He has cold outbound data on 40 million startups. Here's what works. | with Daniel Saks, Co-Founder of Landbase and AppDirect

0:00Product market fit is not something that you don't have and then you have. It's something that you always have to work for within given micro segments. Remember the head of Bell saying, this is going to be on billboards. This is going to be an airport. There's going to be so much that it's going to break the site. Like you got to have the infrastructure to make this work. You know, crunching to get this thing launched. We launched on time. It was like crickets. No one came to the app store. And in fact, like Harley from Shopify came to me saying WTF, the Bell business app store has less traffic than my interns blog.

0:27What happened in the last year is there was a point where there was so much AI slop and so much spam that we're all overloaded. And there was a shot that like, hey, this is never going to work just because it's just our inboxes are flooded and no one's going to ever tune into this. But I think what's happened in the last year is the spam filters have gotten way better at filtering out bad messages and putting in good. It's not just if the message is generated via AI or not. That's not how they distinguish it. It's actually, you know, the relevance and the credibility of the domain. That's product market fit.

0:58Product market fit. Product market fit.

1:00Daniel Saks: I call that the product market fit question. Product market fit. Product market fit. Product market fit. Product market fit. I mean, the name of the show is product market fit. Do you think the product market fit show has product market fit? Because if you do, then there's something you just have to do. You have to take out your phone. You have to leave the show five stars. It lets us reach more founders and it lets us get better guests. Thank you. Dan, welcome to the show, dude. Hey, great to be here, Pablo. Man, I'm excited. You got AppDirect under your belt, which is a massive, massive story.

1:31We'll talk about that a little bit. I mean, multi-billion dollar, doing a billion dollar, and they are close to, you'll tell me exactly, but it's at total scale. And then now you start a company called LandBase, raised a$30 million Series A. And that's in the kind of, if you think about Clay, think about Zoom Info, it does that part of it, but it actually does the reach out as well, a little bit like an artisan, a lot of other companies that, you know, people would know that use AI to actually reach out and get you demos. So it kind of combines a few different pieces of the puzzle. So we're going to talk about that.

1:58And then what I'm really excited about is we're going to take everything that you've learned building land base and talk pretty in depth, actually, about outbound. Because I've got companies, I have one right now at the top of mind, that is moving from inbound to outbound. And it's just not as simple as you might think to really make that work. So you've been doing this for a long time and you've perfected it with land base. So we're going to talk a lot about that. So anyways, over to you. I mean, I'll ask the question we always start with, and I think maybe it makes more sense for AppDirect. But like with AppDirect, when was a moment when you felt like you'd found true product market fit?

2:28So what I like to describe product market fit is the feeling of magnetic momentum. So with AppDirect, we worked at it very hard. And one of our first customers was a telecom in Canada, Bella Canada. And we launched an app marketplace to be able to sell SaaS services. This was back in 2009, 2010, in the early days of SaaS. And some of the initial apps on the App Store included Shopify, which was like a really early stage company at the time, and other Canadian apps in the ecosystem. And that was our first go. We launched it. And because of launching Bell, we had AT &T and Comcast and Deutsche Telekom all of a sudden reaching out.

3:05Because we had this one beachhead, we were able to attract others in the space. And over time, we used that same approach to enter new verticals or geographies. And we would have this strategy of going after a big player. So for example, when we wanted to get into IoT and manufacturing, we had Honeywell. And we would get them, we would evangelize that. And then we found that all the others would come to us saying, hey, we want to do something similar. So what felt like product markets fit to me is this feel of pull, where because of something that you've done here, you've done that elsewhere. And I feel in order to scale, you want to replicate these micro instances of pull or magnetic momentum and expand from beachhead to beachhead.

3:52And my belief is if you want to build a really big business, you can't just do one thing and scale it. Maybe there's a few examples of companies that have done that. But in general, you always need to be innovating. You always need to be changing. And product market fit is not something that you don't have and then you have. It's something that you always have to work for within given micro segments. So our key lesson, which we still take today at App Director is just applicable at LandBase, is you want to look at where is there a leader or an innovator or what I call a digital hero of someone who's going to adopt the technology and everyone else is going to want to follow them because you can see how transformational it was to the company that they're at, but more specifically to the career of the individual that wanted to use your technology and drive a transformation.

