The way people find information is changing fast. Instead of just scrolling through Google results, more people are asking AI chatbots and search engines with AI overviews (such as ChatGPT, Google’s new AI answers, or tools like Perplexity) for quick answers. A recent study analyzing 30 million AI citations found that the four most-cited platforms across these AI tools are Reddit, Quora, YouTube, and Wikipedia. In other words, when AI answers cite sources, they often come from those community and knowledge-sharing sites.
For marketers, this raises an exciting question: How can we make sure our brands and content show up in those AI-generated answers? It’s a bit like the new frontier of SEO – some call it Answer Engine Optimization or even “Search Everywhere Optimization”.
The goal is the same as ever: be where your audience is looking for answers. But the tactics are evolving.
Traditional SEO was all about getting your site to rank higher on Google by building links and using the right keywords. With AI, the game is about getting mentioned in the right places. As SparkToro’s Rand Fishkin puts it, “The currency of large language models is not links… The currency of large language models is mentions”. In practice, that means LLMs (large language models) learn and retrieve from content all over the web, especially from popular platforms like Reddit, Quora, YouTube, and Wikipedia.
In this article, I’ll break down how content from each of these four platforms gets surfaced by AI, and what actionable steps you can take to optimize your presence on each. I’ll also tackle challenges and best practices, how to prioritize your efforts based on your brand and goals, and what strategic questions to ask as you plan for LLM-driven discovery.
Consider this your playbook for getting your brand discovered through search in the age of AI.
Why Reddit, Quora, YouTube, and Wikipedia Matter for AI Discovery
Before we dive into tactics, let’s quickly recap why these four platforms stand out in the AI citation study. According to Profound’s research with Nick Lafferty, different AI systems have distinct source preferences:
ChatGPT (with browsing/search enabled) leans heavily on Wikipedia (47.9% of citations), with Reddit a distant second (~11.3%). ChatGPT’s answers frequently point to Wikipedia for factual info, but community discussions (Reddit) and even product review sites like G2 or Gartner show up for certain queries.
Google’s AI Overviews (the generative answers in Search) show a more balanced mix – top sources include Reddit (21%), YouTube (18.8%), Quora (14.3%), and LinkedIn (13%), among others. Google’s AI is pulling information from social Q&As, videos, and professional content in a more diversified way.
Perplexity (a popular AI answer engine) has an extreme bias toward Reddit (46.7%), with YouTube (13.9%) as the second-biggest source. It loves community-driven content and crowdsourced knowledge, even more so than the others.
Wikipedia, Reddit, Quora, and YouTube are frequently “feeding” the answers that AI platforms give.
If your brand or content isn’t present in these places, you’re likely invisible to the AIs (and by extension, the users asking the AIs). As the Profound study’s strategic advice highlights, marketers need to diversify content across platforms based on AI preferences and focus on high-quality contributions to key platforms like Reddit and Wikipedia.
It’s also worth noting that each AI system has its own flavor. For example, Google’s AI often cites Reddit and YouTube (even Medium and Quora), whereas ChatGPT might pull from LinkedIn or expert review sites for business topics. I’ll discuss differences in strategy for these AI systems later on. But first, let’s tackle each of the “Big Four” platforms and how you can leverage them.
Reddit: Join the Conversation, Become the Answer
Why Reddit matters: Reddit has emerged as a goldmine for AI answers. It’s now ChatGPT’s second most-cited domain (after Wikipedia) and the #1 source for Google’s AI results. Reddit is full of real people asking questions, giving answers, and sharing firsthand insights. AI models (and the companies behind them) recognize that upvoted Reddit threads often signal high-quality, consensus knowledge. A Reddit thread might contain multiple perspectives, personal experiences, and up-to-date information on niche topics – exactly the kind of rich context an AI answer can draw from.
How AI uses Reddit content: Large language models have likely ingested a lot of Reddit data during training (OpenAI even struck a partnership to access Reddit’s data). Moreover, AI search tools retrieve live content from Reddit when relevant. So, a highly upvoted answer on a popular subreddit could be quoted or used as evidence in an AI-generated response.
Actionable steps for Reddit:
Find the Right Subreddits: Identify subreddits where your industry, product category, or target audience’s interests are discussed. For example, if you sell plant-based protein powder, check out fitness or nutrition subreddits, or even threads on r/vegan or r/nutrition.
