David Andersen: When people got Google and search engines, that changed how people get information. It’s changing again here. A lot of people are much more comfortable asking AI for a recommendation on something where previously they would’ve clicked into a whole bunch of websites and done their own research.

I think it was last year where I realized I found my dentist through AI that I was like, there might be a shift in how people are fundamentally searching for products.

Jeremy Balius: Welcome to Go-To-Market Playmakers, where we bring you winning go-to-market strategies from the industry’s best. Each episode, we sit down with B2B tech and SaaS founders, executives, and industry playmakers. Whether you’re scaling a startup, refining your go-to-market motion, or driving revenue growth through a channel program or partner ecosystem, this is where you’ll learn the plays that work.

I’m your host, Jeremy Balius. Welcome to season two. Today’s theme is “AI Search Visibility for Go-to-Market”. I’m joined by David Andersen.

David leads AI and engineering at BrandViz, which is an end-to-end platform helping brands from scale-ups to global enterprise get found and recommended across ChatGPT, Gemini, and other major AI engines. This is a fascinating conversation. I’ve taken so much away from this to implement in my own thinking and into my day-to-day in ensuring that our brand gets found.

I hope you take away as much from this as I did. Let’s get straight into it.

Hey, David, thanks so much for joining me today

David Andersen: Thanks. Thanks for having me, Jeremy.

Jeremy Balius: I’m really excited about what we’re talking about here.

But before we jump into all things AI, search visibility, and everything that entails, can we start with your origin story? Can you tell me about how you got to where you are today?

David Andersen: Yeah, in a… I, I like to say I’ve been working on AI since before it was cool. I’ve been building AI systems for 10 plus years through data science and various different applications across a number of industries including doing it for a whole bunch of network analysis and stuff like this at Google.

It’s been a… AI in general has been a passion of mine for a very long time, and with the, the rise of it in society in general, but also marketing it’s felt very natural kind of moving in and helping people understand how to show up and at a fundamental level how it works.

Jeremy Balius: Think what’s fascinating is that Forrester Research is showing that 89% of B2B buyers are now using gen AI in some form as they’re researching as part of their sales cycles. What does that mean for buying journeys today that didn’t, that it didn’t look like t- even two years ago?

David Andersen: Yeah. One of the major differences, is how people get information, right? And you saw the massive shift 20, 30 years ago when people got the internet and Google and search engines, and that changed how people get information. It’s changing again here, right? In that a lot of people are much more comfortable asking AI for a recommendation on something where previously they would’ve gone to aggregator websites or talked to friends or gone through review or, clicked into a whole bunch of websites and done their own research, right?

I think it was at the point last year where I realized I found my dentist through AI that I was like, this … there, there might be a shift in how people are fundamentally searching for products. And the absolute back and forths that you can now have in a discussion, and you kinda ask AI a question, it gives you responses, you interrogate it, and it’s much more like a, a conversation than previously it felt like research work to do discovery and find information

Jeremy Balius: Is it the conversational aspect that makes it more intuitive than a simple Google search?

David Andersen: Essentially, like in my mind, the AI platforms that exist are fundamentally AI is an interface layer, right? It’s… The main thing it did is enable people to get inf- access information more easily or communicate what’s in their head with a computer in the same way that you would chat with a human kinda, right?

And the ability to do that has, for some people faster than others, changed how they want to interact. And when you can interface with things in different ways, it changes the information you get and how comfortable you are having the conversations. This might be a little high level, but at a basic level it was almost impossible to ask of Google some of the questions people are asking of ChatGPT now, because it goes out, it does its, all its own research, and it pulls back what feels like an expert answer.

Jeremy Balius: I think it’s also w- so accustomed to a search producing million results plus , right? Do you think it’s, the compilation of the recommendation that’s so attractive to somebody searching?

David Andersen: Oh, 100%, right? When you get one answer or a short list of possible answers, that feels so much more approachable than a wall of search results, right? There’s a whole bunch of marketing studies done a long time ago about the appropriate number of options to present to a user.

