Mike King: Cindy is definitely one of my, like, absolute favorite people in this industry. I said absolute. Come on. And, you know, Cindy Crum, she’s amazing. She’s been ahead of everyone for a really long time. I still fundamentally believe she’s the smartest person in our industry.

And so Cindy Crum is the founder and CEO of Mobile Moxie. The first time she interviewed for a job in mobile marketing, it was to design plastic wraps for horse trailers. I need to hear that story. She is currently working on a travel book, which is mostly full of stories about travel for SEO events. I hope this one makes it in the book.

The work entitled is The Traveling Circus, mostly true stories from life on the road. Presenting Word to Your MUM, please welcome Cindy Krum.

Cindy Krum: Alright. Thank you for the amazing introduction, Mike, and good morning to all of you lovely people. Thank you guys for showing up the morning after Busta Rhymes. I know it was a lot of effort, but it was amazing. This conference has been absolutely amazing.

I’m just so excited to be here talking to you today. Even if I did get what might be, like, the roughest spot. Like, how do I follow Busta Rhymes on the agenda? Like, it’s a lot of pressure. So I just keep telling myself that, like, Busta opened for me. And that makes it a little bit better. Now, Mike gave me a great introduction. I’m gonna tell you a little bit more in case you don’t know who I am.

Cindy Krum, obviously. I wrote a book about mobile marketing back in 2010, but I’ve been doing mobile SEO since before the iPhone existed. Because I got a phone and I noticed that the search results were so bad, and I didn’t know anyone at Google, but I knew about how to do SEO. So I was like, well, maybe I just teach people how to do SEO. But for mobile, and no one else was doing it, and people actually made fun of me, because they were like, no one’s going to SEO for mobile.

But I figured they probably would eventually. So I started talking about it, and that history has gotten me into some of the biggest companies and brands around the world because big companies and brands knew the power of mobile too before a lot of people realized it. So I’ve had the pleasure of working with huge international brands, but the problem with some of those huge international brands and huge international companies is that, like, they move slow.

They need to plan things way in advance and so I had to do SEO knowing that my recommendations might not even get implemented for like a year plus down the road. They would sit on the dev queue potentially for months and months and months. So I had to anticipate what Google was gonna do in that next year as I was giving my recommendations.

And that’s kind of how I ended up becoming this person who is pretty good at predicting and understanding what Google is doing and why and where they’re going and how we can prepare for that. That’s kind of like what what starting with mobile and being here today where everyone is doing mobile and everyone cares about mobile. That’s kind of how I got here because I’ve had a lot of really accurate predictions as it turns out. Maybe that’s just luck, but things like understanding the importance of entities, highlighting fraggles, what Google calls passages, where they have a fragment of text and a handle that jump links you to that bit of text on the page. These are all things that I saw and talked about before the SEO community as a whole had really latched on and before Google was really talking about it out loud and in public.

So that’s a long intro, but the reason I gave you that intro is to say that I’m gonna tell you today about what I think is the next big thing that’s gonna impact how we all do SEO. And this is something called MUM. So of course, the title of the talk is Word to your MUM, unraveling blah blah blah. It’s about MUM. The powerhouse of Google’s new algorithms and where they’re going in the future. And people love MUM. Like, they’re getting it tattooed on their bodies already. Right? It’s really really popular, it’s amazing. Actually this last tattoo, if you look at it, is an insult. It’s not actually just MUM, it’s your mum. Right?

So, yeah. Now, before I get too deep into things, I wanna give you some trigger warnings. We’re gonna talk about some things that trigger people. That includes entities, which I know you guys haven’t heard that much about at this conference, but for years and years we heard a lot about entities. I’m gonna talk about mobile SEO a little bit. I’m gonna talk about voice search, which does trigger some people. And then, I’ll talk about, you know, this thing that got overhyped back in 2017, 2018, called micro moments that you guys have probably all forgotten about but it’s still interesting and I think it’s important to the conversation today.

And then finally, I’m gonna talk about a rapper who is very famous but not quite as good as Busta Rhymes or Mike King, right? But he was kind of important and he did have some things to say about MUMs, specifically your mum, and that’s Vanilla Ice. He was the one that brought to the lexicon the phrase “word to your mother.” At least he’s the one that’s given credit to, and it was in the song, Ice Ice Baby’, where he said, ‘word to your mother’, which, you know, has stuck in all of our consciousness now.

