Dmytro Sokhach

7 SEO Tips to Rank on AI Overviews: You spend hours writing. You edit, polish, hit publish… Then Google’s AI Overview takes one glance and goes: "Yeah... no thanks." Painful right? It’s not that your ideas aren’t good. AI just can’t use them if they’re: - Buried under long intros and fluff - Missing the clear, direct answers it wants - Stuck with stats that expired years ago (AI’s picky, not sentimental) The result: Your content never shows up, and you miss out on the traffic, leads, and credibility you worked for. The fix doesn’t require advanced SEO. You need to write in a way AI can actually process. That’s why I pulled together 7 simple ways to make your content irresistible to AI Overviews. → The full list is in the image. ___ And if you’d rather not guess what’s holding your site back, Maverank runs 60-second SEO audits that show you exactly where the problems are, and how to fix them. 👉 Try it FREE: link in the comments 🔗

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📈 +24% SEO impressions 🤖 +331 new AI citations I shared this last quarter, and months later it remains one of the cleanest, easiest, highest-return AEO wins you can implement today. And it came from one of the simplest experiments we’ve ever run at Webflow. Steal this 👇 🍀 What we did We added structured FAQs + clean schema automation to a handful of core product pages — CMS, SEO, Design, Interactions, Shared Libraries, Hosting. No fluff. No AI theatrics. Just clearer answers to real questions people already ask. Huge shoutout to Vivian Hoang and my Growth team (and to AirOps for powering the workflow). This crew continues to ship magic. 📊 The impact ✅ 331 new citations (57% of all new ones across Webflow.com) ✅ +24% SEO impressions ✅ Visibility lifted across almost every tracked cluster Tiny structural change → massive compounding effect. 🧠 Built in AirOps, this AI-driven workflow used Perplexity for deep research and Reddit + niche subreddits + Google PAA + other forums to surface the real questions users are actually asking in our industry and about our product. From there, it: 1️⃣ Analyzed existing FAQs and identified gaps 2️⃣ Mapped and prioritized the highest-intent questions 3️⃣ Generated new on-brand, product-specific answers 4️⃣ Structured everything into clean, automated schema markup 5️⃣ Published a fully optimized FAQ system with zero manual lift AEO in a box. Stepping into 2026, the easiest way to grow isn’t publishing more — it’s answering better. The lift came from clarity, structure, and answer depth...not new pages. Just clearer, more complete answers to the questions people are actually asking. This is one simple experiment that reinforces what Ethan Smith has been calling out so brilliantly: good AEO is an extension of good SEO, extended into an AI-first world. The principles don’t change...sharpen clarity and structure, and both engines reward you.

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How I Spot & Fix AI SEO Gaps Before They Kill Traffic: Search is moving fast. By the time you notice AI is ignoring your brand, your competitors have already taken your spot. The problem? Most teams still: - Only optimize for Google SERPs - Have no idea which sources feed AI answers - Don’t benchmark against competitors in AI search - Miss the conversations that get cited by AI That’s why I use Peec AI to track and compare brand visibility across AI search. With it, I can: → See where my brand shows up (or disappears) in ChatGPT, Claude & Perplexity → Spot the high-impact sources worth doubling down on → Benchmark AI visibility vs. competitors → Track & join the discussions that build real authority signals One client was missing from 100% of AI answers in their niche. Three months later, they dominated the top responses. To help you do the same, Peec created a free Generative Engine Optimization (GEO) guide. It walks you step by step through how to build visibility in AI search, so your brand isn’t left behind. 👉 Comment “guide” and I’ll send it to you.

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It does NOT matter what Google does with cookies or not. 1️⃣ Google is not going to own Chrome soon and their series of AdTech tools are also likely to be dismantled as US DoJ is explicitly after this. 2️⃣ Cookies on its own are not effective currencies for digital ecosystem for many reasons. Can we simply stop talking about cookies in 2025 and simply focus on how Google played with the entire industry for years? Because that is what matters.

