so um thank you all for coming um I'm going to talk to you about possibly the most boring title we've ever had at search NE orang which is conceptual models of SEO and Google exploits and to start I'm going to show you about conceptual models because it's easier than trying to explain and I've brought my famous tennis ball that comes with me everywhere because I want you to take part in a science experiment with me which is very simple I just want you to imagine if I drop this normal tennis ball how high you think
it's going to bounce so put your hand up if you think it will bounce this High put your hand up if you think it's going to bounce about this High what lower think okay I'm just going to do it we'll find out look at this amazing underwhelming about that my point here is there is a way of course to calculate this with the coefficient of restitution and and I'm sure none of you did that in your head you used a conceptual model that you have because you know floor hard tennis ball kind of squishy things
accelerate when you drop them and you've seen some tennis balls bounce before and my pitch to you is you can do SEO in a similar way with conceptual models and in fact this is what Advanced SEO is Advanced SEO is all the tiny bits of information that you pick up understanding how certain things work hearing uh what people uh like Brendan was saying and stitching them together into a model to me that's what Advanced SEO is it's great understanding things like vector embeddings but it's not going to tell you what is and what is not
going to rank and that's what I'm want to talk to you about so if you're a brand new fresh-faced in SEO and you're like this chap I'm going to hopefully change the way you think about SEO if you have a few years under your belt in SEO and you look a bit more like this I'm going to teach you how to add to your conceptual models to build a reliable way of knowing what you should be doing in SEO or if you are like Brendon a veteran SEO living their best life enjoying all of the
work they're doing and by the way hello to all the clients in the room that watch Brendan's talk you must be the nice ones because you're still with us um I'm going to go through uh for those that don't know we found a Google exploit last year um and we got lots of interesting information from that which I'm going to share some with you in this talk but I want to start talking about games because I play lots of games but I play games in a weird way which is I think about them as optimization
problems rather than having fun so I will never play you at Connect 4 because I know if you start and you go in the middle column it takes 41 turns to force a win so it's a solved game I'll probably never play you at Monopoly because when you move is determined by the distribution of two dice rolls which has this bias so you can make a heat map when you take into account the chance cards of where people are going to land and therefore you just know where to buy properties so it's not particularly fun
to play so what do we learn from this apart from I'm a very unfun person to invite to your board game evening it's that there is a game actually and you may laugh at this that I think taught me more professionally than many actual qualifications I did which is this game it was released in 1996 and it's called theme park um it's kind of a simulation game about running a theme park um there's all kinds of really interesting variables you can affect which um change your optimization outcome which is you're meant to make as much
money as possible in this game and this game is really similar to SEO for lots of reasons you optimizing to get the most amount of visitors you're optimizing for them to have a good time um you look at things like how long they spend in your park lots of things seos talk about and like Google there are documented and undocumented things you can do to affect the outcome so an example in theme park is uh you can change the ticket price which if you put the ticket price up you make more money up until a
certain point where people are like oh it's too expensive I'm not coming just like Google has provided as with documented advice about you can uh optimize your title tag and put keywords in it but you know you can't put 500 words in your title tagget doesn't work that way but the really interesting thing about this game for me and why I ended up loving it was the undocumented things you can do to optimize so in this game you can have little shops and they sell french fries sell chips right but I found you can control
the amount of salt you put on the chips and if you put lots of salt on the chips people get thirsty really thirsty so you can make the chips really cheap and then you put a drink shop just down the road and charge five times as much for the drinks and people buy them CU they're so godamn thirsty so it's like this undocumented way to change your outcome and Google has these as well well so Google's most obvious example I think is Anchor text the words you use in the text when you link to web
pages Google really never told us about this but as a community we figured out it was a really powerful way to change how your website ranked unfortunately in Fe Park if you put way too much salt in your chips people puke I found that out as well and if you really overdid the anorex thing you would actually get a penalty from Google that was the the penguin algorithm we spoke about but what really fascinated me was the the advice the Strategic advice in the manual theme park said just aim to build the most fun theme
park your guests will love and it really reminded me of what Google tells us which is just make really good helpful content for your users and this is the framework of our conceptual model right which is Google tells you to make helpful content and I'm certainly not saying this is a bad thing you should absolutely do this but the Google algorithm has a Target and if you think that Target Target is helpful content you will probably find out like many people you will spend ages making helpful content and find out you don't actually rank this
is because there are other forces pulling on this which in Google's case is making ungodly amounts of money which we've learned and the result is the algorithm reality is somewhere in the middle right yeah they want helpful content but they also want to make as much money as possible um I I did have examples of this but then Google got found to be a monopoly so I don't have to bother proving it because it's it's factually true now but this is the same as theme park right just make fun rides but I'm going to Salt