4:38So tell me a little bit about Bell. What exactly did you do for Bell back then through AppDirect? So this is the interesting situation with UpDirect is we spent about two years in a room with no windows, 10 engineers, and we had this vision of building an app marketplace. And we had early sponsorship from the president of Bell Canada, which was huge. I'm Canadian, although we were in Silicon Valley at the time. And we would go fly to the Bell headquarters, spend time with them. the mistake we made is we actually only worked with Bell and it was about a year enterprise sales cycle. So to call it a year to sell six months to a year to implement and then another year to figure out if it was working or not.

5:17So all of our stakes was just on this one deal working or not. What is like an app marketplace in this con? I mean, you got like the Shopify app marketplace, right? Obviously iOS, Android, but like for Bell, like what's the idea? Our technical co-founder, Andy Sen had built the Salesforce app exchange, which was really the first B2B app marketplace of the time. And he joined us early on at AppDirect with the vision of building the app exchange for every other company. And our belief was every B2B business needs an app exchange. And that has truly come to fruition. And AppDirect is grateful to power a big majority of these marketplaces in some capacity.

5:53So whether it's marketplaces like SAP and IBM, or whether it's marketplaces like AWS, that's really the power. And what we found and telecom is they have these big business bases. So essentially, Bell had 500 ,000 business customers in Canada. AT &T had 4 million in the US. These businesses wanted to look to their telecom for other value-added services. So it could be security. It could have been, call it collaboration tools. So what we did is we enabled the telecoms to resell all these SaaS services to their client base. And today that generates upwards of 10 billion in gross merchandise value, meaning the transaction volume of our customers.

6:32But in the early days, we said that GMB is our number one metric, but it took us probably five to seven years to figure out how to really get the flywheel going on GMB. So you brought up this Bell case with us. We launched the Bell App Store, and we actually didn't succeed with it. So we learned a lot, and we had very strong conviction in our vision. But while we got this big enterprise behemoth, it actually didn't work. I remember leading up to the launch, seven, two hours ahead, we were trying to recruit all these apps. We had like all these different apps and we worked aggressively to get these in for the Bell launch.

7:05And I remember the head of Bell saying, this is going to be on billboards. This is going to be an airport. There's going to be so much that it's going to break the site. Like you got to have the infrastructure to make this work. And after, you know, crunching to get this thing launched, we launched on time. It was like crickets. No one came to the app store. Wow. Just the worst feeling. Yeah, the worst. And in fact, like Harley from Shopify came to me a few weeks later saying, WTF, the Bell Business App Store has less traffic than my intern's blog. So it was pretty challenging at the time. But what we did is we learned from that experience and we were able to figure out the right ways to commercialize on behalf of our customers.

7:45And that way, when Deutsche Telekom and AT &T launched, they saw very strong success. And it did take a while. What was the learning? Because I would have assumed that they would have done some amount of marketing. And as much as it might not have been, let's say, perfectly effective or efficient, it should have been good enough if the value was really there. But it sounds like it wasn't. It sounds like there was really some kind of optimization that you could figure out. I think what we've learned with B2B technology, and this still extends today, is that businesses want to buy from people they trust.

8:12So brands of trust where they have the right to play. And what we found is like telecoms have a lot of good reason to sell telecommunications services, of video conferencing, security, but maybe they're not the best to sell zero accounting or something else. So it's a matter of figuring out what should be, what actual products should be in that marketplace. Exactly. It's the merchandising strategy. And then the other component is the reason why someone trusts, call it AT &T or Dredge Telecom in a business capacity, is that they've worked with them for many years. So the other insight that we had was instead of just believing that you can get people from a billboard to go on a website, the better strategy was to actually enable the sales channels and the relationships that already exist.

8:53So once we started training the physical human sellers at these companies, they were able to articulate the value prop and that's really what drove a lot of the success and the momentum. And the other question I had, we're going to talk a lot about Outbound, like how do you get Bell as your first customer? How does that happen? Yeah, so we had a chicken and the egg problem. Our vision was like AppDirect. We want to build an app store and sell cloud services to the world. But in order to get the best apps, we needed to showcase that we have customers. So we had this idea of going to the telecoms, because if you have all the global telecoms, then they represent almost every B2B business in the world that's connected.