Be a Genuine Participant: Active participation in Reddit communities is crucial for visibility. This means don’t just drop in to promote yourself. Spend time understanding the community norms. Answer questions, share knowledge, and be helpful without expecting anything in return at first. Build karma (both literally and figuratively).
“Plant” Your Expertise (Carefully): When appropriate, mention your brand or content in context. Perhaps someone asks a question that your product or blog post genuinely addresses – you or a knowledgeable team member could respond with useful info and casually mention, “Disclosure: I work at [YourCompany], and we researched this – [key finding].” Do it tactfully. The goal is to insert your brand as part of a helpful answer, not an advertisement. One LinkedIn marketing strategist calls this “industry planting” your brand on Reddit, because it seeds your name in authentic discussions.
Deliver Value, Not Ads: Share insights, data, or experiences that stand on their merit. For instance, you might summarize a finding from your company’s whitepaper if it answers the question at hand (and link to it if allowed). If your contribution is useful, it may get upvoted, which increases its visibility. Remember: Upvoted content signals quality to both humans and AI.
Monitor Mentions & Opportunities: Use tools or manual checks to monitor when your brand or product is mentioned on Reddit. Also, watch for relevant questions where you can chime in. Some teams set up Google Alerts or Reddit keyword alerts for this. When you see an opportunity (e.g., someone asks “What’s the best [your product category]?”), you can participate or encourage a friendly power-user to share their experience with your brand if they genuinely like it. Organic word-of-mouth carries a lot of weight.
Challenges & Best Practices for Reddit: Redditors are notoriously sensitive to blatant marketing. Astroturfing (fake “native” promotions) can backfire badly if the community sniffs it out. So transparency and authenticity are key. If you have an affiliation, many subreddits appreciate you stating it. Stick to facts and firsthand experience rather than marketing slogans. Also, take the time to earn trust. A brand-new account swooping in with a promotional answer is likely to get downvoted or removed by mods. But an established user who has helped others will have more leeway to mention a product or link to a helpful resource.
Reddit rewards long-term engagement – you’re playing the long game of community building, which in turn can yield those prized citations in AI answers.
Quora: Provide the Best Answers to Get Noticed
Why Quora matters: Quora is a massive Q&A platform where questions on every topic under the sun get answered by enthusiasts, experts, and sometimes brands. It tends to rank well in Google for long-tail questions, which is one reason Google’s AI often cites Quora content (~14% of its citations). Quora threads are essentially curated, high-quality answers to specific questions – a format that maps closely to how people query AI assistants. If someone asks an AI, “How do I improve my credit score quickly?”, there’s a good chance the AI might pull from a comprehensive Quora answer on that topic (in addition to other sources).
How AI uses Quora content: Much like Reddit, Quora’s content is largely public and indexed. LLMs might have ingested a lot of Quora data during training. More immediately, Google’s generative search can retrieve Quora answers to include in its AI overview.
Actionable steps for Quora:
Identify Relevant Questions: Start by searching Quora for topics related to your domain. Look at the questions that have a high number of followers or views – these indicate popular queries that people (and likely AI) care about. For example, if you’re a cybersecurity firm, find questions like “How can I protect my small business from cyber attacks?”
Answer with Authority and Clarity: Choose questions where you have real expertise to share. Write educational answers, not salesy – Quora readers (and AI algorithms) can smell a sales pitch a mile away. Provide clear, step-by-step answers or insightful explanations. If your brand has a product that fits the solution, you can mention it in context (“One solution businesses use is XYZ software…”) rather than making the answer all about you. The key is to be genuinely helpful and informative.
Include Your Brand Naturally: It’s okay to talk about your brand or link to your blog if it’s highly relevant and adds value. For instance, “Our team researched this topic extensively in [Blog Post Title], and we found that… [brief insight].” Make sure the answer still makes sense without the link, though. Pro tip: frame your answer as if you’re just an industry expert. Mention your product as an example or one of several options. By “mentioning [your brand] in context (as an example, not a blatant ad),” you increase the chance of the brand name appearing in the AI’s training or retrieval results without triggering a spam filter.
