Rewind to Fast Forward 2.0: Play the Classics or Time for Change?

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Rewind to fast forward 2.0 Play the classics or time for change? Bastian Grimm, Peak Ace AG | @basgr

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At least, not really, anymore. Technical SEO doesn’t matter.

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Fully automated, AI-driven content generation is NOT a thing of the future – it’s already here. Nope, content doesn’t, either…

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pa.ag @peakaceag 4 Back in 2008, I used to explain SEO to C-suites like this: Seriously, who doesn’t love the good old 4:3 slide format?! Even back then, there were three crucial pillars… including links!

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You didn’t really want me to talk about links, right?

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pa.ag @peakaceag 6 We’re moving away from “over 200 ranking factors” And as for those “ranking factors studies”… well, ranking signals can't be sorted on a spreadsheet by order of importance – it’s much more complex than that! Source: https://pa.ag/3BbVS6k The MUM algorithm can take images as an input (no keywords!) and provide an answer sorted from web pages around the world, regardless of language. How would a general “ranking factor”, like links or keywords in title, even work in a scenario like that?

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pa.ag @peakaceag 7 Let’s look at a few hypotheticals. What if… Technical SEO doesn’t matter anymore? 1 CMSes like WordPress solve major technical issues by themselves - a "clean" URL structure or parameter handling are no longer a problem. Content is no longer a key differentiator? 2 Content can be produced by AI at scale, with almost no human intervention - and it won't be long before final corrections are no longer necessary. Links don’t move the needle anymore? 3 Links are continuously and increasingly losing relevance - and what if other, more relevant ranking signals / criteria appear?

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Before we go there, let’s take a step back…

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PAST

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pa.ag @peakaceag 10 1996 is just a little while ago now… But: 25 years ago, the (then) Stanford students Sergey Brin and Larry Page started a search engine called "BackRub": Source: https://pa.ag/3EAUhJl

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pa.ag @peakaceag 11 A bit later, an early version of Google looked like this: This was end of ‘98, and Google! Was! Excited! To! Be! Here!

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pa.ag @peakaceag 12 And search result pages used to look somewhat different: This was a bit later, around 2006-2007

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pa.ag @peakaceag 13 Notice anything familiar? Yup, good ol’ left-hand navigation is back – only took Google 15 years or so:

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pa.ag @peakaceag 14 Ok, in fairness – it’s much smarter than it used to be Google calls this "dynamic organisation“; vertically organised on mobile. It appears in different colours, different positions and is sometimes even sticky: Source: https://pa.ag/3hMvY1C

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pa.ag @peakaceag 15 Also, continuous search got introduced in Chrome “Keep searching without needing to hit the back button” – essentially continuous search directly in your Chrome browser, and yes, this can/will also contain competitors: Source: https://pa.ag/3ECb3In […] To make it easier to navigate from one search result to the next in Chrome, we’re experimenting with adding a row beneath the address bar on Chrome for Android that shows the rest of the search results so you can get to the next result without having to go back […]

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pa.ag @peakaceag 16 As well as continuous scrolling on mobile devices Available in Google Search for most English searches on mobile devices in the US: Source: https://pa.ag/3BLJvhM

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There is really only one side to this! This is very helpful for the current antitrust debate…

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pa.ag @peakaceag 18 Google dedicates almost half the first page to its own products, which dominate the coveted top of the page: Source: https://pa.ag/2ZgGJTl

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pa.ag @peakaceag 19 Speak no evil, think no evil! Google makes it obvious that certain words are taboo in both internal and external communication, e.g. don’t use “market share”, or “market” – instead, use “industry”: Source: https://pa.ag/3nQV9Ug & https://pa.ag/3zkWDIN

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For example, between every third to fifth organic results? Maybe some new ad integrations?

