← The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
Moburst CEO Gilad Bechar on winning in the age of AI-driven discovery
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- [00:00]
A
Hi, I'm Greg Kilstrom, host of the Agile Brand and here's a question for you. For the last two decades, the primary question for marketers has been how do we rank on Google? But what happens when the primary question becomes how do we become the answer for an AI? Agility requires not just adapting to new tools like AI, but fundamentally rethinking the systems and the organizational structures that support them. It's a shift from optimizing channels to engineering a connected growth engine for the entire business. Welcome to season eight of the Agile Brand podcast. This season we're going all in on Expert Mode, MarTech, AI and Customer Experience, talking with the people and platforms behind the brands you know and love. Again, I'm your host Greg Kilstrom and I help Fortune 1000 companies make sense of martech, AI and marketing ops. Hit, subscribe or follow to make sure you always get the latest episodes and leave us a rating so others can find us as well. This show is brought to you by Moburst, an award winning digital marketing agency leading how brands succeed in the age of AI. Moburst helps brands grow through data driven strategies across app marketing, media, buying creative and answer engine optimization, helping you win visibility in AI powered search and generative engines. Everything they do is built to connect brands with the right audience and drive measurable growth. Learn more@moburst.com Today we're going to talk about the significant disruption AI is causing not just to marketing tactics, but to the very foundation of how customers discover and interact with brands. This isn't about a new channel to manage, it's about the emergence of a new operating system for marketing. One that demands a move from siloed activities to integrated systems, from search engine optimization to answer engine optimization and a new way of thinking about the teams that we build. To help me discuss this topic, I'd like to welcome Gilad Bashar, CEO at Moburst. Gilad, welcome to the show.
- [02:00]
B
Hello. Hello. How are you?
- [02:02]
A
Yeah, good, good. Looking forward to diving in here. Before we do though, why don't you give a little background on yourself and your role at Moburst.
- [02:09]
B
Sure. So my name is Gilad. I'm the CEO and founder of Moburst. We've been around in the last 13 years and we help brands to hyper getting into a hyper growth mode which means how to help them to achieve their goals and and meet their KPIs.
- [02:23]
A
Great, great. So yeah, we're going to talk about a few things here but want to start from the, from the strategy level and what I what I touched on in the intro and just really this, this idea that AI in particular and other changes too. But you know, AI has really driven a lot of marketers and a lot of brands to rethink their marketing operating models. But many large organizations are still operating in those old school functional marketing silos. You got paid media, content, email, social, each with its own KPIs. How does this traditional structure fundamentally break down when you try to build a more connected, data driven growth system?
- [03:09]
B
That's exactly where it breaks. And I think that that's part of the reason why we are saying 80% year over year growth for ourselves because we are kind of one stop shop for growth. And that means that the creative department and media department and social media and everything related with the PR and podcast and lots of, lots of those capabilities are coming all together in handy. You used to have an SEO agency that would only do SEO things. So they will do all of the technical things into the website and implement this code in this way and schema and frequently ask questions or what have you. But they will not see what happens on the other departments. They don't care about those KPIs. It's a different type of a thing. Social department will only care about engagement and likes and follows. And they don't really mind about too deep of content because who reads it and things of that nature. And you're seeing the creative department are trying to get you the best hooks possible, like how to actually grab the user's attention, but not necessarily telling the brand story or things of that nature. And what you're seeing on those instances is that basically for media buying you need specific things. For the organic side you need other things like each. And for social you want to grow your follower base and it all makes sense, it's all logical. But AI is kind of coming and changing the entire thing and mixing it together. Because AI doesn't just care about your goals, Google ranking for a specific query, it cares about the trust signals. And when it carries the trust signals, it basically looks about what happens on every single one of those venues. So it will read your reviews on third party sites that are actually ranking you compared to your competitors. It will look on what happens on Reddit and how people that engage with your brand or product actually gave the fair feedback about what they thought about it. Good, bad or ugly. It's there on Reddit and you can see questions on Quora that are impacting it and how you're looking on Wikipedia is making an impact of it and, and things that you are having on LinkedIn, like if you have a longer post that actually called the pulse type of content pieces that's also being kind of triggered into those. And if you have YouTube's YouTube videos, how much views they got and how the engagement there was, and you can get ranked for lots of different type of queries that are very long because if you're marked as number one answer on YouTube for that, you're probably good enough to also be cited by ChatGPT, Gemini, Perplexity or Claude. So when they are kind of factoring the ecosystem, they're not just looking about what happens on Google or Bing. ChatGPT was trained on Bing, not even on Google. So when you're looking on all of those elements, each and every one of those engines that are