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Why You Shouldn’t Rely on Keyword Rank as an Exact Metric KeyInsights from Alina Vlaic,AZ Rank The keyword rank shown in Helium 10 is just an average, not your exact position. Helium 10 checks from different locations, times of day, and devices to work out that average rank. It’s normal to see a different rank when you search yourself, as it depends on where and when you’re looking. Keyword rank isn’t completely accurate, so it shouldn’t be trusted as a precise number. Watch the full episode here▶️//sr02.seogroupsbuy.com/?q=aHR0cHM6Ly9sbmtkLmluL2VjaUVCTXZ6 #AmazonFBA #KeywordRanking #Helium10 #AmazonSellers #EcommerceTips #FBAInsights #SellerTools #RankTracking #AmazonSEO #AZRank

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Hey PPC Pro, how about we start the new year with a list Google Ads mistakes from 2025 that we need to avoid in 2026? Let me start: Top mistakes to avoid in 2026: → Have your campaign spend $10k in one hour because you accidentally enabled AI Max → Copy-paste a faulty URL to Final URL without testing → Set audiences to ‘targeting’ instead of ‘observation’ and then wonder where all the traffic went → Launch new campaign on Friday afternoon, and then next Monday, find out it spent the whole month’s budget over the weekend → Run PMax without guardrails and be surprised by it doubling spend via non-converting clicks from the Discovery network → Forget to change Google’s default location targeting setting and burn $20k on GDN traffic in India for a product only sold in the UK → For US advertisers: target the country of Georgia rather than the state of Georgia → Forget to hit the Publish button in GTM and then spend >€5000 on clicks only to see zero conversions → Import GA4 conversions, forget to set the action as ‘secondary conversion’ and then have to explain why spend tripled without corresponding increase in revenue → Let PMax auto-expand final URLs on a lead gen site and then see traffic to outdated blog posts explode Add your mistake?

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Buying aged domains for links? That’s rookie level... Here’s how you launder authority like a pro: 1. Aged Domain → Site Rebuild with GSC (No direct redirect yet) - Rebuild 5-10 original pages w/ AI + archive data - Add internal links to your target anchors - Let Google reindex → add on Search Console (GSC) 2. Stage the Transfer - Slowly link back to your money site from buffer site’s contextual pages - Rotate anchors, mix partials + generics + image links 3. 301 + GSC Site Move - Create a new acquisition page - Add internal links to money pages - GSC site move after 301 4. Index Velocity Control - Submit pages via IndexNow API - Use social signals (Reddit embeds, Twitter links etc) to increase crawl rate - Press release on acquisition to old domain for new link velocity This isn’t even shady, and will often last very long term.

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Top 1 mistake with PMax- Not excluding branded traffic This leads to problems like: - No growth in new customers - Lack of control over scaling - A "lazy" algorithm - Inflated numbers How to fix it: 1. Add brand terms to the negative keyword list (if you already have one in your account) 2. Submit a request through the support form 3. Use brand restrictions Branded traffic requires a different strategy—more precise and more manual. Otherwise, you’re overpaying and limiting your growth. PMax in unskilled hands will eat your budget—while smiling at you with a nice ROAS.

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How should Ladbrokes Coral split a £2M budget between the different channels? For years, agencies have relied on reach curves to decide how to answer this question and to understand when to shift spend between channels. The aim was simple: reach new users at the lowest cost. But reach is only a proxy. What really matters is whether people actually respond to the ad. And not all reach is created equal. Attention levels vary by channel, viewability differs, screens come in all sizes, sound is often off, and let’s not forget ad fraud. Measuring “effective reach” reliably is almost impossible. That’s why we built response curves. Instead of guessing, we measure how each channel converts. If a channel delivers low attention and poor viewability, it naturally shows a lower conversion rate and a higher cost per incremental response — and that becomes clear in the curve. Because we also factor in diminishing returns, brands can see not just where to invest, but also when to stop because the next pound becomes too expensive. How it works: 🔷 We measure response rates at different spend levels per channel based on previous campaigns. 🔷 We plot diminishing returns. 🔷 Then, at any budget level, we calculate where the next £1 should go for the cheapest incremental response. This allows brands to: ✅ Optimise budget allocation across channels ✅ Predict incremental responses ✅ Know the expected cost per incremental response For example, looking at Ladbrokes Coral campaigns over the past 18 months (with assumed CPTs of £8 for TV and £15 for YouTube, Facebook, and Instagram): The optimal split of a £2M budget was: TV £980K, YouTube £480K, Facebook £340K, Instagram £200K Expected result: 291,120 incremental responses at £6.87 each Incremental defined as users who hadn’t visited Ladbrokes’ site or app in at least 2 weeks. 👉 The takeaway: Response curves give you a clear, data-driven way to stretch every pound further — shifting the focus from reach to real, measurable responses.

