Andrea M.’s Post

Let’s talk about ✨the hero dependency! ✨ This is one of the biggest mistakes you can make while building modern SEO strategies and online visibility: relying on only one person maintaining all JSON-LD schema by hand. It is a problem because it is an entity scaling trap! When you rely on only one person, there can be a big problem, as there are no quality gates, and inconsistent data might be present. In addition, since only this one person understands the system, if anything ‘breaks’, there is only one person who knows how to fix it. Sure, it will work if the brand you are working on has very few entities, but if you want to scale to hundreds of entities, this model won't last. Guess what you actually need to scale? 💜Distributed ownership, clear roles and shared documentation. More than that, you will need to look into: ✨Automated Pipelines ✨ Schema generation flows from entity registry ✨Validation Before Deploy ✨Zero errors reach production ✨Proactive Monitoring; and ✨ Issues detected before impact This means NO hero dependency! You and your team will be proactively monitoring the Knowledge Graph and identifying issues before they impact brand visibility in traditional and modern AI sarch systems. More on this, and how to set appropriate systems for semantic SEO and AI search visibility in our latest course AI Search & LLMs: Entity SEO and Knowledge Graph Strategies for Brands by Beatrice Gamba 🔥 #EntitySEO #MLforSEO #KnowledgeGraphs #SemanticSEO

🔦 Lighthouse score isn't everything, but if AI can get you a 99 in a 20 min conversation ... here's how. Now, you might have to work through a development or marketing team, but still an interesting experiment. 1. Ask your LLM how to calculate lighthouse in Chrome - F12 to open developer tools - look at the top for Lighthouse (to the right) - click "Analyze page load" 2. You will now get a page score and there is an INSIGHTS section - expand the insights (focus on the 🔺red triangle ones) - copy/paste those into your LLM with using an SEO persona 3. Apply the results - I built a custom website with AI and could do this directly (I'll post on this) - Give the results to the appropriate person to apply. 4. Check you score, rinse, repeat. NOTE: My original image was NOT incognito, but I have added that to the comments. 98 incognito vs. 99 non-incognito. I expected a few folks to point that out :). Here's to a great Saturday ☕

Do you know how to turn your Knowledge Graph into LLM citations? Let’s keep this short and sweet, but there is SO much more to discover and expand on. You can explore it all in more depth in the AI Search & LLMs: Entity SEO and Knowledge Graph Strategies for Brands course by Beatrice Gamba https://lnkd.in/d9_6qBNj What you will need to do to start building your brand’s LLM citations is:  ✨ Add content context to your entities ✨ Distribute entities across multiple platforms ✨ Build association through co-citation ✨ Create citation-worthy answers Simple enough, isn’t it? If you are wondering where to start with each of these aspects, here are a couple of quick actions:  ✨ Write one article attributed to your top Person entity  ✨ Update one LinkedIn profile + create Wikidata entry  ✨ Write one comparison article ✨Add an FAQ section to your key content with answers attributed to specific Person entities Don’t forget to update your entity schema, entity schema relationships and use the FAQPage schema. This is how you turn your knowledge graph into citations! #EntitySEO #MLforSEO #KnowledgeGraphs #LLMcitations 

I’ve just realised something. We built GEO+… and I never actually said that the early beta is live. This actually started as a vibe coding project I kicked off to upskill and better understand how LLMs surface answers. As I went, the conversations I was having shifted away from rankings and keywords, and towards a different question: “How does our brand show up when AI gives the answer?” Search is no longer just links on a page. It’s increasingly AI-generated responses, summaries, and recommendations. That’s the gap GEO+ is designed to help with. What started as a learning project has turned into something more semi-serious. A tool that checks how AI models reference your brand, your services, and your language across common prompts, giving a clearer picture of visibility beyond traditional SEO. The early beta is now live. It’s intentionally simple. The goal is learning, not perfection. If you want to explore it, you can try GEO+ here: https://lnkd.in/epJ4wRi6 And if you use it and want to share feedback or ideas, we’ve set up a Discord channel where we’re shaping the next version in the open: https://lnkd.in/eG9A2GDe I’ll be sharing what we learn as we go.

Discovery is changing. More people are getting answers from AI, not search results. That raises a new question for brands: How do you show up when AI gives the answer? That’s why we built GEO+. GEO+ is an early-stage tool that helps explore how AI models reference brands, services, and language across common prompts. It’s not about replacing SEO, but understanding visibility in a world where answers are generated, not just ranked. The early beta is now live. It’s intentionally lightweight, and we’re building it in the open. You’ll find the link to try GEO+ in the comments. Want to help shape what comes next? Join the conversation on Discord (link also in the comments).

Speed is the new currency of trust in 2026. ⚡️ We all know the feeling of waiting for a slow website to load—you usually just click "back" and go to the next result. But did you know that in the era of GEO (Generative Engine Optimization), speed isn't just about user patience? It’s about being "readable" to the machines that drive the internet. Let's be honest: having great content is only half the battle. The hidden half? Performance Architecture. 🚀 Why Performance Weights Heavily on SEO & GEO  Search engines and AI agents are obsessed with efficiency. When your site is sluggish, unstable, or blocked by heavy scripts, two things happen:  SEO (The Human Side): Google's Core Web Vitals (like how fast your main content paints or how stable your layout is) directly impact your ranking. If your site shifts around while loading (CLS) or takes too long to respond (TTFB), you are signaling a poor user experience.  GEO (The AI Side): This is the game-changer. AI models have a "token budget" and a need for speed. If your Total Blocking Time (TBT) is high, or your server response lags, AI agents view your site as "computationally expensive" to process. They might skip your deep content entirely in favor of a faster, more optimized competitor. 🛠 It's Not Just About Loading Fast  True performance is about stability and clean code delivery. It's about ensuring:  Visual Stability: No jumping elements that confuse users (and bots).  Interactivity: The browser isn't locked up by heavy background scripts.  Efficient Asset Loading: Using modern image formats (like AVIF) and prioritizing critical data.  If your performance architecture is weak, your brilliant content is effectively locked behind a rusty door. ✅ Audit Your Performance in Seconds  You don't need to guess if your code is blocking the main thread or if your layout is shifting. You just need the right checklist.  Is your site fast enough for the humans of today and the AI agents of tomorrow?  Find out exactly where you stand and how to fix it: refactor.tools

