Most B2B buyers now build their vendor shortlist with AI. 92% say an AI answer shaped who made their list, and 84% use it on purchases above $1,000. This is what takes to show up when a buyer asks an AI assistant about your product i. Build a page for every use case you serve. Buyers prompt with a specific problem, and the page that names that problem is the one the model matches. ii. Rewrite your description until a machine can repeat it. Ask ChatGPT and Gemini what your company does. A vague answer means your own pages read that way, so rewrite them until the reply matches. iii. Put numbers in your case studies. Models quote claims they can attribute to a source, a line like "cut onboarding time from 14 days to 6" carries into the answer while general efficiency language gets left behind. iv. Publish real pricing. When your pricing page says "book a demo to find out," the model pulls numbers from review sites and old listings instead, and that estimate is what the buyer sees before talking to you. v. Write the comparison content yourself. Host the comparison and you set the criteria the model repeats. vi. Audit the verification chain. Buyers who see your name go check it, on your site, in search, and in your review profiles. That step decides whether the mention converts. Only 7% of buyers notice a vendor because they recognize the name. What you publish decides the other 93%, which is why unknown companies can win these mentions. Want the full playbook? Comment "AI" and I'll send over our booklet on how B2B vendors rank #1 in AI search results. Data from @semrush's survey of 600+ B2B professionals.

Most B2B buyers now build their vendor shortlist with AI. 92% say an AI answer shaped who made their list, and 84% use it on purchases above $1,000. This is what takes to show up when a buyer asks an AI assistant about your product i. Build a page for every use case you serve. Buyers prompt with a specific problem, and the page that names that problem is the one the model matches. ii. Rewrite your description until a machine can repeat it. Ask ChatGPT and Gemini what your company does. A vague answer means your own pages read that way, so rewrite them until the reply matches. iii. Put numbers in your case studies. Models quote claims they can attribute to a source, a line like "cut onboarding time from 14 days to 6" carries into the answer while general efficiency language gets left behind. iv. Publish real pricing. When your pricing page says "book a demo to find out," the model pulls numbers from review sites and old listings instead, and that estimate is what the buyer sees before talking to you. v. Write the comparison content yourself. Host the comparison and you set the criteria the model repeats. vi. Audit the verification chain. Buyers who see your name go check it, on your site, in search, and in your review profiles. That step decides whether the mention converts. Only 7% of buyers notice a vendor because they recognize the name. What you publish decides the other 93%, which is why unknown companies can win these mentions. Want the full playbook? Comment "AI" and I'll send over our booklet on how B2B vendors rank #1 in AI search results. Data from Semrush's survey of 600+ B2B professionals.

Google turned AI Mode into a paid surface in under a year. SE Ranking tested 50,032 commercial keywords across 20 niches. Ads appeared on a third of them. Most ad slots in AI Mode come in twos. 71.1% of the time, a second advertiser is in the answer with you. You pay for the slot. Your competitor pays for the one beside it. Google collects on both. The more a keyword is worth, the more likely this is.. Keywords under $2 showed ads 24.33% of the time. Keywords above $10 showed them 53.56% of the time. Then there is the question of whether anyone reads them. Search users learned to skip ads a long time ago. In AI Mode the ad sits at the edge of the response. The citations are the sources the answer is built from. Users read the answer. SE Ranking checked whether advertisers made it into those citations. They appeared as a cited source in the same response 11.53% of the time. So they are paying for a spot on terms they never earned anything on. The spot lasts as long as the money does. An organically cited position is different. Nobody shares it with you. It does not disappear when the budget pauses. And it sits inside the text the user is actually reading. Paid is easy to approve and easy to measure. That is why teams start there. It also puts you in a slot your competitor can buy tomorrow, at a price Google sets.

Grok 4.5 is now live. xAI built it to handle product research and to deliver “Smarter answers to any question” Users can now describe what they want, set a budget, and @grok will return a shortlist. Compare prices, weigh a big purchase, pick between brands. Grok handles the full research phase before anyone opens a store page. The buyer makes their decision inside the chat. This is becoming a major discovery surface for brands. But most brands and GEO teams leave Grok out of their AI visibility work. In turn, few studies exist on AI visibility in Grok, which feeds this cycle of not knowing what to do. However, Grok's adoption numbers say otherwise. @SpaceX 's IPO filing puts Grok at 117 million monthly active users as of March 2026. Grok holds 17.8% of the US chatbot market, third behind ChatGPT and Gemini. It ships inside X, so users start prompting without downloading anything. Those users ask Grok which products to buy, and Grok answers with the brands it trusts most. What this means? Grok selects sources differently from the other engines. It retrieves from two pools at once: the open web and live X posts. ChatGPT reads web pages. Grok reads web pages plus what people post about your category in real time. User-generated content dominates Grok's citation pool at a level ChatGPT and Perplexity don't show. Grok also weighs recency harder than the other engines, so fresh content and active discussion move the answer. Visibility in Grok requires an active X presence, mentions in community discussions, and current content. A brand optimized for ChatGPT alone covers one surface and leaves this one open. Want to learn more about AI visbility? Book a call with us.

