In this week’s In-Ear Insights, Katie and Chris discuss generative AI impact on search engine marketing. What is the impact of services like ChatGPT, Google Gemini, Perplexity, and Microsoft Copilot on traditional SEO and search? Tune in to find out, and what steps you should take to prepare for the future.
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Machine-Generated Transcript
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.
Christopher Penn 0:00
In this week’s in your insights, search is changing more people are using tools like Bing, Google Gemini or perplexity to do searches to ask language models.
Hey, what’s the best place to get a burger around here? Or how do I do this thing? And increasingly, these generative AI models powered by search databases are doing a better and better job.
This is changing the way people search.
This is changing this the SEO world in general.
And one of the questions that came up at a recent event I was at was, what do we do about this folks like random Rand Fishkin, and Andy Crestodina, and Aleta solace, are all talking about how users prefer generative AI searches over regular searches.
In many cases, because there’s less garbage, right, there’s less clicking through to 48 websites, you just get an answer, and maybe a few links to click, and it’s a better user experience plus a consent the size things that you might have to go to five or six search results to get.
And so the question to you, Katie, is, how do we think about the way search is evolving into general AI being the way people search? And what should marketers and company owners be doing to plan for a future where there’s even more intermediaries between you and the customer?
Katie Robbert 1:23
All right, so that was a lot of questions in one.
So let me take a step back for a second.
I’m not using generative AI to search.
And so when as you’re saying, like, everybody’s using it can edit this isn’t to be like a sarcastic thing.
But like, where’s the data on that? Who’s everybody? Like, is it? You know, is it you and other, you know, AI specialists, who that’s your world? So you’re feeling like everybody’s doing it? Or is there data that supports that says consumers are turning to ChatGPT and Google Gemini and Microsoft Bing? To do their searches versus traditional search engines? Like what what does that look like? Because I first just want to understand who everybody is.
Christopher Penn 2:11
Everybody in this case, so this is data from a 16 z the Andreessen, Andreessen Horowitz consulting firm slash incubator, slash, whatever the heck they are in the genitive AI product, sort of the top three for people just top five for people usage out of 100 million that people serve a million people, users ChatGPT Of course, number one character AI, which is a chat bot system for character interaction.
Google Bard, which is now called Gemini poll, and Quill bots, are those sort of the top five in the top 10 is also perplexity.
perplexity is an AI based search engine.
Now, do we know that these behaviors are purely search based? They’re not.
We know, these are these have multiple uses.
But in a number of recent articles and pieces on search engine, the Search Engine Journal, we are seeing more and more people looking at a particular Google Search gender of experiments where Google is putting generative AI, front and center in search results.
So
Katie Robbert 3:10
I will say that, as someone who knows, survey design very well, the flaw with the data that you just quoted to me was that 100 million people were asked about the generative AI search tool that they use not are they using generative AI for search.
So I just I just want to make that disclaimer.
So okay, I just I’m trying to understand the landscape.
But now we can go ahead and move on to the questions you were asking of what marketers need to think about.
So I’m not I’m not trying to push back to say, No, this isn’t a thing.
What I’m trying to do for the people who are listening for the marketers that are listening, is help them get a sense of urgency of how quickly they need to be thinking about updating their organic search strategy in order to fall in line with what’s going on with generative AI versus traditional organic search.
So that’s where my questions are coming from is what is the sense of urgency.
And I’ve also been putting together speaking decks and looking at the data.
And a lot of the data right now is around what we ourselves what marketers in the industry are doing not what general consumer.
So when I think about people like my husband or the rest of my family who aren’t in the industry at all, they’re not using generative AI, they’re still going to a regular Google search engine.
Now Google search, to your point has the experiments built in.
But not everybody is using them nor nor do they know they are using them.
And so I feel like marketers need to be paying attention to a broader audience.
I think there’s a lot of assumptions right now about how and who are using generative AI so there’s this panic of everybody’s using generative AI we have to switch everything immediately.
That leads to are really quick and poor in short term decisions.
What we want to be able to do is take a step back, take a breath, and say, Alright, what is it that we’re actually dealing with? What are the changes? And I feel like it’s a really good opportunity to bring up the five P’s, which are purpose people process platform performance.
And so what you would do in this instance, is walk your thoughts about generative AI for search through the five P’s, what is the purpose of using generative AI for search? Who are the people? What is the process? What are the platforms, you know, whatever your platforms are? And then how do you measure performance? And so thinking about your organic search strategy, in a more thoughtful way versus Oh, crap, everybody’s using generative AI for search, what do we do? Like that’s just, I’m going to encourage people to stop.
So that’s sort of my first piece is everyone needs to slow their roll.
