See how your brand is mentioned, cited, skipped, or replaced by competitors across AI-generated answers — then prioritize the queries worth improving first.
AI visibility is still an emerging category. That is why our methodology separates what we can measure directly from what we score as a configurable signal. You get the evidence behind each result, not just a black-box score.
No guaranteed AI rankings. No magic claims. Just structured measurement, transparent scoring, and action-ready insights.
Traditional SEO tools tell you where a page ranks. AI answers work differently. A buyer may ask ChatGPT, Perplexity, Gemini, Copilot, or AI Overviews for a recommendation, comparison, checklist, or explanation — the answer may mention your brand, cite a source, recommend a competitor, or skip your category entirely.
That creates a new visibility problem:
In which AI engine, for which prompt cluster, against which competitor, and because of which source gap is our brand not showing up?
Every part of the workflow is designed to answer that question. The goal is not to create another keyword report — the goal is to find the AI search gaps that are specific enough to act on.
We start by finding the questions your buyers are likely to ask AI before they choose a product, vendor, or solution.
AI engines often rely on signals from the open web. SERP intelligence reveals which sources may be shaping the answers your buyers see.
We check whether AI engines actually mention or cite your brand when buyers ask relevant questions.
AI answers can change. Repeat checks help your team understand whether a visibility gap is consistent enough to prioritize.
The score helps your team decide what to fix first — not just what to track. Weights remain configurable and validated over time.
Note · Scoring is a decision-support layer, not absolute truth.
How often your brand is mentioned in AI-generated answers for a selected query set.
“Are AI engines naming your brand when buyers ask relevant questions?”
How often your brand or owned sources are cited as supporting sources in AI-generated answers.
“Is AI using your website or content as evidence?”
Your brand's visibility compared with competitors inside AI-generated answers.
“When AI answers mention brands, how much of that visibility belongs to you?”
How often competitors appear when your brand does not.
“Which competitors are winning AI answers you are missing?”
The gap between sources AI uses and sources your brand controls or influences.
“Which sources need to exist, improve, or earn more authority before AI answers trust you?”
Whether the generated answer represents your brand, product, category, or claims correctly.
“When AI talks about you, is it accurate?”
How much results vary across repeated runs.
“Is this visibility pattern stable, or does it change often?”
AI visibility scoring should be useful, explainable, and adjustable. focadio combines direct observations with configurable scoring weights — your team can see why a query is marked as a quick win, competitive gap, authority play, or monitoring item.
The brand has a visible opportunity with relatively clear action potential.
Improve content, strengthen citations, or close obvious source gaps.
Competitors are appearing more often, cited more often, or framed more favorably.
Analyze competitor sources, improve comparison content, and build stronger third-party proof.
The query may require stronger evidence, better sources, or more trusted references before visibility improves.
Create evidence-backed content, earn citations, strengthen external references, improve entity clarity.
The query is relevant but may not need immediate action.
Track visibility over time and revisit when movement or competitor activity changes.
The query has low relevance, weak opportunity, or poor business fit.
Do not spend content or authority resources here unless strategy changes.
Each visibility gap should point to a next step. focadio turns measurement into practical actions across content, citations, authority, and monitoring.
Create or improve content for a query cluster where the brand is missing or underrepresented.
Improve the sources that AI engines may use to support an answer.
Strengthen external references, third-party mentions, and trusted pages connected to the brand.
Correct unclear, outdated, or misleading information that may be causing AI engines to describe the brand incorrectly.
Keep tracking a query that is relevant but not urgent.
Run an audit to see where your brand is mentioned, where it is cited, where competitors win, and which queries deserve action first.
See where your brand appears, where it is missing, and what to improve first.