You- the b- best ballpark being three or four, right? And this is exactly where AI lands for most people that are doing searches

Jeremy Balius: I think that just going back to the stats cited in my question a minute ago, I just think it’s so fascinating that close to 90% of B2B buyers are using AI in some way or gen AI in some way to solve their problems.

David Andersen: Yeah.

Jeremy Balius: Do you

David Andersen: I’m

Jeremy Balius: surprising to people you speak to?

David Andersen: I think so, right? It doesn’t seem intuitive. And the other unintuitive stat is that the, typically the highest users of AI in any company are executives,

It’s the decision, how do I get information in as quickly as possible, right? Obviously coding aside, but in– at least in terms of AI, it is…

The B2B market feels much less, I’d say, explorable than the consumer market, right? At least to me, if– as some intuition, right? If I’m trying to solve a particular technical problem where I have an understanding, I… There’s not as much like marketing and blasting and stuff like this for B2B products that exist.

And businesses are typically much more personalized and particular about what they need and how that fits in than a consumer might be about like a general product. And so it makes some sense, but also the fact that I guess most companies just have AI licenses and are trying to use them as much as possible and this might be self-reinforcing as well, right?

It could be a number of things that are making it, so much higher. I think the, the stats are like about two, maybe three times higher than like consumer use just inside business, yeah.

Jeremy Balius: Oh, fascinating. I hadn’t heard that. So you’re seeing that predominantly it’s overweighted toward e- executive use to parse large data sets to help them make decisions, to compile reports and things like that?

David Andersen: Pretty much, right? Or just going out when you’re doing basic decision-making and research is a very useful tool to enable this. The, I guess the lower down towards implementation, it’s just a kind of different kind of work. And AI lends itself so well to compiling reports and doing research and all this kind of stuff.

Jeremy Balius: Hey, drilling down into how we were just discussing about, a million search results versus a single recommendation, when we think about where one would rank in a particular search and we’re thinking about go-to-market for my product or my solution or service, and ranking high enough to be found in the search engine by a searcher versus being recommended, how am I- how should I start thinking about that as y- know being highly positioned on Google versus a- and potentially skipped by ChatGPT, for example how are we weighing that differently, and how should I be thinking about that?

David Andersen: Yeah. So I do wanna preface this with like Google’s still around, right? And Google is still the major volume that a lot of search traffic is coming through for most businesses, right? And even then with the AI layer they have over the top, there is some alignment here. But there’s a couple of pieces which is that all the search engine or all the like AI that exists, all the LLMs, they typically use different search engine backings in the back of them, right?

So while ChatGPT does touch Google a little, it also uses Bing and like other options to get an index of what’s available on the web and where it accesses, right? And obviously, Claude and Perplexity use their own or different ones that are there. And Google has a particular way of ranking. Bing has a very different mechanism for what they think is good content, and these different algorithms, even just from a ranking perspective, if you have four different major chat engines and they’re all using different ranking systems, there’s going to be differences in bias.

But on top of that, the way and the questions that are asked through AI… ’cause if someone’s talking to AI, typically they have all of their history and all of the context that AI has about them, right? When you’re talking to ChatGPT and you have a paid session, it’s not just, what’s the best kinda like car dealership near me that you’re asking, it’s all the like basic context that model has about you and what kind of person you are and stuff like this that it uses to create a number of like fan out queries.

And so typically, when someone’s interacting with Google, the searches that you get are much higher weighted towards like keywords. Whereas you, you get a lot more long tail or varied queries that even the kind of question that is being asked by the user gets turned into a whole bunch of different questions that eventually go off to search rankings.

And so the kind of space that it covers is much broader and different to Google, right? On top of this, the search engine kind of results that it gets back doesn’t necessarily mean that those are what fill into the answer that actually gets shown to the user, right? So ChatGPT might fetch 20 or 30 sources and then cut down to five or six of those that actually get used to reference the response or get shown to the user.