9:31And the way we got into Bell is we did have an investor relationship. We had an opportunity to pitch. I remember on pitch day, we were pitching against IBM and all these bigger companies, Laszlo Systems and enterprise companies. And you're pitching a marketplace like they wanted a marketplace and you were one of the vendors or you're pitching a new idea to them? No, it was actually an innovation day and we pitched them on the idea of a business marketplace. We came with suits, with printed consulting decks. It was a different time, mind you. I mean, this is what, 2008, you said? 2009, 10, 11. We were 23 at the time, 24 at the time and just went in there and had this conviction.

10:07Tech didn't have the respect that it has today. Do you know what I mean? like especially for a big company like the tacos you gotta you gotta go and suit up yeah we had to suit up it was like serious board meetings long negotiations and uh yeah i remember at deutsche telecom we had a meeting with them and it was like call it 15 people in a formal board meeting with a suit and this was pre-covid you know by a long shot but i was doing the call virtually and i was upstairs i happened to be in my like parents house and just as i was in the meeting, I like had my suit on, but like only boxers on no, no, like formal pants below.

10:44And my mom like opened the door and said, Daniel, lunch is ready. And I stood up. Oh, God. And like years later, the sponsor, George Silicon told me like, yeah, they kind of recognize that, that that happened, but they thought it was cool. They're like, yeah, here's, you know, young guys hustling with Silicon Valley energy and attitude. And, you know, a lot of these big Companies at the time wanted to bring the energy of Silicon Valley to these big enterprises. And that was a lot of the wedge that we had in the early days. I took you off track, but back to that Bell thing, you're pitching against all these people.

11:14Why do you think they chose you? I think it was that we had a very concrete vision of how Bell could make money from cloud. And just like today, every business and every board is thinking about how can we make money from AI? What are the best ways to monetize AI? We had a really strong story for how all these different businesses could benefit from cloud. Got it. You're a co-CEO, is that right? Yeah, I was co-CEO for many years. And then just as AI and Agentec AI was hitting, I transitioned my co-CEO role to my co-founder. He's running the CEO. It's been tremendous under his leadership. I'm still on the board and couldn't say better things about where AppDirect is headed, but had the opportunity to start again in the infancy of the AI phase.

11:57And I think there's a ton of parallels to building in the cloud era and then starting again in the early stages of the agentic era. And a lot changes, but a lot of the same principles or learning stay the same. Yeah, I was going to ask, I mean, you know, just maybe as a segue type question, like what is the app directive today? Because obviously that vision of a market, I mean, I'll just give you maybe a stupid example, but, you know, I'll just buy whatever Claude tells me at this point. You know, I'll just interact with it, be like, let's do this thing. What do you really need? Oh, you really need that?

12:27Okay, fine, buy it. You know, does it have an API? Great. Like, you know, that's the kind of old world of, you know, I log in somewhere and I go into their marketplace and I see these things like seems foreign to me, but is that still happening or is there a new, like, is there a new vision for like AppDirect? How do you think that plays out? Yeah, so AppDirect has become the everything store for B2B. And if a business wants to buy recurring technology, generally a lot of that business is going to go through AppDirect in the backend. And we have now 10 ,000 agents, resellers, VARs, maybe many more.

13:00We have many enterprise app stores. So think of us as like the plumbing in many ways to get access to these ecosystems. And we've grown by category. So now we sell telecom, we sell energy, we sell business services, we sell IT, we sell all types of different business technologies to many different channels. And we've become really the standard. So for a lot of startups, you may just go online and buy your own stuff. but most businesses with procurement arms are always going to buy through people. And that's where AppDirect has really shined. And we've been very acquisitive and we own brands, including PartnerStack, which is a leading referral marketplace that a lot of people are familiar with.

13:40FirstBase, which is one of the ways startups acquire technology and their computers and laptops and other procurement. So there are a lot of avenues in which we've grown, all stemming from this vision of the B2B everything store. and I think in the world of AI, there's a lot that can change. Like how do we index on Cloud, which I think AppDirect is very good at because it has such a deep catalog and knowledge and network. So it's either our agents or our platform customers are probably the ones that show up in Cloud versus AppDirect themselves. You're kind of behind the scenes. Like I might be using it or somebody, some business could be using it.