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SEO = GEO / LLMO? It depends! There are many discussions about this question recently with opinions by Michael King, Jes Scholz or Barry Adams 📰 to name only a few. Here is my opinion: The influence of SEO on LLMO or Generative Engine Optimization (GEO) depends on the extent to which the respective Large Language Model relates to an underlying search engine retrieval system. Generative AI such as ChatGPT, Perplexity, Gemini or Copilot use the retrieval systems of search engines to ground the answers. The greater the influence of the ranking of content within the RAG process for source selection in grounding, the more important SEO is and vice versa. The smaller the overlap between the referenced sources of the generated answer and the top rankend content, the less it is possible to use classic SEO for LLMO/GEO. By shifting to other data sources in the grounding process, such as exclusive data via collaborations, API interfaces to databases, knowledge graphs … the influence of search engine retrieval and thus SEO on LLMO/GEO can decrease. The way in which search engine indexes are evaluated as part of the retrieval process also influences how much influence traditional SEO has. Search engine rankings are determined with a view to the relevance and quality of the content and the trustworthiness of the originator. Traditional SEO still focuses on relevance optimization. For LLMO, it might be more important to focus on quality rating concepts such as Google’s E-E-A-T, rather than relevance. The optimization of E-E-A-T criteria is fundamentally different from relevance optimization. Let's discuss! Marcus Tandler, Kevin Indig, Dan Petrovic More about LLMO in my comprehensive guide: //sr02.seogroupsbuy.com/?q=aHR0cHM6Ly9sbmtkLmluL2VHcF9OSEJ1

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Optimize Your Add-to-Cart Button for Big Revenue Gains Want to boost your revenue with a simple tweak? We tested a small change for a client doing over 8 figures in revenue: optimizing the add-to-cart button size and adding a psychological subheadline The result? 📈 +€200K in additional revenue per year 💰 Improved conversion rates Here’s how to optimize your add-to-cart button and increase your sales without extra ad spend:

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Adobe to Acquire Semrush for $1.9 Billion The irony is striking: Adobe paid $1.68 billion for Magento in 2018. Seven years later, they're spending $1.9 billion for SEMRush. One became Adobe Commerce and has struggled to maintain competitive momentum. The other promises to unlock GEO (Generative Engine Optimization) as a growth channel. Both acquisitions valued at nearly identical price points. Dramatically different trajectories. AEM (Adobe Experience Manager) flourished under Adobe's ownership, becoming central to enterprise content strategy. Adobe Commerce faced integration challenges and market position erosion. Now Adobe is betting $1.9 billion that SEMRush will follow the AEM path, not the Commerce path. The Strategic Opportunity: Brand visibility is being reshaped by AI-driven search Traffic from generative AI sources to U.S. retail sites increased 1,200% YoY SEMRush drove 33% ARR growth in enterprise segment Natural fit with Adobe's Brand Concierge and analytics platform The Pattern Recognition: Similar acquisition price points suggest similar strategic value assessment Adobe excels at some acquisitions, struggles with others Platform integration complexity can either enhance or dilute focused products Enterprise sales motion differs significantly from SEMRush's current model My perspective as someone who witnessed the Magento-to-Commerce evolution: success depends on whether Adobe positions SEMRush as a standalone growth platform or attempts deep Experience Cloud integration. The GEO opportunity is real. The acquisition price is familiar. The execution risk remains the variable. What's your take? Will SEMRush maintain its velocity, or will we see a repeat of the Commerce integration challenges? #Adobe #SEMRush #Magento #MarketingTech #AgenticCommerce #GEO #SEO