And so, a lot has been changing with Google recently. And fortunately, or unfortunately, we have to deal with it. Right? We’ve had some good news this week, we’ve had some bad news this week. But Google is changing, our jobs are changing and we need to rise to the occasion.

So, in that, I want to give you a preview of what we’re going to learn today. We’re going to talk about Google’s main limitations with all the stuff that’s happening in AI, and the cost and and it’s really the cost and the processing power. What we know is that generating an AI result is very expensive. It’s more than a hundred times more expensive than a regular search query in Google. So Google is taking on this cost, but to cover cost, Google is going to have to find ways to increase their revenue.

They’re going to have to decrease cost at the same time. They’ve got to figure out how they’re going to cover this cost and make it plausible as a business model, when it’s already so expensive.

So they’ll also they understand the value of not just money, but they understand the value of data. And Google’s been collecting data about us for a really, really long time using Chrome. I did a really big talk about this and how Chrome is really spying on us quite a lot more than we all think. And so they’re learning about us already. And we think that they’re gonna use that information with MUM, to make themselves more profitable.

And MUM is kind of what gets you there. Now, I’ll talk also about how MUM is core, to Google’s just planned success. Like, it’s part of their future for sure. Because MUM is about context, and it it allows you to combine things that are not even text, like images and videos and stuff like that, to text data in kind of an LLM model. But it’s not actually even language per se, it’s videos and images, right? But it’s putting those along with the text to understand those together with the context. And so we’ll find out about how MUM, Filters and Journeys help limit the processing needs that Google has to use to get to an AI response. 

And how this helps this is gonna help Google personalize search results even more. Because they’ll have personalized journey modeling that saves them money and makes users more likely to convert, to click on ads. And they’re already talking about this. They talk about everyone’s, like, you’re getting less traffic but better customers. They believe that to their core and they also believe it not just about organic but about their ads. Right? They want people to convert, because they want their advertisers to be happy. And then last, we’ll talk about, you know, how MUM journey modeling may be part of this new future with AI Overviews and AI Mode and some other things.

And so, if you’ve seen me talk before, you might think that, like, you might understand, I like to delve deep into problems. And so this is one of my favorite quotes by Albert Einstein. He said, if I had an hour to solve a problem, I’d spend fifty five minutes thinking about the problem and five minutes thinking about the solution. We’re going to do that today.

We’re going to dig deep into the problem. We are going to get to some solutions and some of them are going to make themselves obvious as we go. But I really want you to understand the problem because this is how I come up with these ideas and things. I’m not actually reading all the documentation. Usually, I come up with the idea, I tell my smart friends who read the documentation, they’re like, yeah, there’s a patent on that. Oh, great. Good. Good. 

Okay. So, what we know about what Google is wanting to do, what they’ve said publicly since about 2018, right after mobile first indexing launched, was they said that they wanted to make search more conversational, more predictive and more personalized. Right? That’s what their goal was right after they launched mobile first indexing. They said that’s where we’re going. And remember, mobile first indexing was a massive change. It started out feeling small, but it turned out that Google had changed from understanding the world in terms of URLs to understanding the world in terms of entities. And that was fundamental. It’s gotten us where we are today.

And so, I think this is the next iteration, but they’re very close to this predictive, personalized, and conversational already right now. So the problem is that even before AI Overviews launched, this transition was causing traffic to go down even when rankings were going up, even when relevant rankings were going up. We, as SEOs, were doing our job getting those rankings up, ranking for more and better keywords. Traffic was still going down because Google was starting to crowd the top of the search result with more and more knowledge graph, more and more understanding, answers, featured snippets, whatever, and with people also ask.

So that’s a concern. But now that AI Overviews have launched, we have so many people, and I know you’ve heard, you know, they’ve banged, killed this horse to death a million times this week, but click through is going down. Now this is a study from Will at SEER. Did he go through this? I missed his talk. Okay. No? Okay. So what it says, the box the the green row is organic click through when an AI Overviews is shown.

