How CiteHawk works.

CiteHawk asks the AI platforms the questions your buyers ask, records what comes back, and turns the record into numbers you can track. This page explains what is collected, how often, and how each score is built from it.

What gets measured

The unit of measurement is a prompt: one buyer question, asked of one AI platform, on one collection run. A prompt looks like something a real customer would type, not a keyword. CiteHawk sends each of your tracked prompts to every AI platform your plan collects, then stores the full answer that comes back along with any sources the platform cited.

Each stored answer is read for three things:

Whether your brand is named, and whether your competitors are named alongside you.
Which sources the platform cited, so you can see the domains that shaped the answer.
How your brand is described, which is what the Brand Health score reads.

Nothing is inferred from a search ranking or a proxy signal. Every number in CiteHawk traces back to answers that were actually collected. See the receipts principle below.

Collection cadence

Collections run weekly, every Monday. Each run asks every tracked prompt of every AI platform your plan collects, so week over week you are comparing like with like.

Weekly is deliberate. AI platforms vary their answers from one ask to the next, so a single collection proves very little. A steady cadence over the same prompt set is what turns a noisy signal into a trend you can act on.

On top of the weekly run, every plan includes a monthly allowance of manual runs that you trigger yourself, for when you have shipped a change and do not want to wait until Monday to see whether it moved anything. The allowance rises with the plan. See Billing and plans for the per-plan numbers.

AI platforms per plan

Every plan collects the same base set of 9 AI platforms: Claude, DeepSeek, Gemini, Grok, Meta AI, ChatGPT, Perplexity, Copilot, and Google AI Overviews.

Growth and Agency collect 10 AI platforms, adding Google AI Mode on top of the base set. Starter and Pro stay on the base set.

Platform coverage is a data entitlement, not a feature toggle. During a free trial you get the wider feature set, but the platform set stays the one your subscription actually pays for: the trial opens features, never data.

The platforms split into two kinds. Conversational platforms answer in prose and are asked directly. Search platforms are the AI answers that appear above ordinary search results. Both are collected the same way and both count toward your scores, but they behave differently, and Rankings breaks your numbers out per platform so you can see where they disagree.

The scores

CiteHawk leads with two 0 to 100 scores. Visibility asks whether AI recommends you to buyers. Brand Health asks whether AI describes you accurately and positively. Underneath them sit the component rates the scores are built from.

Visibility score

A single number summarizing how visible your brand is in AI answers, blending presence measures such as mention rate with authority measures such as citations. It exists to make change trackable over time, not to replace the underlying evidence.

The score is the headline; the receipts are the product. Every movement traces back to specific answers that changed, and the exact formula used by the public AI Index is published in full.

Mention rate

The fraction of AI answers that name your brand at least once, out of all answers collected for your tracked prompts. A mention rate of 0.6 means you appeared in 60 percent of answers.

Mention rate is the presence number: the simplest measure of whether AI knows you exist for a given question. It ignores position and volume, so one mention in an answer counts the same as five.

The percentage of brand mentions across a set of AI answers that belong to you. If AI platforms name brands 200 times across your tracked prompts and 30 of those mentions are you, your share of voice is 15 percent.

Share of voice is a market-shape number. Mention rate answers whether you are present; share of voice answers how much of the room you take up. Two brands can both appear in 8 of 10 answers while one leads every list and the other trails at the bottom. Read the two together.

Citation rate

The fraction of AI answers that cite your own website as a source. It measures whether AI platforms are reading and crediting your site, not merely naming you.

An AI platform can name you from third-party sources alone: reviews, directories, comparison articles. Citation rate isolates the cases where your own pages made the reading list. A healthy mention rate with a near-zero citation rate means AI talks about you using other people’s words.

The receipts principle

Every number in CiteHawk opens to the real AI answers behind it. Click a score, a rank, a mention, or a source, and you reach the collected answers that produced it, with the platform that gave them and the date they were collected.

This is a design rule rather than a feature, and it has consequences:

Answers are archived, not summarized away. The text the platform returned is kept, so a number can always be re-derived from its evidence.
The platform and the date are stamped on every answer, because an answer without them is an anecdote.
Nothing is modeled or estimated into existence. If a prompt was not collected on a platform, CiteHawk shows a gap rather than filling it in.

The practical payoff is arguing from evidence. When a number moves, you can show the answers that moved it, which is what makes AI visibility reportable to someone who was not in the room.

Next: read what each surface does, or see how plans are metered.