly disqualify you as a source for time-sensitive questions.
Tables, lists and accurate schema markup parse far more reliably than long prose blocks.
Plenty of sites block OAI-SearchBot by accident, then wonder why they never appear. Check robots.txt and ungate your best pages.
Mentions, citations, sentiment and share of voice across every assistant — tracked over time, not checked once.
AI systems can produce different responses to identical questions. Measurements are based on repeated observations across selected platforms and should be interpreted directionally rather than as deterministic search rankings. We say “your brand appeared in 7 of the last 10 tracked responses” — never “you rank #2 in ChatGPT”.
Brand and competitor names are extracted verbatim from what the assistant actually wrote, then verified against the answer text, so nothing invented by the extractor reaches your dashboard.
AI visibility
across repeated samples
Illustrative sample — your numbers come from your own tracked queries.
AI visibility is how often, how prominently and how favourably your brand appears in answers generated by assistants like ChatGPT, Gemini, Perplexity and Claude. It is measured from repeated observations of real answers, not from a ranking table.
Publish answer-ready content that opens with a direct definition, build topical depth around one subject, earn mentions on the third-party sources assistants lean on (Reddit, review sites, industry press, Wikipedia), keep pages current and crawlable by AI bots, then monitor which prompts surface you and iterate.
A mention is the assistant naming your brand inside its answer. A citation is the assistant linking to one of your pages as a source. Mentions build preference; citations also send traffic. Citeloop tracks both separately.
Assistants run different background searches per conversation and sample their own output, so two identical prompts can return different brands. That is why a single manual check is meaningless and why Citeloop reports across repeated observations instead of a single snapshot.
You can, but it does not scale. Covering dozens of prompts across several assistants every week, and comparing sentiment and share of voice against competitors, needs automated tracking.
Run a live scan across ChatGPT and Gemini, or test any company you like before you set up a workspace.