{"id":11693,"date":"2026-07-15T21:53:01","date_gmt":"2026-07-15T13:53:01","guid":{"rendered":"http:\/\/longzhuplatform.com\/?p=11693"},"modified":"2026-07-15T21:53:01","modified_gmt":"2026-07-15T13:53:01","slug":"how-google-may-understand-unique-content","status":"publish","type":"post","link":"http:\/\/longzhuplatform.com\/?p=11693","title":{"rendered":"How Google May \u2018Understand\u2019 Unique Content"},"content":{"rendered":"<p><\/p> <div id=\"narrow-cont\"> <p>Thanks to Rand\u2019s excellent research and Barry\u2019s expletive-laden ranting, we know that Google processes over 5 trillion searches each year. Trillion. Per day, that\u2019s 13.7 billion. Per second, 158,000.<\/p> <p>There are some sizeable and growing caveats here:<\/p> <figure> <\/figure> <p>That still means Google processes 2.92 billion clicks to the open web every day. It\u2019s still a figure worth fighting for \u2013 particularly for publishers whose business models heavily rely on a click.<\/p> <p>So let\u2019s not totally lose sight of what matters in the here and now. And unique content certainly fits that mould.<\/p> <p><iframe class=\"sej-iframe-auto-height\" id=\"in-content-iframe\" scrolling=\"no\" src=\"https:\/\/www.searchenginejournal.com\/wp-json\/sscats\/v2\/tk\/Middle_Post_Text\"><\/iframe><\/p> <p>I have reviewed a few previous patents (Google\u2019s in-depth article patent explained and how Google ranks news sites), and it is not a thoroughly enjoyable experience. A granted patent protects an idea; it doesn\u2019t prove deployment or real-world use cases \u2013 and it\u2019s certainly not unlike big tech to claim ownership of something just so it can\u2019t be used elsewhere.<\/p> <p>Generally, if:<\/p> <ol> <li><strong>The patent is cited regularly and recently?<\/strong> This patent (Contextual estimation of link information gain) has been cited 24 times and as recently as last year.<\/li> <li><strong>Whether it has international filings?<\/strong> Yes, but with some caveats. US, China, ceased in Europe and worldwide, but extended in the US to 2039 very recently.<\/li> <li><strong>Whether Google has protected the ranking technology around the world?<\/strong> Yes, again with some caveats.<\/li> <li><strong>Does it broadly align with your understanding of the concept (in this case non-commodity content)?<\/strong> Very much so. As the rasping breaths of SEO-first, commodity content make even iron lungs work hard, it would be inconceivable for Google to not measure or evaluate uniqueness in some manner.<\/li> <\/ol> <p>It is more likely to be used in some capacity.<\/p> <h2>TL;DR<\/h2> <ol> <li>Google has multiple public and leaked systems that appear to evaluate originality, effort, and unique contribution \u2013 see OriginalContentScore and ContentEffort.<\/li> <li>The patent describes an <strong>information gain score (potentially in a 0 \u2013 1 framing)<\/strong> that is assigned to a document based on how much <em>new<\/em> information it adds beyond documents a user has already seen on the same topic.<\/li> <li>In my \u2013 and many others\u2019 \u2013 opinion, Google\u2019s systems reward originality in some way. Whether that\u2019s directly through an information gain score and re-ranking system, a Bayesian predictive score, or indirectly through positive engagement signals, I couldn\u2019t tell you.<\/li> <li>Originality doesn\u2019t mean an <em>entirely <\/em>different document. As little as a 10% difference could be the delineator between marketing success or failure.<\/li> <\/ol> <h2>How Does It Work In Practice?<\/h2> <p>This patent is not about the information gain applied to the current set of search results. It\u2019s about the subsequent set of results \u2013 ranking the next set of search results based on wider user search behavior, personalization, and added document value.<\/p> <p>It highlights that documents:<\/p> <ul> <li>May be <strong>reranked.<\/strong><\/li> <li>May be <strong>excluded.<\/strong><\/li> <li>May be <strong>significantly demoted.<\/strong><\/li> <li>May <strong>no longer appear<\/strong> in results.<\/li> <\/ul> <p>Based on the amount of novel, relevant information provided when compared to other similar documents.<\/p> <p>For any tech SEO geeks out there, you\u2019ll be well aware of the concept of preloading. In nerd circles, preloading tells browsers which resources should be prioritized to improve the page load speed and above-the-fold rendering.<\/p> <p>I think this patent works in a similar manner, but with bloody unreliable <em>people <\/em>instead of machines. Maybe bfcache is a more apt comparison, but I haven\u2019t really got stuck into technical SEO for a while, so forgive me for my appalling analogies.