How SeenAndCited Works

AI assistants now answer questions that used to begin as searches. A business can be described, compared, recommended or ignored inside those answers without ever knowing it happened. Most tools in this space report what happened and stop there.

SeenAndCited is built as an AI Visibility Operating System. That phrase means something specific here: one connected workflow that runs from understanding the business, through measurement and inspectable evidence, to a defined improvement problem, a recommended action, committed work, and then subsequent measurement of what happened after that work shipped.

What is happening?

Performance summarizes the current measured picture and meaningful changes in it.

What evidence supports it?

Monitoring lets you inspect the questions, AI engines, answers and cited sources behind that summary.

What could improve?

Where evidence is strong enough, an Opportunity is identified — an underlying improvement problem, not a single failed question.

What should we do?

The AI Action Plan turns supported Opportunities into prioritized recommended work.

What happened afterwards?

Completed work waits for eligible subsequent measurement before any outcome is stated.

Business Identity

Before the system can decide whether an AI answer refers to a business, it has to know what counts as that business. Business Identity holds the confirmed forms of the business name, accepted aliases, relevant product or brand names, and the owned web address.

This matters because a loose approximation is not proof. A confirmed name — or a variant a user has explicitly accepted — can count as a match; an unconfirmed approximation does not. Without an explicit identity, textual mentions, owned citations and competitor evidence cannot be interpreted reliably.

Website analysis

SeenAndCited analyzes the customer’s public website to understand what pages exist, what the business says about itself, which services, products and locations are relevant, how pages are structured, and whether a suitable existing page could support an improvement.

Website intelligence is refreshed when it is needed. Page-level implementation recommendations are made against current analysis rather than a stale picture of the site.

Prompt Portfolio

AI visibility has to be measured against questions. Each site therefore has a Prompt Portfolio: the set of questions SeenAndCited repeatedly measures. Prompts are measurement instruments, not improvement problems — a question that repeatedly fails to produce a citation is evidence, and the problem it points to is represented separately.

Monitoring

Monitoring is the inspectable evidence layer beneath Performance. A monitored result can show the question, the AI engines measured, whether a usable answer was obtained, whether the business was mentioned or cited, which sources were cited, and when the measurement happened.

See how SeenAndCited measures AI visibility, including usable, unavailable and unmeasured results

AI engine coverage

Monitoring can measure across multiple AI engines. Which engines are measured for a given site depends on that site’s current measurement configuration and plan; the workflow itself is the same in every case, while capacity, sampling depth and engine coverage vary. Positioning AI maintains its own separate engine coverage because it uses a different measurement approach.

Performance is the interpreted view: what is currently happening, what changed, and the evidence and context behind it. The primary observed measures are Citation Rate, Share of Voice, and AI Referrals where first-party tracking supports attribution. Coverage sits beneath them as measurement context.

Citation Rate

How often the business was confirmed as cited across eligible measured questions.

Share of Voice

The business’s confirmed citation presence compared with explicitly configured competitors — not general market share.

AI Referrals

Visits arriving from a recognizable AI assistant referrer, where first-party tracking is installed. Many AI-influenced visits arrive without a recognizable referrer, so this is a floor rather than a total.

Coverage

How much of the planned measurement was successfully usable. Coverage is measurement completeness and context, not performance.

See how Citation Rate, Share of Voice and measurement eligibility work

Observed measurement and assessed diagnostics are kept visibly distinct. Specialist scores are labelled as assessments and never presented as equivalent to observed Performance.

Four specialist areas examine different dimensions of the same picture. They are complementary views inside one workflow, not four separate dashboards: where any of them produces actionable work, that work is handed to the central AI Action Plan and follows the same Task and outcome lifecycle.

Authority

Examines external-source and citation-environment evidence that may support or limit AI visibility: which independent sources reference the business, how that changes over time, and where cited sources cluster.

AI Readiness

Assesses the technical and structural conditions that affect whether automated systems can reliably reach, read and interpret the website. High Readiness does not automatically mean high AI visibility, and a check that could not be completed is recorded as unknown rather than turned into a failure score.

AI Understanding

Assesses how complete and coherent the business information available to SeenAndCited is. It is explicitly an assessment of that information — it is not a claim about what any particular AI system knows about the business.

Positioning AI

Examines how supported AI surfaces describe and position the business in relevant market contexts — how a buyer would see the business framed. It is distinct from Citation Rate, from brand mention, from Share of Voice, from sentiment scoring and from SEO ranking, and a Positioning observation does not automatically become an Opportunity.