being questioned every single day and being trusted by hundreds of millions of people every single day to make their decisions, and it's not just factoring what you are doing on the website. So it's not just an SEO problem, it's the brand problem. And a lot of times when you're thinking about how to create content, how to produce the right type of trust signals for those algorithms, you need to not just thinking about it from the level of engagement or the level of how many followers did I get? But also is it clear enough for AI to read it in a snap and understand exactly that I'm the best for X or Y or Z? And if you're not planning this more holistic type of a strategy, you will basically shoot in the wrong direction and you will be hitting your chances of getting ranked and cited by all of those LLMs. And the level of like people that are actually getting a recommendation by ChatGPT, you're asking who is the best mobile marketing agency. And if you see that Mobis comes there in the top three, you're probably going to be going to all of those three sites, all of those three agencies saying, well, okay, let's shoot them an inquiry, let's, let's get their pitch and things of that nature. But this is kind of your research phase. Instead of having like what you used to do before actually going through for 40 minutes about like scouting the Internet on so many different things and then creating your shortlist. You trust ChatGPT because it recommended it and it checked all of those things already for you. So you're creating a shortlist and then within that shortlist, okay, I'm comparing this vacuum or this vacuum, like which one will ever be better for pets or you know, very kind of a nuanced type of queries. And if you'll be able to get the AI to recommend you, the user is already coming with a 90% trust that this is the right direction for them rather than questioning every single thing that you are about to say. So if you're thinking about holistic approach, and that's why I think that our growth is being where it is today. And we are working with startups, we are working with enterprise solutions, we are working with Microsoft Copilot for example, or we work with Samsung and Google and Uber and those type of business. And we also work with startups that just raise a round or B round and they're trying to bridge the market. And each of them is coming with a different pain point. Each of them is coming with a different positioning or a different type of maturity of the business. They have hundreds of thousands of users, they want to go to the millions, they have millions that want to go to the tens of millions or hundreds of millions. The methodology will be different, the execution will be different, but the strategy has to be holistic about how do we actually creating the right trusting for every single one of the channels to make us more reliable by those AI engines.
- [08:09]
A
Yeah, yeah. And so you know, what you're, what you're talking about really is just this, this connected system where we, we used to think in silos, you know, as we were saying earlier, now there's really this connected system rather than a collection of channels. So from the, from the brand's perspective, what does this mean? You know, so everything that you're saying, you know, makes sense. It's the way that consumers are, are consuming and making decisions and everything like that. What's the mindset shift, what's the collaboration shift that needs to happen internally at a brand to really get the most out of this connected system?
- [08:51]
B
I think that it's not just even the consumers, it's also about the businesses themselves. You can actually see a research that was posted asking 300 C level executives about their decisions about should I choose Salesforce or HubSpot for example, or queries like that. And basically they're on the verge of going with Salesforce for example. And then because ChatGPT recommends them to change to house, because it's more on about 1, 2, 3, 64% of them will actually change their mind even though they got whole pitch and you know, they can have nine meetings about solutions and all of those things and they will actually go in the other direction just because ChatGPT, Gemini, perplexity or Claude gave them that recommendation and they feel like this is a PhD level of someone that something that knows everything and it will give me the right answer. So you see that even the most senior executive teams worldwide for the biggest companies on earth making the decisions based on those engines and if you are understanding kind of the level of impact of how credible it appears to be by, by the consumers or by the brands, you're saying this is where the decisions are being made. This is where I can win or lose. And I was doing every single part of my sales team and marketing and every single. But if AI didn't not recommend you, you're going to be in big, in big trouble and you weren't going to know why your conversion rate drops and your sales pipeline leaks. And it's a big part of making the decision to say is this thing trustworthy or not. So I feel like this is something that impacts the day to day life of both consumers and businesses. And, and now because of that there is a massive kind of wave of okay SEO. I understand that's the problem of the past. I need to see how I'm getting in front of those engines. It's not like Google doesn't give you massive amount of traffic to your website. It does and it's doing it also by AI Overview and lots of different things that you are coming in but the decision on when you're asking a very large query when it's built of I'm a B2B company that does cybersecurity and looking to do a new website. Should I actually work with WordPress or Shopify template for this or that like and the answer is so specific that it's exactly tailored made to me and I feel like this is the way for me to make the right decision. And never mind with how many experts I'm speaking with. It's like another thing that sits beyond the back of my mind and basically saying this is kind of the North Star for me of how to choose how to make sure that I'm not making a horrible mistake.