14:17They wouldn't necessarily know. Exactly, yeah. Okay. We have like millions and millions of business users that may not know that we're powering it, but we are. Tell me about this transition period. Like, how do you perceive what's happening in AI and how do you decide to leave something that's grown to be so big to start something from zero again? So I think in many ways, like in 2023, AI was at the infancy and it was unclear of how it would manifest at the application layer within businesses. And I thought if there's ever a time to start something again, that would be it. But I think in terms of just managing that transition, just full confidence to the leadership team that was in place and Nicholas, my co-founder and CEO.

14:59And I think part of my maturity was knowing that, hey, I think the business is ready to have one CEO. I think Nick's the right guy to do it. And that leaves opportunities for me to start new things. So I think that that was a transition that took many years and we were really methodical about, but very excited about what's occurred there. And it allowed me to get back to the startup and entrepreneurial juices that I was really excited about. So you started this like six months or so after ChatGPT. What was the original idea? So really the thesis was I had big conviction that beyond generative AI, agentic AI, which can take action, is what's going to be transformative for businesses.

15:33And we were one of the first people to talk about agentic AI. Yeah, that's early. I mean, that was like right after the moment. Exactly. And where we honed in was on sales and marketing or go-to-market because from my AppDirect experience, the most important thing a business needs is revenue. And it's very hard to predictably identify who you should reach out to and how you contact them to drive pipeline and conversion. So I wanted to start a business that really solves the biggest pain that I went through. And I partnered with Wa Gao, who is a Stanford PhD in machine learning on a co-founding team of EverString, which was a machine learning startup that was bought by ZoomInfo.

16:10And that team became one third of ZoomInfo's revenue and really transformative to their growth. while wanted to, similar to me, start again in the agentic era, taking go-to-market to the next level. AISDR was the most obvious thing to do in go-to-market around that time. Did you start there? Yeah, I'd say I didn't ever love the term AISDR because I believe that it's better to enable humans than replace them. But what we did really hone in on was if you could be really good at identifying who you reach out to, drafting the messaging, and then executing across channels, then you can automate a lot of the manual work that goes into prospecting with better efficacy.

16:48And one of the unique things that we did with our AI lab is we actually built models. The first model was GTM1 Omni. And what we did is we actually, through partners, had access to a lot of transactional data from campaigns. And we trained our AI on what works and what doesn't. And we were able to prove about a 4 to 7x uplift in efficacy for outbound campaigns. And that was really the formational secret sauce. And over time, and this kind of applies to your listeners, what we saw is that it's getting harder and harder to have success in Outbound. And there's two ways people react to that. One is driving volume upwards through AI slop and just spraying and praying.

17:29The other is actually getting super methodical and targeted about how you approach these outcomes. And we're finding the people who are spraying and praying are falling into regulatory headwinds, spam issues, really not driving a lot of value. And it can be very frustrating. The ones that are seeing most success are really thinking about how do I really hyper target the right company and the right people with the right value proposition at the right time. And in order to do that, what we found is that you need to have access to a lot of different fields about a company and a person. so you can intelligently identify the right people to go after.

18:06And that's been the biggest lever across our network in the last, let's call it, year and a half for success. And we have case studies with many businesses where they have large SDR teams and the SDRs were manually going into ZoomInfo and filtering or going into Apollo and filtering. That took 35 % of their time. They'd maybe be starting to use ChatGPT or Claude to draft some messages. but what we can do is we can essentially using our models we can train for your company a unique value prop that understands like what's going to work what's not we can prioritize who you should target and then we can have your reps reach out to the high value targets call it with a phone call or even have your execs go in person but then automate some of the lower tier list and that's driving two to four x connect rates and meetings booked rates across our network so seeing incredible value in terms of the time savings so reps don't have to list build anymore or manually think about a lot of the email and LinkedIn.

19:06And that way they can be more focused on doing what they love and do best, which is being in front of customers. And we're seeing the killer outbound teams be people who are very calling centric or in-person centric. And they're trying to use GTM engineering via a land-based and clod or alternatively to us, you know, maybe a clay to essentially automate a lot of these workflows so they can be very targeted in who they spend time with. I was going to ask you specifically about clay, like they're ripping. I mean, they just raised it like a$7 billion valuation seems to have been. What do you think they got right right in the world of like Zoom Info and Apollo and all these other players?

