📊 A reminder especially with the latest Google Core Update rolling out: One of the biggest mistakes I still see in SEO analysis is assessing performance shifts in isolation 👇 To understand what’s really happening, you need to assess all relevant organic search metrics and configurations together together and in context: ➡️ Organic traffic trends ➡️ Ranking keyword growth or decline ➡️ Keyword overlap vs competitors ➡️ Backlink profile ➡️ Engagement signals ➡️ Content depth and coverage ➡️ Category / section-level performance ➡️ Competitors gaining or losing across the same market This is why I find competitor comparison dashboards genuinely useful when doing SEO analysis: it helps you analyze the different metrics next to each other faster, to identify the patterns that matter faster. I’ve been using the @semrush “Competitor Comparison” report in their Enterprise suite for this, since it lets you compare your site vs competitors across organic traffic, ranking keywords, backlinks, engagement, and content related signals in one place. That broader context is especially useful when you need to answer where you're specifically falling behind, against whom and what's driving the gap. If you're already using Semrush: Check out it. If not, this is another useful dashboard to try out. Disclaimer: This is a cross-promotional post with Semrush Enterprise, an #SEOFOMO sponsor. That said, I’m happy to share it because this is a functionality I genuinely find useful in my own SEO analysis work.

🤖 It Works Until It Doesn't: AI Content Strategies That Backfire - A must read guide by @lilyraynyc 👇 There are very specific scenarios for which content at scale is needed due to nature/reach of the site (eg. marketplaces), but it needs to be generated by going through a careful integration and validation to ensure quality via an editorial workflow and review, while adding useful and relevant, meaningful, unique insights, proprietary data, expert / user advice that really fulfill a need of users... however, most of sites out there, don't really fall into this scenario. In this guide, Lily shows what happens when AI is leveraged in ways that don’t fulfill the criteria above, and it works… until it doesn’t. She analyzed +220 sites publicly associated with AI content creation, automation, and scaling platforms, and the findings are a reminder of what happens when scale is prioritized over substance: * 54% lost +30% of their peak organic traffic * 39% lost +50% * 22% lost +75% The pattern is certainly familiar for anybody that has been in SEO for a while: rapid content growth, traffic increase, then significant visibility drops a few months later, caused by: * Programmatic “what is” glossaries. * Comparison pages at scale. * “Best X for Y” listicles. * Competitor alternative pages. * Thin location or language pages. * Self-serving listicles. * Off-topic content scaled mainly for visibility. AI didn’t created these tactics but made them much easier, faster, and cheaper to scale. The issue isn't using AI for content but using AI to publish large volumes of formulaic, undifferentiated content created mainly to rank, get cited, or influence AI search systems, without enough originality, expertise, topical focus, or human validation. This matters for both traditional SEO as well as AI search. If your AI search strategy damages your organic search visibility, credibility, and topical authority, it can also end up hurting your AI search visibility via grounding. Remember: Don’t use AI to scale like this, because as we’ve seen in SEO many times before, scale without substance might work temporarily, but it doesn't usually end well. Read it here: lilyraynyc.substack.com/p/it…

17 Content Types to Survive Google’s Zero-Click Future - Excellent research by @CyrusShepard We know that Google favors different types of sites now. Winning content tends to be proprietary, unique, and solves problems beyond providing information. Here are 17 content types that currently perform decently-to-excellent in the AI era when properly executed: signal.zyppy.com/p/content-g…

🚨 How Google Click Signals Drive SEO Rankings and AI Answers - A must read piece by @CyrusShepard going through how Google is trying to answer three broad questions from user click data: * Is this result relevant? * Is the content useful to answer the question? * Does this completely satisfy the user search? ... and what can we do about these! Check it out: signal.zyppy.com/p/google-cl…

🚨 Must read: A Fantastic Guide to Generative AI by @gfiorelli1 at the Advanced Web Ranking blog, going through: * The Model: Architecture and Mechanics of LLMs * The Agent: Reasoning, Planning, and Action * The Library: Neural Search and Retrieval Architectures * The Strategy: SEO for AI Search * The Technical Foundation * Content and AI Search * Amplification -- Check it out: advancedwebranking.com/seo/g…

🚀 A must-read: How Growth Works When AI Systems Interpret, Compare, and Choose Brands 👇 by @gfiorelli1 explaining how: * Growth Now Depends on Becoming Legible, Verifiable, and Recommendable to AI Systems * The Strategic Levers for Becoming a Brand AI Systems Can Trust and Recommend * The Program for Becoming AI-Recommendable (with different approach, from minimum viable ones to comprehensive) * Measure Success When Attribution is Fragmented or Invisible * Much more! Check it out: iloveseo.net/how-growth-work…