- [11:18]
A
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- [12:54]
B
So I think that you always need to be skeptic about that. And that's even though that we have like I have A VPAI and six AI directors and then I have BI developers that are only working with AI and then another 16 AI champions with the company. So we are big believers on that. And that's outside of the growth labs that only builds AI products with AI. So I'm saying all of that to explain that even though that I have that and I'm using it on a day to day basis on everything. I usually don't trust one tool by itself. Usually I'm asking like if this is a big question for me or big decision for me. I want to get the second opinion, so to speak. So my go to just for example is Claude and Gemini for example at this stage and basically compare the answers between them. And if this one commands A and this one recommends B, I'm kind of taking the answers and blending them together and trying to see why this is better in here and this is better over there. And besides that, obviously I'm speaking to the team. You know, I have VPs, I have a lot of different directors and lots of great team members in the company. But I feel like this is something that kind of does a sanity check to make sure that I'm not going in the wrong direction and taking exactly the same prompt, copying it on two windows and actually asking in here and there just to make sure that you are not getting a hallucination, the all hallucination. I think that if you are using the most, the newest models, you have less of those. But you also need to be very specific about how you are questioning that specific thing. So within Claude Cowork, when I'm asking a query, we. One of my directions to that is that if you're not sure, tell me that's okay. Don't try to invent an answer. Or if I'm using just for example, with different tools that I need to make sure that there are no hallucinations whatsoever. I'm inserting everything into NotebookLM for example, and only from the things that I uploaded here. Only from here. Give me the recommendation, don't take it from the web from any other thing. So it's only based on what I've trained the model to think about, based on documents of 500 pages. Find me the answer in here based on that manual and don't go crazy to other places. So there are lots of different ways of using AI. You need to know what to use on which type of instant and then how to actually make sure that what you are asking, you're actually getting the best answer. We built an internal tool that also asked the same query in four engines at the same time. Perplexity, Claude, Gemini. And then you're seeing kind of a consolidated view about which one or what is kind of the best answer based on all four of them. And again, implementing xai, for example, should we shouldn't. It's big enough. So again, it's kind of. You always can add more and you can always kind of do it a bit deeper. But it's a question of what type of a question are you asking? What is the cost of a mistake of going in the wrong direction? So I think that we are not kind of the standard user. The standard users just hooked into ChatGPT or Gemini or Claude, whatever that might look like, and just going with it. And this is kind of their source of truth. I do think that you do need to make sure that you are checking yourself before just relying on that blindly. But the more that you walk with it and the more you see that it is reliable and most of the times it's not hallucinating. So you're saying, okay, that will work. I did do a mistake two weeks ago. I bought like something that connects my. I moved the homes and then I moved the office and I needed to connect the Sonos subwoofer to the computer and connecting it. It's Not HDMI regular. I needed to have another plug there in the center. And I asked, hey, Gemini, what would be the best thing for that? I bought exactly what it recommended. And then it said, well, I'm deeply sorry about that. This is really embarrassing. That was the. But I recommended you the wrong system. You need the one that is upgraded to do this and this and that, and this is only doing this. And basically, I'm so sorry. If you want, I can help you to get the return label by Amazon and getting you that fixed. But that time it's okay. The cost of mistake $50 to actually get another box connected to the computer, it's not a big deal. But I'm saying that most of the times when it's a big decision, you want to make sure that you are relying on the right, on the right platforms.