Use Keywords and Phrases the AI Might Look For: Think about the terms an AI might associate with the topic. For Quora SEO, this is akin to using relevant keywords. You should use keywords LLMs like in your answers – i.e., terminology that is common in authoritative content on that subject. For instance, in the cybersecurity example, include terms like “ransomware,” “phishing,” “firewall,” etc., in a natural way. This increases the likelihood that if an AI is matching on relevant content, your answer bubbles up.
Format for Readability: Use Quora’s formatting options – bullet points, numbering, and bold for key points. A skimmable answer often gets more upvotes. More upvotes and views signal to both Quora’s algorithms and potentially AI scraping tools that this answer is high quality. Plus, a well-structured answer might be more easily parsed by an AI looking for specific info.
Build a Profile: Consistency helps. If you regularly answer questions in your niche, you could become a Most Viewed Writer in that topic, which boosts your credibility. It’s not directly about AI, but reputation often correlates with quality content. Also, people might upvote or share your answers more when you’re known, increasing your reach.
Challenges & Best Practices for Quora: The challenge on Quora is walking the line between helpful and promotional. Quora has moderation: overly self-promotional answers can be collapsed, or your account could be flagged. Always lead with value: if someone reads your answer and learns something useful, even if they never buy your product, you’ve done it right. Quora allows you to have a bio line that appears under every answer – you can use that to mention your role and company (“Product Manager at XYZ Security Co.”), so you don’t have to awkwardly shoehorn those details into the answer.
Best practice: write in a neutral, informative tone (as if you’re a friendly expert, not a salesperson). Also, keep an eye on your answer’s comments; if people ask follow-ups, responding can increase engagement (and an engaged answer might stand a better chance of being viewed as authoritative).
Quora content can be long-lived. A great answer could keep getting cited or viewed for years, including by AIs, so think long-term quality.
YouTube: Leverage Video Content That AI Can Read
Why YouTube matters: YouTube isn’t just the world’s largest video platform – it’s also one of the largest search engines. And now, it’s a key source for AI-driven answers. Google’s AI Overview cites YouTube nearly 19% of the time (no surprise since Google owns YouTube), and even non-Google AI engines like Perplexity heavily reference YouTube content (~14%). This tells us that AI systems are “watching” videos (or rather, reading transcripts) to pull out useful information. Think about all the “How to…” questions or product reviews that are brilliantly answered in video form. AI doesn’t watch the video, but it can access the transcript or description. So if a user asks, “How do I fix a leaky faucet?” the AI might cite a popular YouTube tutorial, pulling key steps from the video’s transcript or summary.
How AI uses YouTube content: When an AI cites YouTube, it’s typically referencing the transcript (which can be auto-generated or uploaded) or sometimes the video title/description as a snippet. Google’s generative search, for example, might say, “According to a YouTube video by HomeRepairGuru, you should first shut off the water…” and then link to the video. Perplexity might directly provide an answer and list the YouTube video as a source. The important part is: if your video’s text content contains the answer to a question, the AI can extract it.
Actionable steps for YouTube:
Create Videos That Answer Questions: This is the core of YouTube SEO and now AI SEO. Identify common questions in your niche and create videos tailored to answering them. For instance, if you’re a software company, a video titled “How to [Achieve Specific Outcome] with [Software/Product]” can be both a useful tutorial and a way to get that query space. Or a brand that sells kitchen appliances might make a video “How to choose the right blender for smoothies,” something educational that naturally features their product.
Optimize Titles, Descriptions, and Tags: Make sure your video title is clear and contains the key question or topic (e.g., “How to Fix a Leaky Faucet – Step by Step DIY Tutorial”). In the description, summarize the key points or steps in text. Many creators add a detailed description or even a transcript snippet – this is great for AI visibility because the AI can parse that text. Use relevant keywords in your description and tags as well (but avoid keyword stuffing). Essentially, treat the video description like a blog post that accompanies the video.
Provide Transcripts or Captions: Upload a clean transcript of your video or ensure the auto-captioning is accurate by editing it. This text is what AI will actually “read”. A well-done transcript not only improves accessibility for humans but also gives AI a full text to mine for information. If your video is an interview or a longform piece, consider adding timestamps/chapters with descriptive titles – those can act like an outline that AI might pick up on.
