Digital Profits Podcast – Episode 14: Impacts of Generative AI on Search Engines & SEM

We’ve been talking about how search engine optimization is a key part of success, but have you thought about the role Artificial Intelligence (AI) plays in powering the future of search engines? 

AI isn’t just pie-in-the-sky thinking – it’s here and now! From personalized results to advanced algorithms, AI is already being used by major players like Google, Bing, and Yahoo to deliver accurate results every day. We’ll explore how today’s search engine giants are using AI to shape tomorrow’s web searches – so come along for the ride as we uncover every detail from data collection methods to predictive analytics!

Introducing AI and its role in shaping search engine algorithms 

Are you tired of searching the web and getting irrelevant results? Well, buckle up, because Artificial Intelligence (AI) is here to change the game. AI is revolutionizing the way search engines operate by allowing them to understand the context and intent behind a search query. By analyzing user behavior and preferences, AI can tailor search results to fit the user’s needs and interests. 

As a result, we get faster, more accurate and personalized results. In this era of information overload, AI is a breath of fresh air, helping us find the information we need, when we need it. So, don’t get left behind, embrace the power of AI and enjoy the benefits of a smarter search engine algorithm.

How are AI-driven algorithms improving the user experience and enhancing search results accuracy 

Imagine being able to search for whatever you need online and finding exactly what you were looking for within seconds. Thanks to AI-driven algorithms, this is now a reality. These complex programs help to enhance the accuracy of search results, making it easier than ever to find what you’re looking for. Not only that, but AI-driven algorithms are continuously improving the user experience. 

From personalizing recommendations to streamlining online shopping, these algorithms are making our online lives more convenient and efficient. So the next time you search for something online, take a moment to thank the intelligent algorithms working behind the scenes to make your experience more enjoyable than ever before.

Benefits of AI for marketers, including better targeting capabilities and real-time insights 

Picture this: You’re a marketer sitting at your desk, trying to figure out the best way to reach your target audience. With the help of AI, you’re able to effortlessly tailor your messaging to specific groups, ensuring that your advertising efforts are hitting the mark every time. And that’s not all. AI also provides you with real-time insights into how your campaigns are performing, allowing you to adjust your strategy on the fly and get even better results. 

With these benefits, it’s easy to see why AI is quickly becoming a must-have tool for marketers looking to stay ahead of the competition. So, why not join the AI revolution and see what it can do for your business?

Ways to integrate AI in your search strategy, such as leveraging voice search 

Ready to take your search strategy to the next level? Look no further than integrating AI, specifically voice search. By leveraging this technology, you’ll be able to connect with your audience in more ways than ever before. Not only is voice search more convenient for users, but it also allows for more conversational and natural language. 

With AI powering your search strategy, you’ll be able to gain deeper insights into user behavior and tailor your approach accordingly. So, why wait? Embrace the power of AI and let your search strategy soar to new heights.

The importance of taking a customer-centric approach when using AI in search engines 

Have you ever experienced the frustration of endlessly scrolling through irrelevant search results? As technology evolves, search engines are increasingly integrating AI to provide more accurate and personalized results. But implementing AI is not enough. To truly enhance the user experience, taking a customer-centric approach is key. 

By putting the customer at the center of AI development, we ensure that search engines are tailored to specific needs and preferences. This not only improves the accuracy of search results but also builds trust with the customer, keeping them coming back for more. Let’s embrace a customer-centric approach to AI in search engines and transform the way we search online.

Best practices for using AI-powered tools and how to incorporate them into your existing strategy

Artificial intelligence (AI) is transforming the way businesses operate, and it’s becoming more and more crucial to incorporate these innovations into your existing strategy. In order to achieve optimal results, it’s important to follow best practices for using AI-powered tools. 

First, you should define your problem and identify the data you need to collect. Then, you can select the appropriate AI tool that best suits your needs. Once you have chosen the tool, it’s essential to train it with your specific data to produce accurate results. 

Finally, continuously monitor and adjust your AI to obtain the best possible outcome. With these best practices, you can effectively leverage AI technology to propel your business forward and gain a competitive edge. Start incorporating these tips into your strategy now and achieve success faster than ever before!

AI’s role in revolutionizing search engine algorithms is already taking effect, and forward-thinking marketers should continue to invest in the latest AI-driven tools to keep up with the ever-evolving changes. 