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A
Yeah, yeah. Well, I mean, you know, it goes back to, you kind of do the same thing in real life. You, I mean, you may have very trusted people that you rely on for certain things, but generally speaking, when you make a big decision, you're asking a few other people, you know, you're not just asking a single person, hey, what do you think about this? And following their advice. So, you know, in a sense it echoes that. But I do wonder, you know, the examples that you give are great and you know, I've done some of the same things as far as, you know, kind of seeing, posting the same prompt and kind of seeing results in platforms where that's not possible. So, you know, let's talk a little bit about media buying, for instance. So, you know, AI powered media buying. Certainly there's a lot of opportunity there and a lot of benefits to using the AI optimization. But I mean, I guess you could buy media in multiple, you know, multiple different platforms or whatever, but it's a little harder. It's, it's less of an apples to apples comparison. What should leaders be keeping in mind about this as far as balancing the human strategy part with kind of trusting the algorithm and when it can be a little bit more of a black box?
- [18:15]
B
Yeah, I think this is a great question. I think that when we are looking at that, we are trying to get all of those sources into one big CRM of ours basically to get all of the information. Because what you're running right now on Apple searches and Google and Facebook and Snapchat and Pinterest and Quora and net networks, RTVs, exchanges, influencers, get all of that into one place. That's step number one. Once that's there now you can start running AI analysis about that, about, okay, which are the bids that I need to make higher bids, lower bids, changing creative elements and things of that nature. So AI is really good when you have all of the information in front of you and it knows how to justify the action based on historical data that it sees and things like nature. I feel like that's where AI is very, very strong at. But we always have a human in the loop. So our media managers basically have all of that ingested into one place. We are creating them automatic dashboards based on what was happening in the last day, week, a month, whatever you're kind of analyzing. And then it also gives you another kind of a big output of this is what the AI would recommend you on doing. And you can do that with both. Heiku we're doing it to four different models of Gemini and Antopic, basically of one of Google, one from Claude. And what we are trying to see there is like, okay, you're getting the recommendations based on different AI suggestions and you decide as the human, what will be the right actions for me to do. So there are things that are very clear, okay, Google is performing two times better than Meta Transform more budget from here to there. That's, that's easy. Like that's any medium. I doesn't even need the AI to do that. But in a special analysis that Gemini analyzed and saying during the weekend between 6pm till 10pm, that's the time to increase the bid by 3x because every single lead that you're getting there is a pure value that someone is about to buy your product and lower the bid between 2am to 6am because that's usually people that are just, you know, bored, they can't sleep at night and are not really making purchases. And this level of analysis is something that if a human even will try to do that, searching the patterns about each and every platform, about the purchase behavior of each and every, it's very hard to do. It can take you hundreds of hours to get to that level of analysis. But AI is really good at finding those patterns. So once it spots that you can say, okay, I want to question that, I want to make sure that the data it was trained on is actually based on the last three weeks because we changed the funnel, we changed the landing page, so maybe they're looking on this landing page page compared to that and it doesn't behave the same. So there are a lot of things that the context there and the fact that the human in the loop is kind of Judging the recommendation and then deciding, okay, I need to implement that. I do not need to go after those specific flows. So I feel like that's a very important part there because a lot of times it doesn't have the context. It will tell you, okay, you are running the same campaign in five languages. Kill the Spanish speaker type of campaign because it performs lower than the English speaker one. But if your goal is to expand from the US to Spanish markets, it doesn't make sense to hear that recommendation. It doesn't have the context on understanding that we're trying now to increase the market share in here, on there. And so I feel like a lot of those things are not as easy to just based on the last week, over week results, but also what are you trying to achieve and what is the value that you are getting lifetime value out of those customers? If it's not connected to the lifetime value, maybe those users are more expensive, but they are staying five times more with a subscription later on. And it doesn't have that context. So a lot of those things you need to kind of use it as another helper for the decision maker. But I wouldn't let it do everything it wants by itself because it's not entirely there just yet.