And so the battle is just as much kind of ranking high enough to show up, which from a Google equivalent is, let’s say, top page or two, and then getting through the AI filter to be worthy enough to actually influence the response is a second level challenge that you don’t have on Google.

Jeremy Balius: So interesting. If we’re thinking about being visible or being found through recommendations by, as you mentioned, ChatGPT, Perplexity, Gemini, and Claude, and all the others, versus being found and selected or clicked on in search engines,

David Andersen: Yeah

Jeremy Balius: think of the latter as… or we think of influencing the latter as SEO.

Try, trying to rank higher through search engine optimization to be found in the search engine result page, and hopefully be clicked on so as to elicit some form of interest or intent. but being recommended is different, and that’s sprung up this, what’s a, a lot of people are calling generative engine optimization, or GEO In the way that we were just describing that, is GEO just SEO repackaged?

David Andersen: I, if you… So if you take SEO at its basic component, which is I wanna be ranked in search engines and have people click on me, then the intent behind it is very similar, right? They’re trying to do a very similar purpose in a business. Get organic traffic, let’s say, right?

Jeremy Balius: yes

David Andersen: But the actual strategies and mechanisms you use for this are a little bit different.

I mentioned before about how SEO essentially is all Google, right? That’s been the main player in this game for 20 years, and they have very particular strategies for how that’s ranking, right? And even now with kinda GEO coming through and Google using a more AI mode stuff, the strategies that they’re using and what’s working on Google is shifting I, but I will say from like an SEO perspective, and if you’re trying to show up in AI models, the strategies that you use are like materially different, right?

The way you structure your content for optimizing for either of them changes significantly. Like backlinks are quite useful for like SEO, but increasingly not as useful for ranking on AI models. There’s a difference in how you might wanna structure your metadata between the two. And so while it is very similar intent, the actual strategies about whether you’re ranking on Google or ranking on a particular AI model, they have different approaches in practice.

And so in terms of like providing a service or like doing any of this, you will see kind of specialization for one or the other, I think.

Jeremy Balius: So tactics is something we’re gonna deep dive into. Let’s hold off on that ’cause I wanna pick your brain on tactics in this conversation. But to summarize what I think I hear is that if we’re comparing SEO and GEO, the intent is the same. We want to be found organically by those who are for solutions to the problems that they’re facing or for the products that they need to run their business or to s- to switch out that are no longer working for their business and they’re looking for alternatives. And the optimization is to be found, whether it’s by search engine– Sorry, whether it’s through search engine or by an LLM, but the tactics of appearing in either are drastically different.

David Andersen: Yeah, they can be. The core fundamentals are probably similar, rank, then get ranks, have people talk about you, et cetera, but the specifics do change, yeah

Jeremy Balius: yeah. Ah, that’s fantastic. That’s very clear. We’ve been talking about being recommended or being found. We’re talking about AI visibility. Can we talk about what visibility even means in this context? What are we referring to here?

David Andersen: Sure. Yeah. And this is… I guess because in Google there’s one thing, which is there’s a link that shows up and people click on it, right? That’s very simple.

Jeremy Balius: Yes

David Andersen: In AI, there’s a few different measures I like to use to understand how visible you are, right? Because it is a little more complicated than that.

The, probably the first and simplest way measure is we call citations, in that your website is used as a source when the AI goes out to the web to, find information, right? Whether it’s mentioning you directly, it’s just referenced and pulled to form a response to a user, right?

This gets you as part of the conversation. It’s useful and is the, the Google indicator of you’re shown as part of one of the search results. The second measure is a mention, right? You are mentioned by name somewhere in the response that a user can actually see, whether this is your link being dropped in, or your company name, or whatever your product is showing up directly to a user.

This is typically a slightly harder bar to cross than just being cited as a source, and can come from kinda anywhere. It could be someone talking about the internet. It could be, like, PR campaigns or something like this. Irrelevant of where it actually comes from, your name is being mentioned to a user.

