Podcast Transcript:
[00:00:00] You don’t rank number one in ai. You either qualify or you don’t. So let me show you how AI actually decides which multi-location business gets recommended. Hey, welcome to the [00:00:15] default Answer show. My name is Christian Hustle, and in this episode.
We’re talking about how AI decides which business gets recommended in search, Let’s start with some foundational concepts on what AI systems actually do when they’re [00:00:30] trying to recommend a brand.
Because it’s important to know that AI models are not crawling and sorting pages like traditional Google search result list. Instead, they’re synthesizing search indexes, knowledge graphs, review [00:00:45] data, structured content, and they, they do live lookups and often it is being, but sometimes as is Google as well.
Also very important they are looking at business profile signals. So let me break this down and explain it in very [00:01:00] simple terms.
In traditional SEO for the last, you know, many years you competed for ranking in AI systems, you compete for recommendation eligibility. You compete for proving yourself as a brand to be the [00:01:15] best answer possible for the AI system to recommend your brand to the user.
That is what we call the consensus factor. AI is trying to answer what is the safest, most defensible business that I can answer the user? And for that to [00:01:30] evaluate which one is really the best. It’s looking at review agreement. It’s looking at category alignment. It’s, analyzing consistent positioning of your brand
and it’s really looking for no conflicting signals. AI doesn’t look for who has the [00:01:45] loudest signals, the best review, star rating, or who has the most locations in, in a brand. It’s looking for, which is the business with the most consistent signals out there. And when we start talking about signals, we can start talking about Google [00:02:00] business profile and your reviews.
Google business profile continues to be a structured entity anchor, and it’s, it’s being evaluated as far as the data goes to validate with what’s on your website, what’s in other citations. The reviews. The reviews act as a [00:02:15] natural language reinforcement to analyze if you’re positioning is exactly what the, what customers are experiencing.
The categories in your Google business profile is a semantic classifier to make sure that you are not contradicting yourself on your services, [00:02:30] on your category level, and really what your business does.
And it’s important to mention that. Rating does not mean that you’re going to be recommended automatically. It, it is that reviews language plus the volume plus topical [00:02:45] reinforcement is what is going to create this sentiment that is gonna help you with AI systems. Lemme give you an example. I.
When I look at seafood restaurants in Georgetown, Texas, I get these four options. First of all, it’s kind of interesting that I only get four when I go to places. But [00:03:00] let’s look at these four, right? One of ’em is not even a, a seafood restaurant. It’s actually a steak house, which is kind of funny that is showing here.
But we’re seeing Fish City Grill, Georgie’s and Catfish Parlor. When I go to chat, GPT, uh, this is [00:03:15] incognito, not logged in at all.
And I search for seafood restaurants, Georgetown, tx, which is obviously is not very uh, prompt. You’re not gonna search like this, or your customers are not gonna search like this on chat GPT or AI overall. But I wanna compare [00:03:30] apples to apples here and I can see that. Catfish actually jumps up in the list and when we look at number of reviews start ratings it, it’s actually out of the window because it’s no longer just going by start rating or number of reviews, [00:03:45] and it actually knows that this is not an actual seafood restaurant, which is really cool.
This is where it gets interesting because when you start searching for more complex prompts, which is what AI is built for, what is the best seafood restaurant for family [00:04:00] dinner that sells beer in Georgetown, Texas, again, we see that catfish right there completely competitive. Seafood restaurant is obviously their highest.
Tier category, but if we go deeper into more like the dishes and [00:04:15] more of like specifically catfish or, or specific dishes that they sell or they offer, catfish can jump up or down depending on alignment of the prompt versus what it, what AI knows about your brand.
I guess all that to say that [00:04:30] star rating number of reviews. I mean even a 4.6. Start rating business can outperform a 4.8 generic great service reviews. Because AI is not looking at the count or the start rating. It’s looking at the sentiment. [00:04:45] What are people saying about the business and does it match what the business says about itself?
