Advice and answers from the Advanced Web Ranking Team
AI Brand Visibility Just Got Smarter and More Accurate
AWR’s AI Brand Visibility report now shows which websites LLMs cite when mentioning your brand, with more accurate data, up-to-date sources, and results tailored to your market.
When we first introduced AI Brand Visibility tracking in AWR, we focused more on helping you understand how your brand shows up in LLM-generated results from ChatGPT, Perplexity, Gemini, and Claude. You could finally track what AI platforms say about you and how often your brand appears.
Now, we’re taking that visibility further.
This update adds a dedicated Citations report that gives credit where it’s due. Alongside it, we’ve rolled out a set of accuracy improvements that make your AI results feel more grounded, local, and up-to-date.
1. Citations Report
The new Citations report opens a new layer of insights: the sources behind the mentions. It gives you a complete overview of all domains (websites, publications, blogs, etc) that show up in LLM-generated results for your selected topic (or set of topics), offering a clearer view of their visibility and reach.
But it’s more than a list of URLs. Each source is ranked by how visible it is in AI-generated answers, helping you quickly spot top-cited domains, track citation volume and visibility over time, or see how your brand is distributed across sources and topics.
At the top of the report, three key KPIs help you understand the full scope of the citations landscape:
Total & Unique Citations show how many times brands have appeared on the selected LLM for the chosen topic (or set of topics), and how many of those mentions came from distinct sources. You can view this data either for all brands combined or zoom in on a specific one (your brand or a competitor).
A high total with low uniqueness means that brands are getting cited often, but mostly by the same sources. A strong unique count means a wider presence across diverse sources.
Citations Visibility highlights how much visibility each brand gets based on how often it appears in the top 10 citations from the LLM, for the selected topic(s) and date range. It’s not just about being mentioned, but about how prominently those citations appear on the LLM when generating the AI answers.
Top Cited Domains reveals which websites were cited most frequently by the selected LLM across the chosen topic (or set of topics) and time range. It gives you a clear view of which domains carry the most influence in AI conversations.
Below, in the table, you will find the full list of websites that were cited by the selected LLM across the selected topic (set of topics) and date range. For each domain, the table will display:
Its visibility percentage, based on its placements in the top 10 rankings.
Its average rank when cited. Lower values indicate better visibility and a stronger presence.
The total number of citations.
The number of distinct topics its was was cited for.
2. Accuracy Enhancements for More Local, Relevant, and Fresh Responses
As powerful as LLMs are, they’re useful when the data they rely on is up-to-date and accurate. That’s why we’ve introduced two key enhancements that are meant to improve the relevance, freshness, and local targeting of your AI Brand Visibility results.
Web Search Mode (a.k.a. Grounding)
By default, the AI Brand Visibility updates now use Web Search Mode, which tells the selected LLM (e.g., ChatGPT) to validate its responses using live web search data rather than relying solely on its pre-trained knowledge. Trained data can be months or even years out of date (for example, ChatGPT’s knowledge cutoff is early 2024), which can lead to stale results.
When Web Search Mode is off, the LLM answers based on old training data instead of current web content. This can lead to:
Mentions of websites that no longer exist.
Old brand associations that are no longer relevant.
Missing recent updates (like rebrands, product changes, or new competitors).
When Web Search Mode is on, the LLM performs additional live web searches in the background to validate its answers using fresh data. That means:
More accurate brand mentions.
More relevant citation sources.
Better alignment with what’s live in online search.
Country & Language Customization
Not all markets look the same in AI-generated results, and your AI Brand visibility data should reflect that. You can now tailor the updates by selecting a target country (or custom location) and a preferred language for the LLM to use when generating responses. This helps ensure the brand insights align with how people search and speak in your chosen market.
By default, the location selected at the project level and its default language (eg, English for the USA or German for Germany) are used when performing the AI prompts. But you can adjust them at any time from the "Update Settings" wizard to match specific regional strategies, campaign targets, or local SEO goals.
How many units are required for an AI Visibility update
Unit usage for AI Brand Visibility updates varies based on your setup, similar to how it works for ranking or difficulty updates in AWR. It depends on the number of AI search engines you select, whether you include competitors or custom topics, how often the updates run, and whether Web Search Mode (grounding) is enabled.
The update configuration wizard always displays the exact number of units required before you trigger an update, so you can review and adjust your setup according to your usage requirements.
Feature Availability
The AI Brand Visibility feature is available on all AWR plans, as long as your updates stay within the unit quota of your subscription.
Do you have any further questions or need more information about this product update? Don't hesitate to get in touch with our dedicated support team.
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