<\/p> <h3>Step-By-Step<\/h3> <ol> <li>A user reads a document about a certain topic, let\u2019s say,<em> growing an apple tree.<\/em><\/li> <li>Google understands that the majority of users don\u2019t stop at one page here. It\u2019s a rich topic. <em>When should I plant one? Where? What do I feed it?<\/em><\/li> <li>With 13 months of click and engagement data to hand, Google knows \u2013 with, I imagine, an unerring level of accuracy \u2013 what piece of content each user should be shown and when based on goal fulfillment.<\/li> <li>But new content is written every day. Pages are updated. So this isn\u2019t a static corpus to work with. <em>And maybe someone has a novel way of growing apple trees?<\/em><\/li> <li>So pages are compared. A user reads a document (d1). Google then compares a new or updated article (d2) to the original.<\/li> <li>If d2 generates a favorable information gain score, it will likely be shown to the user as part of their journey. If it doesn\u2019t, it\u2019s doomed.<\/li> <\/ol> <blockquote> <p>\u201cAn information gain score for a given document is indicative of additional information that is included in the given document beyond information contained in other documents that were already presented to the user.\u201d<\/p> <\/blockquote> <p>Let\u2019s say two documents are chosen based on a user\u2019s search and search history. They\u2019re represented as d1 or d2. D1 is an already-consumed document, and d2 is brand spanking new. Well, to the user at least. These documents can be represented as a vector (or some other semantic representation) to help the model fake understanding of the document and its <em>position <\/em>against similar documents.<\/p> <figure> <p><figure class=\"wp-caption aligncenter\" style=\"width: 909px\"><img decoding=\"async\" src=\"https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/07\/https_3a_2f_2fsubstack-post-media.s3.amazonaws-sej-733197.jpg\" alt=\"A diagram showing how documents are scored against each other in the vector space\" title=\"A diagram showing how documents are scored against each other in the vector space\" width=\"909\" height=\"540\" class=\"\" loading=\"lazy\"\/><figcaption class=\"wp-caption-text\">Vector mapping is all about angles and positioning on a graph to quantify a scoring or positioning system (Image Credit: Harry Clarkson-Bennett)<\/figcaption><\/figure> <\/p> <\/figure> <p>The system provides a quantitative score to assess whether the user should also view d2 after having viewed d1. If the machine learning model generates an information gain score of document d2 <em>over <\/em>document d1, then d2 is likely to be shown \u2013 for future use cases, possibly at the expense of d1.<\/p> <p>There are some incredibly practical implications here.<\/p> <p>If a topic has been done to death, you have a more limited chance to rank and generate value without providing something extra. In a scenario where your article scores 0, the system has assessed it provides nothing extra, and a user who has seen d1 is less likely to see d2 \u2013 <em>your article<\/em>.<\/p> <p>If nothing else, make sure you stand out above your closest competitors in some manner.<\/p> <p>A lot of this describes the foundations of creating brilliant content. Being different and standing out.<\/p> <blockquote> <p>As with so many of these Google-led ideas or initiatives there are flaws. You don\u2019t have to follow it to the letter. But E-E-A-T and \u201cinformation gain\u201d are sound principles. You have to be memorable. There is no alternative.<\/p> <\/blockquote> <h2>How Important Is It?<\/h2> <p>I think uniqueness and standing out are more important than ever. Strip the patent out of the conversation. People or brands who publish content won\u2019t survive if they aren\u2019t memorable to people and \u2013 by proxy \u2013 search engines.<\/p> <p>So you\u2019ve got to do something differently.<\/p> <p>In Google\u2019s case, I think it\u2019s more about efficiency than anything else. If they know the information gain scores of two documents are virtually identical, then a user isn\u2019t going to be shown both versions of the document. The second document will be deprioritized in favor of richer, more unique content.<\/p> <p>Google has enough engagement data to go along with these proxy scores to understand what document should be shown and when. They can get a user closer to their goal by removing overly similar pages from a user\u2019s SERP or AI response.