I forgot how much I loved simple B2B SEO! Article published on Thursday, ranking Position 1 and cited within Google's AI Overview today! 😎 Now to get more stuff published for the rest of the funnel!

"What SEO tools should an agency use?" That's rarely a "which tool is best?" question. It's usually a systems + margin question. Because when you're juggling 10, 20, 50 client sites, the real pain isn't a lack of data, it's: - Too much manual work - Tool sprawl and overlapping subscriptions - Reporting that doesn't land well with clients - Proving SEO's impact so retainers renew So instead of asking "what's the best SEO tool?" ask: What job does this tool need to do inside our agency? Here are the tools I see agencies relying on in 2026, grouped by the outcome they support: 1) Proving impact + client-ready reporting 👉 SEOTesting 👉 Google Search Console 👉 Google Analytics 👉 Bing Webmaster Tools 2) All-in-one SEO suites 👉 Ahrefs 👉 Semrush 👉 Moz Pro 3) Technical audits and crawling 👉 Screaming Frog 👉 Sitebulb 👉 PageSpeed Insights (for quick wins and dev ammo) 4) Content planning at scale 👉 Keyword Insights 👉 AlsoAsked 5) Link intelligence 👉 Majestic 6) WordPress SEO 👉 Yoast 👉 Rank Math SEO 7) Local SEO toolstack 👉 BrightLocal 🇺🇦 👉 Whitespark 👉 Moz Local I've put together a full breakdown of what each tool is best for, where it fits in an agency workflow, and how to choose without overspending. Full guide is (as usual) in the comments.

"Should we replace Semrush?" That's rarely a pricing question... It's more of a strategic question. Most SEO teams don't wake up just randomly wanting a new tool. They wake up needing to: - Prove impact - Improve workflow efficiency - Go deeper on links or technical SEO - Or scale reporting without drowning in exports and CSVs Semrush is powerful. No doubt about it. But "all-in-one" often means you're paying for features you don't fully use. So instead of asking what the best alternative is, ask the better question: What problems are we actually trying to solve? Here are 9 serious Semrush alternatives, depending on your needs: For proving SEO impact & structured testing: 👉 @seo_testing For backlink intelligence & competitor research: 👉 @ahrefs 👉 @Majestic For question research & topical expansion: 👉 @AlsoAsked For keyword clustering & content briefs: 👉 @keywordinsights For all-in-one coverage, but a lighter stack: 👉 @SERanking For technical SEO and site crawling: 👉 @screamingfrog 👉 @sitebulb For AI visibility (GEO, AEO, LLMO, whatever acronym): 👉 Waikay We’ve put together a full breakdown of all 9 and when each makes sense. It’s linked in the next post.

I'd be willing to bet that most of you following me use Google Search Console and Google Analytics every single day. So you're (hopefully) not confused as to what they do. But maybe you'd like to know more about how they can be used in perfect harmony! Here's a simple way to frame it: Google Search Console = SERP visibility and technical stuff. - Queries, pages, CTR, average position. All that good stuff. - Indexing, coverage, and technical issues. Google Analytics = Outcomes and user behavior. - Engagement - Events - Conversion paths Both tools are absolutely essential. But neither of them answers the question that you might be asked the most: "What changed, and did it move the needle?" That's the gap SEOTesting was literally built to fill! It sits on top of GSC (and GA4 when needed) to: - Track the changes that are made to your site. - Run time-based, SEO split, and LLM tests. - Standardize reporting across pages and sites. Less exporting. Less guesswork. More "here's what worked." I've shared a full, practical breakdown of GSC vs GA4 vs SEOTesting, including when each tool is the right one to use. It's linked in the next post! 👇

Enterprise SEO has a tool problem! 😅 Not because there aren't enough tools, but because most "SEO stacks" were built for: ✅ 1 site. ✅ 1 team. ✅ 1 set of goals. Enterprise is different. You're dealing with: ➡️ Multiple domains/markets. ➡️ Constant releases. ➡️ Tons of stakeholders. ➡️ And "prove impact" pressure every single month. So you end up needing a stack, not a single platform. Here's how the best enterprise SEO tools stack up: 1) First-party performance + reporting (Google/Bing data) - @seo_testing - Google Search Console - Google Analytics - Bing Webmaster Tools 2) "All-in-one" suites (broad coverage) - @ahrefs - @semrush - @Moz - @SERanking 3) Market + competitor intelligence - @Similarweb 4) Enterprise SEO platforms (exec reporting + governance) - @brightedge - @Conductor 5) Crawlers + technical SEO at scale - @screamingfrog SEO Spider - @sitebulb Cloud - @lumarhq - @botify 6) Rank tracking specialists - STAT Search Analytics - @AccuRanker - @awebranking 7) Content optimization - @AirOpsHQ - @surfer_seo - @clearscope - @MarketMuseCo The "takeaway" I keep coming back to: Enterprise SEO stacks are usually layered. ➡️ 1 suite for coverage. ➡️ 1 crawler for scale. ➡️ 1 rank tracker for accuracy. ➡️ 1 content tool for performance. ➡️ And something to prove impact! I've dropped the full guide in the next post (with all 22 tools + what they're best for).

ChatGPT "likes" fresher content/data? I'm not sure whether this was a hot take to begin with, but it does look more like a pattern! About a week ago, @pelogia shared an interesting experiment: He took ~10k pages and started updating their main content daily. What happened next? 📈 A few days later, ChatGPT-User bot activity jumped. 📈 And it stayed consistently higher than it was before. Certainly a very interesting signal to look at! Seeing ChatGPT-User crawls is definitely useful, but does it paint the full picture? I guess the real follow-up questions should be: 👉 Are those pages getting traffic from LLMs? 👉 Which page types benefit the most from freshness? 👉 Does daily updating change visibility, not just crawl behavior? That's why I'm a big fan of pairing log analysis with LLM referral data, even with how messy referral data from LLMs is! I'd love to see this same test repeated and paired with LLM referral data! 👀