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🔍 What actually makes AI models trust your brand? We asked @Mira Hayashi, our Head of Success, that exact question. Her answer might surprise you. It's not popularity. It's not how long you've been around. It's not even your traditional SEO rankings. It's authority. Here's why: after the early wave of AI hallucination stories, models made a course correction. Now, when they're pulling source and citation material, they're hunting for expertise and deep understanding, not just what's popular. And there's a second factor that matters just as much: freshness. Mira points out that AI models tend to treat content older than two months as out of date. The good news? This levels the playing field. You don't need decades of content history to earn trust. You need to consistently show up with accurate, authoritative, up-to-date content. Authority and freshness. That's the combination that moves the needle right now. What's your brand doing to stay current in the eyes of AI models? 👇

📽️ YouTube is a must-have source of citations for your brand. Thrilled to be working with @Ben Jones and the team at @Sundogs Creative. Ben just dropped findings from analyzing 3,900 videos (with data from @Jellyfish) that every brand marketer needs to see." A few highlights: 💡 YouTube has blown past Reddit as the leading LLM citation source across CPG, Auto, and Tech. 💡 The videos driving those citations are about 60% from creators, 30% from experts and editorial sources, and only 10% from brands. And views, recency, and production quality don't seem to matter Read Ben's post for more insights and to request the complete breakdown. 👉 https://lnkd.in/er74bKcY

⬇️ If you're a B2B agency serving tech clients, listen up: "There is no strategy without intelligence, and I viewed Gumshoe as my intelligence tool to get started with my strategy." @Kris Gösser, CMO at @Shipium Kris explains what made Gumshoe stand out: "What made Gumshoe stand out was the initial commitment to looking at this at a more statistical model." He noted that other vendors had started to view that as something that needed to happen, but he hadn't seen real commitment to building it into the baseline of the product. When he tested a report and looked at the outcomes, the broad approach across different permutations, rather than a discrete result, was what convinced him he was looking at real data and real insight, not something that could be a red herring. From there, the report structure mattered. Kris could build reports tied to the strategies he cared about tracking: versus specific competitors, in conjunction with certain partners, and around themes like AI and shipping. That level of abstraction gave him confidence he was getting the right signal. Gumshoe became the diagnostic driving Shipium's quarterly plan. One quarter it surfaced technical SEO gaps limiting bot indexing, and fixing those drove a lift in visibility scores. The next quarter, it identified content format gaps, and diversifying content drove the next lift. In under four months, citations of Shipium's content across AI models increased by 557%. In Kris's words: "Every AI prompt is basically its own little campaign now." For B2B agencies: clients' buyers are researching vendors in AI chat before sales ever gets involved. See how Shipium built a GEO practice around tracking that visibility with Gumshoe: https://lnkd.in/ezrUMxKi

Where should you publish Gumshoe-generated content? 📍 Posting targeted content in the right places is one of the fastest and most reliable ways to improve your visibility across AI models. Here's what we've found works best: 💡 Your own website is the most powerful channel. 💡 AI models cite brand websites roughly 30% of the time when giving recommendations. Your site gives you full control over structure, metadata, and updates, and it's the fastest path to noticeable visibility gains. Best spots on your site: • Bottom of relevant product or category pages • A structured FAQ section • Resource hubs or learning centers • Dedicated landing pages built for specific topics 💡 Social media matters more than you might think. 💡 LLMs can quickly crawl many social platforms. LinkedIn, Reddit, Quora, YouTube, and TikTok are all on the radar. Social posts work best when they answer a direct, straightforward question, mirroring how users actually prompt AI models. 💡 External channels extend your reach. 💡 PR releases, media partners, industry publications, and third-party collaborations help diversify your authority signals and train LLMs in the domains they're already visiting. Add these to your strategy, but your website should stay the foundation. 💡 One more thing: writing style matters. 💡 Gumshoe offers two options. AI-Optimized (structured, authoritative, great for FAQ or bottom-of-page placements) and Brand Voice (on-brand, still optimized for AI, ideal for anything your audience will actually read). AI visibility isn't just about what you publish. It's about where. Generate GEO / AEO optimized content using Gumshoe AI today 🤓

@Maria Carter, loved having you at the table! Bringing together people from different roles and agencies was very much by design, and it's great to hear it led to a real conversation. See you next time!

💡 If your brand disappeared from AI-generated answers tomorrow, would you know? One of our users, Andres Perea \[https://lnkd.in/eEZrb63w\] of @MilliporeSigma, just published a great piece as part of his search and AI discovery series: "Demand Security: The Strategic Purpose of Search in the AI Era." That's the core question behind "demand security" - the idea that AI search is shaping buyer preferences before anyone visits your site, clicks an ad, or fills out a form. By the time your analytics show it, the demand has already moved on. A few things that stood out: ➡️ Traditional rankings don't guarantee AI visibility - research shows AI Overviews and classic Search retrieve substantially different sources ➡️ Nearly 30% of AI Overview citations don't appear in regular first-page results ➡️ Sessions and conversions are lagging indicators - they don't tell you what AI said about your brand before the click ➡️ Brands invisible in AI-generated answers risk losing demand before they ever see it in analytics This is exactly why we built Gumshoe. Full article linked below - worth the read. https://lnkd.in/eeFrFjAk