And this is time going from the bottom of the chart to the top. So it starts in January 2024 and it goes to January 2025. What you notice here is that click through rate, when there’s an AI Overview, has gone down almost consistently every single month since 2024, since January 2024. So click through rate is going down, especially when AI Overviews are there.

Now just look at the the pink column to the left of it and see that when there is not an AI Overview in the organic, the click through rate is much higher. Right? We know this, but probably not a lot of people have talked about paid stuff. And what you need to understand here is that click through rate, when AI Overviews are there for paid, is also going down.

Does Google care about that? Yeah. That’s how they make money. So why are they pushing this so hard? Like, what is the deal? Why would they keep showing AI Overviews when click through rate, even on their paid stuff where they make the money, is going down? And beyond that, why would they not just roll it out in the US and maybe roll it back or quietly let it walk away? No. They’ve rolled it out internationally. Just a couple of months ago, it started rolling out everywhere internationally and growing and building and whatever.

So we have to make this make sense. Now, from an SEO perspective, realize that it’s not just the AI Overviews themselves that matter, it’s what’s at the top. And we know this study from Accuranker shows us that it doesn’t really matter so much what is at the top. It’s if you’re not it’s it’s more about pixel height and where your stuff shows up in pixel height rather than ranking per se.

And rankings have been alive for years because they’ve started throwing things in that they just conveniently don’t count as a ranking, even though it’s pushing the pixel height of your number one ranking way, way down. So start thinking more about pixel height and where you rank, and when there’s an AI Overview or when there’s not. But the other thing we know is that the rankings have been pretty good and accurate for a while, at least up until we added AI Overviews. And then they started getting wild and crazy.

And so this is a comparison of a bunch of AI tools, that generated AI tools and includes Gemini. Gemini is a little bit different from AI Overviews, but they’re obviously very much related in both from Google. And so this is a study from the Columbia Journal, Journalism Review. And it’s about factuality that they get from the AI tools. Right? And what this says, the dark red is, confidently wrong, the dark green is absolutely right, the lighter colors are somewhere in the middle. Right? Now look all the way over at the right to Gemini. It has the highest number of confidently wrongs and the lowest number of completely corrects of any of the options.

Same study, this shows in the first graph on the left, when it’s when the wrong article is identified, So it either gets you to an article that’s kind of not the point or it gets you to an article that’s not actually there, it’s four zero four. Look at Gemini, it’s the second one down, the yellow is four zero fours. Gemini has the highest number of four zero four links. Why? That’s silly. They have a search engine. They don’t like four zero fours. But they’re linking to a lot of four zero fours, and they’re sometimes linking to the wrong articles.

When they link to the correct article, second one down, it’s also very low. The correct article, they have a very small proportion, and the correct article means are they linking to the original source or are they linking to something that’s maybe syndicated, plagiarized, or just kind of not the right version of the article. And then the last the last graph over here shows when an article is not identified. And oh, surprise surprise, Gemini is the one that’s the least likely to give a citation at all.

Just doesn’t highlight articles. Whatever. It already knew that anyway. Why does it have to show its work? So thinking about that, Google is making their results worse and less accurate, and they’re making less money on it. Why? So we have to go back to the money.

Know that this left side of this graph is how Google makes money. All the different ways they make money. YouTube, Google Search, ad revenue, Google Play, Google Cloud, all those things that make them money. And then on the right are things that cost them money. So cost of revenue, cost to acquire a customer, stuff like that. That’s where the money goes away.

So we know that Google is gonna try and minimize or maximize ad opportunities and revenue, but they’ve got to decrease processing and overhead power and requirements. But right now, the cost of generating AI Overviews is going up, so the revenue from ads just needs to go up. In comes mum.

This is how Oh, I should tell you what it stands for. So it stands for Multitask Unified Model, but everyone gets this wrong and remembers it as, Multimodal, Unified Model because it’s it’s a lot about multimodal stuff, or multimedia stuff as well. So, this is their announcement and they announced it. This came out in 2021, and they call it a new, a new milestone in AI understanding. It was a thousand times stronger than BERT, which you’ve probably heard of that language model. But look at the image that they give for this and look at all the different things they’ve included. They’ve included videos. They’ve included articles. They’ve included, like, fact sheets, maps, and all these different kinds of stuff.