<\/p> <p>Which may be exactly why they\u2019re thinning their index \u2013 the removal of non-value-add content. Well, that and all the AI slop you\u2019re creating.<\/p> <p>It is quite literally down to a) computational resources (money) and b) getting the user to the point of completion quicker. In the DOJ Antitrust trial, Pandu Nayak\u2019s sworn testimony called Navboost \u201c<em>one of the important signals that we have.\u201d<\/em><\/p> <blockquote> <p>\u201c\u2026a shorter query session or fewer dialogue turns can provide a corresponding reduction in the resource demands of the system e.g. with respect to memory and\/or power usage of the system.\u201d<\/p> <\/blockquote> <p>And the Quality Rater Guidelines make numerous references to effort, originality and talent. Frameworks like E-E-A-T and the product reviews update really highlight the importance of actually using products and showcasing the effort you have gone to. The amount of \u201ceffort\u201d you put in is quite literally quantified (highly recommend Sean\u2019s breakdown here). It is part of the Helpful Content update (booooooo) and the more difficult your page is to replicate, the better chance it has of success, all things being equal.<\/p> <p>These are not stupid principles. They\u2019re very good ones. The problem is, effort is expensive. The fewer clicks content produces, the less each article will generate.<\/p> <p>In an attributable manner at least.<\/p> <h2>Google Is Building An Audience Loyalty Ecosystem<\/h2> <p>Don\u2019t take my word for it, take Barry\u2019s. Google has wanted to get rid of click-chasing churnalism for years. Now it can. And it is \u2013 in most cases, I think, a positive.<\/p> <p>They are trying to build something around <strong>engaged users \u2013 <\/strong>like every publisher out there. Your most engaged users are your most valuable. Google\u2019s quietly building a subscriber ecosystem that could one day rival their ad business. No reason to think that<\/p> <p>Publishers that can demonstrate they have an audience outside of SEO are being \u201crewarded.\u201d Although I suspect you could replace rewarded with crushed a little more slowly.<\/p> <p>You can follow your favorite publisher via Preferred Sources and as a Search Profile via the Discover feed (U.S.-only at the time of writing this), and badges like \u201chighly cited\u201d have been in play for some time. It doesn\u2019t work very well, but they are trying to promote unique reporting.<\/p> <p>You can now see how content from social and video platforms performs on Google Search if you meet the requirements. Your digital footprint and impact within the industry you\u2019re in really matters. Particularly when you consider how prevalent social and creator accounts are in Discover.<\/p> <blockquote> <p>I worry that this is completely impossible to explain what is happening to users. What is Preferred Sources vs. a Search Profile?<\/p> <p>It\u2019s tough to force people to follow you on platforms \u2013 maybe that\u2019s the point. Which I kind of understand \u2013 but I think one of these would\u2019ve sufficed.<\/p> <\/blockquote> <p>If you want to know a little more about where Discover is heading, I made a short video about it:<\/p> <p class=\"vcont\"><iframe loading=\"lazy\" title=\"How Google Discover is Moving Away From Publishers\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/dSGzpvtCU_0?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p> <h2>Does Information Density Matter?<\/h2> <p>Yes and no. Long articles are not necessarily more effective at satisfying the user.<\/p> <p>Google has methods to normalize the length of an article to prevent additional keywords and semantically relevant phrases from ranking the document too highly. Factors like\u00a0TF-IDF normalization\u00a0prevent long documents with high word counts from artificially inflating their relevance scores just because they\u2019re quote-unquote\u00a0<em>richer<\/em>.<\/p> <p>More detail may be the wrong phrasing here. Detail and rigor are typically positives. But it\u2019s less important than answering the question and getting the user closer to their end goal.<\/p> <p>User satisfaction is quantified through goal completions and Navboost data \u2013 it trumps everything else.<\/p> <h2>How Does It Affect AI Systems?<\/h2> <p>Well, traditional search ranking is still crucial in AI systems \u2013 whether that\u2019s how effectively you rank for the primary search, your inclusion in the training data, RAG, or suite of fan-out searches run concurrently. And AI searches are extremely personalized \u2013 something that\u2019s likely to only increase over time.