the hell out of the chips because my optimization goal is to make as much money and this is the way you can think about SEO so if this is the rank in reality why is SEO not super simple and part of the reason is it turns out it's very difficult to index and order all of the information in the world so tricky thing to do so Google while that might be their target there is a margin of error and these are addressed with Google updates so generally what will happen is Google do an update and
it will maybe Veer itself of course they'll gather data about why that is or the web kind of changes they do another update which fixes that and creates some other kind of issue and the interesting thing is at each one of these junctures sometimes they land near the middle line but when they're way out it normally means there's something exploitable in the algorithm you can do and this is referred to so if there are any Gamers here you'll be enjoying this this is referred to in online gaming as The Meta does anyone know what that
term means in gaming a few people few people obviously like worried to out themselves so the meta is generally the term used when in competitive online gaming the optimal way of playing the game is discovered the optimal equipment to use the optimal strategy and what happens is everyone starts playing with that strategy and doing that thing and as a result the game becomes less fun so the developers of the game release updates to change the rules slightly to make it more competitive so they change the meta this is exactly what happens with SEO we kind
of figure out what the meta is then over optimize it and then Google's like H the results probably aren't as good as they should be because all these seos are there so they change the rules and I say this because I can provide evidence at Brighton SEO in 2022 I gave this example of multiple sites going from zero to over a million visitors in 16 weeks um on brand new domains just using uh zero volume keywords and basically spamming out AI content and that was because of recent Google updates had left this as like a
big open goal for them we had a whole second Renaissance in Niche blogging I you people just setting up blogs and they found anything ranked really easily um and Google was just kind of like whoops probably shouldn't be doing that and their fix for this was the helpful content update which you can see the algorithm running here this is behind the scenes and it's selecting Reddit there that's Reddit that's Forbes that's quar um being carefully selected as the sites that should rank so what happened was Google essentially started doing the opposite it became very difficult
to rank unless you are these big authorative sites so that is the current meta which is this site reputation abuse currently LinkedIn ranks for 94,000 loans keywords in the US and by LinkedIn I mean these pulse articles which are written by AI by people that don't exist this is Judith and this is all the content she's written about loans in the last 24 hours right and Google's decide this is really helpful I'm going to rank this it's millions and millions of traffic that's like valuable traffic this is LinkedIn you know so this is where the
current meta is so we're going to talk about models and how we add to our own model of how Google works there is this which is a terrifying thing by Dr Mario fiser which he put together this is his model after working in the industry for many years about how he thinks Google works I can see some people grimacing in the audience um you should be it's terrifying and don't worry what I'm going to say to you is you you can use really simple models as well and this will help you decode what Google is
saying so this is an example of a model you can use which is you know there is a ranking stage to Google which is this slow thing that's site Centric and they're scoring sites and web pages and then before you see the results there is a post ranking phase which is query dependent so depends on what people search for um where they might adjust the results based on things like user Interac action why it's helpful to know something like this is you get googlers um such as Gary say we don't use click-through rate directly in
ranking and then lots of seos come out and argue because we've done tests and we found when we pay people to click on this result all the time it shoots to number one and you say you don't use it in ranking now both these things can be true technically it's all down to wording so there is a ranking phase where Google gole does not care how much your site was clicked on or was not clicked on they do um have a predicted click-through rate which I'll talk about later but in post ranking which is they've
decided for this keyword this is how it's going to the site the uh how I'm going to rank the pages they do look at how people interact with the serp and they told us why they do this in the doj trial the antitrust trial they gave the example of if they have a search result for nice pictures and then there is a terrorist attack in France and people are Googling nce pictures and they're clicking on something completely different this defies what Google would expect massively so they rerank the queries and just like every experiment you
see with click-through a manipulation when the manipulation stops the rankings return to what they were originally ranked as so technically we don't use click through a directly in ranking is true our questions are bad and we think of everything before we see the result as ranking so I I always say if if a googler is saying something to you that is opposite to how you believe Google works it's probably some kind of nuance that you don't understand rather than the googler is lying um I haven't ever personally seen a Google intentionally lying but they are
sneaky I will give them that so let's play the game of traffic lights otherwise known as is it a ranking Factor because this is always something we talk about in SEO right and I'm going to run through this example with bounce rate Google analytics bounce rate to be very specific because whenever I post about this I will always get people argue with me about it so there are three rules that I apply to anything before I add it to my kind of mental model of how Google works which is firstly really obvious does it make