Yes, generative AI is out there.
Yes, people are using it.
But it’s not overnight, going to sink your whole business, you have some time to really think through how you want to be in that space.
Christopher Penn 6:11
Great.
Just a couple of points I found while we were chatting, perplexity the which is a search based generative model that has 10 million monthly active users, and Google Bard.
Now this is, this is tricky, because it’s it is Gemini bargin, latest Google, and a lot can get rolled up.
And that has on the order of several 100 million users now, because it’s free and available in 159 million countries, saying for ChatGPT, the free version has something like a billion users now think, again, not all doing search with it.
But increasingly, at least according to The New York Times article from the six days ago, more and more users are using casual non technical people and non nerds.
For for such purposes, so I think your five Ps is exactly on target.
But what we want to do is also encourage people to think about it from the perspective of the audience.
What is the purpose of a, a non nerd, using general AI for search? It’s a cleaner experience.
It’s a faster experience.
And it is you get to your answers faster with fewer ads less clicking around.
It’s, it’s like, it’s the difference between DIY and done for you, if you think about it, right.
It’s like, if you go to a search engine, you type in a query, like who won the Super Bowl, and you get those results, you can click on things.
And Google has been trying over the years to chip away at this to say like, here’s zero quick answers.
Here’s the weather tomorrow.
That’s the Taylor Swift team won the Super Bowl, I don’t know who they are the so but now general AI says, Hey, here’s all the answers for you.
And you can check.
You can check the veracity if you want, but we’re putting it on a plate for you with fewer ads.
And you know, if you go to any of the the major news media sites these days, the moment you click into that, like the screen just fills with ads, you don’t have an ad blocker.
So from the consumers perspective, the purpose is better answers faster with less crap.
The pert the people, the people are the people go ahead, you’re
Katie Robbert 8:08
ahead, I can I can, I can save my disagreement for later.
Okay,
Christopher Penn 8:12
the process is interesting, because the process is really something that from the consumers perspective, you want it generative AI reduces friction, because it means less work for the person.
If I hand this to my 14 year old, right and say, you know, I want you to use a search engine to help you write your term paper, or I want you to use gender a to write your term paper, the process for using generative AI to help search and answer this question is going to be much much faster.
Because also it’s going to be easy.
I know him, he’s just going to use the whole paper.
We know what the platforms are.
The big thing is the other performance side.
When you use general AI for search purposes, you get typically faster performance.
So I was doing a talk recently in Canada on tourism, and I said, Show me some ideas for things to do in Edmonton within walking distance of the JW Marriott.
And I’m particularly interested in First Nations cultures, I’m particularly interested in color, local foods and things like that.
So I don’t want the the mate then MAE name tour straps and I put together a very capable list that I did not have to go and do individual research for it’s synthesized at all.
And that’s the big difference between traditional search and generative AI searches, visual searches, retrieval, gendered AI searches, synthesis, and can bring together a lot of pieces.
So from the the audience’s perspective, not ours as marketers, but for the audience’s perspective.
It’s a fat, it’s a more streamlined, shorter path to answers.
And we know people like better faster and cheaper.
Katie Robbert 9:45
So my disagreement is that with every example you’re so you’re giving really good examples, and I don’t disagree with you on that.
What I disagree with is that your examples make the assumption that people know what they’re looking for.
And I do think that that’s a disadvantage of using gender Have AI is that one of the things and so again, this is sort of me as a casual user, not me as a marketer.
When I go to use a search engine 10 times out of 10, I only have like, half an idea, or like half of what I think I’m looking for.
And one of the things I really like about the way search engines work today is that it completes my thought for me, if I type in just a couple of letters, and a lot of the times I’m trying to figure out, where do I know this person from? What were they in? Or I’m watching a show? And I’m like, Ha, half this gas looks familiar.
Or do I want to keep watching this? What the heck is this thing even about? And all I have to do is put in the name of the show.
And my results are? Here’s the cast here, this, here’s the synopsis, here’s the reviews.
But I didn’t have to put in a whole prompted thought to say, I’m currently watching the show, I want to know who the cast is, I want to know this.
Because I don’t know that I want to know that.
And so I do disagree with you in terms of user experience, like yes, it gets you to more specific answers, but only if you know what you’re looking for in the first place.
I don’t think that at this time today, generative AI is the same sort of like loosey goosey open ended, you don’t really know what you’re looking for.
So I’m going to serve you up a whole bunch of stuff.
And you’re going to fall down a rabbit hole, because that’s more fun to me.
And again, this is just one person’s opinion.
To me, that’s a good user experience.
Because I don’t know what I’m looking for.
