Why AI In GTM Presents Massive Opportunities

Summary

MarTech Podcast ™ // Episode: Why AI In GTM Presents Massive Opportunities

Release Date: December 11, 2024
Host: Benjamin Shapiro
Guest: Daniel Sachs, Co-Founder and CEO of Landbase

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Introduction to Agentic AI in Go-To-Market Strategies

In this episode of the MarTech Podcast™, host Benjamin Shapiro welcomes Daniel Sachs, the co-founder and CEO of Landbase. The primary focus of their conversation revolves around agentic AI and its transformative potential in Go-To-Market (GTM) strategies. Agentic AI refers to artificial intelligence systems that can act autonomously to execute tasks, analyze data, and optimize processes without constant human intervention.

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Defining the Role of Intelligence and Strategy in AI-driven GTM

Segment: What's the Word?

Benjamin initiates the discussion by asking Daniel to encapsulate the role of AI in GTM with a single word. Daniel confidently chooses "intelligence", emphasizing the synergy between human wisdom and machine intelligence. He explains how combining top-tier human performance with advanced AI can lead to exceptional outcomes in marketing campaigns and sales development.

Daniel Sachs [03:02]: "If you can harness that with machine intelligence, that's where you have incredible outcomes."

Contrastingly, Benjamin identifies his word as "strategy", highlighting the current limitations of agentic AI in executing tasks autonomously. He underscores AI's role as a strategy execution tool that aids in analyzing markets and operationalizing tactics rather than fully autonomous decision-making.

Benjamin Shapiro [03:37]: "It's a strategy execution tool. Give me some examples of how you are using artificial intelligence to help with your strategy."

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Building a Successful AI-driven GTM Strategy: The Secret Sauce

Segment: Secret Sauce

In this segment, the hosts metaphorically discuss crafting the perfect GTM "pizza", outlining the essential ingredients for integrating AI into marketing strategies. Daniel introduces Landbase's proprietary AI model, GTM1 Omni, which is trained on comprehensive business contexts, including buyer intent and competitive landscapes.

Daniel Sachs [06:47]: "If you can throw all these things into this pizza, [AI] can come up with magical findings."

Benjamin contributes by emphasizing the importance of competitive intelligence, suggesting that understanding competitors' business models is crucial for a well-rounded AI-driven strategy.

Benjamin Shapiro [10:11]: "I think one of the key things to understand is not only who your customers are... but it's understanding where you fit into the grand landscape of the marketplace."

Daniel elaborates on the necessity of integrating both public and private signals into the AI model. Public signals include customer sentiments, reviews, and competitive positioning, while private signals encompass internal CRM data, customer profiles, and proprietary insights.

Daniel Sachs [08:24]: "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."

The ideal outcome, according to Daniel, is a personalized GTM plan that delineates ideal customer profiles, budget allocations across various channels, and actionable strategies for execution.

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Overcoming Team Resistance: Embracing AI in Marketing Teams

Segment: Role Play - Transforming into a B2B CMO

Benjamin challenges Daniel to adopt the perspective of a B2B Chief Marketing Officer (CMO) at a mid-market company, tasked with encouraging his team to embrace AI in their GTM strategies.

Daniel responds by advocating for a balanced approach that combines embracing new technologies with reinforcing foundational marketing principles. He stresses the importance of:

1. Encouraging Risk-Taking and Open-Mindedness: Fostering a culture where team members feel empowered to experiment with AI tools.
2. Reinforcing the Four Ps of Marketing: Ensuring that fundamental concepts like Product, Price, Place, and Promotion remain central.
3. Leveraging AI to Automate Repetitive Tasks: Allowing the team to focus on creative and strategic endeavors by offloading manual processes to AI.

Daniel Sachs [11:16]: "Just bring it back to basics... you'll find that there's tons of tools at your fingertips that will make that easier."

Benjamin adds that a key managerial responsibility is to identify and eliminate wasted time, using AI to automate mundane tasks and thereby enabling the team to concentrate on more impactful, strategic initiatives.