An Opportunity is the underlying improvement problem, supported by evidence. It is not the monitored prompt, not a generic recommendation, and not a Task.

Where a group of related questions repeatedly fails to produce a citation, the problem is represented once — for example “Improve AI visibility for airport transfers in Havant” — with the individual measurements held beneath it as evidence. That keeps the plan from becoming a long list of near-duplicate, question-level recommendations.

Each Opportunity keeps a stable identity as it is refined, so its evidence, committed work and measured outcomes stay attached to the same problem over time. Absence evidence is expected to repeat across distinct measurement days before it is treated as established; confirmed positive evidence can be verified from the cited source itself.

The AI Action Plan is the prioritized operational view of what SeenAndCited recommends working on next. Each item connects the improvement problem, the recommended response and the supporting evidence, and can be read either by focus or by delivery stage.

Content Growth

Work that improves or creates content so an AI answer has something citable to use.

Authority Building

Work concerned with external sources and the wider citation environment.

Competitor Defense

Work responding to evidence involving explicitly configured competitors.

Other evidence-driven work

AI Readiness and AI Understanding work appears when the underlying assessment supports it, rather than on request.

Users can ask for more actions and choose a focus: Balanced, Content Growth, Authority Building or Competitor Defense. The important principle is that focus changes which supported actions are selected. It does not lower the evidence standard. If only three valid actions exist, SeenAndCited returns three rather than inventing filler to reach a requested number.

Some plan items are not visibility problems at all but setup requirements — such as confirming Business Identity. These are shown separately as System Actions and do not enter the measured-outcome lifecycle.

Knowing that visibility is weak is not the same as knowing what to do. For content-related Opportunities SeenAndCited recommends the specific intervention:

• whether to improve an existing page or create a new one;
• whether a direct-answer or FAQ section is the right addition;
• whether an eligible structured-data enhancement applies;
• which page is the best target;
• where on that page the change should go;
• why that intervention was recommended.

Because these are page-level recommendations, the website analysis behind them is refreshed when it is out of date before a page is targeted with confidence.

When a user decides to act on an Opportunity, a Task is created. The Opportunity is the underlying problem; the Task is one committed attempt to improve it. At the point work is committed, the relevant measurement position is recorded as the baseline for that work episode.

Where no eligible evidence existed to form a baseline, that is recorded honestly and limits what can later be concluded about the work.

A completed Task moves the Opportunity to waiting for results: the intervention has happened and the result is not known yet. SeenAndCited then waits for eligible subsequent measurement — a settling period, and evidence on more than one distinct measurement day — before comparing it against the baseline recorded for that work episode.

Improved

Subsequent eligible evidence is better than the baseline.

No clear change

Enough comparable evidence exists, but it does not show sufficient improvement.

Weaker

Subsequent eligible evidence is weaker than the baseline.

Not enough evidence

A defensible before-and-after comparison cannot yet be made.

A problem may need more than one attempt. If an issue remains actionable after an earlier work episode, new work can be created under the same Opportunity while the previous Task and its recorded outcome are preserved, so the history of attempts stays intact.

Client portal

A simplified live view an agency can give a client: current Performance, measurement context, work in progress, work waiting for results, measured Outcomes, relevant specialist context, and a Positioning summary where applicable.

Report

A period-specific snapshot rather than a live view. It summarizes observed Performance, measurement context, the canonical work for the period, measured Outcomes and material specialist findings.

Reports use the same definitions and the same no-data rules as the product: an unmeasured citation rate is reported as not measured, never quietly rendered as 0%. Reports do not independently invent recommendations — they report the same canonical work and evidence the product holds.

SeenAndCited deliberately does not claim that:

• every AI response is measurable;
• an unavailable or unusable measurement means the business performed poorly;
• no available measurement means zero visibility;
• a completed Task means the work succeeded;
• a subsequent improvement proves causal attribution;
• an assessed diagnostic is the same as observed AI-engine behavior;
• one content format guarantees better visibility across every AI engine, or that individual engines require a particular house style;
• every AI-influenced visit can be attributed.

AI systems are variable. Answers change between runs, availability differs between engines, and no measurement captures every possible answer. Measurements are therefore evidence over time rather than a complete picture, and this methodology is designed to make those limits visible rather than hide them behind a single score.