Define the domain, category and Search Region
Each analysis begins with the website, market category and geographic scope that will remain consistent for comparison. City supports local measurement; Country supports nationwide analysis.
AI visibility measurement methodology for ChatGPT, Gemini and Perplexity
AI Visibility uses a consistent, category-based prompt ecosystem to measure whether a domain is cited or recommended in leading AI answer engines. Results are separated by platform, Search Region and reporting period so brands can compare performance without hiding important differences in one combined number.
A consistent, repeatable AI search measurement process
Build a 100-prompt ecosystem
A fixed set of 100 relevant, recommendation-focused prompts represents multiple user intents around the selected category. The wider sample reduces the influence of isolated AI answers.
Measure ChatGPT, Gemini and Perplexity separately
The same ecosystem is tested across supported production models. Each platform receives its own visibility score, average position and result set because retrieval and answer behavior differ by engine.
Benchmark competitors and track change
Domains recommended for the same prompts create the competitive benchmark. Repeating the configured measurement over time reveals whether visibility is improving, declining or remaining stable.
From baseline measurement to SEO-GEO action
Baseline analysis
The initial report establishes separate ChatGPT, Gemini and Perplexity scores, average positions, cited competitors and the first reference point for future trend analysis.
Gap and opportunity review
Audit findings highlight missing topic coverage, weak entity signals, structured-data opportunities and competitive gaps that can inform content, technical SEO and generative engine optimization priorities.
Ongoing monitoring
Future measurements use the same prompt ecosystem and Search Region. This supports comparable reporting while recognizing that AI models, retrieval sources and generated answers continue to evolve.
Engine-level AI visibility intelligence
Results are not presented as a guarantee that an AI platform will always recommend a brand. They are a measured snapshot of a controlled prompt set. Keeping platform, category and region dimensions explicit makes the data more useful for decisions and clearer for month-over-month reporting.
Key AI visibility metrics we report
Visibility scoreHow frequently the domain appears across the monitored prompt ecosystem
Average positionThe domain’s average placement when cited or recommended in an answer
TrendChange between comparable measurement periods for each AI platform
Competitor benchmarkDomains most often recommended for the same category, prompts and region
Measure your website’s AI search visibility
Establish a repeatable baseline for ChatGPT, Gemini and Perplexity, then use engine-level scores, trends and competitor data to guide your next priorities.
Compare AI visibility plans AI VISIBILITY METHODOLOGY FAQS
AI search measurement questions answered
What is the AI Visibility Score?
The AI Visibility Score shows how frequently your domain appears as a recommendation or mention across the configured 100-prompt ecosystem. It is reported separately for ChatGPT, Gemini and Perplexity so platform-level differences remain visible.
What does average position mean?
Average position indicates where your domain is placed when an AI answer cites or recommends it. A lower average number generally means more prominent placement within the monitored answer set.
What does the trend show?
The trend compares the current result with a previous measurement that uses the same category, prompt ecosystem and Search Region. It helps distinguish sustained movement from a single snapshot.
Why are 100 prompts used per category?
AI answers are probabilistic and can vary between runs. A consistent set of 100 category-based prompts covers multiple intents and reduces the influence of isolated results, creating a stronger basis for comparison over time.
Why is the Search Region kept consistent?
City and Country settings can produce different recommendation contexts. Keeping the selected Search Region unchanged makes future measurements more comparable for local or nationwide visibility tracking.
Why do AI answers change over time?
AI providers update models, retrieval systems and source coverage, while generated answers can vary even for the same prompt. Consistent measurement and historical tracking are therefore more useful than one-off tests.