AI Brand Visibility: Know and Improve How AI Describes You
Is your brand mentioned when buyers ask AI for recommendations? We measure your presence in AI answers, fix inaccuracies and build the signals that earn more accurate mentions.
Your brand is already being described by AI
Whether you planned it or not, AI assistants answer questions about your company, your category and your competitors every day. They may recommend you, ignore you, describe you incorrectly or cite outdated information. AI brand visibility is the work of finding out which, and improving it. It is part of LLMO and GEO, packaged for brands that want monitoring and clear action.
What we measure
- Mention rate: how often your brand appears for a set of commercial prompts.
- Position and prominence: whether you are listed first, among several or only as an afterthought.
- Sentiment and accuracy: how you are described, and whether facts such as services, locations, pricing model and founding details are right.
- Source citations: which websites AI tools cite when they talk about you and your competitors.
- Competitor share of voice: who gets recommended instead of you and why.
- AI referral traffic: visits and conversions arriving from AI platforms.
Our process
1. Prompt library
We build a library of realistic prompts across the buyer journey: category discovery, comparisons, alternatives, pricing, reviews and local searches, in the languages and regions you serve.
2. Multi-platform testing
We run prompts across major assistants and AI search tools, repeating them over time because answers vary. We record results in a structured report rather than relying on one-off screenshots.
3. Gap and risk analysis
We identify missing information, weak sources, outdated pages, inconsistent profiles and misleading third-party content, and rank them by impact.
4. Fixes
Typical actions include clarifying your About, Services and Pricing pages; adding author and company details; implementing schema; correcting directory listings and profiles; publishing comparison and FAQ content; and requesting corrections where sites contain errors. See answer engine optimization.
5. Authority building
We earn credible mentions through digital PR, reviews, partnerships, expert commentary and original research, which strengthen what models and retrieval systems find about you.
6. Ongoing monitoring
Monthly dashboards track trends, new competitors and changes in AI behaviour, with alerts for sudden drops or harmful inaccuracies. See also online reputation management.
Handling inaccurate AI answers
When an AI tool gets facts wrong, the best fix is usually to correct or strengthen the sources it relies on, not to argue with the model. We document the issue, trace likely sources, update your own content and structured data, and work on reputable third-party pages. Most platforms also offer feedback channels, which we use where appropriate. Outcomes cannot be guaranteed.
Reports you can use
Reports are written in plain language for marketing leaders and executives, with screenshots, trend charts and a short list of actions. No jargon for its own sake.
Best fit
Brands with an established online presence, companies in competitive categories, businesses whose reputation affects sales, and agencies that want to add AI visibility reporting for their clients through our white-label options.
AI Brand Visibility FAQs
We test a prompt library across major AI tools and report mention rate, accuracy and sentiment.
We trace likely sources, correct your own content and structured data and work on third-party pages. Results cannot be guaranteed.
Yes, by platform, time, location and wording, so we measure repeatedly and report trends.
Generally no. Visibility in AI answers comes from content quality, authority and clarity, not payment to us.
Yes. Many people ask AI for local recommendations, so accurate listings and reviews matter.