Engagement and Quality Matter: While an AI might not know how many likes your video has, the fact that a video is popular often correlates with it being surfaced. Google’s AI might be more likely to trust or choose info from a video that ranks highly in search or has good engagement. Promote your videos through normal channels to get that initial traction. Also, maintain high quality in terms of content accuracy. If your video spreads misinformation or low-quality advice, it’s less likely to be referenced by quality-focused AI (and it’s bad for your brand regardless).
Collaborate with YouTube Influencers: If you can’t create a lot of videos, another route is to get your product or expertise featured in other creators’ videos. For example, if there’s a well-known YouTuber in your industry, maybe you can sponsor a video or offer your product for a review or tutorial on their channel. If that video becomes a top resource on a topic, the AI might cite it, and your brand will be right there in the content being cited (“…in a review on YouTube by TechGuru, the XYZ laptop was praised for its battery life…”).
Monitor YouTube Search Trends: Use tools like YouTube’s search suggestions or Google Trends (or even a tool like Answer The Public) to see what questions people are asking that have YouTube results. This can guide your content creation. Remember, Google’s own AI has a strong integration with YouTube, so capitalizing on that connection makes sense.
Challenges & Best Practices for YouTube: Producing good video content requires more effort than text, from scripting to filming to editing. It’s an investment, but the payoff is not just in AI citations – it’s also in human engagement (YouTube can drive significant traffic and brand awareness on its own).
Best practices include:
Keeping videos concise and focused (if it’s a how-to, get to the point quickly)
Using visuals or on-screen text to reinforce key info (which also helps the transcript be clearer)
Encouraging viewers to ask questions in comments (which you can later answer, possibly giving more content for AI to pick up!)
Also, ensure the information you present is correct and up-to-date. If your video from 2023 is still being cited by AI in 2025, you want to make sure it hasn’t become outdated or misleading. If needed, update your video or add annotations in the description if something has changed.
One more tip: consider including a blog post version of your video on your site (with the transcript or a summary). This way, you’re covering both angles – your own site’s SEO and providing content that AI can find on YouTube. Plus, you might get a double-whammy: the AI could cite the YouTube video and/or your blog post (some AI answers list multiple sources).
Wikipedia: Earn Your Spot in the AI Knowledge Base
Why Wikipedia matters: If the internet had a “source of truth” trophy, Wikipedia would own it. It’s no surprise that Wikipedia is the top-cited source for ChatGPT and many other AI models. Nearly 48% of ChatGPT’s citations (in that Profound study) were Wikipedia. Even Google’s AI, which uses more diverse sources, still pulls from Wikipedia quite often (it appeared in Google’s top 10 sources as well).
The reasons are clear: Wikipedia is comprehensive, relatively reliable (thanks to citation requirements and community editing), and covers almost every notable topic under the sun. When an AI needs a quick fact or overview – be it “What is the capital of Bhutan?” or “Summary of blockchain technology” – Wikipedia is the go-to.
For marketers, Wikipedia is a double-edged sword. It’s hugely influential (if your brand has a solid Wikipedia page, you gain a ton of credibility and visibility in AI and traditional search alike), but it’s also something you can’t directly control or use for promotion.
How AI uses Wikipedia content: AI models often have Wikipedia baked into their training data. ChatGPT, for instance, was trained on a snapshot of the web that definitely included Wikipedia. That means even without live browsing, ChatGPT “knows” a lot of Wikipedia content by heart (up to its knowledge cutoff). With browsing or retrieval, AI systems will fetch the latest Wikipedia info as needed. Google’s SGE might quote a specific line from a Wikipedia article. Perplexity might list a Wikipedia page as a reference. In essence, a well-crafted Wikipedia entry about a topic becomes a ready-made answer source for AI.
Actionable steps for Wikipedia:
Secure Your Brand’s Wikipedia Page (If Eligible): If your company or organization is notable enough (in Wikipedia terms) to deserve a page, it’s worth ensuring that page exists and is accurate. Notability generally means significant coverage in independent, reliable sources (news articles, books, etc.). If you find your brand meets that bar but doesn’t have a page, you can cautiously attempt to create one, ideally through an experienced Wikipedian or consultant who knows the ropes. Important: Write the entry neutrally, citing external sources for every claim. This isn’t an ad or even a home page; it’s an encyclopedia entry.