Beyond this are a, a higher class of signals, which is that you are ranked or recommended for a user. So beyond just directly mentioning you, often AI will come out with a core list of suggestions or a recommendation for what product or option to go with, right? The, “Hey, given your situation, this is probably the right option.”

Showing up here as the top on the list of their ranked options or showing up as a clear recommendation is the strongest signal you can get from AI, and this is typically where you actually get a lot of the kind of buying intent. It usually comes a few questions into a conversation with AI, right?

Typically, it won’t be the first one. After you’ve added a few clarifiers and worked it out, that’s when you start getting recommendations or being, like, getting ranked options.

Jeremy Balius: Okay, so are where you’re being cited, your brand is being cited by the LLM

David Andersen: Yeah. Or your website is, yeah

Jeremy Balius: your website is being cited. The mention is where you appear in the answer

David Andersen: Yeah.

Jeremy Balius: LLM,

David Andersen: Yep

Jeremy Balius: and then the recommendation is actual amongst the list of recommendations. Here’s the top three, top five, or whatever products that suit your current needs.

David Andersen: Exactly. And AI loves to give those, right? You ask it a question, it’ll always give you an option. You showing up as that option is, it’s like the top… It’s being ranked one on Google essentially. That’s the equivalent

Jeremy Balius: Are we able to understand, if I’m just gonna hone in on recommendations for the moment, are we able to understand how or why it’s recommending a brand over another?

David Andersen: Yeah. And like this will change a little bit depending on the actual AI model, but like fundamentally what AI is doing is pattern matching, right?

little bit how it differs from just Google search is that AI loves nuance and this is… goes into a little bit of the tactics, but like typically it will suggest an option that is tailored specifically to you generally, or just sometimes it will say, “Hey, this is just the industry standard and this is the best and I will use this.”

But fundamentally it likes to give responses which are particularly tailored to you. It will… I’m not saying it’s smart, right? It has a pool of data that it has access to, and based on the question you asked it, it wants to give the most like predictable response. And so if you say, “Hey, I am let’s say a B2B SaaS company and I have this particular requirement.

Let’s say I, I need to keep my data in Australia,” it will suggest like a hosting provider or something like this that meets those specific requirements. Whether or not it’s good, it’s just from the information that it has available there. And it is noisy too. If it gets different sources there’s a bit of randomness in every single response.

And so you might ask it the same question and get three different recommendations on three different days. So there’s no like guarantee. The best you can reasonably do is make sure you’re in the data, make sure that whatever archetype you want, you have the positioning to say, “This is the right archetype for my business.”

And the kind of proof points that when it’s doing double checking that you have validation that you haven’t just made it all up, if that makes sense.

Jeremy Balius: That does make sense. That elicits a couple of more follow-up questions. First one is, I’m thinking about this for my business, in what ways can I be thinking about content that I publish to, elicit this type of understanding from the LLM versus third-party affirmation, whether that’s review sites or directory listings or external reviews or whatever else?

How should I be thinking about that? ‘Cause it sounds to me like you’re saying that it’s taking all of that into account.

David Andersen: Throughout a, So there’s probably two stages to think about here, right? Stage one is, do you get considered in the list of options at all to begin with, right? Which is essentially when someone asks a- an initial query or they’re looking for a problem or they’re finding this and it goes out to the web, do you show up at all in that initial kind of searching?

After that point, a lot of what people will do, if you’re talking to AI, you’ve had a conversation, you ask follow-up questions in detail. At some point, the question will probably be, “Hey, what are the reviews like?” Or has it thought about it this way, right? As part of, a small step back, I like to frame AI for any business as like a sales guy, right?

Your goal for the AI is to arm them with all the knowledge it needs to answer any questions a prospect might have about what your business is and who it’s for and like any proof points and stuff like this you have, right? That’s the, fundamental aim, is you treat it like, I have a sales guy, I wanna make sure it has all the information, so any questions people ask, it can answer it.

