If your organisation already has access to AI Visibility data, the next question your team is probably grappling with is how to actually use that data the right way.
What does it matter if you know that your competitor is being mentioned more by LLMs if you don't know how to change that outcome? How do you actually move the needle so that you can connect your marketing and PR activities to an increase in AI Visibility?
In this article, our team walks through nine different strategies that can help you present your brand effectively to AI models so that your audience sees more positive mentions about you in the AI-generated responses they receive.
First and foremost, you need AI Visibility data to know where you are currently succeeding and failing. Yes, some of these strategies can be implemented regardless of whether you have this data or not. However, without a clear starting point, you can waste time investing in the wrong places.
For example, some teams begin looking into AI Visibility by manually searching for their brand in ChatGPT or otherwise to see how they show up. However, what soon becomes clear is that each time the process is repeated, or the prompt is changed even slightly, answers change. That's why it's so important to be able to see how those answers are changing over time. Doing this manually across all leading LLMs is impossible, especially for smaller teams with little to no time for such a tedious process.
If you're looking for a way to boost your organisation's current AI Visibility metrics, here are the insights we recommend having on hand:
| Metric | Description |
| LLM Sentiment | Distribution of brand mentions across LLM responses, grouped into sentiment bands from positive to negative. |
| Top Cited Domains | The web domains most frequently referenced in LLM responses about your selected entities. This can be used to map the source landscape behind AI-generated content. |
| Top Cited Journalists | The authors most frequently referenced in LLM responses about your selected entities. |
| Top Cited Outlets | The outlets most frequently referenced in LLM responses about your selected entities. Where domains track specific pages, this metric is used to group those trends to pinpoint leading outlets. |
| AI Visibility Benchmark | Shows your average entity visibility (coverage) across your configured LLM sources. For example, compare how visible your brand is against its competitors within ChatGPT, Gemini, and Claude. |
| LLM Word Cloud | The most frequently mentioned entities found within your configured LLM sources. Font size indicates the frequency of the keyword by volume. |
Once you've established regular, ideally monthly, reporting so that you can track AI Visibility movements for your brand and its main competitors in the market across the LLMs which matter to your audience, you can move forward onto optimisation.
The good news is that there is an easily repeatable set of strategies that all organisations can employ to reach LLMs strategically.
This is where your Top Cited Domains, Top Cited Journalists, and Top Cited Outlets metrics come into play. Finding your source ecosystem is arguably the most important preparatory step in the process.
If AI keeps citing the same five outlets for a category, those journalists and authors are the pitch list. They've already proven their credibility to AI and are more likely to be cited, which means less follow-up work to reap the benefits of your earned media.
For example, when the Streem team worked with the Australian Fashion Council for Australian Fashion Week 2026, we identified that for 260 source citations within July 2026 alone, consumer fashion and lifestyle outlets generated almost five times as many citations as business and trade publications, showing that LLMs relied far more heavily on consumer-facing coverage when answering questions about AFW. Their leading sources included:
These insights helped the team at Australian Fashion Council understand which pieces of earned media and outlets were prioritised most by LLMs, and therefore, what kind of narratives were being told about the event. Going into next year, AFC now has access to a directory that shows them where and to whom they should pitch stories to if they identify sentiment or narrative issues in LLM responses.
A newswire release puts a structured, attributed, timestamped version of the story on high authority sites and in front of the journalists who write the coverage AI cites. It's why PR Newswire was the twelfth most referenced domain by LLMs in Semrush’s most recent study on AI citations.
There are a few reasons press releases are favoured, including:
It's well-known that AI reads transcripts, titles and descriptions.
Videos that answer one specific question in plain language get pulled into answers, so script for the question people are asking. Even better, transcribing your YouTube content as blog content on your owned site is just another opportunity to disseminate your message.
Reddit is one of the most cited sites across every AI tool, but it can't be gamed. Despite having over 1.2 billion monthly active users, those users continue to expect authenticity - real answers from real people. Intervening as a brand in the threads where your category is being discussed is looked down upon, especially when a post is purely promotional.
To do well on this platform, you need a real person (or people) and genuinely helpful additions to the conversation to work on fixing your organisation's narrative and the complaints that live there.
One company that did this particularly well, with earned media acting as a multiplier after the fact, was audio company Sonos. In the midst of ongoing issues with a new product launch, newly appointed CEO Tom Conrad began engaging directly with customers on Threads and Reddit, introducing himself directly to a host of customers on the Reddit thread r/sonos and earning over 2000 upvotes. What this meant is that the company could work on their brand narrative without interrupting what users expect on these platforms.
If you've noticed, credibility and attribution are running themes within these strategies. On LinkedIn, another frequently cited domain, articles and detailed posts from actual people are being cited far more than company page announcements as they're easier to credit reliably than a carousel on your company page with a short caption and no author.
While you may want to prioritise other forms of LinkedIn content to keep your audience engaged, long-form on personal accounts is the best way to disperse a story or your organisation's key messaging and have the highest chance at earning citations by LLMs. What your team will need to interrogate is who those experts could be within your organisation. At the end of the day, sometimes relevance to the topic and existing networks trump authority.
G2, Trustpilot, Tripadvisor are frequently cited as a way for LLMs to provide responses that have a foundation in real consumer feedback. This means that accurate, current profiles matter more than you might think.
Make sure your company description, product features, and pricing information is up to date. Respond to reviews, address recurring customer complaints and incentivise current customers to get on the platform and share their experiences. Pay particular attention to any themes that shine through again and again in reviews, and this can potentially influence LLMs drawing on that content.
If your organisation doesn't own any profiles, this can still reflect poorly on your team. LLMs can interpret a lack of noise as a sign that the organisation may be unreliable.
Wikipedia is a whole other ballgame. Its editorial standards mean that you're not able to create or edit a page without a legitimate reason that follows the platform's conflict-of-interest guidelines. This means that building a broader ecosystem of trustworthy information about your brand is critical.
Surveys, benchmarks and original research give LLMs statistics to quote and journalists a reason to write, which can lead to further earned media and brand mentions.
You don't need a huge research budget. Customer surveys, industry trend analyses and reports based on your own data can all uncover insights that other people want to reference. The key is to offer something genuinely new, rather than rehashing information that's already widely available.
Make your findings easy to cite by publishing clear statistics, explaining your methodology and creating a dedicated landing page. Then distribute the research through PR, industry publications and relevant partners.
The goal is to become a source of information, giving AI systems more opportunities to encounter and reference your brand.
At the end of the day, you have most control over the content you own, which means you can optimise it for LLM pickup. For any product pages or 'About Us' pages, blog posts, or otherwise, make sure that you're providing the most important and searched-for answers first. Employ clear headings, FAQs, keep pages updated, and describe your company the same way everywhere so that AI isn't guessing.
You can even se AI Visibility data to find real prompts that people are searching to find out about your brand, then craft content around those questions to fill gaps in your content library.
Brand conversations are already happening inside AI searches and answers, with models increasingly shaping which brands audiences see, and how they stack up against competitors.
With Streem AI Visibility Dashboards, your team can now monitor all leading LLMs, find their top-cited sources, and refine your media strategy to fill gaps, all inside the same platform you already use for media monitoring, social listening, and outreach.