Seeing that AI Overviews and Perplexity source heavily from Reddit, we've stopped just monitoring brand mentions and started strategic engagement. We deploy our teammates to find and answer complex questions in niche subReddits and build real visibility there. They post as themselves, with their own user flair, to build genuine authority, not to just drop links and spam communities—that would get them banned and destroy trust. We're seeing a lot of progress in branded search from those communities, and with every model update, we've seen our AI citations rise.
We optimized our top-performing content with clearer structure, FAQs, and schema markup to help AI models identify our expertise more easily. Within weeks, we saw our brand mentioned in AI-generated summaries and conversational queries on platforms like Perplexity. The real proof came from higher direct traffic and branded search lifts in HubSpot analytics, without a matching rise in ad spend."
We shifted budget from generic content to publishing original research reports with quotable statistics, making our brand the primary source that AI models cite when answering industry questions. Validation came quickly: within 60 days of publishing our first data study, we appeared in 67% of AI responses related to our key topic versus 8% before. We track this through monthly prompt testing and correlate it with a 3x increase in 'attributable to AI discovery' pipeline in our CRM.
Google's AI mode gives you a query fanout that shows where it looks for answers, and we've found that it often pulls data from obscure, high-trust directories and best of lists rather than the top organic search results. We've built a small task force to audit these pages the AI trusts and focus our outreach on getting EnableU listed. We know it's working because our brand mentions in AI-generated answers for local queries have increased by over 50%, even when the click-through-rate is zero.
The greatest difference was when we realized that AI engines are looking for clarity of the original source, so we made certain each article included attributable data and not just opinions. About two weeks after adding expert quotes & inline citations to our articles (and also beginning to track) we began showing up in AI-generated answers. Our use of a tracking tool and clean-up of attribution caused a noticeable increase in citations. I would say one of the most surprising aspects was how quickly we were able to see results with commitment to structured content as opposed to quantity.
I'm Andy Zenkevich, Founder & CEO at Epiic. Here's my answer to your question. One thing we do to accelerate brand visibility in AI-generated answers is to do an "AI visibility audit" showing where/how our brand appears in answers to buyer queries returned by the leading AI search engines — ChatGPT, Gemini, Claude, and Perplexity. We treat the models as new ecosystems, and we prompt them with tens of buyer queries to see if/how our brand appears in the replies (citations, brand mentions, sentiment). We then use that info to identify precise topical gaps, and build or optimize pages we can get cited from in replies to buyer queries. We track week-on-week growth in mentions of our brand in each model's replies using a mix of prompts, AI tracking scripts, and share-of-voice tools to judge change versus competitors. So after building things we identified in our visibility audit, the share of buyer queries that mention us positively on citation in AI grew from under 5% of prompts to over 22% two months later, and we can track that growth to productized content changes and the resulting growth of direct AI chat traffic and inbound organic leads. It's like an SEO audit with the models treated as meta search engines. The beauty is that it's totally explicit where/what to build.
- In order to increase the presence of our brand in AI generated responses, we are seeking the development of useful content with enriched keywords that meet the current AI search needs and friendly readability. This plan will help the positioning of our brand in sources of authority. Our success metrics include citations and sentiments used in AI responses that include the mention of our brand. In its turn, such a strategy will make sure that our brand will not only be visible, but also significantly mentioned in a positive way. This approach has largely helped in making us more visible in terms of brand name, as we have been in the painting industry for a long time.
Very clearly structure and segment content across your site, with a focus on commercial and navigational pages (About page, FAQ page) rather than just leaving all informational content to your blogs/guides. This means that LLM's are able to understand what your business is about and common questions related to it from within your core commercial pages which get crawled consistently, and any additional content isn't then detracting from the primary points on the page for users.
As AI models become the new curators of trust, the real marketing game has shifted from SEO to GEO (Generative Engine Optimization). Attracting AI crawlers through content dominance by publishing expert Q&As, PR features is a way to make your brand visible with structured data (something that AI crawlers love). We've been using tools like MarketMuse to create semantically dense content that LLMs can easily recognize, and ultimately reward with brand visibility within the AI responses.