In the instance, where I know exactly what I need, like, you know, how long do I need to hard boil an egg for to get the perfect? You know, yolk? Yes, I do think generative AI is a good resource for that, because I don’t need to click through 800 different recipes to get one single answer.
That’s really annoying.
So I feel like there’s the two sides of the conversation is one, you know exactly what you’re looking for.
And two, is you just kind of tooling around trying to figure out like, this person looks kind of familiar.
Let me just kind of keep going down a rabbit hole.
Christopher Penn 12:10
Yep.
And I think, to your point, some models, particularly the smaller models definitely struggle with understanding your intent, the larger models are better at that, like you can type in, where do I know the cast of Firefly from and it will attempt to infer based on just that simple question.
Katie Robbert 12:27
But what happens if you type in just Firefly nothing you
Christopher Penn 12:31
will get for the larger better engines, you will get a follow up question, what would you like to know?
Katie Robbert 12:37
And the question is, I don’t know.
Whereas if I put into a search engine, Firefly, it’s going to come up with here’s some cast, here’s some images, here’s some reviews, here’s some backstories here’s news on what people are doing.
And to me that’s like, oh, okay, now I can pick and choose what I want versus with a generative AI system, I kind of have to know what I’m looking for,
Christopher Penn 12:57
or at least be willing to have a conversation about it.
Yeah, I don’t like the the one thing I’ll push back on you there is that you are a curious and intellectually rigorous and a persistent person who cares about quality? And who cares about getting things done the right way? You are not most people, most people are in curious.
They just want the answer fast.
They don’t even care if it’s correct or not.
Most people want a better user experience that is not polluted by ads.
Or in your the example you gave the mother’s cousins, friends, roommates, second brother’s favorite recipe and why the developer in college they just wondering, oh, how many eggs put in an egg salad? Just tell me.
Exactly.
And again, that’s that’s a perfect example.
A gentleman does a much better job.
And, and people want fast.
So to your point, if if general AI can create a fast, easy answer, that is good enough for the in curious person, which is most people these days.
And that does not require critical thinking, which is most people these days at a population level, I think there’s a very strong probability that it will become the default experience for a lot of things because it’s just, it’s, it’s like Amazon.
Amazon makes it frighteningly easy to order things like you can sneeze wrong.
And like, oh, look, a six pack of Kleenex just arrived at my house.
Katie Robbert 14:22
Well, they’re all listening to your question.
What should marketers do? I think that this is where they really need to think about their content strategy.
And so I often go back to the hero hub help framework.
And, you know, there’s this notion of like your Cornerstone content and all supporting content.
And this is really marketers opportunity to creating to create a wide variety of content around the same topic.
Like we should have been doing this all along anyway.
And I feel like similar to how when we were talking about data privacy, it’s not a new concept.
Just because generative AI is on the scene now, content marketing is not how we approach it is not new, because generative AI is on the scene now.
So to your you know, so I feel like we can take sort of those two sides of the conversation and break it down into what we would do as content marketers.
And so there’s the, I have specific questions of where do I know the cast from Firefly from, we can create content to specifically target for that.
So that’s one side of the coin.
The other side of the coin is we know someone’s just going to type in Firefly.
So it’s our job to create.
Here’s where you know, the cast from, here’s what the cast is up to.
Now, here’s the synopsis of the TV show, here’s where you can find things that are related.
If you like this TV show, here’s recipes inspired by the TV show, like we have to be doing both sides of the conversation, we have to be creating content for people who know what they’re looking for.
And for people who don’t know what they’re looking for.
That is what we as marketers need to be doing in order to play along with generative AI.
And so when I say this out loud, I’m like, wow, nothing’s changed.
We still have the same thing.
Christopher Penn 16:12
You’re exactly right.
In fact, we’ve been following a content strategy that, you know, our friend Todd different came up with back in 2008, right, which is content atomization.
Take one piece of content trends a lot.
It is advice that you know, my my former high school friend, Gary Vaynerchuk, has been espousing for a decade too, which is create content at scale, not by trying to make lots of stuff, but just documenting what you do, and sharing it in as many forms as possible.
When you look at the way Trust Insights does, or its content marketing, we’d start with video, right we have this podcast, we have our live stream, we take that video, transcribe it we have that appears a blog post on our blog that goes in our newsletter that goes to the the pieces of the newsletter gets split up into separate blog posts, that audio gets loaded places, the video gets loaded places with closed captions, we are creating a lot of text in as many areas as possible, we try to be everywhere we can.
And we rarely say no to guest appearances on podcasts.
And when a podcast goes up, you know that we’re guessing on that does not publish a transcript, we make one.
So because we need that text to be everywhere we issue press releases, because that puts text everywhere.