And to get back, a little to, like, how you do this, this all happens after the initial do I show up at all, right? And so the content you put for that is fundamentally a little bit more of your basic search engine strategy of making sure your website ranks well, is targeted towards the kinda avatar that you’re targeting as a business, and then ensuring from there that you have the content depth and review and stuff like this.

You can ask probably a bunch more follow-up detail questions and we can get into that, but it’s a pretty large kinda space. Yeah.

Jeremy Balius: Yeah, absolutely. And here they come.

Here’s the next follow-up question. You mentioned earlier, that on any given day, the answer might be different due to the randomness of the response. Can you tell me a little bit more about that? Because that’s materially different to the way that business leaders have been thinking about how they can invest in being organically found.

There was some type of assurance, maybe not over the long term, but at least some type of medium term that, that where they’re showing up in search isn’t gonna fluctuate too badly unless there’s some type of core algorithm update or something significant happened. But by and large it’s r- pretty set over the medium term but having things fluctuate day by day, tell me more about that, ’cause that’s fast.

David Andersen: Yeah. So I’d say there’s two ways that this shifts and changes, right? The first one I’ll talk about a little, which is that about how search queries are formed and kind of noise. So with L- all LLMs, they are built in such a way that there is noise and randomness in the response, right?

I think this was originally when they first came out, it was called temperature. It’s just how creative the AI gets on everything, right? So whenever you ask a question of AI, the question that it decides to go and ask the search indexes that it has access to can vary. So it might just ask a different query of the search index, depending on the conversations you’ve had in the day and the slight differences in context.

And so it will be slightly different every single time just because they build randomness into these systems. The query it makes in the back end of the search index probably won’t change that much, but the actual query changes and the fan out in the way that it builds those. So that’s one way that it changes.

The second is that in Google, your ranking might fluctuate a little bit, right? But if you’re ranked, say, fi- fifth or seventh or eighth, it doesn’t matter too much. But on each query that goes out from the AI, it will only fetch, let’s say, five responses for each query. And if you fall either side of that kind of line, it’s the difference between showing of like you don’t exist or you do exist, right?

And so small fluctuations in that individual query, because all of the fan outs are just a little short list, it’s like one to zero rather than slightly up or down on the same page, which is why slightly different queries, slight variations in like search index can result in completely different answers.

Second part is around AI models. They keep changing and they keep releasing new AI models every month or two. And all of them have different behaviors in how they construct queries and how they think about answering problems and the number of kind of targets they go out and search. ChatGPT is the one that is the wildest for this.

I think the different versions and the different thinking models they have materially go out and search the web differently. They have different biases. I think it was 5.4 that they had a few months ago. It’s still around. It just loved Wikipedia and government sites and stuff like this, and then they changed the model, and it completely changed the priority of the sources that it was going after and the way that it was structuring its queries and all of this.

And so every time a new model comes out and we roll over to the new testing, there’s just a massive shakeup for a lot of the companies, that there’s a lot of winners and losers and changes just in how they’re going out and information, and it’s just not stable compared to Google, which has the big public launches about, “Hey, we’re changing all these things, and this is the new direction.”

And ChatGPT’s like, “Oh, we’re just searching differently next week. Good luck.”

Jeremy Balius: Is that why for a while a lot of responses we saw come through were citing Reddit, and then after a while not anymore?

David Andersen: Yeah. Like it’s… They can just change these biases. Like different AI models have very different preferences about how they get sources. But yeah, they can just change in the back end how they’re making queries and how those queries are biased, and they will do this for a number of reasons. It could be that, like I think Perplexity had a lawsuit against Reddit a while ago where they were crawling it too much, and so they decided to stop it.

Or they’re just like, “Oh, I think we can give people a better search experience by twiddling these things,” and they don’t have the kind of the built reliance and reluctance to make systematic changes to how things occur. And so you’ll just see some of these major sources go, disappear, change overnight when new model releases come out.