And this is what it really is. It’s bringing these things together. So to give this example about Mount Fuji, think about Mount Fuji as an entity and there are things that you might wanna do with this entity. So Google starts giving us these journeys that are associated with entities, right? And they say, you know, they think about it, you could climb Mount Fuji, you could paint Mount Fuji, but this journal is about climbing Mount Fuji. So what do you need if you’re going to climb Mount Fuji? You might need an airplane ticket, you might need a hotel, you might need a backpack. Google wants to model that journey so that they don’t have to process so hard every time when they’re coming up with an AI overview that suits your needs.

If they can identify what journey you’re on, they have the basic model to answer the questions that you’re probably gonna have on that journey. Are you guys with me? Is it too early?

Okay. Yeah. Okay. So, this is what gets this is where we come to in kind of our life span of an SEO. We started our well, let’s say, the evolution of data modeling for search started with keywords and URLs, and then it went to entities, and the next stage is the MUM journeys that modify those entities. That’s how Google is thinking and that is how we should be thinking. Right? We optimize for keywords, then we optimize for entities, and now we have to optimize for MUM journeys.

So we’ll look at some search results and realize, I know this is not an AI Overview. This is just an old school knowledge graph that used to show up, but doesn’t show up as much anymore because it’s replaced with AI Overviews. But what we can see here is that Google has been using AI for a long time. Ruth said this on stage the other day. They used AI to get all the information in the knowledge graph. There was not a human sitting there writing down what day was Vanilla Ice born. Right? They they had the corpus of information, they pulled it in, and they organized it in their brain, and that gets us knowledge graph.

And that’s the beginning of their framework of understanding for the entity, but it’s also then the beginning of the framework of understanding for the potential journeys. And so you look at the navigation, most searches just have the top nav. But this one is such a known entity that Google gives us a sub nav. And it says, do you want the overview of who Vanilla Ace is? Do you want his songs? Do you want his movies, events, albums? Do you want to listen to him? Because these are the things that most people want. They’ve already mapped this part. Right?

So we know from the filters what they know, what they’re really confident in. And then we even know, like, what what else they can surface as a factoid that’s so popular they just give it to you by default. So the the other thing to know is that they’re adapting these kinds of knowledge graphs, not just AI Overviews, but knowledge graph results based on the query. So that one was just for Vanilla Ice, this one is for kind of a nonsensical backwards query that says Vanilla Ice, where is he from? Answer, South Dallas, Texas. And then they also give you other facts. This is his birthday, this is how old he is, this is his dad’s name, who is also, I guess, a little bit famous. And they give you a little bit of a featured snippet down there, or a Wikipedia featured lift.

So the thing is, when you drill down, especially in some kinds of queries, you get so many filters that you can really start to understand what Google knows about a topic. So when we put in the query “Vanilla Ice book” – did you know he had a book? He does. So, Vanilla Ice book, we get this huge carousel of Googles like, That’s kind of a weird question, not many people search for that, but okay, we got you. Here’s our understanding of Vanilla Ice book. And they have under 20 bucks, price, online use, biography, cookbook, store, boy, nonfiction, images, whatever, for sale. And they show you some popular products that are kind of Vanilla Ice books. Cool. But then we click on something random. We want a vanillaized coloring book. Does that exist? Yes, it does. So, they filter the result. And so this is the journey, right? They’re modeling the journey based on my clicks of filters down into their funnel, and they’re mapping that to save because other people might follow that journey too. And so that gets us to a vanilla ice coloring book for adults.

So, the interesting thing is none of that was with AI Overviews, that was all knowledge graphs and filters that have existed for a while. But now we get into AI Overviews, and what you need to understand is they’re not just showing up at the top, they’re showing up now, sometimes mixed in with the results, and even in People Also Ask. So that Google can continue to try and mine and understand and predict what is your next question, what is the next answer we need to surface for you, so they can modify the stuff at the top based on the engagement and clicks on those things in the search results.

They’re trying to learn about this. And this is like, you know, is Vanilla Ice married? No. Not currently? Blah blah blah. Because lots of people might ask that, but it’s not big enough yet to show up in the top. But I think this is an entryway, like getting a people also ask and an AI Overview or even just a link in a people also ask. I believe this is how Google’s testing is this a relevant enough topic to add to the model long term.