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pa.ag @peakaceag 21 Google is really becoming creative with more ad space “You can traffic full-page web ads that appear between page views“ – like seriously?! Source: https://pa.ag/3FjJlR4

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pa.ag @peakaceag 22 Google continues to pull as much data as possible For most queries about this year’s Olympics, there was no need to leave the SERP: Source: Alistair Lattimore via https://pa.ag/3ztZjDM

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pa.ag @peakaceag 23 Nothing new, right? That’s very true actually; in fact, I used this example in a presentation years ago: Source: Peak Ace presentation from 2018 via https://pa.ag/3hPQfU1 new president usa The searcher instantly found what was expected= happy user!

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pa.ag @peakaceag 24 It’s more than pulling in data: it’s making you “stick” Now, you need one more click to get to what you need (like a phone number, or a route) – essentially, Google is artificially inflating the number of searches, again: Source: https://pa.ag/39kdxwz

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pa.ag @peakaceag 25 Tons of smaller changes, impossible to really keep track Around July ’21, Google started testing indenting search results from the same domain: Source: https://pa.ag/3hPsSda

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pa.ag @peakaceag 26 Google introduced various types of in-SERP warnings E.g. for fast-changing information and to fight misinformation: Source: https://pa.ag/3tUcVqR

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pa.ag @peakaceag 27 Back to the big stuff: Much more than visual changes High-authority sites (with health info) started seeing massive increases in June 2020, which were (partially) scaled back during the December 2020 core update: Source: Sistrix Toolbox & Lily Ray via https://pa.ag/39Bkslf

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pa.ag @peakaceag 29 But speaking of updates… summer of updates, much? Passage ranking (EN only) 10.2. June core update 5.6. Page experience update 15.6. Web spam update (Part #1) 24.6. Web spam update (Part #2) 30.6. July core update 4.7. “About this result” panel update 22.7. Page title update 25.8.

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pa.ag @peakaceag 30 Can‘t keep up? Sistrix (Google Updates Checker) or Semrush (Sensor) has got you covered, for free! Source: https://pa.ag/3koWG1S & https://pa.ag/3hLQDTi

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Who'd have thought that Google would actually mention links from time to time ... "Web Spam Updates“ are back…!

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(Yet) Maybe links aren’t entirely dead?

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No one really uses fancy “new“ attributes like rel=sponsored, but Google desperately wants the data. My guess?

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pa.ag @peakaceag 34 I think there’s a reason why this is all happening at once… In May 2021, Google published a major release of “TF-Ranking” that enables full support for natively building LTR models using Keras (a high-level Tensor Flow 2 API): Source: https://pa.ag/3EJYRoG These [Keras] components make building a customised LTR model easier than ever and facilitate rapid exploration of new model structures for production and research. Our most recent release [is] the culmination of 2.5 years of neural LTR research.

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pa.ag @peakaceag 35 OK…?!

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LTR is a class of techniques applying supervised machine learning (ML) to solve ranking problems. LTR = Learning to Rank

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Ranking unseen lists of items in a similar way to lists in training data The LTR approach

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A comprehensive framework that includes several of the best LTR algorithms, multi-item scoring, ranking metric optimisation and, most importantly, unbiased LTR. TF ranking

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End-to-end open-source machine learning platform originally developed by the Google Brain team Tensor Flow

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40 Over 300 million predictions per second ...! Zemanta (an Outbrain subsidiary) uses the Tensor Flow framework for their DSP (Demand Side Platform), producing over 300 million calculations / second: Source: https://pa.ag/3cbLII6

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A (high-level) neural network library built on Tensor Flow Keras

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The use of Keras in Deep Learning (DL) is a very user- friendly way to keep prototyping quick and easy Keras

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Because: most machine learning to date has been, or is, a big black box. It gets even better…

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pa.ag @peakaceag 44 Interpretable LTR using GAMs (=interpretable rankings) GAMs are compact, intrinsically interpretable models which consider both the ranked items and context features (e.g. query/user profile) Source: https://pa.ag/2ZcvBXs

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pa.ag @peakaceag 46 Evaluating LTR by means of neuronal ranking GAMs "NR-GAMs are compact, intrinsically interpretable models that take into account both ranked items and contextual features (e.g. query / user profile)." Source: https://pa.ag/2ZcvBXs

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NR-GAMs produce interpretable, comprehensible models. Each feature’s individual contribution, and of its contextual features, is clear to see. LTR models become transparent

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... and can therefore be corrected or optimised much faster! LTR models become transparent

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pa.ag @peakaceag 49 We should be prepared for the update frequency to continue to increase - and that overlapping updates will become the rule, not the exception.