AI visibility is the most compounding visibility a brand can build. Once a brand owns a category in AI answers, it keeps that spot 90.4% of the time, month to month. But SEO rankings need constant refresh. A competitor with fresher content or more links can push you off page one in a quarter. Kevin Indigo analyzed 50,000+ brands across 1,094 ChatGPT categories from January through June 2026. → 15.2% of categories have a clear owner → 89.3% of AI-search demand sits in categories with no owner yet → Owners hold first place 90.4% of the time, month over month → 74% of users pick the first brand the AI names In Google, ranking first gets you a click. In ChatGPT, being named first gets you the sale. There's also a gap between what AI reads and what it recommends. The top-cited source and the top mentioned brand overlap in only 20.8% of categories. Your page can feed the answer while a competitor gets picked. We call that gap ghost rankings. Two moves follow: → Pick one category. Track five prompts inside it: definition, comparison, alternatives, use case, buying question. Ownership needs a 5-point lead over the runner-up to hold. → Track mentions as the ownership metric. Citations tell you AI is reading your page. Mentions tell you it is actively recommending your brand. The window is open now. Claiming a category in 2026 costs less than displacing an incumbent in 2027, and the data says displacement is a fight most challengers lose. Want to learn more about AI visibility and how we can help you click the link below. Credit to @Kevin_Indig for the research.

Everyone thinks organic traffic is dying. Here's the trap we keep seeing brands fall into: They've been publishing 4-5 informational articles a month for years. That rapidly improved traffic, so they kept doing it, thinking their SEO strategy was working. (Even though sales didn't follow) Then ChatGPT, Perplexity, and Google's AI Mode started answering those questions directly. No click needed. Traffic collapsed. Now everyone's declaring Organic visibility dead. They're half right. Traffic from blue links is dying. Organic demand is bigger than ever. It just moved. Your buyers ask AI one question and act on the answer. "Best CRM for a small law firm." "Which real estate agency should I use in Austin." "Top universities for a marketing master's in Europe." The AI names 3 to 5 brands. T hose brands get the traffic, the trust, and the sale. Everyone else is invisible. That's AI visibility. Right now it's the highest-leverage organic channel there is. Barely anyone is optimizing for it, and AI referral traffic converts harder than search ever did. The AI pre-sells the visitor before the click. Three things to do this week: 1- Ask ChatGPT and Perplexity the questions your buyers ask. See if you're in the answer. 2- Check which sources the AI cites for your category. That's your new link building target list. 3- Stop measuring rankings. Start measuring how often AI recommends you. SEO told Google you exist. AI visibility makes the AI tell your buyers you're the answer.

Unsolicited AI visibility tip: @msftClarity (Microsoft Clarity) launched Topic Insights. A free tool that shows how often your content gets cited in AI-generated answers, how much it shapes those answers, and which competitors appear alongside (or instead of) you. A few things worth knowing: → Share of Authority tells you what slice of AI citations in your niche belongs to you. A 20% SoA means one in five AI answers on your topic pulls from your site. → Competitor tracking surfaces every domain that shows up in the answers, including sources you never added to your list. → Content gap recommendations point to specific topics where you have ground to gain. → Data windows run 7, 28, and 90 days once the Clarity script has been active on your site for a week. For context on why this matters: Google Search Console's generative AI performance report still only shows impressions. No citation detail. No competitive context. Adobe, Amplitude, and most standalone GEO platforms sell this category of insight as premium functionality. Microsoft is giving it away for free. Want to see where you stand today? Run a free audit at audit.algomizer.com

AI agents don't read your website the way you do. @Google just published the playbook. Agents work from three inputs: screenshots, raw HTML, and something called the accessibility tree. That last one is where most sites fail. It's a hidden, stripped-down map of your page. Roles, names, headings, states. Screen readers have used it for decades. AI agents use it now too. Check yours in Chrome: + Right-click any page, hit Inspect + Click the double-arrow icon in Elements + Select Accessibility + Toggle on "Show Accessibility Tree" A clean tree shows your headings, buttons, links, and page structure. A broken one is a wall of nothing. UC Berkeley and Michigan researchers found agent task success drops from 78% to 42% on sites with a degraded tree. Fix it with proper HTML headings, labeled inputs, descriptive link text, alt text. Source: web.dev/articles/ai-agent-si…

OpenAI just became the first ad platform that turns away your money. ChatGPT now runs product feed ads. A retailer connects the same product catalog it already sends to Google Shopping. Then ChatGPT builds the ads itself from the titles, images, and prices in that file. → No design work → No campaigns to set up → Up to one million products per advertiser But before any of that happens, OpenAI asks for a sample of 100 products. If the data in that sample is messy, the brand cannot advertise at all until it gets fixed, unlike Google, Meta, and Amazon that let everyone in, then flag bad listings one by one. Why so strict? Because these ads sit right under ChatGPT's answers. A bad product recommendation makes ChatGPT look bad, and OpenAI knows it. Here is where it gets interesting for anyone working on their AI visibility The same catalog does double work: → It powers the sponsored ads → It powers the organic product results ChatGPT shows for free The model reads the conversation and picks the products that fit, in the ads and in the answers. It makes that call based on how well your data describes what you sell, who it serves, and when it belongs in the conversation. That decision runs on GEO work. Structured data, clear product information, content the model can read and trust. A brand that has this in place shows up in the free answers and gets picked more in the paid slots. A brand that skipped it spends money and stays invisible. People come to ChatGPT for advice, and one bad recommendation under an answer eats into that trust. Rejecting ad money costs them less than letting messy data break the experience. AI visibility work was optional when it only affected organic mentions. Now it decides your ad performance too. Learn more about AI visibility, check out algomizer.com