<\/p> <p>When Claude starts knowing what toilet paper I buy or selects a poorly chosen \u201cHappy Mother\u2019s Day\u201d card for my mum\u2019s birthday that showcases my lack of effort and empathy, it\u2019s time to call it a day.<\/p> <p>According to Kevin Indig\u2019s latest excellent research, first-party research is rare in AI citations, but it earns 3.3x more. And original data is the strongest single predictor of page originality. Good for traditional SEO, good for AI search. Who knew?<\/p> <p>The ideas described in this patent map almost too neatly onto how modern AI search systems retrieve relevant information. Of the SGE. It helps anticipate the user\u2019s next interest in an assistant-like context. Personalized, \u201chelpful\u201d and with extreme memory.<\/p> <p>As Roger Montti pointed out, this may give a clearer indication of how AIOs use pages that the user in question may be interested in. Their entire job is to synthesize answers from multiple sources and searches to provide the perfect jumping-off point. I suspect this scoring system is an excellent way to avoid computationally expensive, unnecessary utilization of documents.<\/p> <blockquote> <p><strong>contentEffort <\/strong>\u2013 described as a <em>\u2018Large Language Model (LLM)-based effort estimation for article pages\u2019 \u2013<\/em>\u00a0estimates the amount of effort invested in creating an article. As slop makes up more than 50% of the internet, this is seemingly one of Google\u2019s way of dealing with it.<\/p> <\/blockquote> <h2>How Can I Use This Effectively?<\/h2> <p>Make differentiated, non-commodity content. It\u2019s really simple. Apply what we call information gain in this context to your own content \u2013 if you cannot add anything of value to the existing index, then don\u2019t bother.<\/p> <p>You can use this with:<\/p> <ul> <li>Original data.<\/li> <li>First-hand experience.<\/li> <li>Interviews.<\/li> <li>Real reporting.<\/li> <li>Being first on the scene and developing the story as it happens.<\/li> <li>Proprietary analysis.<\/li> <\/ul> <p>You don\u2019t need a big budget. You can do amazing things with a few free data sources, some creativity, and a bit of rope. Just make sure the article has an element of uniqueness.<\/p> <p>I think this really helps frame whether content is still worth creating. If you\u2019re doing something just for SEO reasons and you can\u2019t add anything extra to the existing suite of information, kill it. If a document contributes very little new information, the patent suggests it\u2019s a strong candidate to be deprioritized when selecting subsequent documents.<\/p> <p>Still costs time and money to make, but is less and less likely to drive any real value. Stay in your lane, but drive a nicer car.<\/p> <blockquote> <p>I have a feeling your indexation report in GSC is invaluable here. Beige content has a shelf life so low it\u2019s in the running for the new UK Prime Minister. So check for any pages dropping out of the index at scale for more serious issues.<\/p> <\/blockquote> <p><strong>More Resources:<\/strong><\/p> <hr\/> <p data-pm-slice=\"1 1 [\" table=\"\">Read <em>Leadership In SEO.<\/em> <u>Subscribe now<\/u>.<\/p> <hr\/> <p data-pm-slice=\"1 1 [\" table=\"\"><em>Featured Image: Roman Samborskyi\/Shutterstock<\/em><\/p> <\/div> <p>Content,SEO#Google #Understand #Unique #Content1784123581<\/p> ","protected":false},"excerpt":{"rendered":"<p>Thanks to Rand\u2019s excellent research and Barry\u2019s expletive-laden ranting, we know that Google processes over 5 trillion searches each year. Trillion. Per day, that\u2019s 13.7 billion. Per second, 158,000. There are some sizeable and growing caveats here: That still means Google processes 2.92 billion clicks to the open web every day. It\u2019s still a figure [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":11694,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[185,75,28038,4652],"class_list":["post-11693","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-accessibility","tag-content","tag-google","tag-understand","tag-unique"],"acf":[],"_links":{"self":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts\/11693","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=11693"}],"version-history":[{"count":0,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts\/11693\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/media\/11694"}],"wp:attachment":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11693"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11693"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11693"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}