Now, in the past, SEO became optimization for Google. Google was the big whale and everything was the. Really built around Google. But with ai, it’s actually [00:05:00] interesting that the Bing index, that means bing.com is being used to run some of the live web lookups. They are using, uh, Bing to validate facts before they even recommend a business to the user.
Which is why if, if your business isn’t clearly [00:05:15] understood across multiple data sources, AI is just simply going to hesitate to recommend your brand or specific locations if you run multi-locations. That is because it brings me back to a little bit more of a technical side of things, but this is structured data and semantic [00:05:30] and alignment.
And I don’t wanna get too technical here, but let me explain what I mean and what is structured data and semantic alignment mean? This goes back to your website. This means very clear headings on your page. H ones, H twos, H three. [00:05:45] Service, clarity, location, clarity. So really being explicit about what do we do?
What do we offer, where are we located? Whether you’re a single location, you know, you may just have a one page homepage and that’s your entire website, or you have 500 [00:06:00] locations, and you have location pages that need to align with what you have, what you sell, and what is that location, you know, doing out there.
This all has to be aligned so that you’re not creating uncertainty for AI [00:06:15] systems.
On the other side, schema helps machines parse everything, all the information that it needs much quicker without even having to look at your page. So let me know in the comments if you want me to go more in depth into Schema. A schema can be a video on its own.
But I [00:06:30] want you to remember something. AI doesn’t guess. What do you do or what the, your business does? It extracts what you clearly state on your website, on schema on, on all your different platforms. that’s why I review language matters more than rating.
Because [00:06:45] AI is reading the sentiment on these reviews and, and it’s instead reading adjectives. It’s reading service availability, it’s reading repetitive patterns. It’s building this contextual reinforcement of what’s on your website versus what are your [00:07:00] customers saying about your service or your product.
Think of reviews as machine language that’s right. Reviews is the machine language on how they’re validating a third party, meaning your customers, what they think and what they say about your [00:07:15] brand.
Now let me turn all this theory and concepts into something actionable. You can start your analysis today as soon as you’re done with the video. Hopefully you finish it all the way through ’cause the best is coming up. But if you wanna understand why you are or you [00:07:30] aren’t recommended,
start by prompting ai. Things related to your business and see who gets mentioned. Is it you or is it a competitor? If it’s a competitor, go analyze the review depth, go analyze their positioning, clarity. Is it matching what, what their website [00:07:45] says with what’s on the sentiment on the reviews? Yes. You’re gonna have to read some reviews there.
Then compare the category alignment. Is it matching the prompt better to their. Website and their data versus you. Maybe your category alignment is not where it needs [00:08:00] to be. There’s some misalignment there. Look at their website structure. Do they have very well positioning paragraphs with subtitles? And the idea just flows and it gives all the data that AI needs versus maybe your website is, is lacking.
It’s not [00:08:15] doing it right. What you wanna do is compare consensus patterns. You want all these patterns to be completely aligned so that you are not creating uncertainty for ai, and then you give AI a very obvious reason why they should recommend your brand.
Now if you wanna [00:08:30] take this a step further and you wanna see whether your business qualifies for AI recommendation eligibility, you can run a free Selecta audit. I’m gonna drop the link in the description below. It’s a system, an auditor that we’ve been building. For the last 12 months, it’s our V two.
[00:08:45] Actually, we had a V one back in the day. It’s gotten better and we’re actually using it with our clients, so we’re just opening it up. If you wanna go check it out completely free, just enter your business information, some of your, you know, category and things like that, and let the system run. Let’s see what you [00:09:00] can find.
Come back and let me know in the comments. Where did you find discrepancies? Where was misaligning happening? Or maybe you’re just crushing it and your business is already being recommended on most prompts out there. Either way, I hope you get some takeaways from this video.
Smash that [00:09:15] subscribe button, if you wanna watch more videos that are coming out here in our default answer show that are going to be helpful and are going to really set your brand to become the default answer.
Alright, I’ll see you on the next one. Keep hustling.