As more search engines adopt AI-powered technologies, it is essential to stay ahead of the curve by regularly monitoring trends and understanding how customers behave. Doing so provides a key competitive advantage in the digital landscape and enables you to shape your strategy around customer needs while leveraging smarter approaches powered by AI for marketing success. 

Incorporating these AI techniques into account management processes and optimizing user experiences will help marketers build a better understanding of their target audiences, allowing them to craft targeted campaigns that get maximum reach and engagement. By properly utilizing AI in search engine algorithms, marketers are sure to bring valuable insight and ROI quickly—and stay ahead of the competition.

Ready to revolutionize your business growth? Join the Profit Squad in EP 14: Impacts of Generative AI on Search Engines & SEM of the Digital Profits Podcast. Don’t miss out on the insights that will shape the future of search engine results pages. Anticipate user needs, refine data analysis, and gain the edge in digital marketing. Tune in now! 

Welcome to the Digital Profits podcast, where you’ll learn how to grow your business faster using paid traffic and SEO. Each episode will feature a breakdown of digital marketing trends and answers to your burning questions that will provide actionable takeaways to make your marketing better. So join us Ben Page, Ray Sawvell and Blake John, as we guide you on your journey to higher profits. Remember to join the Profit and get ready to profit. In three, two, one. Welcome to a special episode of The Show. Today we’re going to have the Random Show, and I’m joined by Ray. Hello. And Blake.

Blake John: Hey, team.

Ben Page: So we’re back together and here to just kind of share some of the fun insights, things we’re excited about, things we’ve been learning lately, in hopes that it gives you some ideas for actions, things to try, things to pursue. So thought it’d be cool to start with more advancements in AI. The more that I experiment, the more that I learn about different platforms. It’s a cool time, everyone. Where should we begin?

Blake John: Guys, I think we should talk about the changes in the makeup of search engine result pages and how things have just really progressed over the last really, it’s only been, what, six months?

Ben Page: But it’s like accelerating back in my yeah, right, right. Yeah. It’s so different. I mean, Blake, you had this point before we started recording that doing a year over year comparison isn’t really fair anymore or it’s just so different right, because of how that landscape is changing.

Blake John: Yeah, absolutely. I think it’s something that’s always in the back of my head whenever I’m doing data analysis. It’s so hard to win an organic click these days with all of the different SERP features. And there’s more and more ads than ever before, which should be a surprise to no one, but we always take into account seasonality. It’s so important to take into account seasonality when you’re doing data comparisons. You don’t want to compare June to December if you’re a swimming pool, I don’t know, supplier of some kind. Right. That’s not going to be fair comparison. But it’s interesting because we’re sort of in like a new era of search, and last year around this time, maybe things were sort of becoming more available, but nothing like we’re seeing now. 
Right. And so things have just changed so drastically, really. I would say probably within the last five to six months that those year over year comparisons, it’s the best we have. I’m not saying don’t do year over year comparisons, but it’s something that I think should be there’s like an asterisk by it all the time. Like, hey, this has changed a lot. The SERP is not anything like it used to be this time last year. So it’s just something to keep in mind and always know in your analysis. Always just keep it on the side.

Ben Page: Yeah. And like, context for our listeners. Microsoft has, of course, the new Bing. They’ve got the Chat know and kind of widget built into their Bing search experience. The Bing search engine. On the Google side, we now have SGE search generative experiences. Depending on your settings within Labs, you can either have SGE for search or SGE while browsing, or both. Really cool. So this is level up. We’ve kind of got rumors circulating very recently, end of August, early September, that Google’s Gemini is forthcoming. It may be released sometime this fall, which is alleged to be trained on twice as many tokens as GPC Four. That could be yet another leap in capability. And sophistication but even what we’re seeing now with these SGE Labs options, it’s like a level up from kind of what Bard was when it first dropped. So these are some of the technologies that are starting to become embedded within that search experience. And maybe let’s describe how these function, what they look like in search, just kind of paint the picture for listeners if they don’t have these plugins, I guess enabled, how is it actually impacting search?

Blake John: Yeah, so I actually have some complaints about generative AI in search because just as the SEO guy, Google’s always preaching like core web vitals and cumulative layout shift is a CLS, is a core web vital. And the way that it works is you Google something and then sort of at the top of the search result page, there’s this generative. And sometimes when you Google, it’ll just start spinning. It’ll start thinking right away, and you’ll scroll down, and while you’re sort of scrolling down to find whatever result you want to click on, it’ll expand all of a sudden, and the layout shifts completely. So as a SEO guy, it drives me actually bonkers that Google is going against the grain of what they preach all the time. But that’s exactly what happens, like what I just explained. So when you Google something and you have generative AI like SGE enabled, it’s literally like a synopsis of the top ten results just show up at the top of your SERP. And what’s relatively recently, Google has been providing more source links within the content, within the synopsis, in the generative AI, which is really interesting because there are basically organic links now in more organic links. There were always kind of like some organic links, but more organic links embedded directly within the synopsis that Google, the generative AI is providing, which is really interesting.

