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SEO Tools and Resources

Discuss popular SEO tools like SEMrush, Ahrefs, and Google Analytics, and share resources that make SEO easier.

  1. If you look at job postings on Indeed and LinkedIn, you’ll see a wave of acronyms added to the alphabet soup as companies try to hire people to boost visibility on large language models (LLMs). Some people are calling it generative engine optimization (GEO). Others call it answer engine optimization (AEO). Still others call it artificial intelligence optimization (AIO). I prefer large model answer optimization (LMAO). I find these new acronyms a bit ridiculous because while many like to think AI optimization is new, it isn’t. It’s just long-tail SEO — done the way it was always meant to be done. Why LLMs still rely on search Most LLMs (e.g., GPT-4o, Claude …

  2. We need to have a talk about KPIs and AI search. I’ve observed numerous SEO professionals on LinkedIn and at conferences talking about “ranking No. 1 on ChatGPT” as if it’s the equivalent of a No. 1 ranking on Google: On Google, being the first result is often a golden ticket. Going from No. 2 to No. 1 in Google search will often result in 100%-300% increases in traffic and conversions. This is almost certainly not the case with AI responses – even if they weren’t constantly changing. Our team’s research shows AI users consider an average of 3.7 businesses before deciding who to contact. Being the first result in that list on ChatGPT isn’t the g…

  3. Search is no longer a blue-links game. Discovery increasingly happens inside AI-generated answers – in Google AI Overviews, ChatGPT, Perplexity, and other LLM-driven interfaces. Visibility isn’t determined solely by rankings, and influence doesn’t always produce a click. Traditional SEO KPIs like rankings, impressions, and CTR don’t capture this shift. As search becomes recommendation-driven and attribution grows more opaque, SEO needs a new measurement layer. LLM consistency and recommendation share (LCRS) fills that gap. It measures how reliably and competitively a brand appears in AI-generated responses – serving a role similar to keyword tracking in traditiona…

  4. OpenAI is serving ads inside ChatGPT, and new findings suggest the experience looks quite different from what the company originally envisioned. What’s happening. Research from AI ad intelligence firm Adthena has identified the first confirmed ads appearing on ChatGPT for signed-in desktop users in the U.S. The big surprise. Early speculation suggested ads would only surface after extended back-and-forth conversations. That’s not what’s happening. When a user asked “What’s the best way to book a weekend away?”, sponsored placements appeared immediately — on the very first response. What they look like. The ads feature a prominent brand favicon and a clear “Spo…

  5. Every week, thousands of media buyers perform the same ritual, opening Meta Ads Manager, scanning metrics, and deciding which campaigns and ads were winners and which were losers. If ROAS is positive, they’re pleased. If not, the mouse quickly heads toward the toggle button to disable the asset. This is the scoreboard trap some advertisers fall into. When you treat metrics like a scoreboard, you’re looking at the outcome without understanding the full picture or how to improve going forward. The score of the game doesn’t include the fact that your strikers aren’t getting any passes from midfield. To scale performance, it’s important to move from reporting to diag…

  6. LLMs and their influence on traffic to a brand’s website are a major topic in our client conversations. Everyone wants to know what’s happening, how they can do better, and what the best practices are. My recommendation to brands right now is to start with the data and focus on what they can know for sure. To glean insights into how LLM traffic is influencing key metrics, we analyzed our dataset of LLM prompt referral traffic in Google Analytics across our customer base over the last 13 months (Jan. 1, 2025 to Feb. 7, 2026). We focused on traffic from various LLM models to brand sites and the conversion events closest to true business outcomes. In some cases,…

  7. Remember when it was easy to rank partial-match domains and headings to commercially intended search queries? When paired with the right methodologies and conversion-optimized widgets, you could silently earn tens of thousands of dollars in affiliate revenue per month with minimal maintenance. It was possible to get by with just updating articles for relevancy and freshness signals, for example. Pressure-testing Google’s spam update Before the experiment, I had spent several months scaling an affiliate initiative in a much more above-board way for a longstanding website in a YMYL category. We had success with hiring subject matter experts (SMEs) to wri…

  8. For years, ecommerce ran on a simple model: Google drove traffic, and your site did the selling. Rankings, clicks, and conversion rate determined performance. That model just changed. With the Universal Commerce Protocol (UCP) and AI Mode, Google can now discover, compare, and complete purchases inside its own AI experiences. Search is shifting from a traffic channel to a transaction layer. Visibility now depends on whether Google’s AI selects your product data. When AI makes the recommendation and closes the sale, optimization moves upstream. The question isn’t just whether you rank. It’s whether you’re chosen. Here’s what changed and what SEO and AI optimiza…

