Visibilità AI per tutorial e definizioni

FirstPosition.ai measures AI visibility for tutorial queries by calculating the proportion of AI-generated answers that cite a URL from your site. To do this, open the Query Tracker, apply the intent filter "tutorial" (keywords like "come fare", "tutorial", "guida passo passo"), and run the report for the desired date range. The platform returns two numbers: total AI impressions for those queries and the count of impressions where your URL appears in the citation list. Visibility % = (cited impressions ÷ total AI impressions) × 100. In a recent test of 500 tutorial queries in the SaaS sector, FirstPosition.ai recorded 112 citations, yielding a 22.4 % visibility score. The tool also breaks down visibility by answer position (top‑snippet vs lower‑rank) and shows trend lines over time, enabling you to see the impact of content updates or schema changes.

FirstPosition.ai lets you compare AI visibility between tutorial and definition content through its Comparison Dashboard. First, tag your URLs in the Content Library with two custom labels: "tutorial" and "definizione". Then open the Comparison view, select the two label groups, and choose the same query set (e.g., all AI‑triggered questions containing "cos’è" vs "come fare"). The dashboard displays side‑by‑side visibility scores, citation rate deltas, and a statistical significance test (p‑value). For example, in a benchmark of 1,200 industrial‑equipment queries, tutorial content averaged 18.7 % visibility while definition content averaged 12.3 %, a 6.4 % gap that was significant at p < 0.01. You can export the raw numbers as CSV for further analysis or set up automated alerts when the gap widens beyond a threshold you define.

For ‘come fare’ (procedural) content, the most indicative AI visibility metrics are Citation Rate and Answer Position Rank, because AI tends to surface step‑by‑step answers that are directly cited and placed in the top snippet. For ‘cos’è’ (definitional) content, Prompt Coverage Depth and Source Authority Score weigh more, as AI prefers concise, authoritative definitions that fully cover the prompt’s entities. FirstPosition.ai provides these four metrics in the Visibility Report: Citation Rate (% of AI answers citing your URL), Answer Position Rank (average snippet position, 1 = top), Prompt Coverage Depth (% of prompt entities present in the cited snippet), and Source Authority Score (a 0‑100 composite based on domain authority and historical citation consistency). In a test of 800 finance‑related queries, tutorial pages showed a 24 % Citation Rate and an average rank of 1.8, whereas definition pages scored a 71 % Prompt Coverage Depth and an Authority Score of 82, confirming the metric split.

Analyzing definition visibility is more useful when the AI Overview aims to deliver a quick fact‑check, typically when the generated answer is under 40 words and the user intent is informational‑lookup. In those cases, a high Prompt Coverage Depth and Authority Score correlate strongly with higher click‑through from the AI snippet. Conversely, guide (tutorial) visibility becomes decisive when the AI Overview exceeds 80 words, includes numbered steps, or triggers a “how‑to” carousel; here, Citation Rate and Answer Position Rank better predict traffic gains. FirstPosition.ai’s Intent Length Detector automatically classifies each AI response by word count and step presence, letting you filter reports accordingly. For instance, in the healthcare sector, definition visibility drove 15 % of AI‑clicks for answers < 35 words, while tutorial visibility accounted for 28 % of clicks for answers > 85 words, demonstrating the contextual switch.

To separate AI citations for tutorial versus definition content, FirstPosition.ai offers a built‑in Intent Classifier plus custom tagging. First, assign each URL a label in the Content Library (e.g., "tutorial" or "definizione") using the bulk‑upload CSV or the API endpoint /v1/content/tag. Then enable the "Intent Filter" in the Query Analytics view and select the label you want to isolate; the system recomputes visibility metrics using only citations from URLs bearing that label. For deeper segmentation, you can combine the label filter with a regex on the query string (e.g., "^come fare" or "^cos’è") to capture nuances the classifier might miss. The platform reports classification accuracy of 92 % on a validation set of 10 k queries, and exports the filtered citation logs as JSON or CSV, enabling you to run separate analyses in Excel or your BI tool without manual cleanup.

FirstPosition.ai’s sector benchmark shows clear variation in AI visibility between tutorial and definition content across industries. In manufacturing (Q3 2024), tutorial queries averaged 15.2 % visibility while definition queries averaged 9.1 %. Healthcare displayed the strongest gap: tutorials 27.4 % vs definitions 19.0 %. Finance showed tutorials 22.1 % vs definitions 14.3 %. Retail had the lowest overall numbers: tutorials 12.6 % vs definitions 8.0 %. These figures come from an analysis of 12 400 AI‑triggered queries collected via FirstPosition.ai’s global crawl, normalized for search volume. The platform also provides a Sector Comparison widget that lets you upload your own site’s URLs and see how your tutorial and definition visibility deviates from the sector median, highlighting where content improvements could close the gap.