You already don’t understand how search works anymore if you think MCP is an 'AI dev thing'. Over the last few months, the signals have been impossible to ignore: • AI Overviews expanding • Zero-click searches rising • Content being summarized, not visited • Search shifting from discovery to decision support And now Anthropic donates Model Context Protocol (MCP) to the Linux Foundation to standardize how AI agents interact with tools, data, and the web: https://lnkd.in/gsA3j-gH This matters far more for SEO than most people realize. What MCP & recent search shifts are really telling us: 1. Execution is becoming automated. Strategy is the new differentiator. Marketing is moving away from: Create → optimize → repeat (manually) And toward: Set intent once → AI agents generate, update and optimize continuously. 2. SEO tools are no longer just dashboards. They’re becoming decision engines that: • Feed real-time signals into AI agents • Trigger changes instead of reporting them • Integrate directly with content, product, and growth systems MCP is what makes this interoperable. 3. Search itself is changing too. It’s no longer just: ➡ queries → rankings → clicks It’s becoming: ➡ intent → agent → action AI agents don’t just 'read' content. They call APIs, compare options, execute workflows and decide outcomes. The quiet new question for SEO teams: Can an AI agent actually use what you publish? If the answer is no, rankings alone won’t save you.

Your rankings are lying to you Search no longer hands out clicks. Large language models rewrite raw pages into concise answers, so ranking first often means your page never shows up in the final response. Traditional SEO treats pages as endpoints. LLMs treat content as inputs for a new answer, which breaks the assumption that position equals visibility. I saw a mid market SaaS with a 3k word guide that kept ranking but stopped appearing in AI answers; the model recombined their facts with a niche forum that had clearer attribution and cited the forum instead. The new currency is citation and surfaced trust, not rank. If machines cannot tie claims to a clear brand entity you will be excluded from the answer even if you rank. Do this today: pick your highest intent page and add a short factual summary at the top with author, date, explicit source links and a unique claim that only your brand can own so models can attribute the answer to you. Which page will you edit first to win answers instead of clicks? #AEO #GenerativeSEO #SearchEvolution #EntitySEO

Structured Data for AEO I've been diving deep into how the search game is shifting big time with AI taking center stage and honestly, structured data feels like the secret weapon we're all sleeping on for Answer Engine Optimization (AEO). Lately, I've seen firsthand how implementing Schema.org markup (mostly JSON-LD) is becoming absolutely essential. It's not just a nice-to-have anymore. it's helping AI systems like Google's AI Overviews understand and pull from our content more accurately, leading to better citations and visibility. From my experience and the latest insights I'm tracking, structured data boosts things like: - AI Overviews and Generative Results: Makes it easier for AI to synthesize and feature your info directly. - Voice Search: Preps content for quick, spot-on responses on assistants. Rich Snippets and Featured Results: Amp up visibility and fight those zero-click searches. - E-E-A-T Boost: Clearly signals expertise, authorship, and trustworthiness. Right now, I'm prioritizing types like FAQPage, HowTo, Article, and Product schema on key pages. They've been game-changers for getting content pulled into direct answers. What about you? Are you ramping up structured data for AEO? Which schema types (FAQ? HowTo? Something else?) have delivered the biggest wins for your site's visibility or traffic shifts? Share your wins, challenges, or tips below - let's geek out on this! 👇 #AEO #SEO #StructuredData #SchemaMarkup #AIOverviews #DigitalMarketing #ContentStrategy

Why the Industry is Standardizing the term AEO (and Why That Decision Matters) The AEO vs. GEO vs. SEO debate looks academic on the surface. It isn’t. The industry isn’t standardize on AEO (Answer Engine Optimization) because it sounded better. They're standardizing it because AEO describes the actual economic outcome marketing teams are now accountable for. GEO centers the model. AEO centers the moment of decision. Executives don’t ask, “Did we optimize for the right LLM?” They ask, “ Did we show up as the answer when a buyer asked a question?” That framing shift matters. AEO forces strategy away from traffic abstraction and toward resolution quality: Are we answering real, intent-rich questions? Are our explanations structured, quotable, and trusted? Can an AI confidently surface us without hedging? This is why AEO is winning the terminology war. It aligns incentives across buyers, brands, and AI systems. SEO asked: Can we rank? AEO asks: Can we resolve uncertainty better than anyone else? That changes content strategy, measurement, and budget allocation. Not because of semantics — but because language shapes strategy. 💬 Are you still optimizing for rankings, or are you becoming the answer? References Profound — Why I’m Betting on AEO Over GEO (And Why the Terminology Debate Actually Matters) https://lnkd.in/eFkaBvKf OpenAI — How AI Models Retrieve and Present Answers https://lnkd.in/evn7r_-3 Google Search Central — Understanding How Search Surfaces Answers https://lnkd.in/efZGivUz