Ben Page: Yeah. And there was a short window of time where the browsing plugin within Chat GPT was functioning. I feel like it was a matter of weeks before it got shut down. And once I got enabled on that, it was epic. Right? I was making so much progress on different topics. So like GPT Four, it’s trained up until whatever date, 2021 or something. So it’s really good at things that are unchanging or there’s things that have a great corpus of text leading up to that point, but anything that’s really recent or really new, it’s not great at. Unless it has access to the Internet. At which point it’s doing what SGE and Search is now doing, scraping the top results, providing a synthesis and a readout of that, using the wisdom of crowds type approach. So that’s why I’m really excited about SGE for Search right now, because it’s like bringing back that functionality that I lost when they killed or nerfed the browsing plugin in GPT four. So, like, one practical use case for me is tinkering with code things, and especially when I’m trying to do coding applications related to say, Google Ads, right? And like, oh, there’s a new API version out, or if there have been recent changes, this is kind of the way to go. So I don’t know. So that’s super cool.

Ray Sawvell: I think one interesting quick call out just when it comes to coding as well, is I’ve tended to not trust GPT 3.5 as much as I do four when it comes to coding. Specifically, nowadays I’ve written Google Ad scripts and it tends to get a lot closer with GPT Four compared to 3.5. So you still have to tinker with things a little bit. And Google might look back I’m sorry, GPT might look back in Google and say, hey, this script, we think it’ll work. Some of the variables might be different within the code, but I guess my word of advice would be if you have the subscription to GPT, try to use four for anything code related.

Ben Page: Yeah, and I’ve been starting to use it more for Sheets formulas as well, to use more complicated nested formulas and lookups, which historically and Blake, maybe the same is true for you. Were you an Excel guy before? On the paid side, it was like such an important thing for manual biding and Pivot tables and reports and all this stuff. So I’m like, I feel like I was always at least an intermediate Excel user on that basis. But now this is like an unlock because now I can instantly generate conditional lookups and different functions.

Ray Sawvell: And that’s what I’m really excited for with a lot of this Google Lab stuff. We’ve been talking about SGE a lot, but there are additional plugins that kind of plug into Google Sheets, where you can plug Google Sheets to this AI piece and you can organize charts and tables and supposedly even create additional formulas as well. So I think moving forward, the barrier to entry might be a little bit lower when it comes to Google Sheets formulas or Excel formulas, but you still have to know what you want. But you should be able to use tools like GPT or Gemini potentially, to write some of these formulas for you.

Ben Page: Yeah, well, and we just enabled Google’s Duet AI for workspace within the last several days, so we’re starting to experiment with it. But early take within docs within Gmail. It’s got kind of a composer editor proofreader type of tool within Sheets. Yeah, like organizing data. It’s a little bit clunky. Like I’ve tried several queries and it would just say like, cannot compute, try later. More features being added. I’m sure that’ll get better with time. But what I’m really excited for is within Slides, I can appreciate a well put together deck. It’s also challenging at times to add that level of polish and so on. But the prompting engine, the Duet AI within Google Slides, it’s like having a mid journey built in to it. So you give it a prompt and it’s generating these cool, unique images and so on. Like, wow, that’s going to lower the friction, the difficulty score. We can all have much more polished, informative presentations this way.

Blake John: I didn’t even know that was a thing. We just started using Duet this week, two days ago, so I have only very little experience with it. I had no idea that was even a possibility. It was like mid journey in Google Slides. It’s incredible the leaps we’re taking, how quickly it’s happening.

Ben Page: Right. And in the Google documentation for Gemini, what they’re hinting at, what my take on some of that is know, they’re talking about API interoperability and building it in a way that it’s scalable, in a way that it, know, plug into other tools. So I’m sure that’s probably where this is headed, right. Is like the human side. How can you take this technology, connect it to other tools to extract better insights or start training more effectively? Or there’s going to be so many cool use cases and ways to master the use of this. And our roles are going to be more about like we talked about before. It’s like, can you become a master prompter on the data side? Can you be the engineer that architects and masterminds? The way all of these are working together?

