Viziquo’s Visibility Analysis examines how your brand performs across real buyer questions, AI providers, buyer intents, personas, competitors, citations, and retrieved sources. It moves beyond a single visibility score to show where discovery succeeds, where it breaks down, and what is shaping the answers buyers receive.
The result is a reviewed analysis your marketing, content, SEO, brand, and competitive teams can investigate together. Every conclusion can be traced into the conversations, citations, and search evidence behind it.
Every Visibility Analysis states the audit date, number of conversations, AI providers tested, and the market model used for the run. You can select a completed analysis, move directly to a major section, and download the reviewed analysis as a PDF.
This context makes the results interpretable and shareable. Visibility is always evaluated against a defined set of buyers, questions, providers, and evidence—not presented as a universal score without a denominator.
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A reviewed synthesis of the most important signals from the selected analysis, covering discovery, exposure, competitive pressure, and citation authority.
The central visibility problem, where it occurs in the buying journey, who benefits when your brand is absent, and whether your own sources are influencing the answers.
Teams can begin with the conclusions that deserve attention before investigating the supporting dimensions and evidence.
Headline measures for overall brand visibility, organic discovery, competitor-led visibility, brand-aware visibility, and owned citations, each shown with its underlying evidence base.
Whether your brand appears at all, whether AI assistants introduce it without prompting, whether competitor questions lead back to it, whether direct-name questions produce recognition, and whether your website supplies cited evidence.
The measures separate different kinds of visibility that a single blended score would conceal. Teams can identify whether the immediate weakness is discovery, competitive association, direct recognition, citation authority, or a combination of them.
Prioritized actions derived from the audit’s visibility gaps, competitor patterns, and citation signals, with the rationale and expected contribution attached to each recommendation.
Which visibility improvements deserve attention, why they were selected, and what evidence should change if the work succeeds.
The analysis produces a defensible order of work rather than leaving teams with observations they must translate into a plan themselves.
Visibility separated into brand-aware, competitor-led, category-led organic, and unbranded organic discovery paths.
Whether buyers must already know your name, whether competitor comparisons introduce your brand, and whether AI assistants discover it through category or problem-led questions.
Each discovery path requires different supporting authority. The breakdown helps teams distinguish a recognition problem from a category-discovery or competitive-association problem.
Brand visibility for ChatGPT, Claude, Gemini, and Perplexity, with organic and competitor-led context for each provider.
Whether a visibility gap is concentrated in one AI assistant or repeated across providers—and whether apparently similar overall results are produced by different discovery paths.
Teams can avoid treating a broad authority problem as a platform anomaly, while still identifying provider-specific differences that merit investigation.
Brand appearance and citation performance across educational, diagnostic, tactical, comparison, vendor-selection, and brand-aware questions.
Where your brand enters or disappears from the buying journey, from early research through shortlist decisions.
Visibility at one stage does not guarantee visibility at another. The breakdown shows which kinds of buyer guidance, category authority, comparison support, or evaluation content are missing.
Visibility, organic discovery, competitor-led visibility, brand-aware visibility, leading competitors, citations, and a reviewed interpretation for each buyer persona in the market model.
Which audiences can find your brand, how their discovery patterns differ, who displaces you for each audience, and which sources shape their answers.
An overall result can hide sharply different experiences across marketing leaders, content teams, competitive teams, researchers, and methodology learners. Persona-level findings help each team focus on the buyer context it can influence.
How often competitors appeared when your brand was absent, including their share of brand-absent conversations and the domain associated with each competitor.
Which alternatives capture the most missed answer space and whether competitive displacement is concentrated or fragmented.
Teams can prioritize the comparison paths and competitive narratives buyers actually encounter instead of relying on a predefined SEO competitor list.
The share of citations going to brand-owned, competitor-owned, and other domains; the most frequently cited sources; and owned-citation performance by buyer intent.
Whose evidence AI assistants rely on when forming their final answers, where your own website contributes authority, and where third-party or competitor sources dominate.
Brand mentions without supporting citations can be fragile. Citation analysis identifies the sources already influencing the category and the buyer contexts in which your evidence is—or is not—being used.
The domains AI providers retrieved while researching their answers, classified by source type and kept separate from final-answer citations.
Which sources enter the AI research process even when they are not ultimately cited, and how often brand-owned pages are retrieved relative to competitor, documentation, review, community, and other sources.
Retrieval and citation are different stages. Separating them helps teams distinguish a discovery problem—your pages are not being found—from a selection problem—your pages are retrieved but not used as final evidence.
The Visibility Analysis connects directly to the rest of Viziquo:
Brand Framing examines the tone, narrative, strengths, caveats, and positioning attached to brand appearances.
Recommendations provides the full rationale and expected contribution for prioritized improvements.
Tasks turns approved recommendations into implementation-ready work.
Evidence retains the conversations, answer citations, and retrieved search sources supporting the analysis.
Trends compares completed analyses across time once comparable run history exists.
Technical Readiness investigates website-level barriers that may affect discovery, retrieval, and citation.
Pages investigates URL-level barriers that may affect discovery, retrieval, and citation.
No. Prompt testing supplies the evidence, but Viziquo adds a reviewed analysis of discovery paths, buyer intents, personas, competitors, citations, retrieved sources, and the actions those findings support.
Yes. The Evidence area retains the tested conversations, citations presented in final answers, and sources retrieved during AI search.
Citations are sources presented with the final AI answer. Search sources are pages retrieved while the provider was researching the answer. Viziquo stores and analyzes them separately.
Yes. The Visibility Analysis can be downloaded as a PDF, while the Executive Dashboard provides a more condensed leadership view of the most important findings and priorities.
Share your website. We’ll test real buyer questions specific to your brand in ChatGPT and deliver a reviewed analysis showing where your brand appears, how it is framed, which competitors and sources shape the answers, and what to do next.
Full Viziquo analyses include ChatGPT, Claude, Gemini, and Perplexity.
Free · No credit card needed · Delivered within 3 business days