Pod Insights MarTech Podcast ™ // Marketing + Technology = Business Growth Why AI In GTM Presents Massive Opportunities About this episode Co-founder & CEO Daniel Saks from Landbase, a leading agentic AI platform for go-to-market strategies, delves into the vast opportunities presented by AI in GTM. Discover how Landbase's GTM-1 Omni suite, powered by specialized AI models, streamlines sales and marketing workflows to enhance lead generation and conversion at scale. Explore the vision shared by a team of seasoned founders and operators to revolutionize go-to-market processes through automation, unification, and optimization. Show NotesConnect With: Daniel Saks: Website // LinkedInThe MarTech Podcast: Email // LinkedIn // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Transcript 0:00 Speaker 00 The Martech Podcast is a proud member of the I Hear Everything Podcast Network. Looking to launch or scale your podcast? I Hear Everything delivers podcast production, growth and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit iHereEverything.com.
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0:53 Speaker 00 Welcome to the Martech Podcast, a member of the I Hear Everything Podcast Network. In this podcast, you'll hear the stories of world-class marketers that use technology to drive business results and achieve career success. Here's the host of the Martech Podcast, Benjamin Shapiro.
1:15 Speaker 04 Welcome to the Martech Podcast. I'm your host, Benjamin Shapiro, and today we're going to discuss Agentic AI. Joining us is Daniel Sacks, who is the co-founder and CEO of Landbase, whose proprietary suite of specialized large language and action models are trained to orchestrate sales and marketing workflows, helping businesses automate, unify and optimize go-to-market processes all in one place. And today, Daniel and I are going to discuss how Agentic AI will transform marketing. All right, here's my conversation with Daniel Sacks, the co-founder and CEO of Landbase. So I want to move on to the next part of our conversation.
1:55 Speaker 04 We've been talking about Agentic AI and how in theory, we are going to be prompted by our artificial intelligence instead of us prompting the AI. I think that just in general, artificial intelligence is going to create some massive Of opportunities for go to market. So let's talk a little bit about that. Let's start off with a segment we like to call what's the word? And specifically, when we think about artificial intelligence and go to market, I think that there's the opportunity for it to play a couple of different roles. So what's your word for the role that artificial intelligence plays in go to market today?
2:31 Speaker 05 My word would be intelligence. So what we find is that you can harness the intelligence of humans and the wisdom of the crowd, but you can also harness machine intelligence. And what we find is that average human performers, when it comes to campaigns, or let's say, sales development, produce really bad results. Average like AI prompting also produces really bad results. Top human performance, so a top creative marketer, a top sales development rep, they're going to produce incredible performance. That's probably like next level. But if you can harness that with machine intelligence, that's where you have incredible outcomes. So my word is intelligence.
3:06 Speaker 04 It's interesting. I think my word would be strategy. At this point, I don't think we really have agentic AI nailed down. I don't think that we have artificial intelligence that can go and execute tasks for you or look for trends and then tell you about them. You have to prompt. And so what is the most impactful is using artificial intelligence to walk through, analyze a market and think about how you can then go operationalize your tactics. Right? It's a strategy execution tool. Give me some examples of how you are using artificial intelligence to help with your strategy? Or am I wrong and you're just using it for execution?
3:46 Speaker 05 We're leading the way to enable execution. In order to have that intelligence and execution, you had to train our agentic model. And we're the only ones that have trained in an agentic model with go to market. There's a huge barrier in terms of compute scarcity of talent. So our chief data scientist was a Stanford PhD in neural networks, training with many of the professors that enabled the transformer models and the large language models. So there is like a high barrier to action here. Now, what I would say, though, from a strategy perspective, is that we can tap into the intelligence of the model and it can tell you how to have far better go to market efficiency. So one of the first First learnings we had in the model is that about forty five percent of campaigns full up fail to generate leads that convert. That's wild. That means about half of sales and marketing spend just goes to waste.
4:31 Speaker 05 But that definitely correlates to when I speak to businesses. So I'll talk to a business and say, hey, how did your marketing campaign perform? And they'll say, I don't know. I didn't really generate any more leads, so stop doing the billboard. Or how did your sales development team do? And they'll say, well, I hired an SCR. They did a lot of outbound. They didn't have success. So I hired, or maybe they hired a lead generation agency and it flooded them with leads, but they didn't convert any. So it's very common that a lot of campaigns fail. And the costs of those experiments are incredibly high. So to your point on strategy, one of the things that we can tap our model for intelligence is actually a footprint and playbooks about what campaigns you should try across what channels. And therefore it gives you an output of what strategy you should take to be able to optimize.