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Fail to give searchers what they want, and your chances of ranking are slim to none But it‘s not only updates; intent also plays a huge role!

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pa.ag @peakaceag 51 30-second recap: what’s search intent anyways? Search intent is the why behind a search query: why did the person make this search? Are they looking for information, to make a purchase, or for a specific website? Informational Navigational Commercial Transactional ▪ “Jason Statham movies” ▪ “Berlin Paris distance” ▪ “what are carbs” ▪ “peak ace address” ▪ “gmail” ▪ ”instagram login” ▪ “Dubai winter temperature” ▪ “haircut near me” ▪ “best webinar software” ▪ “Audi rsq8 price” ▪ “champagne next day delivery” ▪ “BER CDG flights”

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pa.ag @peakaceag 52 Google is obsessed with “Intent” The current version of their Search Quality Evaluator Guidelines mentions “Intent” over 400 times – the “Needs Met” section spans over almost 30 pages: Source: https://pa.ag/2W1qRCS

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pa.ag @peakaceag 53 Hate to say but it… again, ML plays a role here as well: Back in 2007, Microsoft published a patent that suggests that 87% of ambiguous queries can be identified and understood with supervised machine learning: Source: https://pa.ag/2XHdZTt We propose a machine learning model based on search results to identify ambiguous queries. The best classifier achieves accuracy as high as 87%. By applying the classifier, we estimate that about 16% queries are ambiguous in the sampled logs.

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pa.ag @peakaceag 54 Thanks to recent advances in ML, Google has made huge leaps ahead with getting search intent right - and they're only going to get better at it. I expect them to reduce the number of results once they’re ~100% certain.

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pa.ag @peakaceag 55 Can’t get your head round it? Automating at scale? Kevin Indig has got you covered! Go check out his two articles on the topic: Source: https://pa.ag/3u41oFj

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pa.ag @peakaceag 56 You‘re late to the party if you haven‘t figured this out yet: It’s of utmost importance right now to get intent mapping right; intent means relevance and therefore better rankings. Get this wrong, and you have no chance of ranking long term.

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So yep, tons of things going on – let’s fast forward to today:

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PRESENT

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Wait a second - this isn't new! Isn't this just what we used to call “domain authority”? Expertise, Authoritativeness and Trustworthiness (E-A-T)

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pa.ag @peakaceag 61 Back in 2019, Google gave us their official “confirmation” E-A-T is an important part of their algorithms. If you have been negatively affected by a core update, you need to get to know the QRG as well as E-A-T specifically: Source: https://pa.ag/3u1kBrm The concept of E-A-T is discussed in detail in Google’s Quality Raters’ Guidelines (QRG). Demonstrating good E-A-T both on and off your website can (potentially) help improve rankings.

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Google's algorithms don't give an E-A-T score. Quality raters analyse E-A-T in their checks, but don't give a score and it doesn't directly affect your rankings. There is no E-A-T score

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pa.ag @peakaceag 63 E-A-T is not an algorithm (on its own) [Google has] a collection of millions of tiny algorithms that work in unison to spit out a ranking score. Many of those […] look for signals in pages or content. When you put them together […], they can be conceptualised as E-A-T. Gary Illyes at PubCon in October 2019:

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pa.ag @peakaceag 64 E-A-T is not a “real ranking factor” Source: https://pa.ag/3zAqvAO See what I did there?