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Over the years, I’ve reviewed the work of dozens of CRO vendors, some hired before us, some hired after us, and others who pitch themselves as “optimization experts”. And I’ve noticed a pattern. Not all CRO agencies are equal. In fact, some of them are structured in a way that guarantees low-impact results. Not because they’re bad people or lack intelligence, but because the model they operate in is flawed from the ground up. Here are the 5 types of CRO agencies I’d never recommend working with, no matter how impressive their pitch deck looks: 1. The “Split Test Factory” Agency They promise velocity. “We’ll run 10–20 tests per month.” Velocity is good, but not if it's about testing micro copy changes, button colors, and layout tweaks that will never move the business forward. These programs often suffer from statistical fatigue and internal team exhaustion, and six months in, you’re left with dozens of “ran tests” but no strategic insights. 2. The “Web Designer Disguised as a CRO” They’re good at making things look pretty. But ask them: What’s the insight behind this redesign? What behavior are we trying to change? What friction are we removing? Most can’t answer. Because they’re not working from behavioral data or real customer evidence, they’re working from taste. 3. The “We-Do-Everything” Full-Service Agency They offer it all, CRO, SEO, PPC, email marketing, social, branding, you name it. And on paper, that looks efficient. Why not have one partner handle everything under one roof? But here’s the problem: conversion optimization is not an add-on service. It’s not something you sprinkle on after the traffic lands. Most (not all) full-service agencies bolt on CRO as a secondary offer, staffed by junior generalists, not true specialists. We’ve stepped into so many projects where a full-service agency was “handling CRO,” and what we found was that it had been deprioritized, underfunded, and often misunderstood from day one. 4. The “Junior Team in a Senior Wrapper” Firm They bring in a partner or senior strategist to close the deal, then hand off your project to junior associates with little experience running experiments at scale. You get surface-level insights, oversimplified A/B test ideas, and a team that doesn’t push back or lead, just executes. For complex sites or high-stakes business models, that’s a huge liability. 5. The “We-Don’t-Touch-Code” Optimizers They’ll help you come up with test ideas, write copy, even design a few variants. But when it comes to actually launching the experiment? They tell you to loop in your dev team or wait for the sprint cycle. Most of the times, that delay kills momentum. By the time a test goes live, your campaign is over, your offer has changed, or your team has lost interest. The truth is...most brands don’t need more CRO ideas, they need better execution, faster insight loops, and tighter alignment with business outcomes.

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Stop doing traditional keyword research. Query fan-out analysis and semantic intent mapping is the future. Let me show you how I do it with this free tool. Most SEOs still optimize for single keywords. They look at search volume. They check keyword difficulty. They create content around exact matches. But that's not how AI search actually works. When someone searches (or prompts) "construction tool tracking," AI doesn't just look for that exact phrase. Take a recent study from Writesonic as proof: "[...] the original search query doesn’t appear 86.85% of the time in AI-generated summaries, showing context matters more than keyword matching." It expands into dozens of related queries: I tested this with our client ToolSense. Their main keyword for an article was "construction tool tracking". This an excerpt of related queries that ChatGPT or Google AI Mode might use: 1. "How to prevent tool theft on construction sites" 2. "RFID vs GPS tool tracking systems" 3. "Best tool inventory management apps" 4. "Real-time tool tracking benefits" This is called query fan-out. Traditional keyword research would miss this entirely (or only hit by accident). You'd optimize for your main keyword. You'd miss 80% of actual user intents. Your content wouldn't perform in AI search. Smart SEOs map semantic intent instead. 𓃋 Tyler Gargula just released a free Query Fan-Out Analysis tool that lets you check this whole process for your page super easily. Here's what it does: 1. Takes your target keyword 2. Generates realistic search variations 3. Maps your content against competitor pages 4. Shows exactly where you have coverage gaps 5. Provides actionable optimization recommendations How to use this: → Option 1: Expand your existing page by covering missing intents. → Option 2: Create new dedicated pages for different intent clusters. → Option 3: Optimize content chunks to ensure matching specific query types. Stop optimizing for keywords. Start optimizing for user intent patterns. The future of SEO is semantic, not syntactic. Want to try it yourself? I'll drop the link to Tyler's free tool in the comments. 👇 You might be surprised by what you discover. Have you already thought about query fan-out analysis? Share your insights below.

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