Content Strategies to Improve LLM Citation Visibility

I'm hearing CMO's talk about AEO (AI engine optimization) a lot. They're asking "How do I rank in genAI platforms?" So what should CMOs ask their teams to do in order to become citable, authoritative sources for AI? The AEO playbook is still being written. New measurement are being created. From what I'm seeing and what experts in the field are saying, the consensus is that AEO is more like SEO (search engine optimization) than not, but with some important tweaks. 1️⃣ Double down on genuinely valuable, original content (especially original data): This cannot be overstated. AI engines are getting smarter about recognizing true expertise as they get excellent signals from users about what's useful or not. While Google was the "database of intent" from a search query, LLMs typically get the benefit a back and forth with users that make it really clear to the LLM what's valuable or not to the user. 2️⃣ Optimize for answers rather than keywords: Rather than building original content for a keyword you want to rank for and then a cluster or keywords around it, build content that fully answers a question you think your prospects are asking... and then build content for a cluster of questions they might ask around that original question. This reframing is important for your content strategy. Also consider conversational language in your writing to more closely mirror how people actually ask questions in LLMs. While we all needed to learn how to "speak Google" as users of search, the LLM query is, as we all know, much closer to a typical conversation. 3️⃣ Structure for AI Consumption: LLMs "remember" better clearly organized information. Consider these techniques: * Direct answers up front: Get to the point quickly * Clear hierarchies: Use your H1s, H2s, H3s logically. This structure is important for the LLM to understand difference in and relationships between concepts * Scannable formats: Bullet points, numbered lists, and FAQ-style sections are often your friends, but not required * Schema Markup: Another useful way to clearly indicate to LLMs the structure and meaning of content 4️⃣ Build and broadcast authority: High-quality backlinks still matter. New for LLMs, authoritative sites mentioning _in plain text_ that your brand is an authority on specific topics is really important. Why? Because LLMs consume that plain, unlinked text for training. You can think of each repetition in plain text as another round of the LLM trying to memorize something... the more reps, the more you remember. 5️⃣ Technical Readiness: * AI Crawler Access: Can bots like GPTBot & Google-Extended actually reach your content? Check robots.txt and consider llms.txt. This is a simple extension from SEO * Speed & Clean HTML: Fast-loading, well-structured pages win, which is not really a change from SEO This is the best guidance I see in a rapidly evolving space with no definitive guidance. What are you seeing? Please share in the comments

Authority just became the new ranking factor for AI systems. BrightEdge's latest data reveals that Google AI Overviews are increasingly relying on authoritativeness as queries become more complex. But this isn't just a Google trend… we're seeing the same pattern across ChatGPT, Claude, and Perplexity. The more sophisticated the user query, the more AI systems scan for clear expertise signals before deciding which sources to cite. This changes everything about content strategy: Generic bylines and scattered expertise areas won't cut it anymore. AI systems want to see consistent authority patterns across multiple platforms before they'll trust you enough to cite. We've been tracking this shift with uSERP clients for six months. The brands with strong author authority signals are getting cited way more often in complex, high-value queries compared to companies with fragmented expertise positioning. What actually builds AI-recognized authority: - Consistent identity across every platform using the same byline on your site, LinkedIn, and professional profiles. Unified author bios with consistent SameAs schema links help AI systems connect your expertise across sources. - Topical expertise clusters by focusing content around 3-4 core areas rather than scattered topics. LLMs favor specialists over generalists when forming citations for complex queries. - Proper Person schema implementation through JSON-LD markup including knowsAbout, sameAs, and professional credentials. This helps AI systems understand and triangulate your expertise across platforms. - Authoritative citations in respected industry publications and academic sources. LLMs weight mentions from .edu sites and recognized publications higher than generic content. The pattern is clear: scattered personal brands won't survive AI-powered discovery. The experts who build systematic authority signals across platforms will dominate citations in their categories.

Here’s how I build an LLM content strategy in 2025: — 𝗦𝘁𝗲𝗽 𝟭: 𝗥𝘂𝗻 𝗮𝗻 𝗔𝗜 𝗩𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗔𝘂𝗱𝗶𝘁 → Where is your brand mentioned in ChatGPT? → What prompts surface your content? → Where are competitors cited that you aren’t? This shows you the gap—and the opportunity. 𝗦𝘁𝗲𝗽 𝟮: 𝗘𝘅𝘁𝗿𝗮𝗰𝘁 𝗕𝘂𝘆𝗲𝗿-𝗟𝗲𝗱 𝗣𝗿𝗼𝗺𝗽𝘁𝘀 → Use Google PAA, Reddit, and call transcripts → Identify bottom-of-funnel prompts → Reverse-engineer the decision journey Don't guess what users ask LLMs. 𝘍𝘪𝘯𝘥 𝘰𝘶𝘵. 𝗦𝘁𝗲𝗽 𝟯: 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝗬𝗼𝘂𝗿 “𝗙𝗨𝗤𝘀” → Frequently Unasked Questions = massive opportunity → These are the gaps no one is filling → Original research helps you 𝘣𝘦 the source New answers → new citations. 𝗦𝘁𝗲𝗽 𝟰: 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗔𝗻𝗰𝗵𝗼𝗿 → Create a single “entity home” page → Add schema + “sameAs” links → Include clear founding, product, customer, and differentiator info LLMs need to know who you 𝘢𝘳𝘦. This is how they learn. 𝗦𝘁𝗲𝗽 𝟱: 𝗖𝗼𝗿𝗿𝗲𝗰𝘁 𝗬𝗼𝘂𝗿 𝗠𝗲𝘀𝘀𝗮𝗴𝗶𝗻𝗴 𝗘𝘃𝗲𝗿𝘆𝘄𝗵𝗲𝗿𝗲 → Align bios, PR, press pages, affiliate blurbs → Keep descriptions consistent → Don’t confuse the model If your brand presence is inconsistent, the model won’t know who you are. 𝗦𝘁𝗲𝗽 𝟲: 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗳𝗼𝗿 𝗔𝗜-𝗣𝗮𝗿𝘀𝗮𝗯𝗹𝗲 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 → Short sentences. Ordered sections. → Semantic triples (subject → object → predicate) → Clear headers + natural language Think “easy to quote” — that’s the bar. 𝗦𝘁𝗲𝗽 𝟳: 𝗣𝗶𝘁𝗰𝗵 𝗖𝗶𝘁𝗲𝗱 𝗦𝗼𝘂𝗿𝗰𝗲𝘀 → Identify the blogs, pages, and publishers ChatGPT already cites → Get featured or collaborate → Build citations like you used to build links In the LLM era, citations 𝘢𝘳𝘦 authority. 𝗦𝘁𝗲𝗽 𝟴: 𝗧𝗿𝗮𝗰𝗸 𝗧𝗵𝗲 𝗥𝗶𝗴𝗵𝘁 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 → Count your share of citations per prompt → Identify funnel stage breakdown (TOFU/MOFU/BOFU) → Measure growth in agentic bot activity (e.g. ChatGPT-user) No GSC for ChatGPT means you build your own dashboards. 𝗦𝘁𝗲𝗽 𝟵: 𝗧𝗿𝗲𝗮𝘁 𝗬𝗼𝘂𝗿 𝗟𝗟𝗠 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆 𝗟𝗶𝗸𝗲 𝗮 𝗚𝗿𝗼𝘄𝘁𝗵 𝗟𝗼𝗼𝗽 → Audit → Act → Re-measure → Repeat This is LLM-led growth. And it works. _ 📄 Save for future reference. ♻️ REPOST so others can learn too. P.S. Hit the 🔔 for weekly #AI + #SEO updates.