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pa.ag @peakaceag 65 E-A-T approximates what the algorithms should do Source: https://pa.ag/3CCXW7I […] what would Google do algorithmically to impact those [E-A-T] things? When it comes to, say, health – would Google employ BioSentVec embeddings to determine which sites are more relevant to highly valuable medical texts? […] I tend to think they’re experimenting here [… and] this is a far better conversation than say, should I change my byline to include ‘Dr.’ in hopes that it conveys more expertise?” This quote from AJ Kohn contains a fantastic, hands-on description:

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pa.ag @peakaceag SE = sentences and their semantic information as vectors. This makes it easier to understand context, intent and other nuances. Sentence Embeddings (SE)?

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pa.ag @peakaceag 67 BioSentVec: Sentence embeddings for medical texts Having been fed >30 million articles (mainly from the health sector), these bots help to better assess the trustworthiness & accuracy of texts. Source: https://pa.ag/3u3EttK

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pa.ag @peakaceag 68 Still confused about what EAT is & how to improve it? Check out these articles from Marie Haynes (MHC) and Fajr Muhammad (iPullRank): Source: https://pa.ag/39uPgUo & https://pa.ag/2W3gb6T

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Introduced in early 2021, it gives more information about the sites that appear in Google Search “About this result“ panel

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pa.ag @peakaceag 70 Continued investment in information literacy features “About this Result” has been viewed 400M+ times since its launch, and a new version with even more details is on the way: Source: https://pa.ag/2YlOdUQ The panel will now include information about the source itself (Wikipedia description), and what the site says about itself, as well as news, reviews and other contextual information that can help the user to better evaluate unfamiliar or new sources.

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If you find yourself on Wikipedia, make sure that the first 3 sentences of the description are up to date! Who remembers noodp?

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… or Passage Indexing? Or both? Passage Ranking

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pa.ag @peakaceag 73 Passage Indexing >> Passage Ranking Google’s approach to better understand and rank “less well-structured” long-form content: Source: https://pa.ag/2W0Sqw3 Focus on very long pages and/or pages that target multiple topics Improved understanding of certain sections (“passages”) of a page better which previously might have seemed irrelevant Passages won’t be indexed alone; the passage identified will be given additional weight in ranking, thus “passage ranking”.

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pa.ag @peakaceag 74 Passage Ranking went live on February 10, 2021 But: “only in the US in English” (read: for English-language search queries) Source: https://pa.ag/2W0Sqw3 Sooo… maybe they’ll tell us, maybe not?!

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“Continue to focus on great content” – that’s what Google tells us. So why even bother? There’s nothing special creators need to do!

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pa.ag @peakaceag 76 Could there be another “ML connection” going on here? Check out Dawn Anderson’s fantastic coverage of BERT, its capabilities as a re-ranker including current limitations and why BERT is (most likely) used in passage ranking: Source: https://pa.ag/3u0KuaN […] it is highly likely BERT has a strong connection to the change [passage indexing], given the overwhelming use of BERT (and friends) as a passage re-ranker in the research of the past 12 months or so.

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pa.ag @peakaceag 77 Passage re-ranking using BERT BERT has probably been (completely) repurposed to add contextual meaning to a training set of passages in two stages: Source: https://pa.ag/3oCy0Wh Super super(!) simply put, a “re-ranker” takes classic rankings signals and then re- ranks the initial results based on additional or more refined input and/or data. Essentially, a re-ranker is a layer on top.

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So, where does all this lead?

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FUTURE

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pa.ag @peakaceag 81 Here’s what I think is going to happen… Google is moving towards becoming a fully automated recommender system, operating in an (almost entirely) query-less world, which anticipates your every question based on your individual search journey/context.

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pa.ag @peakaceag 82 What’s a recommender system? Recommenders produce items based on user history/similarities. Results are computed by predicting their rating or by recommending similar items: Source: https://pa.ag/3CCSIJa Google has a lot of experience with this and has already published a number of patents and concepts on how recommendation services can become even better. You will have already come across these services, as most of the recommendations you see, for example on YouTube, are based on these systems.