- [22:10]
A
So I want to go back a little bit. I know we touched on whether the terms are varied, but answer engine optimization, geo, whatever you refer to it as. I know we touched on a little bit at the beginning, but want to talk more about the operationalizing it now. I think a potentially dangerous approach is to just think, oh, this is just like SEO. It's just a little different here or there. I think there are some similarities, but maybe could you unpack that a little bit for us? So you know what, what is similar? You know, for those that had really strong SEO and content strategies already, where are they set up for success but also where do they need to think differently?
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B
Yeah, I think that that's a great, a great question. So SEO was the game of us bombarding with a massive amount of content. And that content wasn't as structured because there is a big paragraph about it. It looks like more dense. A lot of time SEO people will say, well, this content is ranked and they have 3,000 words, we need to have 3,500 words. So our content will be even better than that one. And it was measured by how much content you had on the page and not how it was structured specifically. So there are differences. Like both love content. Okay, you need a lot of content that's there. There is no doubt about that you need content in order to be successful there and you need to educate it about what you do best about the type of questions that people might ask. And you're drafting the content in a different path. So it's not just the technical side and schema and how fast that site loads and like how to make sure that the bots can actually read the content very easily. And things like nature like that's obvious. Okay, that's technical part that you just need to cross V next to all of those things robot text. You have a lot of different things entities that you need to work on the technical side. But the difference is that you need to structure the answers like with question answer like the frequently asked questions is one thing that the AI really love because basically it tried to find a specific fit for that query. So it runs that query. Let's say someone is now looking for best app promotion agencies worldwide. What it does saying, okay, this is what the user was searching for. It breaks it into five or six other queries. That's something that the engine itself is doing best US agencies that deal with growth for up marketing. Lots of lots of subqueries that can become out of that. And then it checks all of the answers that it gets and what are the top citations or what are the top sites that are being recommended to provide you that solution. And then it reads within those sites what is the recommended sources. And basically if it read an answer about hey, Mobis is one of those sources, it will go to our website to learn what are we doing, how are we doing it, who are the type of clients, what type of case studies do you have? And then it researched my own company and then two other competing agencies and then tries to kind of give you like okay, based on the accommodation, those are the top three that I think that's going to be going to be the best for this specific thing. They specialize on this, they specialize on that and they are doing much more of that. So it does that type of homework about you. So the more that you have the structured content on your website to help dictate I'm the best in this niche. This product of ours is the ideal solution for that audience. And then it tries to basically find it can be that you are the best at everything for everyone. Like usually it's not the case. So if you are thinking about again cleaning devices or refrigerators or what have you, it's a big family, it's a small family with ice maker, without ice maker, the electricity, what's the Most important thing for you. And it needs to find what you're going to be ideal for and who will be ideal type of audience for that. So it tries to match that with what it knows about the user who is searching for it. How price sensitive are they? Oh, it knows that Mobis is a company with let's say 100 to 200 employees bracket. So it won't recommend me a solution that's going to be only for crazy enterprises that are going to cost me $5 million a year because it knows that it's not the price range that I usually spend on architecture. While you know, Google or Microsoft might pay tens of millions of dollars for this subscription or that subscription or that cloud solution or hundreds of millions depending on what they need. So it matches it to what it knows about you and then the more information that you have within the side that kind of gets the AI to understand the ideal for these cases. They are doing a really good job on those things. It helps them to dictate the relevant score that you are getting compared to the others. So I think that how the content is structured is very, very important to help guide it to your ideal Persona. And you can also lots of different low hanging fruits of things that you can do. You probably have a sales team, they probably have those handbooks about what we do best, how do we actually serve this company or that company. You can just publish them as kind of structured content on your blog and on your resource centers and in that nature that is very easy to find and the AI can read them very easily. It's like question, answer, question answer about lots of different topics and it helped dictate what you're actually doing better than anyone else on different departments, different services, different offerings or solutions that you have.
- [27:35]
A
Yeah, yeah, love it. Well, as we wrap up here, got a few things for you. I want to looking ahead, certainly we've talked about a lot of shifts and a lot of changes from a marketing team perspective. You know, as we talk about silos breaking down, as we talk about just changes and, and evolutions in marketing, what are the skills and even the roles that are becoming more and more critical as you, you know, think about the future of a marketing team.
