Welcome to Shift Happens the art, science, and chaos of modern marketing. Each episode unpacks the forces reshaping marketing from AI and data to privacy, creative and performance, and asks experts how they transform disruption into advantage.
Nasser:
In every sport, in every category, in every industry. There’s a LeBron, right? There’s the guy that everybody associates with that sport. And we have the LeBron of location optimization here with us today – Kyle Harris, is our director of local optimization. He helps multi-location brands stay visible where it matters most when customers search nearby. He’s been analyzing how AI is influencing local discovery and which changes are real versus which are just noise. Welcome to the show, Kyle.
Kyle:
Thank you very much. And I also like to consider myself the Michael Jordan of local search, not LeBron.
Nasser:
And what would you say is the difference?
Kyle:
Well, Jordan’s number one and LeBron’s number two.
Nasser:
Yeah, but it’s a different era. You got to think of it that way. It’s a different era. And actually LeBron has far more… listen I’m not going to have this debate with you right now because the fact is I’m trying to make you sound even better than you’re saying that you are.
Kyle:
Fair enough. I’ll take a compliment when I get one.
Nasser:
There you go. So, Kyle, you know, one of the thoughts that’s been bouncing around is that, like, with all the hype about AI changing search, do we still need to invest in listings and reviews and local optimization for physical locations? And that’s what we’re going to be exploring in today’s episode, Local Search, In the age of AI. Smarter strategies for brick and mortar brands. And you know, there’s been a lot of noise about AI. And some executives are asking if you should optimize for ChatGPT or rethink your entire local strategy. From your perspective, what’s the reality of what clients and users are actually experiencing right now?
Kyle:
Yeah. So in local, I think we are a little bit lucky in that you don’t have this massively complicated decision tree of I can only do, you know, one thing or a couple of things, right?I kind of have to choose which baskets to put my eggs in. In local, we are decently lucky at this point where foundationally, the things that you’ve been doing in local are going to be and are right now powering these AI experiences. So investing in listings is something I would have told you to do five years ago, and it remains critically important today. Investing in reviews and ratings and making sure that, you know, the sentiment related to your brand is, you know, on point again, five years ago is something I’m pushing.
I am tripling down on it. I think it’s more important than ever. But in terms of net new tactics, of what I have to do to get in and break into all of these things, we’re talking about it, you know, 2 to 4 degree pivot and or expansion, not necessarily brand new practices, brand new teams, brand new disciplines. We are really lucky in that the foundation in what you’re doing to be successful in AI is very similar to what most successful multi-location location brands should have really been doing for the last couple of years, for sure.
Nasser:
So where are you starting to see, AI actually have an impact on local discovery?
Kyle:
Yeah, so this is really interesting. Depending upon your category, we’re seeing this impact kind of play out a little bit differently.But AI is essentially the world’s greatest recommendation machine. And if getting a recommendation about where to essentially get a service done and or where to, you know, buy a product or what product actually, you know, fits your needs the most, we’re seeing a lot of that discovery actually happen on these AI platforms. Whether it be AI mode or through an AI overview or directly in these LLMs, we are seeing that there is a decent amount of traffic that is happening directly there, going through that flow to get a recommendation.
But then, at the end of that flow, oddly enough, a lot of the times people are jumping back into Google to get reviews on a location or reviews on a product, or to actually find out of a store is open, or if it actually has that, you know, product in inventory live. So we’re seeing a really nice blend of a lot of this top funnel discovery happening in these LLM platforms, and then still the last mile execution happening almost exclusively on Google.
Nasser:
So as we see a collapse or a compression of the customer journey, essentially, down to a couple of steps where AI is an assistant is helping you explore and engage and do all of these things. And then when people are ready, which is happening much faster, if I understand you right? That’s when they’re turning to the local experiences. And that’s where it needs to be really closely aligned with, with everything else that’s being done.
Kyle:
Correct. It’s really interesting. And again, like, you know, looking into the future, I think that last you know, my whole experience in these LLMs is going to get, you know, a lot better. It’s, to be honest, not perfect today, right? Like, it can hallucinate a little bit and there’s no robust data set. You know, that all of these LLMs have they’re kind of borrowing local information from Apple and Yelp and Google and all these other places. Which is why that, you know, like, hey, how do I get to a place is still very much happening on these navigation apps that, you know, that top of the funnel piece is really exploded.
And I think one of the most interesting things is it’s happening faster than ever, because AI is incredible at helping you ask the right questions during this journey to get you to whatever product or service best actually fits your needs. That part is happening faster than ever, and it’s a really exciting time to essentially be trying to do digital marketing.