Jeremy Balius: How should we be thinking about that environment as a GTM team in wanting to be found, in wanting to invest our efforts and time into activities that l- beyond a few days?

How should we be thinking about that? Is this is this just signing up for a wild ride, or are we able to think about, affecting change or affecting how we are appearing in LLMs or recommendations that, that, that can survive that volatility?

David Andersen: Yeah. So I will say that while this might affect kind of hacky tactics more than anything, a kind of basic approach to ensuring that all the information that you want and positioning for your company is out there, or that you’re, like, communicating clearly about what your company is and who it’s for and who your products are for, and ensuring that you have the right signals, this kind of strategy seems to…

While there are fluctuations, it seems to be reasonably long-lasting at the moment in that the basic principle of what an LLM is trying to do or what a search engine is trying to do is find useful information for users. And so while there might be some fluctuation in how it does that, typically it shifts everyone at once.

And if you kind of over-index in the very short-term strategy of what seems heavily weighted for an individual model for a short period of time, this is a challenge you’ll constantly be chasing, right? It’s the kind of hacky strategy to boost yourself to the top.

Jeremy Balius: Yes

David Andersen: But the kind of long-term basic strategy seems to just work no matter what, and there’s some fluctuations, but it’s a better long-term stable approach.

Jeremy Balius: Yeah, I can see that and I can understand that for sure. The hacks and the tips and the tricks and all that stuff comes and goes, but there’s a foundational aspect that seems to be ringing true for me here in the way that you’re talking about it is standing for something and being meaningfully differentiated for something that drives their recommendation for a specific person. Does that sound right?

David Andersen: Yeah. That’s exactly it, right? There are some players that are large enough that they just need visibility, right? You’re the large company, so they’re default and it just, it- as long as they’re showing up, it’s good. But everyone on the internet’s talking about them, so that’s not a problem, right?

someone’s looking to listen to music, Spotify’s gonna come up as a recommendation. But your niche music playing app needs to really broadcast why it’s differentiated, who it’s for, and what the market is for that, and why they get returns to really… it’s marketing. It’s a billboard, right?

It’s, you gotta provide this ammo, and you need to differentiate yourself ’cause you’re not competing on the main keywords from a, like a search engine perspective.

Jeremy Balius: In B2B tech land, there’s a lot of sameness. know, you’ve got a lot of service providers who’ve built services on top of the same vendors, the same platforms, the same s- security outcomes.

Are these types who’ve never really needed to be clearly differentiated in the past facing a future where they will need to figure out what makes them different so as to be recognized by LLMs to recommended?

David Andersen: This is I guess part of the question around how much LLMs will eventually take over how people, go into the… search the internet and find it, right? But even right now say I– you see an ad about a company or you hear about something, right? At a very basic level, you need to at least have the answers for who you do, what you do it for, and the kind of questions people are gonna have, right?

Say they see an ad for your company, they go to an LLM and they’ll do a bit of research about who you are and if you’re a good fit for them or something like this, right? It’s increasingly just from that perspective, thinking about all of your presence on a web as how people are gonna discover and in-inform themselves about whether you’re the right fit to talk to as a brand.

That will, I think, inevitably become much, much more common, right? you have a sales meeting with someone or you do a reach out, the secondary check is go ask AI if they’re bull— or something like this, right? And yeah, I think it’s increasingly important as people use this to discover products.

There are a number of products on the web that feel like they just got an absolute boom by being the default recommendation for stuff in AI, especially a lot of software tools or development tools, hosting, stuff like this. Yeah

Jeremy Balius: If we’re thinking about LLMs or being recommended as a attribution source for prospective buyers or even just leads, if– I be thinking about that as just more work, or does this replace something else in my business? Or do I need to figure out how do I keep up with what I’m already doing and get on top of this? Where do I start with that?

David Andersen: Yeah. This is a very common challenge, right? A lot of businesses are doing some version of getting themselves visible, right? It doesn’t necessarily need to be a a starting from zero. I… A lot of the kind of initial work we do with a brand is taking all of the content and information they have and just making sure it’s in a way that is visible and repurposed and reused, right?