  9. If your brand’s content arm has been active for a few years, I’m guessing you have plenty of material that can be revised to help you show up more prominently in AI search answers — we’ll call this AEO throughout the article. I’m getting bombarded with brand marketers’ questions about how to get AEO traction these days. “Revise your old content” is a favorite answer that often produces an “aha” moment for the other party, possibly because the nature of AEO is so forward-looking. That answer sparks a few important follow-up questions I’ll tackle below. How do you reformat content for better AEO performance? I like to lean on three principles when I tackle co…

  10. You’ve probably heard developers talk about the DOM. Maybe you’ve even inspected it in DevTools or seen it referenced in Google Search Console. But what, exactly, is it? And why should SEOs care? Let’s take a look at what it is, why it’s important, and how to best optimize it. What is the DOM? The Document Object Model (DOM) is a browser’s live, in-memory representation of your webpage. It acts as the interface that allows programs like JavaScript to interact with your content. The DOM is organized as a hierarchical tree, similar to a family tree: The document: This is the root of the tree. Elements: HTML tags like <body>, <p>, and <a…

  11. The largest annual survey of PPC professionals finds the industry under growing pressure — more opaque platforms, weaker measurement, and AI tools that help but haven’t transformed the day-to-day. Why we care. More than half of practitioners (53%) say PPC is harder than it was two years ago, up from 49%. The dominant reason isn’t competition — it’s that platforms are making more decisions advertisers can’t see or override, and that gap is only widening. With 89% of digital spend flowing to just three companies, advertisers who don’t build measurement infrastructure independent of platform reporting are increasingly flying blind. By the numbers: 1,306…

  12. We joke every time we hear Google’s John Mueller answer a question with “it depends.” But actually, it’s true. There are few definitive answers or universally established facts in SEO. Do meta titles matter? Yes. Is internal linking a good practice? Yes. Is duplicate content bad for SEO? Yes. But if I tried to make a list of SEO questions with a single, clear, absolute answer, it wouldn’t be long. That’s the real challenge: we operate in an industry where things almost always depend on context, intent, competition, your website’s situation, and the platform itself. Yet over and over, we see questions framed as if there must be one right answer. SEO tips ar…

  13. With AI-driven search and hyper-fragmented media channels reshaping how people discover brands, the “set it and forget it” approach to marketing measurement is officially dead. Measuring impact isn’t a static check of dashboard data. Used strategically, measurement is a virtuous cycle where data informs your ad platform settings and those settings, in turn, generate better data (and business outcomes). Here’s how to build a measurement flywheel that keeps your growth efficient. The 4-step measurement cycle Imagine a Bay Area SaaS company, PowerLoop, selling an AI-powered analytics platform. They’re investing heavily in Google Search, LinkedIn, and some eme…

  14. Google redesigned the Asset Optimization section in Google Ads for Demand Gen campaigns, consolidating AI-powered creative controls into a single, cleaner interface. Why we care. Advertisers managing creative at scale now have a centralized panel to toggle automated features on or off — making the process less manual and time consuming. What’s new. The redesigned layout groups three key automation capabilities together: Auto-generated shorter videos — AI trims existing video assets into shorter cuts to qualify for additional placements. Automatic video resizing — Videos are adapted across multiple aspect ratios to maximize inventory coverage. Landi…

  15. Google is leaving the door open to advertising in its Gemini AI app, with a senior executive telling WIRED the company is “not ruling them out” — a notable shift from the flat denials made just months ago. What’s changed: In January, Google DeepMind CEO Demis Hassabis told reporters at Davos that Google had no plans to put ads in Gemini. Now, SVP Nick Fox is saying otherwise — noting that learnings from ads in AI Mode will “likely carry over” to Gemini down the road. The current strategy. Rather than rushing into Gemini, Google is using AI Mode — its Gemini-powered Search product — as a testing ground for ad formats in AI experiences. Ads are kept separate fr…

  16. Chloe Varnfield, a digital marketing specialist at Atelier Studios with nearly eight years in PPC, joined me to share the mistakes that shaped her career — and the lessons every advertiser should take from them. When Google sneaks settings past you Chloe’s first story centers on Google’s account-level automated assets setting — a feature so well hidden that many advertisers don’t know it exists until a client sends a screenshot asking why their headline looks completely wrong. The setting, buried behind a three-dot menu, defaults to on, meaning Google can automatically generate and serve headlines advertisers never wrote or approved. The takeaway: always audit your…