Nasser:
So that that’s interesting, because the implication there is, if you are a business that relies on foot traffic, right, with physical locations, there’s usually entirely different teams and capabilities and strategies that focus on everything that isn’t, you know, driving people into physical locations. But isn’t that going to increasingly be a problem for brands and marketers if we are seeing this kind of convergence and collapse of the customer journey into far more, far faster decisions?
Kyle:
So I’m going to answer your question, I think in a decently unique way. Historically in my career in dealing with multi-location brands that are all about driving in-store traffic, right? And we that’s a quite a lot of brands that we talk to, getting buy in on the tactics that will actually make that happen is probably one of the hardest things to actually get done.
There’s budget restrictions, there’s people and teams and there’s cross-functional things. So saying, hey, you know, multi-location brands should really, you know, triple down on reviews is very easy for you and I to say. Operationally at these, you know, Fortune 500 companies that need to do this, there’s thousands, if not tens of thousands of locations with hundreds of thousands of employees all having individual consumer interactions.
And then to turn those into reviews and properly manage that and then get that into every corner of the organization and manage all of that, it’s very challenging to do that properly at scale. So internally, getting clients to invest in, properly manage, giving them the tools and technology to do that properly is very challenging. The brands that are doing it well, though, are reaping the benefits of seeing increases in in-store traffic.
That’s very interesting that tactically, if you get buy in on these things, it will absolutely work on the KPI you care about that is in-store traffic. It’s just we’re investing in something, you know, online, digital that is very far away from someone setting up a banner or doing something a lot more intrinsically easy to grasp – why it would get someone to come into a store.
Nasser:
So I’m going to ask you, how do you do that? Right? How do you connect these things? How do you drive greater in-store traffic? But before I do, I’d like you to kind of consider the fact that right now, with all of the disruption that’s happening, one of the things that I’ve certainly been told a few times now from, you know, prospects and that kind of thing is obviously in the local optimization and local search space. There are platforms, that you, you know, self-directed platforms for optimization of these listings and local experiences. And what I’ve heard played back to me is, well, because of all the disruption that’s happening, you know, organic traffic is down in the listings space. And if your traffic is flat, then that’s a win.
And yay you right? And yay us collectively. First, do you agree with that statement? Or is should, you know, is flat the new up, for want of a better word?
Kyle:
Sure. So I think there’s a couple different ways to break that down. So number one, there’s more opportunity to fragment search than ever today. There’s people that can be getting, you know, restaurant recommendations from TikTok or Instagram or Reddit or Google or AI platforms.
So search fragmentation is and the opportunity to get a good experience on a lot of different platforms exists, which from a marketing standpoint, makes your KPIs incredibly hard to track year over year. Right? So that I think that levels up into that is flat. The new Wow, everyone is doing amazing in marketing. I think that’s playing out a bit there.
The other part is that – all tracking is not created equal. As marketers, I think we’ve been spoiled in how much information Google has been giving to us and how much of a monopoly they’ve been for the last couple of years, wherein it was pretty easy to track almost all of your local search discovery because it all was happening on Google.
When people start to be, you know, doing top of funnel searches and ChatGPT, a lot of your impression share it looks like is going away, which is why a lot of our clients are seeing, you know, impression drops, but driving directions actually increase. And I think what’s happening is you are dealing with these AI platforms for recommendations, for refining what it is you’re looking for, for you’re getting these recommendations.
But at the end of that funnel, I still have to go back to Google, to actually click call or I still have to click driving directions. So we’re seeing that data. We’re just missing a big part of what’s happening on other platforms before they make it to Google for the last mile.
Nasser:
So are you basically saying that if you continue looking at things and measuring the local search environment and performance the way that you’ve always done historically, then sure, your expectation, the best you can expect is that you’re flat year over year?
Kyle:
Correct.
Nasser:
But if you start looking at things in a much more holistic way from a measurement perspective, and you integrate local search metrics into a broader, integrated story, then you need to raise your expectations in terms of what this these activities can do?
Kyle:
Yeah, absolutely. I mean, if you’re not looking at local search in terms of social platforms and AI platforms and Reddit and pretty much everything in between, if local search to you is still just Google Business Profile, you are massively missing how your customers are finding you and potentially not finding you.
Nasser:
So if I’m leading local marketing today, at an enterprise, what should I focus on?
Kyle:
Okay, the number one thing that I would do if I was in charge of a Multi-location brand is make sure that I have my data and the facts about my business as locked down as humanly possible. So what’s really interesting is, no matter, you know, what type of Multi-location brand is, there’s going to be some regional and local differences and why that is essentially important is if you don’t know the truth about your own business, there’s definitely no way that social platforms and AI platforms and Google and everything else is going to as well.