Ray Sawvell: Things like gemini and duet. Do you guys remember that little paperclip guy that used to be on Microsoft? It’s almost like that on steroids. Like all this additional stuff that’s being know clippy, right? Yeah, clippy.

Ben Page: It’s like, dude clippy, clippy on Clippy’s back. Yeah, we should actually generate that within Slides later. Yeah. Or mid journey buff clippy. That’s super cool. Yeah. And what we’re trying to figure out here so we’re talking about impacts of AI on the SERPs SGE, it seems, Blake, like from an organic standpoint, it’s almost like the evolution of optimizing for featured snippets and zero click results. Some of the best practices or thoughts. For me, I’m thinking structured data. Some of the basic things still apply. You have to make sure that you have a fast site. It’s easy to crawl, it’s easy to index. What other thoughts do you have though? Like where this is headed, potential impacts. How do we even think about how we’re performing organically with this in the mix?

Blake John: There’s so much to think about. I mean, truly. Because on one hand so going back to what you said about optimizing for Featured Snippets, it is kind of a level up from that. That’s sort of in my mind the way that it’s working. But what’s unique about this is not every like the Featured Snippet is the same every time. It’s a static result. This is sort of dynamic. This is generative AI, right? Like it’s changing, but you can really study the specific sources that Google provides within the generative AI when it provides that source. And what source provides is what you can really pay very close attention to and make an effort to optimize for that. So as an example, you could Google like, what is ADHD just as an example. And then it’ll have maybe, I don’t know, 100 word synopsis of what ADHD is. Generative AI will within that synopsis, it’ll have five drop down arrows with sources essentially. And each drop down area is like sort of a segment of how Google is getting that result. Like that specific piece of generative AI, you know what I mean? And so you can study that and kind of make sense and piece it together and say, okay, if we want to show up in this generative AI we want to show up in this as a source here we need to sort of answer this little snippet that it’s providing and give it an opportunity to see us as the expert for that explanation. Again, you can kind of keep that’s sort of how Featured Snippet optimization works. I think in Featured Snippet there’s also like the specific types. There’s bolded list, Ordered list, sometimes there’s tables in Featured Snippets, I feel like that’s a little less relevant. Currently it’s mostly just like text based.

Ben Page: Results with links to exactly.

Blake John: I think there’s also a case for image optimization. I’ve seen images show up in the.

Ben Page: Thumbnails on the cards for the sources, quote unquote.

Blake John: Exactly. I think that’s going to be important, but I don’t think, I mean, a lot most people are publishing at least with at least one high quality image. That’s usually not a barrier to success for most. But yeah, it’s really just studying where and when Google drops in the source link and then figuring out exactly what they’re grabbing from that source and kind of replicating it, obviously delivering a better answer and kind of piecing it together. As you continue to go down the sources within the generative AI. That’s kind of how the process that I think needs to be taken.

Ray Sawvell: It’s almost like people ask similar type of questions because I’ve kind of went down a rabbit hole where it’s like I may not necessarily know, I’m not an expert on the piece that I’m searching, but then it’s like, hey, did you consider this or do you want to go deeper into this piece? So I don’t know if that falls into optimizing for some of that, but that’s kind of where my head is going, is I tend to go down the rabbit hole where it’s like, oh, I didn’t consider this lens or go that route.

Blake John: Yeah, absolutely. I think the people also ask, and we talked Schema and FAQ markup specifically makes a lot of sense. And that’s been true always. But you can kind of keep going further and further and you can pay close attention to what are the other things that Google is suggesting right.

Ben Page: At the bottom, I’ve seen people also ask style exactly within the SGE. They appear as bubbles at the bottom as, like, follow up prompts, basically, if.

Blake John: You want to think of it, that’s exactly it. And then you’ll even kind of get another result, like a search under Result page, sort of when you do that. And so you can pay attention who’s ranking there and who’s kind of, I guess, winning that SERP. I don’t know if that’s really I mean, it is a SERP in a way, but not in the traditional sense. But traditional is sort of dead.

Ben Page: We’re trying to get the impression, but it’s like we’re trying to get the attention, the impression, the engagement, like we’ve always done, but just the way that we like as the marketer, the way that we reach the user and provide the value. The vehicle is changing and the way it’s delivered is changing.