sense right bounce rate on your Google analytics is something fully under your control you can make the bounce rate of a page 100% you can make it a zero you can make it 5050 it doesn't make a lot of sense for Google to rank a site on something that you are full control over like that as a metric so I don't think off the bat and I can't even tell you what a good balance rate would be um because if you're Googling some really specific bit of information you load up a page you spend five
minutes reading it you're like that's what I wanted to know and you leave that's 100% bounce because you haven't done anything but you've had a really good experience so to me doesn't make sense doesn't scale is a really important question whatever you're saying Google uses as a ranking um as a ranking Factor it has to scale across the web now initially I was like well no bounce rate doesn't scale um because not all Sites have Google analytics on when I thought about it a bit more deeply they've probably got enough data that they could build
a model to give a good guess on what bounce rate is so I'd give that a maybe someone that knows more than me might be able to explain how they could do that and lastly is there any evidence evidence comes in all shapes and sizes evidence is things googlers tell us they are doing or not doing clearly it comes in paintting now while there might be a painton for something it doesn't mean that's actually in search but it's good supporting evidence uh tools like cyric semrush HR do big data studies where they can show us
correlation again correlation doesn't equal causation but it's supporting evidence there is basically no supporting evidence that I found that's compelling for bounce straight so it's a definite no no to me these three questions ask them for everything we have a discussion I wonder if Google uses this as a ranking Factor so we're on very quickly now to Google exploit facts for your models so this is for maybe experienced seos um these are things that we found uh so our team found basically a Google endpoint Google has these endpoints that talk to each other that send
data to each other and um they do this in a in a format called protuff does anyone know what protobuffers are no protobuffers are basically a super shorthand like code that Google uses uh where they have almost like a translation file where they're like yeah if I say pigeon it actually means this 100w function and it lets them send information across their endpoints really fast because it's like a compressed data source we found a Google endpoint and we very conveniently found that by manipulating some of the network requests Google would just translate it into plain
text for us hooray so we got loads of uh data um we ended up submitting this um a while after we found it um to the Google uh vulnerability reward program they paid us $3,337 because it was a high exploitation risk and it was um highly likely to be abused we gave that money to um bring Futures so they've benefited from that this year um but we ended up getting two terabytes of data we identified over 2,000 properties Google uses to classify queries and sites and we got this data over 90 million queries so what
did we find Google has talked before about how they try and work out if information is reliable um on the web and they've talked about this notion of consent before and what we found out was Google actually counts the number of passages in content that agree with contradict or neutral to the general consensus and it will generate a consensus score that consensus score is likely to impact whether you rank on a specific query or not because we also found interestingly there are all these classifiers for queries such as this one which is is debunking query
so this is basically Google deciding if what the user's asking is they're trying to debunk misinformation an example for this is is the earth flat would be classed as a debunking query and what you'll notice about the results is they are all extremely with the consensus which is might be news to you the Earth is roughly a sphere for different topics where it's more subjective for political questions Google intentionally tries to have some con consensus some neutral some non-consensus which is also interesting because it may be that your content is perfect your site is perfect
but the reason you are not ranking is Google just already has a good site which fulfills that need and you're not going to rank third and fourth because Google wanted something specifically that didn't agree with the consensus there and you did so think of it like making a good recipe like if you're baking a good cake there's more ingredients unfortunately than just like sugar they have all the like loads of these kinds of um classifiers as well there's a news score for how like related to news the query is there is unsurprisingly a medical classifier
trigger which Google have mentioned before when they talk about how they fight disinformation so Google specifically told us about what they call ym yl queries which is your money your life which is when someone does a query that is about something important where if Google gets it wrong it could impact someone's health or finances and they specifically tell us they waight their algorithm differently when they detect this is a ym yl query so things that might not be so important somewhere are more important in these types of queries which is why again there's no generic
what works for one website might work for another we also found um and I don't believe this has ever been published before Google seems to classify almost all queries into one of eight query classes RQ stands of refined query semantic classes which are on the screen I won't read them out what's interesting about this is we looked at the distribution of these over 90 million queries and a huge chunk of them were short fact or bull which stands uh for Bing which means a question that essentially has a yes or no true or false type
answer I find this particularly interesting because if you are making kind of your this is is where you're getting a lot of your search traffic from I think this is what's going to evaporate with AI overviews that Google are pushing out if it can be answered with a yes or no or it can be answered with one paragraph Google's just going to generate an answer rather than send them to your website because they make more money that way and that's on their their uh their wants um we're actually building some classifier models where you can