So okay, we know now about MUM journeys and filters. The filters map the journey, and that gets you close to a conversation. Because if you think about a conversation, when I’m talking to you about something, you’re already listening, but also thinking about what you want to say, and what question you want to ask, and whatever. You’re also trying to understand the next topic and where the conversation is going, just like Google is doing.

So, we can look and see, like, Google is changing the results based on what you’re clicking on the filter. They’re mapping that out, and they’re adapting it. So sometimes they don’t even do a refresh, they’ve loaded all of it and they show, and they modify but they modify the query sneakily, and sometimes they show you new ads. So if you were searching for Vanilla Ice and then you click on the song Ice Ice Baby, it doesn’t like it adds ice. See how many times the word ice is in that query? Three times. Ice, ice, ice, baby. Vanilla ice, ice, ice, baby. It’s kind of funny, you can really screw with it sometimes.

Anyway, so that’s lots of fun. But, what you might not realize is Google is saving all of this information when you’re logged in to your history. So you used to just have a chronological list of history, but now there’s another tab hidden in there. It used to be called ‘Journeys’. And if you did a Vanilla Ice query today, on your phone, and tomorrow on your computer, and blah blah blah, it was collecting your behavior across all of your devices, and then clustering it by topic, going, oh, you started looking for Vanilla Ice, and then you ended up with a Vanilla Ice coloring book. Yay you. Now, they have, conveniently renamed that, but notice notice that they’re mapping not just the queries, but where did you end up?

Do we think that might be a signal? If you engaged on that last place, do you think that’s probably good For rankings? Probably. Engagements good, Google likes it. So, if you look for this now, it’s called by group. It’s not as fun, because it distances itself from the description of MUM, but just know that it used to be called Journeys.

So, they also, oddly enough, this I couldn’t get a Vanilla Ice example, but, I got this example. They’re adding people also asked, like, topics in your Journeys tab. So I searched for, like, Kanye West and Kim Kardashian, and randomly in the journey’s history, it’s like, hey, do you want to start this up again? And are these topics related to that? Pete Davidson, Bianca Censori, Kylie Jenner, are they related to that? They’re trying to map even from Journeys, so they could be like, hey, take the next step in this journey. Is this the right step? Is this the wrong step?

So, this is what it looks like when you map it out. You’ve got Vanilla Ice, the entity, and there might be more sub entities, but the map is about behavior. What are you trying to accomplish? And so you can see Vanilla Ice songs, Ice Ice Baby, and you can get to the lyrics, that’s one path. Same entity, you can get books, cookbooks, Walmart, on sale. Or, you can get vanilla ice books, cookbooks, ice cream. But wait, that’s wrong! They’ve included something wrong in the map, because definitely ice cream showed up all over the Vanilla Ice queries. So, they’re going to use engagement to eventually figure out that vanilla ice cream is different from Vanilla Ice.

So, filters and Journeys, conversations, all are coming into AI Overviews. We know that when AI SGE first launched, it had a speech icon. It was meant to be vocal, conversational, interactive. And so notice that when we do queries and we now get the AI Overviews, we do book Vanilla Ice. This is a bit of an ambiguous query because we’ve been talking about his coloring book, but what if I want to book him for a show?

That’s how it understood that one. But it understands that that’s kind of an ambiguous query. So it hedges its bets and puts Vanilla Ice book information in the AI Overview too. It’s taking the possible journeys and saying, we think you’re on this journey, but there’s another journey you might be on. And it’s gonna evaluate what’s right and what’s wrong based on where the engagement happens, and if anyone’s clicking on the book. Right?

So it’s hedging. And this is how that fan out comes out. We’ve heard a couple people talk about the fan out model. And and Google came came out, like, publicly about it, the AI Mode, Gemini 2.0, uses a fan out technique, that issues multiple related searches concurrently across subtopics and multiple data sources and then brings those together to provide a response. That definitely sounds to me, with the multiple data sources, brings them together, that sounds like MUM. That sounds exactly like how they described MUM.

So, we get this, we have the map, it’s just like a fan, right? So just think about it that way. Okay. So what? Why do we care? Well, when Google uses MUM, the MUM journeys decrease the processing power of the cost of the AI result. Which means that, MUM journeys can increase the number of SERPs that are served and ads that are clicked by linking people to more search results, which is pretty shady.

