What you receive
- Platform-specific KPI set
- Documented prompt/query set
- Bing AI Performance and Search Console
- Citation/mention tracking
- Monthly action-oriented reporting
Why one visibility score is not enough
A score can simplify trends but often hides important differences. A brand may be mentioned in many broad knowledge questions while remaining invisible in commercially relevant vendor questions. A smaller number of high-intent citations may be far more useful to sales.
We therefore separate reach, source presence and commercial relevance. By system, we also distinguish whether a URL is cited, a brand is mentioned, a vendor is recommended or an external source is used that happens to discuss the company.
What first-party data is available
Microsoft provides AI Performance in Bing Webmaster Tools, showing citations across Copilot, AI-generated Bing summaries and selected partner integrations. Google provides Search Console data for generative Search features and continues to expand those reports.
First-party data is valuable because it comes directly from the platform. It still needs interpretation: an impression does not tell you which buyer question was involved or how close that context was to a purchase decision.
Prompt sets instead of isolated tests
For ChatGPT and other systems, we use defined question sets built around real buying tasks: understand a problem, compare solutions, identify vendors, evaluate market conditions, clarify requirements and assess risk.
Each test records date, language, market, system and result. This makes change visible over time without pretending that individual responses are stable or perfectly reproducible.
Metrics we keep separate
We distinguish source/citation visibility, brand mentions, URL visibility, query coverage and buyer relevance. We also review classic organic performance, referral traffic, direct sessions and lead quality where available.
Weighting depends on the business goal. Source visibility can matter for thought leadership. Vendor and solution questions are more important for a service page. A market analysis can create value when it is repeatedly cited for specific market questions.
How reporting stays actionable
A report should not merely show where the brand was mentioned. It should explain which topics work, which sources are repeatedly used, which owned pages are missing and what actions follow.
We therefore focus on a small number of useful observations each period: meaningful gains and losses, new citations, recurring competitor sources, technical issues and concrete content gaps. AI visibility stays connected to marketing decisions rather than becoming a separate dashboard without action.
From analysis to action
Further AI visibility building blocks
AI Search for B2B
AI search is not a separate universe from SEO. Visibility still depends on indexable pages, clear information architecture, useful content, credible evidence and consistent expertise. The difference is that systems can retrieve sources across multiple subquestions and comparison tasks.
ChatGPT Visibility for B2B
There is no guaranteed placement in ChatGPT Search. A strong foundation includes public pages, access for OAI-SearchBot, clear information structure, useful content and externally credible expertise. The goal is visibility for relevant B2B questions, not merely getting the brand name mentioned.
Sources, Entities and Mentions
A clear entity is not created by adding as much schema markup as possible. It comes from consistent naming, unambiguous profiles, strong internal relationships, credible primary information and relevant external mentions. Structured data helps describe visible content in machine-readable form.
Connecting SEO and AI Visibility
Google confirms that SEO fundamentals remain relevant for generative search features. We therefore treat AI visibility as an extension of the search and content system: the same strong pages, a broader source perspective, more complex buyer questions and system-specific measurement.
Content for AI Answer Systems
We do not use a special AI copy style. We improve information density, definitions, section clarity, primary sources, examples and internal relationships. Google continues to recommend helpful original content and says special AI files or AI-specific markup are not required for its generative search features.
Sources & current references
OpenAI — Publishers and Developers FAQ
Google Search Central — Optimizing for generative AI features
Google Search Central — AI features and your website
Bing Webmaster — AI Performance in Bing Webmaster Tools
Make AI visibility measurable and actionable
We measure AI visibility by system and query set. This combines first-party data such as Bing AI Performance and Google Search Console with documented prompts, source observation and buyer-intent classification. A single “AI visibility score” can be an internal model, but it is not objective truth.