5:16 Speaker 05 One of the very cool things about these types of models is that you can test things or simulate things within the model without having to spend any costs. So in the past, you maybe had to do focus groups or you had to do A B split testing, where you're actually spending money to be able to discover what the right messages that hit. And then you roll it out and it's. Today, what you can do is you can have a protagonist and an antagonist in the model that can simulate and predict the probability that an outcome is going to be had. What that means is that marketers can have the intelligence, devise a strategy that is much more likely to be cost efficient and ultimately drive better go to market efficiency for your clients.
5:56 Speaker 04 I want to move on to a segment that we call secret sauce. So we're going to be making a go to market pizza. And I want you to think of the recipe that you need. What are the ingredients that you need for using AI in go to market execution? Not just strategy to make sure that it's a delicious meal.
6:16 Speaker 05 If I were cooking up my pizza, it's actually just what we did with our AI model, GTM1 Omni. And what you want to throw into the oven is the context on every business in the world, who they want to sell to, the buyer intent. And if you can throw all these things into this pizza, out can come magical findings. So what we did is we trained our model, GTM1 Omni, on all this context, and then we can ask it to give insights. And you mentioned this, that right now, it's not so likely that people are using AI in an agentic way, where it's about execution. They're probably using it more to chat. And that is the reality of today.
6:56 Speaker 05 I think if you forecast out 24 months for every function, just like what land-based is doing for sales and marketing, there will likely be a very sophisticated AI model that can shift things from strategy, or chat, or language, to execution, action, and outcomes. And there are already examples in the cogent space, like you mentioned, there's companies like DevRev, Magic, Cognition, that can automate the AI software engineer. Likewise, in the BTO space, or the support space, there's companies like Decagon and Sierra. And then in the go-to-market space, there's land-based that can help really bring together this intelligence. So that's what I've thrown into the model.
7:35 Speaker 04 Hang on, I'm putting my grocery list together. You said to build a go-to-market strategy using artificial intelligence, you need to have your, what was it, customer data? Give me the list of things that you're throwing into the model to get a good GTM result.
7:52 Speaker 05 If I want the perfect pizza to come out specialized for your business, what I'm going to put in the oven is going to be all the elements that I know about your business, both public and private. So on the public web, I can understand the way people perceive your sentiment. So what are people saying about you? What are the ratings and reviews? What are your competitors? And how are you perceived next to your competitors? What channels are you using today that the internet can pick up? These are all these public signals. You don't only want the public signals for you as a business, but you also want to throw in the signals of your customers. Understand their psychographic or their buyer intent or where they're living and what their pain points are. So you want to throw all that in the model. But on top of that, there's also private signal.
8:35 Speaker 05 So in terms of what we could learn from your own data, it could be what's your perfect customer based on your CRM data? And who's close and who's been retained? It could be secret differentiators about your product that are going to unlock the key message in the campaign. But it could also be private data that we may have about a business, whether it's contact data, the ability to reach someone where they're visiting, what their demographics are. You want to know all these things. So if you can harness public and private information about you and your prospects or customers, and you throw it into this oven. What you want is for this AI engine or model to do its work and pull out all the interesting insights.
9:15 Speaker 05 And coming out of the model, you have a personalized plan that tells you exactly who your customers should be. So your ideal customer profiles has the contact data for them, tells you exactly how you should spend your budget across different channels. Whether that's phone, email, ads, billboards, in person, et cetera. How you should spend that across channels and then it should be able to execute that for you. And that would be the ideal recipe.
9:40 Speaker 04 I liken my pizza to put the crushed red pepper flakes and the oregano and the Parmesan cheese. So I'll add a couple of things that maybe you didn't have in the oven, but I feel like make it a delicious meal. You didn't mention your competition and understanding their business model. I think one of the key things to understand is not only who your customers are to come up with your ideal profile and look for similarities and understand how people are talking about you publicly, but it's understanding where you fit into the grand landscape of the marketplace. And so looking at who the other competitors are, what are people saying about them? What do you know? What competitive intelligence can you do? I think that's always an important factor and something that your AI models definitely should take into consideration.
10:25 Speaker 04 All right, I want to move on to our last question for you. We're going to do a little role play. Close your eyes. You're going to transform into a B to B CMO at a mid-market company. How do you get your team to embrace artificial intelligence for their go-to-market strategy instead of assuming that they know how to do it without modern technology?