Blake John: I will say, too. And I’m waiting for I don’t know how this data will be because these are, in a way, zero click searches, in a way, but they’re much more interactive and so it’s less likely that there truly is zero clicks. You know what I mean? But that’s what’s being delivered is like your overview answer. You don’t need to go any further. Which is a bummer for that’s why I said earlier it’s hard to win an organic click these days. But I would be really interested to see what kind of engagement these generative AI snippets are actually getting. And I don’t know if we’ll ever truly get that data, but I think that would be really enlightening. I also wish within a Source Medium report, if we could somehow see if the user clicked on our result within a generative AI.

Ben Page: Right.

Blake John: That would be really enlightening, sort of, because then you have the data to build the use case to spend time and start optimizing for it.

Ben Page: I know Will Reynolds is working on it.

Blake John: Right. I would love that data would be yeah.

Ben Page: Yeah. That’s awesome. All right. Two kind of really related lanes to this. One is the thought of, okay, if SGE is using the wisdom of crowds to generate its results, right? This AI, it’s not really good at novel idea, like novel creation. Right. That’s still like the human element is like creating something brand new. This is like synthesizing. Okay, back to your example of what is ADHD. Okay, here’s what the top ten articles say it is. Boom, boom, boom, boom boom. Here’s what the say and the gov say and DA DA DA DA.

Ray Sawvell: Right?

Ben Page: So it’s doing that, but it’s almost like if you followed in the legal niche, I think they call this shepherdizing sources. So, like, hey, we’re citing this legislation, and then there’s like a reference to this case over here. And then you go there and you’re like, okay, what’s this statute? Oh, what’s this sub statute? Okay, what was this other case over here? And you go deeper and deeper, deeper until you finally reach the bottom, and it’s like some original thing from 1938 or whatever. And the same thing is true when you read books like, oh, The Power of Habit or something. You go in the bibliography and there’s like 50 sources, and all of a sudden you’re like, oh, it all goes back to this 1974 academic study of this and this body of research by this not very well known group or something, you know what I mean? So it’s almost know in our process. Blake on search with content intelligence and just building, like trying to build and engineer the most valuable piece of content within a niche. But I wonder if there’s an argument for if you can conduct your own original research, like basically going as deep into the well as you can. So go to the original source to generate something that’s truly new and valuable or a unique take on it, because otherwise you’re just like one of ten and you get lost in the noise of the crowd, the wisdom crowd, and there’s probably a value there and stuff.

Ray Sawvell: You’re just rehashing the information that’s already there.

Ben Page: Exactly. Everyone’s rehashing a rehash of a rehash. And how do you win? Well, you just have to be like one of the top five rehashes of the real insight or definition from 50 years ago or whatever. So that was kind of one thought, was, can you do original research or can you shepherdize? You’re in SGE, and this is if you’re in SEO and you care and you want to rank right, go deeper. Okay, what are all these articles drawing from? Okay, what was that now? Okay, what were those drawing from? And just go to the beginning and say, okay, what is this really telling us about this topic? Or whatever? And how can we do more research or reinvent this or bring unique value to that user? That’s one, but here’s the second one. Like, where does this go? All right, do either of you guys have the Chat GPT app on your phone?

Blake John: I don’t actually know.

Ben Page: Dudes. Got to get it. You know why? Because all right, like voice plus AI. Right. SGE plus AI in. Ray on your Pixel. Have you ever done on the Home tab or in the Google app on your Pixel and use your voice search that then spawned AI results?

Ray Sawvell: Yep, I know what you’re talking about.

Ben Page: Right? So if you have the GPT app on your phone, you can use voice to do input and interact with, right, to keep prompting it or edit it or whatever. This idea was kind of spawned by your comment, Blake. Right. This is dynamic. And it’s just like GPT ray. You can put in a prompt, I can put it in a second later, I can put in the same prompt three different times, and I’m going to get a slightly different result each time. And we know that a huge percentage of searches are new to Google, even to this day. And so you add Voice in, that’s going to multifactor the amount of combinations, but just the speed and the way that people are going to get information using AI powered search, plus Voice on mobile. And yeah, just thinking about untangling that spaghetti from a reporting standpoint, but yeah, just kind of thinking about how are people going to use this and how will Voice impact it? Will that be the unlock? Right? Because it’s like no friction. It’s like, now I have the frickin Oracle at the sound. I just have to say, hey, Oracle, find me the blah, blah, blah, blah, blah. Best thing ever. Okay, here’s everything that mankind has ever known about that great, cool.

Blake John: Yeah, I’m waiting for the day where it’s just embedded in your brain and you don’t even have to say it out loud.