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pa.ag @peakaceag 83 Collaborative Interactive Recommender (CIR) CIRs are able to interact with users in any order, so as to understand and meet their needs in the best possible way. Source: https://pa.ag/3CCSIJa RecSim from Google is very exciting. The platform is supposed to make CIRs even smarter and comes with a lot of tools that can be used to build super smart "mega recommenders".

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pa.ag @peakaceag 84 A query-less world – but how? Obviously, it’s already possible to search on lots of devices without a keyboard; but AI- driven solutions allow for surfacing info/content without actively searching for it: Source: https://pa.ag/2W1E3ro Google Discover is a content recommendation engine that suggests content across the web based on a user’s search history and behaviour. Google Assistant allows users to engage in two-way conversations and get answers from the system without ever even looking at a “classic” search result. Google Lens lets you search what you see - from your camera or photo. Over 3 billion searches monthly already, and especially popular in learning.

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Google has been figuring out what people might ask based on search history, user data and other data points for a long time. Just see “people also ask”! Anticipate questions before asking?

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pa.ag @peakaceag 86 In fact, at Search On 2021 Google confirmed exactly this: Prabhakar Raghavan (SVP , Google) said: Source: https://pa.ag/3amVV3L My team and I spent a great deal of time providing high-quality answers to questions that haven’t even been asked yet.

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Moving beyond standalone, individual search queries which were meant to provide “the best answer” towards understanding context and language in search. Search journeys?

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pa.ag @peakaceag 88 The Google Multitask Unified Model (MUM) Google’s most recent push into AI, seeking to deliver search results that overcome language and format barriers to deliver an improved search experience: Source: https://pa.ag/3kvuUAQ & https://pa.ag/3CFMMiP ▪ Like BERT, it’s built on a transformer architecture ▪ 1,000x more powerful than BERT ▪ Can acquire deep knowledge of the world ▪ Understand and generate language ▪ Trained across 75 languages ▪ Understand multiple forms of information

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pa.ag @peakaceag 89 A lot of innovation in NLP comes with larger datasets MUM uses the T5 model which is pre-trained on C4 and achieves state-of-the-art results on many NLP benchmarks: Source: https://pa.ag/3EFfRfT To accurately measure the effect of scaling up […], one needs a dataset that is high-quality and massive. […] To satisfy these requirements, we developed C4, a cleaned version of Common Crawl that is two orders of magnitude larger than Wikipedia.

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Common Crawl? (MUM) Web crawl (220 TB) with about 3 billion webpages (BERT) Wikipedia with around 56 million articles VS.

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pa.ag @peakaceag 91 One thing that often gets overlooked… Source: https://pa.ag/3CFMMiP MUM is multimodal, so it understands information across text and images and, in the future, can expand to more modalities like video and audio.

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pa.ag @peakaceag 92 Google Cloud > Vision AI (for images) Vision API offers access to powerful pre-trained ML models. Detect objects and faces, read printed and handwritten text, etc. Source: https://pa.ag/3u3nOGR

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pa.ag @peakaceag 93 “Search part of the page with Google Lens“, anyone? Want a test-drive? Go to > chrome://flags > Enable Lens Region Search (restart Chrome) Source: https://pa.ag/3DfKc3o

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pa.ag @peakaceag 94 Also, Google is getting into brands in a big way They will soon be measuring brand penetration using image recognition: Source: https://pa.ag/3AK3Lz0 Image analysis by e.g. using Google Street View can tell them a lot about brand saturation and capacity in different geographic areas – Google might already know how much more than what we actually think they do.

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pa.ag @peakaceag 95 Google Cloud > Video AI Current core features around understanding “things” in a video (e.g. objects, location and actions), various new stuff in beta (celebrity, face and person detection): Source: https://pa.ag/3CAE2KD Google’s Video AI API services have some really powerful features: ▪ Streaming video analysis ▪ Object detection and tracking ▪ Text detection and extraction ▪ Explicit content detection ▪ Automated closed captioning & subtitles ▪ Celebrity recognition ▪ Face detection ▪ Person detection with pose estimation ▪ … and more!