But happens a lot in AI Overviews. But also knowing that people are gonna get closer to the thing that they want to click on and are gonna be more likely to click on an ad because it’s more and more targeted to the actual journey the person is on. 

So that’s good. The numbers here are fixed. Right? They’re now down and up, instead of both up. So MUM journeys funnel searchers into, the way this happens that we’re going to go into is MUM journeys funnel searchers into Google’s four possible monetized channels that they talked about in 2017 called micro moments. They talked about it in terms of mobile because at the time they just launched mobile first indexing and they were like, oh we want people want to engage in micro moments on their phones. We need to understand these micro moments. But I think micro moments are actually important across the board on desktop and mobile.

And that was just a convenient way for them to say, we’re trying to model and understand specific user behavior and journeys, through these monetizable channels. And so, the micro moments, if you have forgotten, which I know we haven’t talked about them in a while, since 2017, but they were like covered to death in 2017. They were: I want to know, I want to go, I want to do, I want to buy. Does anyone remember this or is it just me? Some of you guys. Okay, good, the smart ones. Sorry to just know that everyone, everyone. Everyone, everyone, we love everyone.

Okay, so I wanna know is monetized with regular PPC ads? Google’s got this figured out, it’s what they’ve been doing for years. Right? So if you search for something that’s just an informational query, they’ve monetized it with regular regular PPC and of course they’re monetizing it by linking to other search results with other PPC ads. So they get to show more ads, more potential click, and they get to inflate the number of search queries that they can show in their ads dashboard for that particular keyword. And remember, they’re modifying the keywords so they get diversity in there too. And they get the data of tracking it when people click on those ads. Lots to monetize there.

I want to go is with Maps and Auto. Remember, Google has added lots of ads to Google Maps. Google gets lots of detailed information about businesses, and monetizes that. Google has also added Merchant Center to Google Maps. And they’re tracking you if you have Google Auto or Android Auto. They’re tracking where you go on a day to day basis, and they can relate something that you put into your car GPS or your Android Auto to a search that you did on your desktop pretty easily. Right? So, that’s a bunch of data. They’ll take the money, they’ll take the data, they prefer the money, but they’ll take the data as a second place.

Okay. I want to do is this one’s hard to think about, but it’s engaging with media, when you say you want to do. So, it’s YouTube, YouTube Music, remember all these things, music and podcasts all got rolled into YouTube. Why? Because YouTube monetizes like crazy. They’ve got pre rolls, they’re monetizing it by subscriptions, if you want to subscribe to YouTube TV. They’re trying all these different and they’ve got ads on the page, like, and they get loads of data of what you’re interested in, what ads you click on there, what video ads you like, what videos you care about. Lots of data there. And then last of course, the probably most monetized or the most obvious is how much the e-commerce queries have changed. So I want to buy.

This is Merchant Center, flights, hotels, things that Google has been monetizing for years but has gone hardcore with Merchant Center. These days, if you are an e-commerce brand and you are not in Merchant Center, you are going to struggle to benefit from Google at all. So, what it means when I say that Google is using MUM Journeys to monetize queries is when they figure out which journey you’re on, they’re trying to put it into one of these buckets. Or they’re trying to prioritize these buckets and say, this is most likely a Merchant Center kind of query, and we can monetize that way, but it might also get some good traction with videos, let’s show those lower down.

So they’re using this as a way to be like, how are we going to make some money back for the cost of that AI Overview? And it’s going to work. And they’re going to get the clicks and the ads back, at least for paid. So, that’s not it. I think that there’s more going on here that’s interesting to talk about.

I think that there’s like a suspicious accident, potentially, or not accident of timing in the way things are happening right now. Where Google started rolling out AI Overviews internationally a couple months ago. Then, I think basically within the same week, they announced that they’re gonna try to, they’re gonna consolidate all the Google ccTLDs. Where if you were in Canada, you might search from Google CA and if you were in the UK, Google[.]co[.] uk.

They’re gonna try and consolidate those. Now, they have done that once before. The last time they tried it was just after mobile first indexing launched because they were trying to get this entity understanding and unified language agnostic search. It didn’t work the first time they tried it. So they’re trying it again.