You’re running webinars, you’re running content, you’re putting stuff on LinkedIn, you’re doing it in a number of different spaces. Making sure all the work you’re currently doing is also, let’s say, available on the internet, on, on your website rather. Or doing your best to gather reviews and stuff like this across a number of sites.

yeah, all of this is a little bit more or different work to what you’re already doing, right? The slight variation of if you’re already doing some SEO, adding a little bit more strategy and stuff on top of this is a little bit more work. I You do get, I would say, quite a lot of reward for just a little bit of work to begin with.

Let’s say a lot of businesses, they’re… They’ve vibe-coded a site or they like, they pulled something together and it’s missing some basic technical stuff that’s making it not renderable to AI. Fixing this, just making sure what’s there is good, is like a very simple first step. Or getting a basic set of content on your website from your internal brand guidelines or positioning just to say who you are and what you do and clearly represent this information not just in like a marketing language speak, but in a technical kind of this is what we do and this is who it’s for and this is why it’s whatever, right?

And so that as a baseline is probably an easy win that most companies can get to even if it’s not the main strategy that you’re employing long term.

Jeremy Balius: I wanna take a a turn in the conversation and refer back to your background as Google engineer when you were building probabilistic models of network failure and using weak signals to work out which parts of networks were breaking in real time, non-deterministic type. What did you see then that led to founding BrandViz?

David Andersen: Yeah, I… This whole space at the moment is a whole lot of weak signals for, like, how everything touches together, right? Marketing attribution, how you walk through all of this is like a… attribution is always a problem in marketing, but search used to be, like, a little bit stable and you get some strong signals, right?

All of solving the challenge of what are the right things to put up and how do they move the needle and how do you actually get signals back through to understand whether what you’re doing is working is a very disjointed and similar challenge to, given I have a bunch of signals that start in certain cities and they don’t end up in other ones, how do I work out, what’s connected in the middle and what’s broken is…

I, I– At least the approach we went to work out what works and stuff like this is a, a very similar kind of challenge

Jeremy Balius: So tell me about BrandViz

David Andersen: Yeah. So fundamentally, as a company, we believe the challenge in this space is less about like understanding where you’re positioned and more about the kind of the execution and actually like going… getting the effort, adjusting the websites, going through and delivering the content to actually kinda get visible, right?

A lot of marketing teams, especially small ones, are gated behind, let’s say, like technical teams or like delivery complexity, like in high content costs, stuff that just is a wall behind getting visible. So at BrandVis, the main goal is we start with kind of a fundamental, this is how you’re visible and this is how you’re showing up.

From a kind of opportunity and you’re– this is how you’re talked about and this is how you’re represented and this is how you’re recommended, the… who you’re recommended to, and take this and build a strategy and then deliver kinda end-to-end in kind of a, a complete the full loop so that we can deliver kind of the website updates, the, the content, and give you all the kind of guidance and clarity that’s needed to kinda step this through and start to see kinda feedback cycles.

Because a lot of this market at the moment it’s very constrained on delivery and just kinda clarity on what the kinda the next right step is.

Jeremy Balius: Yeah, it’s amazing, and it’s an amazing product. Full disclosure, we at Filament are using BrandViz for those listeners, who are thinking about it, and highly recommend it. one of the things that I really appreciate what you’ve built is in the way that you were just talking about the clarity, is pulling apart from a logical perspective how different types of structures and context could potentially influence overall visibility as well as a whole bunch of other metrics that that you, you put in front of it.

So the way that you’ve taken this to a dashboard level I think is phenomenal. We get, we get pitched this type of stuff all the time by SaaS vendors, and we went with you guys because the way that you’re structuring it and thinking about it is just so amazing and very helpful.