We discovered that LLMs mostly cite authoritative, semantically rich sources. Therefore, we started optimizing our content with special focus on context depth rather than keyword density. Each piece of content we publish includes clear, factual summaries, concise definitions and structured data. To validate results and spot opportunities, we carefully track our brand mentions in ChatGPT and other LLM outputs using advanced tools and prompt monitoring. We also compare spikes in direct site traffic and branded search volume after every optimization cycle to determine if we achieved our target.
We focus on creating AI-friendly authority clusters. We have moved from publishing scattered blog posts to building tightly linked content ecosystems. Each blog post focuses on a specific niche topic, covering it in detail. The goal is to ensure no aspect related to the topic is left untouched. We include even the smallest details that may seem obvious to some, but not to others. This structure helps LLMs connect our business brand with highly specific intent queries. We measure the success of our efforts by tracking where our brand is cited in ChatGPT, Claude, and perplexity outputs using Brand24. We also monitor referral traffic from AI-surfaced snippets in Google Analytics.
At Plasthetix, we stopped guessing and just started answering the questions patients were actually searching for. How do we know it's working? Our name started showing up in ChatGPT and Gemini summaries. It's really that simple. If you're starting out, focus on creating content people genuinely want to read with clear attribution. AI models notice what's actually helpful.
At Magic Hour, we started rewriting our best case studies into clear, simple summaries packed with hard data. We put everything in one place, like campaign results, client quotes, and specific metrics, so AI can easily grab what it needs. Since then, we've seen more AI directly cite our work and our name pop up more often. I've learned it's worth taking the time to organize your data. It really does help more people see your stuff.
We turned our content into Q&A blocks. They are easier for AI models to index and quote. Each article opens with a 40-60 words fact-based summary answering a specific question.
At the core of everything is a triangle with three vertices: the brand, the company website, and subject-matter experts. To connect these vertices, each piece of content is published with real experts. These are our experts—CTOs, CMOs, and engineers—who have public profiles and are cited in industry publications. This has increased brand mentions in AI responses. This is especially true for ChatGPT and Perplexity, which, as practice shows, increasingly cite texts with clear author attribution. We track the growth of mentions through brand alerts (we use Ahrefs, which works with the five most popular AI models) and analyze phrases where the AI connects us to specific topics.
AI-generated responses are becoming the new search frontier and thus, the strategy of our team has been to make expert-driven, semantically rich content that AI models can confidently cite. In addition, we apply entity optimization and structured data to our content for making LLMs interpret and reference our content easily. For the measurement of the success, we have been monitoring brand mentions across AI tools such as Perplexity and ChatGPT through visibility monitors and also comparing engagement lifts from branded queries over the period of time.
One of the strategies that have already demonstrated their efficiency in terms of brand visibility on AI-generated answers is optimizing the content with the keywords and phrases that resonate with the frequently asked questions. Thus, by checking what questions individuals tend to develop or what words they tend to input when making a search on real estate topics, for example, one can use these to create naturally flowing blogs, articles, or publications. Given that AI is fed with millions of pieces of content on the internet, it is more likely that the content that contains similar questions or keywords to the search engine's top performance will be used in the published output. One can check the efficiency of this strategy by examining how often his brand is used in the AI-generated answers. Brand monitoring software can trace all brand mentions and analyze the overall sentiment towards each. Given above-average performance and seeing an increased engagement or bid numbers by certain individuals who mention that they have got recommendations via such platforms indicate that the strategy works. Thus, in addition to making one more visible, one also becomes an authority in this field.
We enhanced AI visibility by including concise summaries at the beginning of articles, which are frequently cited in AI responses. Success is measured by their appearance in AI snippets and related brand mentions in traffic and CRM data.
We started embedding proprietary insights from 3L+ patient journeys and real-time user polls into our articles; like one where 769 Hindi-speaking users shared their top sexual anxiety concerns. These unique, localized data points are increasingly showing up in AI-generated answers on ChatGPT and Perplexity, making our content more quotable and trustworthy.
We build linked entity networks. The network connects every piece of content, author and client mention through a structured schema and verified digital identities. AI models connect entities, i.e., people, brands and conceptions to determine credibility and relevance. Entity networks confirm the person is real, the brand is authoritative and the content is trustworthy.