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pa.ag @peakaceag 96 Google Cloud > Speech-to-Text (for audio, e.g. podcast) Audio input processing at-scale including complex features such as multi-speaker recognition, etc. Source: https://pa.ag/3lLG3wO

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pa.ag @peakaceag 97 MUM & Lens were the hottest topics at Search On 21 According to Google, MUM technology is going to revolutionise the way we engage with information; if you haven’t watched the video yet – make sure you do: Source: https://pa.ag/3l8DAgK MUM can simultaneously understand information across a wild range of formats and draw implicit connections between concepts, topics, and ideas of the world around us.

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Google is already very capable of understanding formats way beyond simple text!

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What does that mean for our SEO work?

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Maybe “doesn’t matter” is a little strong. Going forward, I see tech SEO as more of an “enabler” Technical SEO

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Or as some people call it: “edge SEO“ or “SEO on the edge”. Ever heard of it? Serverless SEO

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pa.ag @peakaceag 102 Back in Sept 2017, Cloudflare introduced their “Workers“ Workers use the V8 JavaScript engine built by Google and run globally on Cloudflare's edge servers. A typical Worker script executes in <1ms – that’s fast! Source: https://pa.ag/3otrFMK

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Using Workers to overcome challenges and limitations with popular CMS and e-commerce platforms

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Workers are fairly straightforward and easy to implement, requiring only minimal dev efforts. Easily build a proof-of-concept rollout & business case

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pa.ag @peakaceag 105 Does this only work with Cloudflare? Similar implementations are also available with some of the most popular CDN providers out there: Compute@Edge Edge Workers Cloudflare Workers Lambda@Edge

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pa.ag @peakaceag 106 With full control over the HTML response, it’s easy to test new content!

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Signed exchanges (SXG)?

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pa.ag @peakaceag 108 SXG allow Google Search to prefetch your content Similar to AMP , SXG allows resources like HTML, JS, CSS, images and fonts to be pre- fetched directly from the SERP – allowing for an “instant experience“ post click: Source: https://pa.ag/3AbSlUg

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pa.ag @peakaceag 109 Again, Cloudflare has got you covered: The technical implementation process is not simple, so I expect this to be huge! Source: https://pa.ag/3uFs3IW

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pa.ag @peakaceag 110 According to Sistrix’s research, CWV seem to have impact: Source: https://pa.ag/2WHBn2t Page experience in the form of the Core Web Vitals has a measurable influence on the Google rankings. […] for most commercial websites, it is worth it. In addition, fast websites not only help the Google ranking, but also improve UX.

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User-Agent client hints?

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pa.ag @peakaceag 112 The User-Agent string is messy, like, very messy: Over the decades, this string has accrued a variety of details about the client making the request as well as cruft, due to backwards compatibility: Mozilla/5.0 (Linux; Android 6.0.1; Nexus 5X Build/MMB29P) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.82 Mobile Safari/537.36 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)

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pa.ag @peakaceag 113 The UA string will be frozen, client hints to take over User-Agent Client Hints are a new expansion to the Client Hints API and enables developers to access information about a user's browser – or a crawler’s features: Source: https://pa.ag/3AiiUaI

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pa.ag @peakaceag 114 It‘s never too early to start testing these things: Googlebot (running Chrome >89) already populates those CH-headers:

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pa.ag @peakaceag 115 There will always be new things in search: Technical SEO will almost exclusively focus on testing for humans and crawlers alike - providing crucial recommendations enabling sites to rank in search.