  17. LinkedIn is launching a new AI-powered feed ranking system that uses large language models and GPUs to analyze post content and surface more relevant updates to its 1.3 billion members. Why we care. Understanding how LinkedIn surfaces content is critical if you want your posts — or your brand’s — to be discovered. The new system prioritizes topical relevance and engagement patterns, LinkedIn said. Posts that demonstrate expertise and align with emerging professional conversations may travel farther across the network — even without existing connections. The details. LinkedIn rebuilt much of its feed recommendation system using large language models, transformer mo…

  18. YouTube is experimenting with a format that keeps ads visible even after users skip — potentially reshaping how advertisers think about skippable inventory. What’s happening. YouTube is testing a sticky banner overlay that appears once a user skips an ad. Instead of the ad disappearing entirely, a branded card remains on-screen until the viewer actively dismisses it. How it works. After hitting “skip,” users return to their video as normal, but a persistent banner tied to the original ad stays visible within the player, extending the advertiser’s presence beyond the initial skip. Why we care. This test from YouTube creates a way to maintain visibility even…

  19. Perplexity’s new Comet browser for iOS defaults to Google Search. That’s because mobile queries often focus on navigation, local results, and transactions, where “Google does a much better job … than anyone else … including Perplexity,” according to Perplexity CEO Aravind Srinivas. Comet for iOS. It includes Perplexity’s AI assistant directly in the browser. Comet for iOS also blends AI answers with standard search results. For many queries, you’ll still see a traditional results page. You can ask questions by voice while browsing. The assistant can summarize pages, answer questions, and take actions like drafting emails. Deep Research features generate cit…

  20. A new version of the Google Ads API is out, bringing a handful of targeted updates across video, app campaigns, and audience planning tools. Key changes in this release. A new VideoEnhancement resource that surfaces whether a video ad is Google-generated or advertiser-provided — giving developers clearer visibility into auto-enhanced creative A new AppTopCombinationView resource providing read-only insights into top-performing asset combinations in App campaigns The ability to disable the hotel feed in Demand Gen campaigns via HotelSettingInfo.disable_hotel_setting A new conversion metric for indirect first in-app installs across Campaign, Customer, and …

  21. The U.S. Justice Department and a coalition of states plan to appeal a federal judge’s remedies ruling in the Google search antitrust case. The appeal challenges a decision that found Google illegally monopolized search but stopped short of imposing major structural changes, such as forcing a divestiture of Chrome or banning default search deals outright. What’s happening. The DOJ and state attorneys general filed notices of appeal yesterday, challenging U.S. District Judge Amit Mehta’s September remedies ruling, Bloomberg and Reuters reported. Mehta ruled in August 2024 that Google unlawfully maintained its search monopoly through default search agreements w…

  22. Google Ads is rolling out recommended experiments on the Experiments page, surfacing test ideas based on an account’s setup and performance data. How it works: The platform suggests experiment opportunities — such as testing bidding strategies, creative variations, or new campaign features — and presents them directly inside the Experiments dashboard. Each recommendation includes a preconfigured experiment setup Advertisers can launch immediately or customize settings Suggestions appear alongside the standard Create Experiment workflow Why we care. By removing the need to build tests from scratch, Google is lowering the barrier to experimentation. A…

  23. In her third annual letter, Vidhya Srinivasan, VP/GM of Ads & Commerce at Google, lays out how AI is transforming shopping and advertising in 2026 — making experiences faster, more personal, and more seamless for both consumers and businesses. Key trends: Creators to commerce: YouTube continues to be a discovery hub, with creators acting as trusted tastemakers. AI is helping match brands to the right creators, turning influence into measurable business impact. Search ads evolve: With conversational and visual queries on the rise, AI Mode is reimagining ads as part of the discovery journey. New formats, like sponsored retail listings and Direct Offers…

  24. Google’s AI Overviews have moved beyond the experimental phase and are now a permanent part of search. To assess their impact, Adthena analyzed data across six major industries from late December 2025 to January 2026, tracking performance metrics from hundreds of thousands of advertisers, including more than 5 million ads. While aggregate data suggests stability, a deeper look reveals a different picture. For advertisers, these automated summaries are no longer just a visibility concern; they directly threaten PPC revenue. What AI Overviews mean for paid search revenue Generative summaries fundamentally change the math of a successful campaign. When an AI Overv…

  25. The last year has had many of us trying to understand how to report on AI visibility and understand what it takes to be seen and cited by AI. But Rand Fishkin’s latest study on AI response variability has emphasized that LLM outputs aren’t as stable and predictable as search rankings, making this KPI an inconsistent piece of the puzzle. The study found there’s less than a 1 in 100 chance that ChatGPT or Google AI will return the same list of brands across two responses. They analyzed thousands of prompts across multiple LLMs to highlight just how varied they are. This has left some of the SEO community questioning the value of rank tracking at scale. But, rank…





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