But, they also announced that Google Discover is coming to desktop. That’s a lot of big changes all at once that feel very consolidated. Right? And the month before, we had the launch of AI, well, we had a couple of months before AI organized search results and then AI Mode. So, this is a hypothetical, but it’s all interesting coincidences, so go with me on this. What if they’re getting ready to slam all these things together and put Google Discover as the new AI Mode whatever, in a consolidated way? They’re trying to support fewer things and get you into this holistic, really smart thing that’s very, very personalized for you. I think that’s what they want to do.

I’m not sure they’re going to be able to do it, but I think it’s what they’re trying to do. Because remember, all of these cool things that we’re getting launch almost always for logged in users first or only. Why? Why? Because they want to know about you. They want to be able to market to you. They want to map your journeys. And so, all, like, discover has always been logged in, you couldn’t even get it off your, you know, if you weren’t on a phone, it was hard to get on iOS.

They want all the data about you, right? This seems like what Google would want to do, so that they can make their money back. They’re making some big plays, big moves. I think you should watch out for this, or at least consider the idea that it might happen. And also consider this patent that someone smarter than me sent, that Google has published, about using answers from a user’s search history. Right? This exists, they’ve already talked about it, they’ve made patents to plan for it. It’s probably what they’re doing, I think.

But that’s going to get us to a place where we might have to deal with, eventually, hyper personalized search results that are nearly impossible to track in a non-personalized way. In a, you know, I rank in position five for this keyword way. There are already a lot of things impacting where and when you can rank. And like people saying, well I rank for this query, you know, I rank number three on this query.

Well, I have so many questions. On what device? Where? Like, what time? Like, what language is your default setting? All of these things. Where are you standing when you do that search? All of those things can change. How high you are on the page, who your competition is on the page, and, what’s actually ranking there.

But the the tools we use generalize and aggregate that. But I think it’s gonna be more and more important to learn and pay attention to the differences, the things that change that search result, and it because it might get so personalized that the tools mean even less. Right right now, you can’t bank on a ranking number out of any of the SEO tools. It might be different for you, just based on where you’re standing or what device you’re using. And I think that’s going to get to be a bigger and bigger problem. We’re going to have to use different things to inform our decisions.

So, let me pull this all together for you. Here is what you can do with this information. We’ve done our hypothetical and theoretical 55 minutes of understanding the problem. Let’s let’s crystalize the solution.

We need to start optimizing multimodal sites, multimedia sites, multitask journeys. We need to think about not just what’s on our site, but what’s on the internet related to our entities and the journeys that we want people on related to those entities. We need to start mapping the entities that we care about and the potential journeys associated with them, and kind of put a line in the sand and say, do we care about this part of the journey or no? Are we going to optimize for this journey or that journey? Then, we need to see how Google is classifying those journeys in terms of micro moments. Is it ‘I want to know, I want to go, I want to do, I want to buy?’ Is it a little bit of both? Is it a little bit of all?

Which is the most important one? We need to anticipate how Google is going to monetize those queries and those journeys and be there. So you don’t just stay in Google. If Google If you think Google is going to do a Merchant Center thing, you absolutely have to be in Merchant Center if people are going to be shopping. If you think Google is going to send more people to YouTube, then you need to be there with organic content. I’m not saying you have to pay to be there, though it might not hurt, you probably should.

But be there in an organic way. So align your content with the journeys that Google knows and has mapped, and then if Google is missing journeys, build those out and be the authority on the new part of the map that Google needs to learn. Right? And and make that your best, highest quality content. Spend a lot of time there. And then build out your multimodal, multimedia content, video, images, maps, fact sheets, audio, anything that you can associate with the entity that isn’t just text, but is uniquely yours and shows your value and the reason Google needs to get your stuff on that journey.

And then follow, how and where Google monetizes that and just watch it like a hawk to know, is Google making money? How is Google making money? Where is Google making money at the different parts of a journey? And be there as much as you can.

And that’s the way forward. So, now we know all about the problem. We have some ideas about the problem. And you know what Mr. Vanilla Ice says about having a problem? He says, if you have a problem, if you have a problem, check out the hook while my DJ revolves it. Ice ice baby.

We’re a tear mother.