If done right, that page can become a factual resource that AI pulls from. Maintaining accurate Wikipedia entries is crucial – you don’t want incorrect info on Wikipedia propagating through AI answers.
Contribute Information (Carefully and Ethically): Even if your brand itself isn’t Wikipedia-notable yet, you can still be part of the Wikipedia ecosystem. Let’s say you’re a specialist in renewable energy and your company does battery tech. You might improve Wikipedia articles on “Lithium-ion batteries” or “Renewable energy storage” by adding well-sourced information (perhaps findings from a study your company did, cited to a journal or news piece). This way, your work or expertise enters Wikipedia’s content indirectly. If your CEO or a key team member is notable (maybe they wrote a book or have been cited in the news), they might merit a Wikipedia page – ensure it’s accurate and not promotional.
Earn Your Mentions: One strategy is to create content that others end up citing on Wikipedia. For example, original research, industry reports, or data that no one else has, if it’s published on your site or in a journal and is picked up by journalists or academics, might be used as a reference on Wikipedia pages. This is a long play, essentially a PR/authority strategy, but it can work. If your survey of 1,000 consumers gets cited in a Wikipedia stat, your brand name might appear in the reference. AI might then mention “According to a 2025 survey by [YourBrand]…” in answers (it has happened!).
Keep Pages Updated: If you already have a Wikipedia page for your brand or related topics, monitor them. Set a watch on those pages (you can create an account and add pages to a watchlist). If someone vandalizes or adds incorrect info, correct it with proper citations. Also, update the page when new notable things happen (e.g., your company gets acquired, or releases a notable study) – again, with third-party references. Active maintenance ensures that AIs always get the latest and most accurate info.
Understand Wikipedia’s Rules: Engage with the Wikipedia community if needed. If there’s a fact about your company that’s outdated, you can’t just delete it because you don’t like it, but you can edit it if you have a source or discuss on the Talk page to reach consensus. And if you have a conflict of interest (like you’re a marketer for the company in question), the best practice per Wikipedia is to disclose that on the Talk page and politely suggest edits rather than directly editing the article. This transparency helps your changes stick, and it’s the right thing to do.
Challenges & Best Practices for Wikipedia: The biggest challenge is that you do not own your Wikipedia presence – the community does. If your brand isn’t considered notable, you might struggle to get a page or even a mention on a page. Pushing too hard can result in backlash (like speedy deletions or warnings for undisclosed paid editing). The best practice is to approach Wikipedia with a sense of contributing to public knowledge, not as a marketing channel.
That said, having a solid Wikipedia page is incredibly valuable. It’s like having a trustworthy public bio that every AI (and human) can reference. Many companies work with specialized Wikipedia consultants for this reason, to navigate the rules ethically. If you do engage someone to help, make sure they follow Wikipedia’s guidelines (no sneaky editing without disclosure).
Look at the Wikipedia pages of your competitors or similar organizations. See what content they include, which references are cited, etc. This can guide you on what a good page for your industry looks like. Also consider related pages – e.g., if there’s a page for your industry or a list of companies in your sector, make sure your company is listed if appropriate (with a citation).
The Profound study underscores Wikipedia’s importance: “Wikipedia’s dominance [in AI citations] suggests the importance of maintaining accurate Wikipedia entries”. In other words, treat your Wikipedia presence as a critical piece of your SEO strategy. It can pay dividends both in AI contexts and regular search (Google often shows a Wikipedia sidebar for known entities, and users trust it).
In part 2 of this series (coming here on Wednesday), I’ll dive into strategic planning for these platforms. Does, or can, one size fit all? And how can you use all of the information presented to guide your LLM discovery strategy?
Sources:
Profound (Nick Lafferty) – AI Platform Citation Patterns: How ChatGPT, Google AI Overviews, and Perplexity Source Information
LinkedIn (Josh Blyskal, Profound) – Post on Reddit citations spiking
SparkToro (Rand Fishkin) – How Can My Brand Appear in Answers from ChatGPT…; “Search Everywhere Optimization”
Search Engine Journal – AI Search Optimization: Data Finds Brand Mentions Improve Visibility (Matt G. Southern)
LinkedIn (Joseph Siegel) – Post on increasing LLM SEO via Reddit, Quora, etc.
Search Engine Journal – How To Build Consensus Online To Gain Visibility In AI Search (Kevin Rowe)