R-U-KnownBrand visibility
See whether your business is absent, found, mentioned or recommended in answers to questions potential customers may ask AI.
What does R-U-Known track?
R-U-Known tracks your visibility across a repeatable set of questions relevant to your business. Instead of reducing AI visibility to one score, it keeps the question, the AI answer, the competitors and the available grounding sources together. Its AI analysis then interprets the results, identifies the gaps and recommendations, and turns the evidence into an action plan your team can implement.
Competitor appearances
See which competing brands appear when yours does not, and where competitors are being recommended for relevant questions.
Grounding sources
Preserve the sources supplied with an AI answer so you can investigate which pages and websites are influencing the information landscape around a question.
Repeatable benchmarks
Use a consistent question set to establish a baseline and compare later benchmarks after meaningful changes have had time to be discovered.
AI brand mentions
Track where AI actually mentions your brand rather than assuming that being indexed or retrieved means the brand appeared in the final answer.
Evidence behind movement
When visibility changes, inspect the underlying answers, competitors and sources instead of reacting to a number without context.
AI analysis and action plans
Analyze benchmark results, questions, visibility gaps, competitors, sources and recommendations, then turn the findings into a prioritized action plan that can be implemented.
Invisible, Discovered or Recommended?
AI search visibility is not binary. R-U-Known separates different levels of visibility because an AI system finding information about a business is not the same as presenting that business to the user.
InvisibleThe brand does not appear in the answer for that benchmark question and there is no supported evidence that it was surfaced as the target brand.
DiscoveredEvidence of the brand is found, but the brand is not necessarily presented as a recommendation to the user.
RecommendedThe AI answer actively presents the brand as a relevant option, solution or choice for the question being asked.
Why this distinction matters: a business can be discoverable on the web and still fail to appear when a customer asks an AI assistant for a recommendation. R-U-Known is designed to expose that gap.
Why use an AI tracker for search visibility?
Traditional search tools tell you where pages rank in search results. AI-generated answers work differently: the user may receive a synthesized answer containing a small set of brands, recommendations and citations. R-U-Known measures that answer layer.
| Traditional SEO tracking | R-U-Known AI visibility tracking |
|---|---|
| Tracks keyword rankings and search-result positions | Tracks whether a brand appears in AI-generated answers |
| Measures clicks, impressions and organic traffic | Measures brand discovery, mentions and recommendations |
| Compares competing pages in search results | Shows which competing brands AI presents instead |
| Focuses primarily on the search-results page | Preserves AI answers and available grounding sources for evidence |
| Often monitored continuously | Uses controlled benchmarks to measure meaningful change over time |
How an R-U-Known benchmark works
A benchmark starts with questions that reflect what the business does and what potential customers may ask. Local or service-area context can be included when it is relevant to the business.
1. Establish the questions
Build a consistent question set around the business, its market, customer needs and relevant discovery or recommendation scenarios.
2. Analyse the answers
Record what the AI answered, whether the target brand appeared, which competitors were surfaced and what sources were supplied. AI analysis brings these results together to explain what deserves attention.
3. Freeze the evidence
Keep that benchmark intact as a baseline rather than allowing later AI answers to overwrite the original evidence.
4. Find the gaps
Identify questions where the business is invisible, competitors dominate, or particular sources repeatedly shape the answers.
5. Implement the action plan
Turn the analyzed gaps, recommendations and source opportunities into prioritized changes to the information, content or external visibility around the business.
6. Benchmark again
Run the same questions later and compare the new evidence with the earlier benchmark to see what actually changed.
Why R-U-Known does not chase daily AI fluctuations
AI answers can change from one run to another. R-U-Known is built around controlled benchmarking rather than treating every daily variation as a meaningful ranking movement.
Make a meaningful change, allow time for crawlers and AI search systems to discover new information, and then compare another benchmark using the same questions. This makes it easier to distinguish a useful signal from ordinary answer volatility.
The principle: do not just ask whether a score moved. Ask what changed in the answers, competitors and sources — and whether there is evidence explaining why.
AI competitor tracking: who appears when you don't?
Knowing that your brand is invisible is only half the story. R-U-Known also records the competing brands that appear in relevant AI answers so you can understand who is winning visibility for the same customer questions.
That creates a practical form of AI competitive intelligence: which competitors are mentioned, which are recommended, what questions trigger them, and which sources repeatedly occur around those answers. The purpose is not to copy competitors. It is to understand the information environment in which AI systems are choosing between brands.
AI source tracking: where are the answers coming from?
When an AI provider supplies grounding or citation information, R-U-Known keeps those pages with the benchmark. This helps you investigate the sources associated with an answer instead of seeing only the final response.
A grounding source should not automatically be treated as proof that it caused a brand mention or recommendation. R-U-Known preserves source evidence so retrieval and interpretation can be examined separately. That distinction matters when trying to understand why a brand is visible — or why it is not.
R-U-Known FAQ
Is R-U-Known an AI tracker?
Yes. R-U-Known is an AI tracker specifically focused on AI search visibility. It tracks whether AI-generated answers find, mention or recommend a brand, which competitors appear, and the available sources associated with those answers.
What is AI search visibility?
AI search visibility describes how a business, brand, product or service appears in AI-generated search and recommendation answers. Visibility can include being discovered, mentioned, cited or actively recommended.
What are AI brand mentions?
AI brand mentions occur when an AI-generated answer names or discusses a brand. R-U-Known records those answers so a business can see which questions produce a mention and which questions surface competitors instead.
Is AI visibility tracking the same as SEO rank tracking?
No. SEO rank tracking measures positions in traditional search results. AI visibility tracking examines the generated answer itself, including whether the brand appears, how it is presented, which competitors appear and what supporting sources are available.
Can R-U-Known track competitors in AI search?
Yes. Competitor analysis is part of the benchmark evidence. R-U-Known records competing brands that appear in relevant AI answers so businesses can investigate where competitors are gaining visibility.
Can R-U-Known show which sources AI uses?
Where the AI provider supplies grounding or citation information, R-U-Known preserves those sources alongside the answer. This helps users investigate which pages and domains are associated with the AI response.
Why use consistent benchmark questions?
Keeping the question set consistent makes later comparisons more meaningful. Instead of comparing unrelated prompts, you can compare how AI answered the same business-relevant questions at different points in time.
How often should AI visibility be checked?
R-U-Known favors meaningful benchmark intervals over reacting to daily fluctuations. A weekly or fortnightly rhythm can give changes time to be discovered and gives the resulting movement more context.
When AI answers, are you known?
Establish a benchmark for your business and see what AI knows about your brand, which competitors appear instead, and which sources are shaping the answers.
Explore R-U-Known