Benjamin Shapiro [12:31]: "If you're running into these repetitive tasks, that's probably something that you can automate... it's easier now than ever."

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Conclusion and the Future of Agentic AI in Marketing

As the conversation draws to a close, Daniel underscores the invaluable nature of time and how agentic AI can reclaim it by automating manual, repetitive tasks. He envisions a future where AI not only enhances efficiency but also humanizes marketing, allowing professionals to engage in more creative and meaningful work.

Daniel Sachs [13:31]: "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."

Benjamin reflects on the current challenges marketers face with the evolving AI landscape, acknowledging that while agentic AI is still developing, tools like Landbase are pioneering its application. He emphasizes that the core remains understanding customer needs and leveraging AI to enhance data analysis and strategic execution.

Benjamin Shapiro [14:25]: "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."

The episode concludes with Benjamin encouraging listeners to stay informed and adaptable, as AI continues to reshape the marketing and technology landscape.

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Key Takeaways:

• Agentic AI holds significant potential to revolutionize GTM strategies by combining human creativity with machine intelligence.
• Successful AI integration requires a balanced approach that respects foundational marketing principles while embracing technological advancements.
• Data Integration: Both public and private data sources are crucial for developing effective AI-driven marketing strategies.
• Team Empowerment: Encouraging a culture of experimentation and leveraging AI to automate repetitive tasks can enhance team productivity and strategic focus.
• Future Outlook: As agentic AI evolves, it promises to make marketing processes more efficient and human-centric, enabling marketers to focus on creative and strategic initiatives.

Notable Quotes:

• Daniel Sachs [03:02]: "If you can harness that with machine intelligence, that's where you have incredible outcomes."
• Benjamin Shapiro [03:37]: "It's a strategy execution tool. Give me some examples of how you are using artificial intelligence to help with your strategy."
• Daniel Sachs [08:24]: "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."
• Benjamin Shapiro [10:11]: "I think one of the key things to understand is not only who your customers are... but it's understanding where you fit into the grand landscape of the marketplace."
• Daniel Sachs [13:31]: "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."

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For more insights and detailed episode summaries, visit martechpod.com. To connect with Daniel Sachs or explore Landbase's offerings, visit landbase.com or find Daniel on LinkedIn.

Transcript

[Podcast Announcer]

The Martech Podcast is a proud member of the iHear Everything Podcast Network. Looking to launch or scale your podcast, iHear 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.

[Benjamin Shapiro]

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.

[Daniel Sachs]

Person with the right message and a.

[Benjamin Shapiro]

Clear call to action, then it's just.

[Daniel Sachs]

A matter of timing.

[Podcast Announcer]

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 a host of the Martech Podcast. Benjamin Shapiro.

[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.

[Current Podcast Host]

But before we get to today's interview, I want to tell you about what I'm listening to. Ever wanted to sit down to a candid conversation with marketing leaders from the world's biggest brands? The current podcast is your chance. On the current podcast you'll find exclusive interviews with the experts and trendsetters who are on the front lines of digital advertising and they always leave the ad tech jargon at the door. So subscribe to the [e-mail] or anywhere you get your podcasts today.

[Benjamin Shapiro]

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'd 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 today?

[Daniel Sachs]

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 agenda 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 them. 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 messages that hit and then you roll it out and 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 Landbase 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 Landmass that can help really bring together this intelligence. So that's what I throw into the model or the outfit.

[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 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 liken 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 making 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. 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 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.

[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. 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. 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 and 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 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 his company's website, which is landbase.com A special thanks.

[Current Podcast Host]

To the Current Podcast for sponsoring today's interview. If you're looking for candid conversations with marketing leaders from the world's biggest brands, then give the Current Podcast a listen. On the Current Podcast you'll find exclusive interviews with experts and trendsetters who are on the front lines of digital advertising, and they always leave the ad tech jargon at the door. So subscribe to the [e-mail] or anywhere you get your podcasts today.

[Benjamin Shapiro]

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 Benjshaft 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 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 in 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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