Reading your AI visibility dashboard

Whether you're tracking a brand, a category or a keyword, Vurto displays the same types of indicators on every dashboard: an average visibility score, its breakdown by AI engine, its evolution over time, and the competitors identified in the answers. On top of that, your product pages get an independent semantic score evaluating how well they can be understood and reused by generative AIs.

The indicators common to all three dashboards

The brand, category and keyword dashboards share the same structure. At the top, the number of tracked elements (active brands, categories or keywords) and the average visibility score, which sums up in one number how often and how well you appear in AI answers across all your prompts. That score then breaks down by engine — ChatGPT, Claude, Gemini, Perplexity, up to eight models depending on your plan — revealing gaps the overall average hides: it's common to be well positioned on one engine and nearly absent on another.

Reading the trend curve and the engine breakdown

The trend curve shows how your score moves over time, wave after wave. It's this curve, more than the instant score value, that should guide your decisions: a score of 40 trending steadily upward is better news than a score of 60 that's been dropping for three waves. When a score drops on one engine in particular, don't look first for a technical explanation on your side — start by checking whether a competitor gained visibility at the same time on that same engine. For example, if your Perplexity score drops from 55 to 38 over two waves while staying stable on ChatGPT and Claude, chances are a competitor got better cited on the sources Perplexity favors for your sector — the competitor table on the same dashboard lets you verify this directly rather than assume it.

The competitor table

Below the score indicators, Vurto shows the competitors identified in the AI answers linked to your prompts, with, for each one, the persona active when they were mentioned and the sources the AI cited to recommend them. This table gives directly readable context to any score change: a drop can almost always be explained by one or more specific competitors gaining ground, identifiable row by row rather than as a diffuse phenomenon.

The detailed analysis

On results that warrant it, Vurto offers a detailed analysis that goes beyond raw numbers: an executive summary of the situation, the dominant and absent players on the tracked topic, a structured competitive comparison, an identification of risks and opportunities, and recommendations organized by time horizon — immediate actions, medium-term actions, foundational actions. This is the level of reading to favor before deciding where to invest time, rather than reacting to a single score change.

Semantic scoring of your product pages

Independently of the visibility dashboards, Vurto evaluates each product page on ten criteria: title, description, structured data, FAQ, technical specifications, customer reviews, multimodality (photos, videos), alt text, out-of-context readability, and hierarchical structure. Each page gets an overall score out of 100, along with detailed recommendations per criterion. Out-of-context readability deserves particular attention: a generative AI usually only shows an excerpt of your page, without the rest of the site around it — a page that assumes context it doesn't provide (a vague page title completed elsewhere, for instance) loses clarity once isolated, even if it reads well in its original setting. A page scoring 45/100 with FAQ and structured data both at 0 doesn't call for the same action plan as a page also scoring 45/100 because of missing customer reviews and uncaptioned visuals: the overall score guides priority across pages, the per-criterion detail guides the work within a single page.

Cross-referencing the visibility dashboard with competitor analysis

These two readings complement each other and shouldn't be done separately. A visibility score that stagnates despite a good semantic score generally points to an external issue: the sources cited by AIs in your sector don't yet mention your brand, even though your own content is solid. Conversely, a low score paired with a low semantic score points first to a content issue to fix before even looking for external explanations. The detailed competitor analysis lets you settle between these two hypotheses instead of guessing.

How often to check these dashboards

Visibility scores vary from one analysis wave to the next, sometimes for one-off reasons (a slightly different phrasing in an AI answer, momentary news). Checking the dashboard after every single wave without stepping back exposes you to reacting to noise rather than to a real trend. A weekly review, focused on the trend curve rather than the latest isolated point, gives a more reliable basis for decisions than a daily check.

Reading the three dashboards together rather than in isolation

The brand dashboard, the category dashboard and the keyword dashboard each answer a different question, and reading them in isolation can hide important situations. The brand dashboard shows whether your company itself is recognized and recommended as such. The category dashboard shows your position on a type of product or service, regardless of whether your brand gets named. The keyword dashboard narrows this further, down to specific queries. A brand that's rarely named directly can still be well represented at the category level if its products keep coming up without the AI systematically naming the brand — which points toward strengthening brand awareness rather than product content. Conversely, a well-recognized brand that's absent on specific keywords points to a more targeted issue, often tied to specific pages that aren't sufficiently structured rather than an overall awareness gap.

A 3-point prioritization method

Facing several tracked brands, categories or keywords, prioritize in this order. First, scores dropping continuously over several waves, which signal active deterioration rather than a simple one-off variation. Second, high-commercial-stakes product pages with the lowest semantic scores, since these are the fastest fixes to implement and the most direct payoff. Third, prompts where the detailed analysis identifies a clear opportunity — a topic no player yet dominates in AI answers — because that's where effort produces the best ratio between investment and visibility gain.