Which GEO tactics are easy to implement, and which produce the best results? Here's the data from 512 marketers.

7 AI search myths #SEOs keep repeating, tested against real data. 👉 Most fall apart, from llms.txt to "AI is killing search." Each myth, the claim, and what the data shows: searchengineland.com/seo-ai-…

Where does AI authority come from?

In the last 2 years, web traffic to news sites has fallen by about 28%.

🆕 in AI Overviews answers Google is now testing showing anchor links which instead of taking to a webpage takes to AI Mode. Another day - Another Tactic! from Google to push users from usual search results to AI Mode #SEO

Google accidentally revealed how its AI search systems choose which sites to recommend and send traffic to. Now that none of it is much of a secret anymore, let’s talk about it. With the new Google Search rolling out as we speak, it has never been more important to understand how to maximize value from this marketing channel. If you want to see where your site stands across Google, ChatGPT, Claude, Perplexity and broader AI search, you can do so for free here: seo-stuff.com/free-audit Let’s start from the beginning. Metehan Yesilyurt, who previously went viral for his analysis of Perplexity’s ranking factors, recently broke down Google AI ranking factors in a fascinating blog post. A lot of what he found also lines up with what SEO Stuff (seo-stuff.com) has been doing all year to get customers more traffic and sales. Specifically with the done-for-you package: seo-stuff.com/gold-plan-pack… Basically, Google sells much of the underlying retrieval infrastructure through Google Cloud Discovery Engine, also called Vertex AI Search. By analyzing what Discovery Engine exposes, Yesilyurt was able to show how Google’s AI retrieval and ranking stack works. The seven major signals he identified were Base Ranking, Gecko embedding similarity, Jetstream cross-attention relevance, BM25 keyword matching, predicted click-through rate, freshness and Boost/Bury rules. In simpler terms, Google is combining traditional ranking signals with semantic similarity, deeper contextual relevance, keyword matching, engagement predictions, recency and manual business logic. Discovery Engine exposes a maximum chunk size of 500 tokens, roughly 375 words, while ancestor headings can travel with each chunk and tables, images and page layouts can all be parsed with Gemini-enhanced understanding. That means important ideas need to make sense inside relatively small, clearly labeled sections. If your content is one massive wall of text, Google has a much harder job extracting the exact information it needs. This is also why I keep talking about question-based headings, direct answers, clear comparisons and structured pages. Additionally, Discovery Engine shows Google processing structured data using separate Searchable, Indexable and Retrievable settings. Those can affect whether information can be found, used for filtering or ordering and surfaced by the model. Mind you, they are independent. So a field can potentially influence retrieval or ranking without necessarily being displayed in exactly the same way. That gives us a pretty significant clue about why structured data continues to matter as Google becomes more AI-driven. Discovery Engine also reveals a four-stage pipeline: Prepare, Retrieve, Signal and Serve. Google first interprets the query, handles things like synonyms and intent, then retrieves and chunks relevant content, applies ranking signals and finally uses Gemini to generate the response with grounding and safety rules. Traditional Search, AI Overviews and AI Mode can be thought of as different configurations built on much of the same underlying retrieval infrastructure. So what does all of this mean for businesses? You need to optimize for several layers at once. Your content needs strong semantic alignment so Google clearly understands what the page is about, enough contextual detail to handle nuanced searches such as comparisons and “best for” queries, and clean chunk-level structure so useful answers can be extracted without digging through hundreds of words of filler. That means clear definitions, direct answers, comparison language, question-based headings, concise sections, factual claims, TLDR summaries, clean HTML and useful tables where appropriate. This is exactly why SEO Stuff content is structured the way it is. The done-for-you package combines 10 long-form, search-focused articles with three DR50+ contextual backlinks: seo-stuff.com/gold-plan-pack… The content is designed around semantic relevance, keyword alignment, structured sections, comparisons, freshness and extractability, while the backlinks help strengthen the underlying authority of the pages and domain. The Premium Content Bundle takes the same idea much further: seo-stuff.com/premium-conten… It includes 60 long-form articles designed to build broader category coverage, stronger semantic associations and more opportunities for Google to retrieve useful sections across the different questions customers ask. Then there is the Premium Backlink Bundle: seo-stuff.com/premium-backli… It adds three contextual DR50+ backlinks designed to strengthen search authority and reinforce the company’s identity and category across the web. And if you want to see where your site stands across Google, ChatGPT, Claude, Perplexity and broader AI search, you can do so for free here: seo-stuff.com/free-audit

👀 Are you an ecommerce seeing important YOY drops in organic search traffic from your top performing non-branded queries/topics even if you haven't actually decreased in real positions? It's not you, it's Google! Just compare the SERPs from September 2025 vs the ones of 2026, and you'll see an insane increase of: * AI Overviews * Shopping packs (two or three times in many cases) * People Also Ask * Local Packs ... and that's not even going into more visibility to ads across many verticals! In the first page of the SERP: * A year ago we still had 7-8 organic search ranked pages vs 1-2 search features * Now it's 4-5 organic search ranked pages vs 4-5 search features. It's all about keeping engagement within the SERPs. Welcome to Google's featurization era 😐 and say goobye to your traffic!

Content marketing hit a 12-year performance low. AI use reached 92.4%, but showed no relationship with stronger results. The bigger issue: proven tactics are being used less. Check the findings here: searchengineland.com/content…

Google's John Mueller says the old "position 1 - 10" is hard to map for site owners seroundtable.com/google-posi…