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pa.ag @peakaceag 116 Technical SEO testing – Peak Ace runs its very own test lab We are trying to understand how Googlebot handles “things“… Set up new HTML documents/tests with the click of a button Add an unlimited number of server-side headers, such as X-Robots, canonicals, hreflang, redirects, caching, etc. Add elements to the document , for example meta robots, canonical or tags to run JS Add unique content to the page, depending on the language you want to test for (sometimes, content generation has a valid use-case) Add any type of HTML to the <body> / DOM Integrated bot tracking (JS for evergreen Googlebot + non-JS) by default Automatically generate output by using standard tags (e.g. <iframe>) as well as JavaScript (to ensure rendering is in play) And lots more…

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pa.ag @peakaceag 117 Testing beyond technical SEO stuff – real SEO AB testing SearchPilot and Ryte offer robust solutions to get you going (as in testing!) asap: Go check them out: https://www.searchpilot.com/ & https://en.ryte.com/

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How to win in the era of “infinite content”? Content

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pa.ag @peakaceag 119 The danger of heading towards search singularity: AI makes it easy to churn out vast quantities of mediocre content […] there’s a real risk of medium to long-tail targeted search results becoming a battle between human- and AI-generated content - a search singularity.

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pa.ag @peakaceag 120 GPT3 is only just the beginning… In Sept 2020, The Guardian had GPT-3, OpenAI’s powerful language generator write an essay for them from scratch based on a short instruction and some prompts: Source: https://pa.ag/3moPX83 GPT-3 produced eight different outputs, or essays. Each one was unique, interesting and advanced a different argument. The Guardian could have just run one of the essays in its entirety. […] Overall, it took less time to edit than many human op-eds.

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pa.ag @peakaceag 121 Check out Jarvis – its quality is already really good! AI trained to generate original, creative content such as headlines, blog posts, sales emails, video transcripts, and more: Source: https://www.jarvis.ai ▪ Relies on GPT-3 API, meaning its best results are in EN ▪ 50+ templates for super-specific briefings (e.g. FB ads, blog posts, headlines, etc.) ▪ Specific modules for Amazon, online shops, or functionality such as a “summarizer”. ▪ German language available ;) ▪ Don’t just take my word for it! And try Copy.ai, Writesonic or Copysmith

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OK, let’s talk about the elephant in the room: quality. But it won’t be good enough to rank!

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pa.ag @peakaceag 123 But it won’t be good enough to rank! Or will it? Source: https://pa.ag/3BoVRMo It’s easy to argue that AI-written content is… not good enough to rank; that it simply dumps connected ideas together [and connects them with] passable sounding phrases. [A] simulacrum of good writing, [it] looks good at first blush but falls apart on closer inspection.

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Especially on mid- and longtail, it’s fairly common: No narrative. Repetitive information. Unoriginal formats. Have you looked at the SERPs lately!?

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pa.ag @peakaceag 125 Truth is, machine-generated content already ranks well! Granted, this doesn’t always last long term – but still, its totally possible. And has been for years already, long before AI – with good ol’ “spun” texts: Source: https://pa.ag/3Bg4xok

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(maybe add some… links?) And if your content doesn’t rank?

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pa.ag @peakaceag 127 Check this out: r/SubSimulatorGPT2 “This is a subreddit in which all posts and comments are generated automatically using a fine-tuned version of the GPT-2.” Source: https://pa.ag/3DpBsbm

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pa.ag @peakaceag 128 In all seriousness though: We’re going to get to a point where language models – not GPT-3, but one of the successors in the near future – will be able to generate perfectly optimised content.

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Even if it‘s just to generate some headlines, titles and meta data for you; I‘m sure you‘ll be surprised! Give GPT-3/Jarvis a try!

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pa.ag @peakaceag 130 Super exciting research: quantum computing + NLP At present, we are still far from using the maximum power of quantum computing for anything like DL or ML or NLP - but when it finally *does* work... Source: https://pa.ag/3cfg10w

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pa.ag @peakaceag 131 Quality is a powerful differentiator today, but it’s about to become even more important: Source: https://pa.ag/3BoVRMo ▪ Focus on information gain in every article you create ▪ Diversify beyond search and invest in thought leadership (counter-narrative opinions, personal narratives, network connections, industry analysis & data storytelling) ▪ Share the same information but create a new experience

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Cool! Now, who’s excited to hear about some links?? Links

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Nope, still not going there…

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134 Now what?