Ben Page: Oh, that’s coming in 2026.

Blake John: At this point, I believe it.

Ben Page: Right? Well, yeah, but here’s what’s interesting, too, back to that idea of what is the human’s role as this continues to evolve. So at some point and I was like, hey, Gemini rumored to be trained on twice as many tokens. When do we run out of training corpus material for these agents? Right?

Ray Sawvell: Because when do the robots train themselves?

Ben Page: Well, that’s what I wondered. All right, let’s go into philosophy really quick, seriously, because look, all we’re doing right now is like, we’re bringing all right, we’re teaching these models to learn on different kinds of material content, right? It’s largely written, so a lot of the work so far, it’s like, how do we translate YouTube videos into transcripts and then feed that in? How do we take all the books ever written and digitize them and feed that in? How do we take all the music ever compose and feed that? Great. So that’s one lane. And then we’re like, how do we teach it how to look at images and figure out what’s going on with that? And like, oh, it’s a man standing over here with a dark shadow and blah. So now it’s going to do that and then it’s getting into video, but at some point and even audio, right? But at some point, it will have mastered all that and it will have consumed everything that humans have ever output and been documented. Right? So then we’re going to start generating new works or it will start synthesizing and producing like all right, now we’re going to take all of these ideas. We’re going to prompt it with this. We’re going to add chaos level four. I don’t know if you’re familiar with Chaos Ray from mid journey.

Ray Sawvell: Maybe not.

Ben Page: No, I don’t think it’s like a randomness score. It’s like a z score. You can say, I want low randomness. So you know how you get like four variants with each image that you generate? So if you say like low chaos or no chaos, it will have very similar variants of image. But if you have high chaos, be like, all right, different orientation, like different aspect, all these different changes, different noise, different styles, et cetera. But what happens when it starts generating net new content and then ingesting it and learning from what it just created?

Blake John: Well, I mean, that’s I don’t know.

Ray Sawvell: Maybe when do the humans go away, right?

Blake John: Exactly. But that’s kind of the way Google works. The literal search engine is a machine learning algorithm. It’s learning on machine.

Ben Page: Right.

Blake John: And there are scientists or data engineers or whatever at Google who don’t nobody truly knows exactly how it gets you the results that it does.

Ben Page: Right. The hallucination factor. Right?

Blake John: Yeah. There’s just so much that it’s learning from itself that it doesn’t understand. And as soon as it gets better and stronger, it sort of cuts off what it doesn’t need and then it does it again. It replicates the machine learning process and it gets better and better and better, and then it just drops the dead weight and then it gets better and better and better, and it keeps learning more and more and more. And that’s how Google has become the powerhouse in our world that it has today. But honestly, I’m thinking if it gets to that point and it’s learned truly every single piece of data, I’m wondering is it now just going to start outputting new content?

Ben Page: That’s what I mean. And the second that it does and it starts training, its that’s like that’s the key.

Blake John: Truly new content training itself, not just synopsis. You know what I mean? You’re saying new research almost could it do that?

Ray Sawvell: This 1937 study did not consider this from this other paper over here. Two pieces together, right?

Blake John: Exactly.

Ben Page: Oh, like without a human prompting it. Because right now, that’s kind of where we’re at.

Ray Sawvell: There’s this blind spot in this one study that didn’t happen and wasn’t accounted from this study over here, and then boom.

Ben Page: Yeah. What happens if we merge the findings from right. Yeah.

Blake John: That could be a new piece of content that no one’s put together that a bot could do. Well, I don’t know that we’re there yet, but in this hypothetical that you’re talking about now, maybe that’s what happens. Maybe it’s developing its own and not just synopsis. Right. We’re at that stage now where it’s kind of summarizing that’s exactly what it’s.

Ben Page: Just synthesizing the current existing corpus it’s been trained on. If you’re lucky, you have plugins, you feed it proprietary data, it synthesizes that. It’s good at understanding it and giving us things like summaries, like the best of or the highlights or whatever. But that’s why right now it’s so key to be a master prompt engineer is what I keep calling it, because it’s up to us to have the insight to say, oh, yeah, there was that study. There was, oh, Charles Duhig. And I combine that with James Clear atomic habits, and now I have the ultimate machine to master my habits or know. But eventually, right, it’s like, what if it becomes the agent and we don’t you know what I mean? It starts doing unpredictable combinations to produce novel outputs and I don’t know, I just thought that was crazy to even think about.