People use "AI model" and "LLM" like they mean the same thing. They don't. Understanding the difference is not just a technical detail. It is the foundation for making smarter decisions about how AI-powered tools actually work, and which ones are built to solve your specific problems. Here is the breakdown: 💡 An AI model is a broad term. It refers to any machine learning model trained to perform one or more tasks. Image recognition. Speech processing. Recommendation engines. Fraud detection. These are all AI models. The category is wide because the applications are wide. 💡 A large language model (LLM) is something more specific. It is a type of AI model, yes, but one built around understanding, reasoning about, and generating human language. It is a subset of the broader AI model category, purpose-built for language-based applications. Think of it this way: every LLM is an AI model, but not every AI model is an LLM. The same way every search engine is a software product, but not every software product is a search engine. As AI-powered search and language processing continue to evolve, this distinction matters more than ever. The tools you choose, the outputs you trust, and the workflows you build all depend on knowing what kind of model is actually under the hood. At Gumshoe, we think clarity is the starting point for everything. Know what you are working with, and you will know what it can do for you.

Search took 15 years to reach a billion monthly users. Social media took 10. AI did it in under 3. Our CEO @Todd Sawicki has been thinking about this for a long time, and his explanation for why is worth sitting with. It is not momentum or hype alone. It is that AI solved a problem search never could. Search was built on links, not understanding. Google crawled the web and ranked pages by who linked to them. Popularity, not accuracy. And because it was a popularity contest, people learned to game it. The most optimized content won. Not the most useful. Here is why that happened. Google never actually read the content on a page. Reading every word on every page across the entire internet was too expensive. So instead, it looked at links between sites and treated them like votes. The more links pointing to a page, the more authoritative it was assumed to be. That was the system. And once people figured out the system, they built an industry around gaming it. Content that ranked was not always the best answer to a question. It was just the most popular. Or the most engineered to look popular. AI changed the entire premise. AI does not look at links. It reads content. It understands context and semantics. It is trying to figure out what a page is actually saying, not how many other pages point to it. And from that understanding, it tries to give you an actual answer, not a list of candidates you have to sort through yourself. But the shift goes even deeper than that. AI is not just trying to answer the question. It is trying to answer the question for you, specifically. Every response operates on two axes at once: everything it knows about the world, and everything it can infer about you as an individual. Search gave everyone the same list of links. AI gives each person a personalized answer built from the full context of what they asked and who they are. That combination of genuine utility and personalization is why a billion people adopted it faster than any platform in history. It is a better experience. Not incrementally better. Fundamentally better. For marketers, the implications are significant. AI is not just a new channel. It is a fundamentally different way of surfacing information, one built on understanding rather than popularity. How brands get found, understood, and recommended has fundamentally changed.

🏖️ One of the standout sessions on AI and brand discovery is happening on Wednesday at Cannes Lions. 🗓 Wednesday 24 June, 11:30–12:00 ⏰ 30 mins - Location: LinkedIn Rooftop, The Carlton Hotel "Winning the AI Discovery Era: Marketing to Minds and Machines" brings together: 🎙️ OpenAI CRO @Denise Holland Dresser 🎙️ Google CMO @Lorraine Twohill 🎙️ JPMorganChase CMO @Carla Zakhem-Hassan 🎙️ Savvy Matters CEO @Shiv Singh Moderated by LinkedIn CMO @Jessica Jensen, to unpack one of the most important shifts in marketing right now: AI isn't just changing how brands create. It's changing how buyers discover. For decades, marketing followed a predictable model: build awareness, drive traffic, convert demand. That model assumed buyers would search, scroll, and find you. But in an AI-mediated world, discovery is no longer linear. It's a compressed decision moment shaped by what systems can find, summarize, and recommend. Your brand is either part of that answer or it isn't. The question on the table at Cannes this week isn't just about creativity. It's about visibility. When your buyer asks an AI for a recommendation, is your brand part of the answer? And if it is, what is it saying about you? Most brands don't know. That gap between the work marketers pour into campaigns and what AI actually tells buyers is the defining challenge of this moment. That's exactly what we built Gumshoe to answer. We measure how AI talks about your brand across top models through the lens of your actual buyer personas. Not just whether you're mentioned, but how, when, and to whom. Wednesday's session is a signal that this conversation has arrived at Cannes. We think it's just getting started. See Details: 🔗 https://lnkd.in/eCydD8tB

A few years ago, you searched for something on Google and got 10 blue links. Today, you get an answer. AI-powered summaries are now deeply integrated into Google, Bing, and other major search platforms. And the numbers reflect just how fast this shift is happening: 📊 Up to 60% of searches now include an AI-generated summary. 📊 AI search queries account for 2–30% of total referrals, depending on the topic and industry. 📊 ChatGPT alone processes 500 million unique searches per month. This isn't a future trend. It's already the default experience for millions of people searching online right now. For businesses, that changes everything. Visibility used to mean ranking on page one. Now it means being understood and referenced accurately by AI models that synthesize information before a user ever clicks a link. That's where AI Optimization (AIO) comes in. Unlike traditional SEO, AIO focuses on how AI systems interpret your brand: your structured data, schema markup, and content clarity all play a role in whether an AI model surfaces you accurately or skips you entirely. Gumshoe's AIO tools provide model-specific recommendations to help brands understand how AI systems interpret and surface their content.