David Andersen: Yeah, I, one of the biggest challenges, at least from like a data point of view, is not so much collecting all the analytics and the data, it’s turning it into what is the the key takeaway and the the insight that actually allows me to do action, right? I… And this it’s a constant ongoing challenge to make that as easy as possible for people to understand, right?

It’s… But I’d say there’s a little, my, my… We have a very strong background in kinda data analytics and data science, and the whole field of taking very complicated sets of data and turning them into things that kind of executive leaders and marketing leaders can use to make decisions. That’s the, the background there.

Jeremy Balius: The other part I appreciate about it is you need thick skin for the amount of not negativity, the amount of, the, the amount of shortcomings that, that appear. but I appreciate it because it really forces you to think about what is it that you stand for, whom are you selling to and serving by way of your company’s mission, and how are you projecting it in a way that can be understood?

that, I think is missing from a lot of businesses, that, that abundant clarity of whom are you serving and why and how.

David Andersen: Yeah. It’s a fundamental challenge of a lot of businesses, especially small ones, right? The challenge of who actually am I? Cause if I just blast out that I solve this problem for everyone, it, it’s a weak signal and you’re just gonna be overrode by larger players. That’s a universal challenge in marketing.

It’s that cut through, and it matters just as much for when your ads as, as it does for AI positioning, right? It’s a challenge of any kind of like small or medium business is just that framing.

Jeremy Balius: So I think congratulations are in order. At the time of recording this, you’ve just been accepted and are well underway, I see, with the Startmate Accelerator program. How’s everything going with that and what’s next for BrandViz?

David Andersen: yeah. Thank you. No it’s been a kind of wild month after kinda joining Startmate and chatting to so many different customers and users over the last month. And I guess it’s… We’ll see how this goes. We got demo day with them and a lot of kind of very ambitious targets over the next few months as we kinda push out and scale and work with all the businesses that are, like, starting to come through.

We’ll see where we are in a few months, but it’s probably gonna be kinda… It’s gonna be an exciting few months from here for us.

Jeremy Balius: Awesome. I love to hear it. If I’m a GTM leader, marketer, business owner, founder, I wanna start figuring out where I stand and what to do. How can I make best use of BrandViz’s audit?

David Andersen: Yeah. The free audit that we have up at the moment is essentially just a, like a technical scan of the website, right? It’ll mainly run through, it’ll highlight any kind of conflicting information you have across pages, if there are any key technical blockers that are stopping your website from being visible, as well as a lot of just small improvements or tweaks you could make to make your site more visible.

Just, technical SEO hygiene stuff. Comes with, at least for some of them, just copy-pastable instructions that you can give to a dev or your AI of choice to deliver that. but mostly it’s a framing or understanding for where you’re currently at, right? And this is a basic sanity check for anyone that has a website up.

It’s good to at least know where you if there’s anything you can easily fix today. After that, for any business that’s trying to understand this, there are a number of, tools or platforms, something like this, that you could go out and get a free visibility audit, an understanding of how AI’s talking about you these days.

Obviously we do have this, and there is a trial up at the moment if you just wanna see that. From our perspective, get like a qualitative picture of how you’re being talked about and how you’re being represented to users. And understanding at least these two basic framings allows you to start making decisions about it, right?

The general strategy of is this something we need to change? Say you’re going to market with like a, a new product or you’re looking to growth, you wanna understand that as part of your strategy when you’re putting out press releases and marketing and all this kind of stuff, are we being talked about the right way, and how can we reuse all of this kind of internal framing we have about this product to turn it into content and stuff that is kinda parsable by not just humans, but also kinda AI.

Jeremy Balius: Awesome. For those listeners who want to know more or get in touch, where’s the best place to find you?

David Andersen: You can email me directly at david@brandbiz.ai, or if you go to our website brandbiz.ai, you can, there’s contact us, there’s free audits, there’s anything you want there.

Jeremy Balius: Fantastic. Awesome. I appreciate your insights. This has been so helpful. Thank you so much, David.

David Andersen: Thank you very much for having me, Jeremy. It was great.