We’ve been and we’ve been following this blueprint for since the founding of the company, we decided very early on, we’re going to do a lot of media.
And what has happened is, as these models were created, they start pulling all this text from all over the internet.
And the more places you are, the more you’re the models will associate your brand with specific terms.
And so there’s a lot of catching up people have to do.
And they have to be and I know this is a part that that irritates a lot of content marketers, you do have to create content at scale, a lot of it because that’s the way these predictive models work.
They’re all they are is word prediction machines.
And those predict those probabilities prediction are influenced by how often they see text on their input side.
So if you are not everywhere, you are going to struggle.
Katie Robbert 18:20
And I do want to add the caveat that yes, you have to create content at scale.
But you have to create good valuable content at scale.
So anybody can create a bunch of really crappy content, that’s really not going to help you.
So one of the things that we were just discussing this this morning, during our sort of prep conversation is, we had another topic that we were thinking about recording for a separate podcast episode.
And we paused for a second and said is this is this content that we want to create because it’s focused and helps move the company forward.
And we decided it’s an interesting topic, but it’s more of an academic curiosity than it is for, you know, actually being beneficial and giving us so what to our audience.
And so we decided to change the topic.
And so there’s definitely still those moments where we can create a lot of content we can create, we can talk about a lot of things related to generative AI, is still has to make sense for our company.
So we still have to focus in as we’re taking the time because if we’re trying to create content at scale, we then have to be picky about the kind of content we’re creating the topics that we’re talking about writing about.
Because if you’re creating a lot of really crappy content at scale that yes, we’ll get you known it will get you into the search results for generative AI, but not for anything useful.
People are just going to be like, I don’t like that.
Because I do know that in some systems, you can rate the responses you get.
And I’m sure that definitely plays a part in what kind of results you get moving forward.
So if you say I want to get you know, a hard boiled egg recipe and Trust Insights shows up.
You’re going to read it thumbs down and be like don’t show me this crap and so trust it sights are brand reputation, whether we know it or not, is being damaged.
Because we’ve created a bunch of really crappy content about things that we don’t even do.
Why are we talking about hard boiled eggs? We have no business talking about that.
Let’s get back to talking about how we can help content marketers create content at scale.
Christopher Penn 20:15
Exactly.
However, so yeah, that is essentially you have to be everywhere.
And this is again, the the challenge that every marketer faces, the things that you will need to succeed in the age of general AI is you have to have the most best data, right, which is a challenge for a lot of companies.
And you have to have the most best ideas.
Because creativity is is still something that humans need still narrowly edged out the machines on.
And if you don’t have either of those, you are in a lot of trouble.
If you have one of those, you at least have a fighting chance if you have both of those.
And do you start early meaning now in your industry, in your vertical, you stand a very good chance of gaining an early lead and the nature of generative AI of these predictive models is whoever is best, earliest retains a commanding advantage over time, because the data is automatically biased in their favor.
So get started sooner rather than later.
And if you’re not sure how, drop us a line, also, if you want us to guest on your podcast, drop us a line.
When you show up for peanuts on podcast, go to trust insights.ai/contact.
But that’s that it’s like you said, Katie, this is not new.
This is not news.
This is not innovative.
This is do the things that people have been saying do all along and do them soon.
Katie Robbert 21:43
Yeah, I think that, you know, with a lot of things, marketers have been able to kind of skate by doing the bare minimum and now with the changes in technology, it’s forcing their hand to do the work.
And so we’re gonna see that split of people who can do the work and people who are just kind of okay, let me go find something else to do with my life.
Christopher Penn 22:01
Exactly.
And here’s the upside if you do all this, and you know things radically change, oh, no, you created a lot of great content that people enjoy and it’s out there for people to find you like gosh darn, if you’ve got some thoughts about how you were helping your brand show up in general AI or you want to discuss you know how your brand currently is dropped stop on our free slack go to Justin says AI slash analytics remarket is where you have over 3000 other marketers are asking and answering each other’s questions every single day.
And wherever as you enjoy our show.
If you would prefer it somewhere else, go to trust insights.ai/ai podcast where you can find us on most major platforms.
And while you’re on your platform of choice, please do leave us a rating and a review.
It does help share the show.
Thanks for tuning in.
I will talk to you next time.
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Trust Insights (trustinsights.ai) is one of the world's leading management consulting firms in artificial intelligence/AI, especially in the use of generative AI and AI in marketing. Trust Insights provides custom AI consultation, training, education, implementation, and deployment of classical regression AI, classification AI, and generative AI, especially large language models such as ChatGPT's GPT-4-omni, Google Gemini, and Anthropic Claude. Trust Insights provides analytics consulting, data science consulting, and AI consulting.
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