Blake John: And the vacuum cleaners take over your house, and the microwave team up, and.

Ben Page: It’S the meme of the roomba with the knife, right?

Blake John: Yeah.

Ben Page: Oh, man, that’s wild. Well, okay, that’s exciting. Hopefully that’s at least, like, three to six months out. It’s going pretty quick, though.

Blake John: Maybe three to six weeks at this point, with how things have evolved.

Ben Page: Yep. Wow.

Ray Sawvell: So where do we go from here?

Ben Page: I don’t mean, you know, we could talk really quick about in Bing. So if you go in Bing, the new Bing, and you have that chat right? So if you prompt it through the chat right. Use their AI infused search experience. We’ve been noticing for a couple of months now that they’re serving ads within those AI powered results. I can only assume that’s what’s next on SGE, right? Once they get enough adoption, because now it’s like in Labs and you have to opt in all this. But once it’s like, the default, everyone has Gemini. It’s like now. It’s imagine spring 2024. SGE is, like, the default. It’s powered by Gemini. Google has more compute than anyone, so it’s just, like, rolled out. And this is like the new like, we were joking before Blake about it’s. Like when Mobile first SERPs went live as, like, the Know. Now it’s like, imagine SGE is the default. And this goes back to the thing about shopping, right? Because so far I’ve got Alexa at home, and I use it, and it’s pretty great for different things, but it’s really limited. It’s like, well, if I really want to do something really cool, I’d need an app. And probably an app doesn’t even exist for the use case I’m imagining yet. But now imagine it’s all embedded in SGE, like, all that functionality, if and when ads happen. Now we’re back to the voice thing.
So now I’ve got my phone, I’m sitting in the kitchen at Know. Hey, Google, can you order some more bananas? And then Google Pay. Dude, it’s done. All right. Hour later, it’s there. That’s where this is headed. Right. And ads, whether it’s RSAs or whatever, right. That’s all coming. And I wonder too, blake, you talked about how SGE is primarily text right now with some cards and stuff, like, like in the future, does SGE decide what SERP features to pull in based on the query? It’s like, oh, based on your search, that was navigational and it’s local. So guess what? Now the map pack is going to be in there and now it’s going to be like one click to Google Maps and you can just be, you know, throw the directions on my Google Maps. Right.

Ray Sawvell: Like if it’s not a commercial intent keyword, perhaps that’s maybe where you get more SGE or it’s probably more text.

Ben Page: Based, but then right, it’s like, oh, it’s commercial this. Okay, here’s a shopping carousel within it or it’s directions. What are the hours? And this? Oh, do you want a reservation? Yes, I do. Okay, your reservation is done.

Ray Sawvell: Here’s what you best birthday gift for blah, blah, blah. Here’s shopping ad.

Ben Page: Right.

Ray Sawvell: Or something like that.

Ben Page: And then it’s like you might like, what are you planning on wearing? Oh, well, the dress code is this. Okay, do you have that? No, I don’t.

Ray Sawvell: Oh, here’s party plan.

Ben Page: Here’s a blue shirt. Great. Awesome.

Blake John: I just did a search for a restaurant near me and I feel like it’s already sort of happening.

Ben Page: It’s learning from our conversation.

Blake John: Yeah. Right now. But it just pulled up like a list of restaurants that are near me.

Ben Page: With the labels on it too.

Blake John: Yeah, it’s incredible. It’s got reviews, it’s got its location, a brief overview.

Ray Sawvell: Wow.

Blake John: And then similar results embedded next to it as well. Like as the source. Again, this is sort of as the source. It’s happening, honestly. And this is the case too. A lot of times have been. And this is why I talked about I want to see the engagement levels on these generative AIS, because a lot of times too, I’m ignoring it. I’m ignoring generative AI because I’m scrolling past it. I’m scrolling past reason sometimes. And I don’t know how Google does this or why it decides to do this, but sometimes it will automatically generate the generative AI automatically. But sometimes you have to click generate.

Ben Page: Yes.

Blake John: And then it will do that. And in those cases, I’m almost always ignoring it. It just hasn’t been a common prediction score.

Ben Page: Then it has to know, like, based on this one, we can predict what you’re likely to need or want in that micro moment. Therefore we know high confidence. Like, this is one we’re going to give you.