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pa.ag @peakaceag 135 I hope by now we can all agree on this? AI is fundamentally going to change the next generation of search experience.

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pa.ag @peakaceag 136 Still not convinced? "Current AI models are trained to do exactly one thing. Pathways AI allows us to train a model to do millions of tasks." Source: https://pa.ag/3GIeyxF A single AI system to generalise across thousands or millions of tasks: ▪ multi-tasking (one model doing multiple things) ▪ multi-modality (one model handling multiple media types as well are more abstract ones) ▪ efficiency (one model that is sparsely activated for more efficiency)

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pa.ag @peakaceag 137 We’re familiar with many of today’s biggest global challenges […] we’re also sure there are major future challenges we haven’t yet anticipated. […] we’re crafting the next- generation AI system that can quickly adapt to new needs and solve new problems all around the world as they arise. Source: https://pa.ag/3GIeyxF

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pa.ag @peakaceag 138 In my opinion, we’re going to see a fundamental shift: Technical SEO, content and links - machines will take care of them all as a basic requirement.

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Experience & Satisfaction

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If Google were omniscient and could understand content/context perfectly, how would you rank one page above another if both are equal in quality and relevance? Let’s fast forward a bit then, shall we?

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pa.ag @peakaceag 141 If a page's elements and content don't affect Google's understanding of it, user experience becomes the differentiating factor. Experience and satisfaction will be most important to users, and therefore search engines. Let’s fast forward a bit then, shall we? If Google were omniscient and could understand content/context perfectly, how would you rank one page above another if both are equal in quality and relevance?

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pa.ag @peakaceag 142 The three cornerstones of SEO – 2022 edition Ensure crawl- & renderability, optimise architecture, internal targeting and linking. Provide unique, holistic and qualitative coverage of relevant topics for your readership. Off-page On-page “Get people to talk about us.” External linking, citations, brand mentions & PR Trust Technical Content Experience & Satisfaction

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pa.ag @peakaceag 143 The war for data is already raging! Google is delaying cookie blocking, Amazon is blocking Google’s FLoC, IOs 14 tracking prevention, etc. Source: https://pa.ag/3rBMynk

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pa.ag @peakaceag 144 Google is going to double-down on ecom/payment data Until AI works perfectly, Google is going all-in on payment – because ecom data (like shopping baskets) for attribution and measurement (of satisfaction) are gold! Image Source: https://pa.ag/3ovhF5D Experimental features are already part of Chrome - try for yourself: chrome://flags (#ntp-chrome-cart-module)

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I don’t think so – but here’s some takes on “near” future changes I predict we’ll be seeing: Too far in the future?

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pa.ag @peakaceag 146 Here’s what I think we’ll be seeing soon: 01 Continued push for entities & structured data With a major focus on solving the challenge of inconsistent data sources and to train ML algos to perfection. 02 Establishing Chrome as the OS for the web Google needs this layer of data and will push hard (e.g. Apple/Safari deal) for continued market domination 03 Increased competition due to MUM While AI will make Google even better at interpreting complex intents, at the same time you’ll need to compete against more websites. 04 Emphasis on task-driven (classic) search To remain relevant in “classic search”, Google needs help answering any user question at any time. Re-finding things will become a major task; the “new” SERPs will reflect that. 05 “Buy now” button in search results With ecom and CMS’s moving headless and APIs everywhere, we should see this within 12 months…!

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Care for the slides? Any questions? [email protected] Take your career to the next level: jobs.pa.ag www.pa.ag twitter.com/peakaceag facebook.com/peakaceag Bastian Grimm https://pa.ag/dme22 [email protected]