10:45 Speaker 05 If I'm the B to B CMO of a mid-market company, I want to leverage the intelligence of digital transformation. And really, the classics to enabling digital transformation is that, sure, there's technology you can adopt, but it's actually more about the people and the characteristics. This has been the same over last generations of software, whether it was on-prem, in the cloud, or now AI. So the first thing I would do is I would encourage my team to take risks, to be open-minded, to try new things, but also push for the basics. So I think the first thing I learned in marketing was the four P's. What's your package of positioning, pricing? You want to think about those basics and you want to use first principles, just the concept of like, think for yourself critically, about what you want to achieve for your business or for your customers,
11:29 Speaker 05 and just break it back down to basics. And then what you'll find is that there's new technologies emerging every day that can help support you in that and that can help automate a lot of the manual repetitive tasks or that can help bring together siloed teams. So I think just bring it back to basics. You don't have to be in front of a screen to do this. Be with your team, ask the questions, and then, once you kind of identify what you need to do and what you need to solve for and what some of these creative strategies are, then you'll find that there's tons of tools at your fingertips that will make that easier.
12:00 Speaker 04 I think the biggest challenge when you're managing your team is helping them understand where they're spending wasted time. So as much as you don't want to be a micromanager, when you sit down with your team, I do this all the time. Where are you struggling? What are the problems? What are you doing that is repetitive, right? And if you're running into these repetitive tasks, that's an opportunity for you to start thinking about using artificial intelligence to remove that, right? Use technology to get the repetitive work off your plate so you can get into spending more time on the deeper thoughts and solving the actual Customer problems. Part of this is just a management style of sitting down with your team and understanding where they're spending their time to help them reallocate.
12:44 Speaker 04 And if you're constantly doing the same task over and over and over again, that's probably something that you can automate and it's easier now than ever. Daniel, any last words that you want to say in terms of the use of Agentic AI, Landbase, what you guys are doing? Let's land the plane, give you your big finish.
13:00 Speaker 05 One thing you could never take back is time. Time is precious and it's our greatest resource. The speed in which businesses are moving today is faster than ever, which means we have to make very quick, intelligent decisions to be able to push ourselves forward. And ultimately, what we hope is that technology can automate away the manual repetitive processes, can bring together the siloed teams and can remove the fragmentation in a siloed software stack, be able to bring everything together to allow you to move faster with more accuracy and intelligence. So ultimately, you can do less mundane work and you can reclaim your day and do more of what you love. So you said it best earlier in the conversation, about going back 30 years ago to the old days of marketing, where you're thinking about creative pursuits and strategy and bringing that to the forefront again.
13:44 Speaker 05 I believe in a world where AI, specifically Agentic AI, will actually make us more human and will allow us to collaborate and will bring us back to that era. So that's what I hope for in the future.
13:54 Speaker 04 It's a confusing time for marketers and there's this new wave of technologies that can do so much. And ironically, I think that we all just want the artificial intelligence to do what we do and do it better. And it turns out, right now, that takes work. It takes effort to sit down and think about what your manual processes are. To build the automations using artificial intelligence to have AI take some of the work off of your plate, it takes work to get rid of the work. And that won't always be the case. Artificial intelligence will get better and get smarter and be more useful at prompting us what's happening. That's what Agentic AI is for. It is on the way. It is not quite here yet for most marketers.
14:39 Speaker 04 There's tools like Landbase that are working very hard to make it reality. But fundamentally, what is not going to change- Change is that marketers need to understand who their customers are and what their problems are. And if you're able to use artificial intelligence to mine and refine the data set that you have to understand your customer problems, you're going to be able to move faster, get more time back to yourself, and be more successful in your marketing programs. And that wraps up this episode of the Martech Podcast. Thanks for listening to my conversation with Daniel Sacks, the co-founder and CEO of Landbase. If you'd like to get in touch with Daniel, you can find a link to his LinkedIn profile in our show notes, or you can visit this company's website, which is landbase.com. Just one more link in our show notes I'd like
15:24 Speaker 04 to tell you about. If you didn't have a chance to take notes while you were listening to this podcast, head over to martechpod.com where we have summaries of all of our episodes and contact information for our guests. You can also subscribe to our newsletter and you can even apply to be the next guest speaker on the Martech Podcast. Of course, you can reach out on social media. Our handle is @martechpod on Twitter, Instagram, and Facebook. You can contact me directly on LinkedIn. My handle is Ben J. Shap, B-E-N-J-S-H-A-P. Also, we're doing a lot of work on YouTube. So if you want to follow these conversations or get some short form snippets, you can go onto youtube.com and look for Martech Podcasts. And if you haven't subscribed yet and you want a daily stream of marketing and technology in your podcast feed, we're going to publish an episode every day this year. So hit the subscribe button in your podcast app and we'll be back in your feed tomorrow morning.
16:09 Speaker 04 All right, that's it for today. But until next time, my advice is just focus on keeping your customers happy.
16:41 Speaker 00 Thanks for listening to the Martech Podcast, and I Hear Everything production. Looking to launch or scale a podcast like this one for your brand? Then visit iheareverything.com.
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