Ray Sawvell: I just did like a similar search, but I also said I did a follow up question and I said, what are gluten free options? Because my wife likes gluten free options. And then it also gave me it seems like it’s combing through reviews, for example. So now it’s like, here’s this restaurant combing through reviews. It has XYZ gluten free options, and then it says other top restaurants in that area, so you’re able to interact and chat with it as well. And then it gives me a bunch of other things people also asked, which is cool.

Ben Page: It’s digging up the follow up question info sooner, because usually what would be the user journey? The menu you’d click? Yeah. And then you’re on the PDF, and then you’re like, I don’t know, is this cauliflower pizza thing? Is it on there? Is it gluten free? What’s going on? No, it has flour in it, but it’s like scraping that. So back to the importance of having rich data and having those details. Yeah, that’s interesting. But Blake, to your point, even if you scroll past, isn’t it going to be like a net click Share game? Just like with ads, right? It’s like, I never click on ads, but hey, aren’t you more likely to click on it organically? If you saw the ad, you saw it in the Map pack. Now you’re seeing the blue link or whatever. Like you’re seeing reinforced featured snippet. Yeah, it’s like, oh, it’s appearing again, again above the fold or in the top ten, whatever, right? You’re like, more likely just no click Share perspective or even a branding. Like, let’s say you did the search, had to set the phone down, kids going crazy. But then the next day and you come back and you’re like, what was oh, that’s right. I was seeing the Acme Corp, like, four times. I better go on their Facebook and look up Acme Corp and get the thing that I need there. You know what I mean?

Blake John: Right in the middle of your child’s temper tantrum.

Ben Page: No, like the next day or whatever. You know what mean? Like because that’s what I know.

Blake John: I know.

Ben Page: I mean, it’s like a branding or.

Blake John: Like you want to be there if you right, at the end of the day, you want to always be there. And we talk about this. This is something too, we talk about internally, and I think maybe it’s come up in another podcast. But having ads over your just the whole landscape, you want to be there every single time that you can possibly be there because you’re more likely to win the click at the end of the day, which is also, I mean, and obviously, ads are always first, so it’s always harder to win the organic click. I know. I just have to remind everyone that.

Ben Page: Good ads are first.

Blake John: Yes, exactly. Good ads.

Ben Page: Well, they’re also below.

Blake John: They really sandwich it. Yeah, I kind of lost my train of thought. I’m just blinded by blake hates ads.

Ben Page: It’s the idea of maximizing your visibility.

Blake John: Exactly.

Ben Page: Regardless of it’s a zero click SERP. It’s whatever.

Blake John: Exactly. A zero click SERP. If you can win the featured Snippet. A lot of times those are zero click. That’s what we think about when we think of zero click, you want to win. That featured snippet. It’s a branding play at the end of the day, like you’re talking about. So if there’s an area in which you can win and you want to be there, you want to win it because you can increase your brand awareness. They’re more likely to remember you down the road as well. Yeah, that’s right.

Ben Page: I think this is heading to an increasingly interdisciplinary approach because at the end, right, it’s like, what are we doing? We’re doing search engine marketing and there used to be a lot cleaner lanes between Paid and Organic. Those lanes are blurring, especially if SGE, like, if the SERP goes SGE first, which I predict it will at some point, otherwise why would they have it occupy so much real estate currently? It’s faster, it’s better. I mean, the fact that you’re getting the follow up question answered immediately, without clicking through, without the headache, it’s clear it’s got to be better for users. So, yeah, interdisciplinary approach. And that’s where we’re going to look at the totality of what is it’s like? Back to keyword research user needs. Understanding that user need at the core, anticipating likely follow up questions and information like just knowing what that journey is for that user need and designing content and advertising that can address each step of that need to ultimately bring that user into your ecosystem and help them out, help them solve their problem. That’s what I think good marketing will be, which is what it’s always been. It just looks a little bit differently now. Right. Aided by technology. Cool. Well, anything else for the random show?

Ray Sawvell: Not for me, I don’t think.

Blake John: No, I think we’re good.

Ben Page: It really turned out to be the impact of AI on Search and SERPs more than the random show, but it was really fun to deep dive on this. So if anyone’s seeing anything cool in their own experiments or their own experience with the search engine results pages, or curious how this applies to them, how they can get ready, I guess, or just really take action now because it’s changing so quickly, let us know. Go to Two One and contact us and look forward to catching up with you guys. Thank you so much for listening. Your support means the world to us and allows us to help more people and grow the community. Please take a minute right now to subscribe and share this. Wherever you listen to podcasts and sign up for the Profit, this will get you insider access, additional tools and swipe files, and help you elevate your marketing game to the next level.