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B
Yeah, I think that one of the roles that becomes the most relevant is the ability to self talk yourself, like self learn. And I think that becoming a native is something that I would always prioritize someone trying to test all of those tools compared to the people that are saying yeah, well I know what I know and I know what Also, I am not strong at and AI is a bit more like I'm not into code, I'm not looking for everyone to be developers, not whatsoever. But you can create today whole systems just by envisioning them thinking about a problem, thinking about the solution and vibe code it without even need to know how to program. You just need to think outside of the box and you need to keep on challenging the status quo and you need to have the mentality of saying I understand that it wasn't possible before, but there is a way to solve it. And I think that that's probably the thing that is the most important today. Because the pace of innovation today is insane. Things that used to take you five years and a team of 15 people to build can actually be happening today in the middle of three weeks with one talented person. And I feel like the capabilities of one good person in the right place in the organization that is AI native, that is trying to fix things in a more interesting way. One of my team members from the HR division just created us an HR bot and she's not an AI expert. She just said hey you know what, if we can actually create this type of a thing that let's train it with the handbook that we are giving for each and every employee. And then if they're asking about the next vacation or if they can do this or they can't do that, or based on the policies on how much time you are getting after you gave birth in this country or that country, there are so many details in those things. And just asking and getting a question and putting that as a friend of yours on Slack, HR friend type of a thing and it's innovation. I didn't expect the HR team to create something like that three years ago, but nowadays I feel like if an HR person can actually create something like that, there is no reason that every single team member on every single department will challenge the status quo, will say this is another repeating query. I'm wasting 5 hours every week of answering team members about different things. Let's try to solve it. So I want again, I only have two questions a week instead of 15 because it's repetitive and it doesn't make sense. And they have the handbook but they are not checking into it and they just prefer to go to the hr let's have an HR bot that will give them those answers and getting my five hours back. So I'm saving myself an hour a day to not do that repetitive thing. So I feel like every single person that is currently employed when they're just doing what they used to do in 2025 or 2024. They're probably doing it wrong. And you need to rethink about systems that you can build to automate. Labor intensive and kind of a low value type of things that you have to do. It's part of reporting you have to do that. But it's taking a data from here, putting it in here, creating a graph, uploading it and tidying up a deck, looking on the font size like who wants to do that? Why not? Creating a cloud skill that creates you automatically, all of those things pull it together and basically you just tap on a button. Here you go, we have that. You can inspect it, saying, well, just like a chef, you are tasting it. Well, it's too sour. No, it's too salty. But you're basically just testing the thing that was created for you instead of actually creating it every single time from scratch.
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A
Yeah, yeah. Love it. Well Gilad, thanks so much for joining today. Got one last question for you as we wrap up here. What do you do to stay agile in your role and how do you find a way to do it consistently?
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B
Great question. I think that I'm just testing every single new tool that comes to market and I think that just like my team basically I know that if I weren't going to be going into all of those newer tools, I will stay behind. So I keep on engaging with other CEOs to see what they are doing, how they're doing, how they're actually creating the new systems, how they're doing, the integrations of new platforms and solutions. And I'm trying to kind of stay ahead of the curve by reading a lot about everything that happens in the industry and trying to see what does that mean and if this and that and that is kind of a trend, how do I get ahead of it? To make sure that we are not basically kind of reading the news but we are not acting on them and then basically we are staying behind.
- [32:17]
A
That's great. Well again I'd like to thank Gilad Bashar, CEO at Moburst, for joining the show. You can learn more about Galad and Moburst by following the links in the show notes. And thanks again to our sponsor, Moburst. This show is brought to you by Moburst, an award winning digital marketing agency leading how brands succeed in the age of AI. Moburst helps brands grow through data driven strategies across app marketing, media, buying creative and answer engine optimization, helping you win visibility in AI powered search and generative engines. Everything they do is built to connect brands with the right audience and drive measurable growth. Learn more@moburst.com and thanks again for listening to the Agile Brand podcast. If you like the episode hit, subscribe and drop a rating so others can find the show too. And if you're interested in consulting, advisory work, or if you need a speaker for your next event, feel free to reach out. Just visit GregKilstrom.com that's G R E G K I H L S
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B
the
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A
Agile Brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile.