Why AI in GTM presents massive opportunities

Summary

MarTech Podcast ™ // Marketing + Technology = Business Growth
Episode: Why AI in GTM Presents Massive Opportunities
Host: Benjamin Shapiro
Guest: Daniel Sachs, Co-Founder and CEO of Landbase
Release Date: May 8, 2025

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Introduction

In this enlightening episode of the MarTech Podcast™, host Benjamin Shapiro engages in a compelling conversation with Daniel Sachs, the Co-Founder and CEO of Landbase. Landbase specializes in leveraging advanced AI technologies to streamline and optimize go-to-market (GTM) processes. The duo delves deep into the transformative potential of agentic AI in marketing, exploring how it can revolutionize strategy, execution, and overall business growth.

Understanding Agentic AI in Marketing and GTM

The conversation kicks off with Benjamin introducing the concept of agentic AI, prompting a discussion on its theoretical and practical implications in marketing.

Benjamin Shapiro (01:15):
"Artificial intelligence is going to create some massive opportunities for go to market."

Daniel Sachs (02:30):
"Today 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."

Daniel emphasizes that combining human intelligence with machine intelligence can lead to incredible outcomes, surpassing average human and AI performances. He highlights that top human performers, when augmented with machine intelligence, can achieve next-level results.

The Role of Intelligence and Strategy in AI

While Daniel focuses on intelligence as the cornerstone of AI in GTM, Benjamin introduces his perspective, emphasizing strategy.

Benjamin Shapiro (03:05):
"My word would be strategy. I think that there's the opportunity for [AI] to play a couple different roles."

He points out that current AI applications in marketing often require manual prompting and lack true agentic capabilities. Instead, AI acts as a strategy execution tool, assisting marketers in analyzing markets and operationalizing tactics.

Optimizing Go-To-Market with Agentic AI

The discussion transitions to how agentic AI can enhance GTM efficiency. Daniel brings to light a concerning statistic:

Daniel Sachs (03:46):
"About 45% of campaigns fully fail to generate leads that convert. That's wild."

This high failure rate underscores the inefficiency in current marketing and sales efforts. Daniel explains how Landbase's proprietary AI model, GTM1 Omni, can simulate and predict campaign outcomes, thereby reducing wasted spend and improving conversion rates.

Daniel Sachs (05:55):
"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."

By providing data-driven insights and strategic recommendations, agentic AI helps marketers allocate budgets more effectively across various channels, such as phone, email, ads, and billboards.

Building the "GTM Pizza": Essential Data Inputs

In the "Secret Sauce" segment, Benjamin and Daniel use a pizza-making metaphor to describe the essential ingredients for an effective AI-driven GTM strategy.

Daniel Sachs (06:15):
"If I were cooking up my pizza... 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."

He elaborates that the AI model requires a blend of public and private data to generate meaningful insights:

• Public Signals: Customer sentiment, ratings, reviews, competitor analysis, and channel performance.
• Private Signals: CRM data, contact information, customer retention rates, and internal differentiators.

Benjamin Shapiro (07:35):
"What I'm going to put in the oven is all the elements that I know about your business... you want to understand where you fit into the grand landscape of the marketplace."

Benjamin adds the importance of competitive intelligence, ensuring that the AI model accounts for competitors' business models and market positioning.

The integration of these data points enables the AI to produce a personalized GTM plan, detailing ideal customer profiles, budget allocations, and strategic channel investments.

Encouraging AI Adoption within Marketing Teams

Moving to the practical application of AI, Benjamin introduces a role-play scenario where Daniel assumes the role of a B2B CMO at a mid-market company tasked with encouraging his team to embrace AI.

Benjamin Shapiro (10:45):
"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?"

Daniel Sachs (10:45):
"I would encourage my team to take risks, to be open-minded, to try new things, but also push for the basics... use first principles."

Daniel advocates for a balanced approach that combines fundamental marketing principles with the adoption of new AI technologies. He stresses the importance of:

• Encouraging Risk-Taking: Motivating the team to experiment with AI tools.
• Focusing on Fundamentals: Reinforcing core marketing concepts like the four Ps—product, positioning, pricing, and promotion.
• Integrating Technology as a Tool: Using AI to automate repetitive tasks and enhance collaboration across siloed teams.

Benjamin Shapiro (11:59):
"Understanding where you're spending wasted time... if you're running into these repetitive tasks, that's probably something that you can automate."

Benjamin complements Daniel's approach by highlighting the need to identify and eliminate redundant tasks through AI, thereby allowing the team to focus on strategic and creative endeavors.

Final Thoughts on Agentic AI and Future Outlook

As the conversation draws to a close, Daniel shares his vision for the future of agentic AI in marketing.

Daniel Sachs (13:00):
"The speed in which businesses are moving today is faster than ever... technology can automate away the manual repetitive processes... allow you to reclaim your day and do more of what you love."

He envisions a future where AI not only enhances efficiency but also humanizes marketing by freeing up marketers to engage in creative and strategic activities. Daniel believes that agentic AI will bridge the gap between data-driven insights and human intuition, fostering a more collaborative and innovative marketing environment.

Benjamin Shapiro (13:54):
"What is not going to change is that marketers need to understand who their customers are and what their problems are. 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 gonna be able to move faster, get more time back to yourself, and be more successful in your marketing programs."

Benjamin reinforces the idea that while AI tools like Landbase are instrumental in optimizing marketing efforts, the fundamental understanding of customer needs remains paramount. The synergy between human insight and AI-driven data analysis is key to achieving sustained business growth.

Conclusion

This episode of the MarTech Podcast™ offers a deep dive into the transformative power of agentic AI in the realm of marketing and go-to-market strategies. Through insightful dialogue, Benjamin Shapiro and Daniel Sachs elucidate how integrating advanced AI models can lead to smarter, more efficient, and strategically sound marketing campaigns. They highlight the importance of combining human intelligence with machine capabilities to overcome the high failure rates in current marketing practices.

Notable Quotes:

• Daniel Sachs (03:46):
  "About 45% of campaigns fully fail to generate leads that convert. That's wild."

• Daniel Sachs (09:39):
  "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."

• Daniel Sachs (13:00):
  "Technology can automate away the manual repetitive processes, can bring together the siloed teams and can remove the fragmentation in a siloed software stack and be able to bring everything together."

• Benjamin Shapiro (13:54):
  "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 gonna be able to move faster, get more time back to yourself, and be more successful in your marketing programs."

For those interested in leveraging AI to revolutionize their marketing strategies, Daniel Sachs and Landbase present a compelling case for embracing agentic AI as a pivotal tool in driving business growth and operational excellence.

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To learn more about Daniel Sachs and Landbase, visit landbase.com. For additional resources and episode summaries, head over to martechpod.com. Subscribe to the MarTech Podcast™ on your preferred podcast platform to stay updated with the latest insights on marketing and technology.

Transcript

[Benjamin Shapiro]

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 iheareverything.com.

From advertising to software as a service to data, across all of our programs and clients, we've seen a 55 to 65% open rate.

[Daniel Sachs]

Getting brands authentically integrated into content performs better than TV advertising.

[Benjamin Shapiro]

Typical lifespan of an article is about 24 to 36 hours. If we're reaching out to the right person with the right message and a clear call to action, then it's just.

[Daniel Sachs]

A matter of timing.

[Benjamin Shapiro]

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 used to technology to drive business results and achieve career success. Here's the host of the Martech Podcast, Benjamin Shapiro.

Welcome to the Martech Podcast. I'm your host, Benjamin Shapiro and today we're going to discuss agentic AI. Joining us is Daniel Sachs, 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 Sachs, the co founder and CEO of Landbase. So I want to move on to the next part of our conversation. 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. And I think that just in general, artificial intelligence is going to create some massive 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 different roles. So what's your word for the role that artificial intelligence plays in go to market?

[Daniel Sachs]

Today 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.

[Benjamin Shapiro]

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?

[Daniel Sachs]

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 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 learnings we had from the model is that about 45% 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. 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 sdr, they did a lot of outbound, they didn't have success, so I fired. 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 cost 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. 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 cost. So in the past you maybe had to do focus groups or you had to do AB split testing where you're actually spending money to be able to discover what the right message is that hit and then you roll it out in a mouse. 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.

[Benjamin Shapiro]

I want to move on to a segment that we call secret sauce. So we're going to be making 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.

[Daniel Sachs]

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. I think if you forecast out 24 months for every function, just like what Lambase 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 Cogen 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 Landbase that can help really bring together this intelligence. So that's what I'd throw into the model or the other thing.

[Benjamin Shapiro]

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.

[Daniel Sachs]

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 to 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. 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 photographics 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. And coming out of the model, you have a personalized plan that tells you exactly who your customers should be. So to 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.

[Benjamin Shapiro]

I like in my pizza to put the crushed red pepper flakes and the oregano and the Parmesan cheese. So I'll add a couple 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. And I think one of the key Things to understand is not only who your customers are to come up with your ideal profile, 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. 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 B2B 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?

[Daniel Sachs]

If I'm the B2B 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 Ps. What's your package 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 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 silo 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.

[Benjamin Shapiro]

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 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 problem 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. 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? Land base what you guys are doing. Let's land the plan, give you your big finish.

[Daniel Sachs]

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 and 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. It's 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. I believe in a world where AI, specifically agentic AI, will actually make us more human and will allow us to collaborate, will bring us back to that era. So that's what I hope for in the future.

[Benjamin Shapiro]

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, there's tools like Landbase that are working very hard to make it a reality. But fundamentally, what is not going to change is that marketers need to understand who 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 gonna 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 his company's website, which is landbase.com Just one more link in our show notes I'd like 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 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 Benjschaft 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 on to YouTube.com and look for Martech Podcast. 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 on your feed tomorrow morning. All right, that's it for today, but until next time, my advice is to just focus on keeping your customers happy.

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