type in a query and we'll tell you what we know about it whether what category it is if it's ym well Etc we're sending them out on our newsletter just core updates.com we've already sent out some data lastly the really interesting things we found was there appeared to be a click probability um for every organic result which is what I was talking about earlier which is Google uses clickthrough rate to build a prediction model and they've been doing this for years and actually I ow half an apology for K who brought this up to me
once on LinkedIn I was like that's mate um turns out wasn't um so it appears that Google does factor in How likely it thinks someone is going to be to click on your result this would change if we modifi the page title they have a tool that can give you hints about this in the Google ads planner because it'll tell you an estimated click-through rate there um again this is something I'd really like to build a kind of a model for so we can uh optimize this ahead of time so again Google doesn't use clickr
directly in ranking but they have a prediction and you can perform against that prediction the real thing that may give me my kind of shocked pekachu moment was uh Google had what they called a site quality score for every single website on a subdomain level it gave them a score of zero uh to one and we got this data for 800,000 domains um firstly it being on a subdomain level was really interesting because Google's already always said they don't care about subdomains but they do score them um differently and I we did this distribution of
the scores we had and you'll notice that site quality here starts at 0.4 it does actually go lower than this this data was grabbed from when we were looking at a specific Rich type of result in Google Rich results are things like feature Snippets people also ask and what we found is if you have a site quality less than 0.4 you are not eligible to get things like feature Snippets or pasas it doesn't matter what guides you follow on optimizing for these things you won't get them and that's something that became apparent in this algorithm
is there's lots of uh like heat races you need to qualify to get to the next kind of stage in ranking so it doesn't matter what you're doing over here if you're not even in that race because you haven't filled this prerequisite first so what is site quality um this is the short version of this talk basically there is a painton by Google called site quality score which is super helpful um to give you the short version site quality score is calculated based on how many times people specifically search for your website along with other
Search terms how often they select your website even when you're not number one and how often your website name or brand name if you want to call it that appears in Anchor text around the web so it's essentially kind of like a Layman's if you want call it like brand measurement in a way but what about when there's no user data to tell them this they have a predicting site quality called painton which was super helpful to find um and basically they take sites that they have scores for and they build what's called a phrase
model which is basically they take the content on the page and turn it into a load of numbers that apparently means something to smart people and they have like the numerical shape of this website and they can predict how good that site's going to going to be in terms of how it compares to other sites they know which is why we saw so many visibility graphs like this over the months which is this is a famous AI content abusing site called causal that shot up the rankings and then Google kind of worked out what was
going on and it got massively penalized we've seen that happen a lot and I believe this is because AI content broke this prediction model so previously if you were spamming content you'd be using techniques called markof chains or spinning which would be if you read them as a human you could kind of see it didn't feel quite right that's incredibly easy to detect from a computer point of view because of how large language models like chat GPT inherently work with token probability the kind of content they generate because of their training set I believe will
score highly on site quality because it's based on good content right it's based on good English so the issue they had and why I think we had the 2022 issue partly was because all these brand new sites were coming on board and Google was doing this quick evaluation of how good do I think the site quality is yeah it looks good yeah you published 100,000 pages and Google was like yeah why not and obviously this became a big problem so Google released the helpful content update which essentially makes it almost impossible unless you are a
big website known brand um to rank this is also backed up by this is Tom kapper he did a brilliant study for MZ where he found the sites most impacted by The Helpful content update were ones with high uh domain Authority metrics that's pretty much like how many links you have and low brand Authority metrics so if it looks like you've been doing lots of SEO lots of SEO success but I've never heard of you that's kind of fishy and there was a really obvious correlation to those sites getting penalized um we've even got historic
comments from like Eric Schmidt the ex CEO of Google saying brands are the solution not the problem brands are how you sort out the Cesspool so we've kind of hit our three things here it makes sense it scales and there's all kind of evidence there's paintting there's real world data there's uh there's large data studies there's Eric Schmidt quotes um and we've found this with clients where classic SEO metrics are less reliable so this is one of our clients uh rehabs um it's ranking top for a ym yl type query around addiction it's outranking uh
ukat which has been around way longer than them it's got like 15 times as many links it's outranking NHS again on all those other metrics from a classical SEO point of view they should be losing but they're not so finally conceptual models help you understand why things are ranking the why is sometimes more important than the how although the how is fun uh please be cautious when people are telling you things are or are not ranking factors and certainly if it's cares don't just be like no it's mate because he knows what he's doing um
and lastly uh definitely play more video video games cuz they help uh that's it thanks