Restaurant menus change, the features of a location change, and consumers really want to plan what it is to visit your business. If you’re not giving them all those details, you’re in trouble. So you got to get your data locked down. Once that’s locked down, I would be tripling down on reputation management in. It does not matter what platform you’re looking in, whether AI is getting trained on that.
You know the copy included of these reviews. Google having the world’s, you know, biggest corpus of reviews, you know, pretty much for any category. This is the foundational building block for how you are successful in what’s going on today and guaranteed what is going to be the future. So I would be incentivizing employees, to actually generate reviews.
I would be monitoring this. I’d be figuring out and finding operational challenges from this data so that I can fix my business. It is a treasure trove that I would be, you know, as invested in as humanly possible. And getting everyone around me essentially tied into that metric. Like everyone tracks revenue, everyone track sales. I don’t think at its C-suite level, every C-suite is looking at what is my average star rating?
And I think that is just as important as a leading indicator for revenue. I would be injecting that type of, you know, value into what I want me and my employees to care about.
Nasser:
Why do you think the AI platforms and the AI modes care so much about that?
Kyle:
It’s in a format that’s so easy for them to understand, so that the way that someone will, number one is user generated content, right? So again, you go to a brand’s website and it’s going to be positive sentiment for that brand. What you get is real life. I mean it’s why Reddit is blowing up so much. It’s supposed to be and it’s probably as close as we can get to authentic feedback around products and services on the internet. It’s just people having conversations.
That is exactly what a review is, and AI has a really easy time ingesting and breaking down written copy as it relates to a business or a product, and then turning that into, you know, part of how do I recommend, you know, businesses and or service or products? So the format and having be essentially being extremely text heavy makes it a format that’s very easy to train models.
Nasser:
So AI loves reviews because it’s in it’s in its or from its perspective, exceptional content made accessible in a structure that it is designed to consume and analyze.
Kyle:
Yes. And it’s very easy to understand if it’s current. So the average review, I mean, pretty much every review has a date. It’s when it’s written. So it’s very easy for AI to train on new content related to products and services and businesses that it knows is relevant to the here and now.
Nasser:
So, Kyle, I’m only half joking when I call you the LeBron of this space because you eat, breathe and live local optimization. And as somebody who is so embedded in this industry like unlike anybody else I’ve ever met, what signals are you watching to know where I will really reshape local search?
Kyle:
Sure. So I am a little bit on the fence in terms of spending my time figuring out how this works now, and then projecting what I think is going to work long term. And I think there AI is still a little bit in in its infancy, and it doesn’t have all of the years of figuring out what works and what consumers want and all of those things. So the user testing is still, you know, nascent. What’s working now is really a lot of the tactics that used to work in regular SEO many years ago. So, getting, you know, into blogs and articles and, you know, best of lists and a lot of like traditional digital PR stuff is absolutely what’s working today. Long term, right… And Google figured this out. Every link is not created the same. And every, you know, website is not created the same. And quality content is supposed to be what ranks.
That’s not what’s happening today. And it’s very very easy to game those results today. So you know, if I have to hit my, you know Q now numbers, these are definitely the tactics that I’m doing because because they work. I am absolutely doing a crazy amount of digital PR. Long term, and this is probably a bit of a boring recommendation, but I do think that quality content is going to win out.
That is, as an organization, the thing that you can invest in long term that doesn’t have an expiration date. If you create what consumers are looking for and answer questions that they have during that buying process, that is essentially what is going to work long term. If I have to tactically turn that into something, what I go to a lot of brands and say is, hey, you know, you’re a service-based business, why don’t you put your pricing online?
And it’s like, oh, well, because it’s different and it changes and cool. But it’d be wonderful for your consumers to understand how much in on average something like this cost. You could stand out from your competition. Why not do that? Take a risk, put that on there. Those are the types of things, I think long term that are going to really pay dividends, whether we’re talking traditional SEO or AI search.
Nasser:
So here’s the shift. Despite the hype, AI hasn’t replaced local search. Customers still rely on accurate listings, trusted reviews when they’re ready to buy, and the brands that win are the ones that are getting the basics right, today, while quietly preparing for tomorrow’s AI driven changes. Now make it happen. Follow Shift Happens. Leave us a review. There we go with the reviews, and share this episode with your team.
If you have any questions for the podcast, email us at shifthappens@dacgroup.com. We’d love to hear from you. Thank you for your time today, Kyle, and thank you for not, knocking over that plant a second time.
Kyle:
My pleasure, it was great today. Thank you very much.