19:41Like what did clay get so right in your opinion? I think the key thing was there was no infrastructure to be able to aggregate different data sources and therefore orchestrate or automate capability. So in the past, you had to have a user going into ZoomInfo or Apollo with a cursor and make their own judgment on who they go after. And therefore, it's just a really manual fragmented process. And no one data vendor has the best, call it, access to understand who you should go after and to have the right contact info. So I think what Clay got right was really leveraging the creativity of sellers in a way that they could act as engineers to orchestrate data in new ways.

20:24And I think Kareem was like super ahead of his time. It's amazing what they did because they really started this pre-AI, but were able to leverage a lot of the AI to take it to the next level. What can you do is like you're a go-to-market person and you're going to use ZoomInfo or you're going to use Clay and then we're going to bring in land-based. But I just want to understand just from that perspective, I mean, ZoomInfo is pretty straightforward, probably like Apollo. Like you just, you set filters, like I want businesses, there's many employees, this geography, you know, this industry, whatever.

20:51And it builds you a list. At least that would be my simple understanding. I played a little bit about it. I'm not an outbound GTM person, right? So I don't go super deep. With Clay, though, what would be, how would that work? What's so different about it? Yeah, so on ZoomInfo, you would be manually, you know, filtering within your interface. And it's very time-consuming to build a list. And you get charged credits every time you, like, download a list. And then you call that list, and the list might have very low efficacy. The challenge with Clay is that you need to be very technical. You need to be a GTM engineer.

21:18You need to have sophistication in order to build these lists. But essentially what they did is they connected to the Zoom Infos and Apollos and many others and allow someone to import data from many different data sources, play around and prioritize that data, even potentially like validate that data through online sources, and then push it out to your sequence or call it, push it out to Instantly or push it out to Outreach or whatever that might be. So it's similar, but it's just better because it ties to many different data sources. Is that a simple way to think about it? Yeah, that's a good way to put it is that ZoomInfo has their own data and you can only use your own data.

21:51You need to be interfacing it on the ZoomInfo, you know, call it software. Whereas with Clay, you can pull in the data sources, you can play around in tables, and then you can push them to what you need. And what's different about LandBase, because we started a Gentic native, is that we actually built it for agents to reason over. So instead of a GTM engineer needing to call it, like spend a lot of time with clay credits and clay tables, essentially land-based can go and learn a lot about you. We have a lot of information about every business, but you can give it access to your CRM or to your other data.

22:24And we can then autonomously identify and score who your top accounts should be, suggest how you go after them, suggest messaging. And we're built native within Cloud Code and Codex. So one of the challenges with Cloud Code and Codex is that if they're recalling info from an LLM, they're sharing what's available on the public internet, but that's nowhere near the comprehensiveness of what exists in terms of people and companies. So with land-based plus Cloud Code, we're giving the Cloud and Codex context to call it 40 million businesses, 400 million business profiles, about 1500 fields on each of these areas that you can use as custom signals.

23:03So if you wanted to say, one query that I just did is, hey, we want to target companies that have over 100 SDRs or prospecting companies in the US. No one else has the data in order to, or is able to write the SQL in a way to do that analysis. But land-based in cloud code can do that in minutes and give really good evidence. The other thing that we did recently, and we're going to actually be sharing at Pavilion coming up in September in New York, is we did benchmarking. So just like there's the software engineer bench that OpenAI pioneered, where you can benchmark the efficacy of co-gen players to create engineering workflows, we did the same thing for prospecting, where we looked at how do you have the most precise list that's going to drive the best outcome?

23:45And we tested Lambace, Apollo, ZoomInfo, Clay, and our precision is more than 2x, and I think that correlates with the results that our customers are seeing. But the way we were able to get there is to index all this info so agents can reason over data, and therefore it makes it easier for someone to just focus on what they do best, which is calling or being in person with clients. And you can go online or LinkedIn and you see a ton of people talking about land-based and the impact that they've had. These are, call it fractional SDRs or SDRs at companies that for many years had to source things manually in these databases.

24:18Or if they did use Clay, they had to spend a lot of time on Clay and a lot of credits and costs. Whereas now they can go to Claude and put it in land-based and just say, hey, who should my top accounts be? Who I go after today? and why? Can you choose them? Can you score them? So you can set up land-based in an always-on way where it's always telling you, hey, today, here's who you should go after and why. Here's what you can, here's who you should call. Here's the phone number. Do it now. And it's all automated. If you want it, will it email and call for you? Yeah. So we don't have voice calling because it's not, there's regulatory hurdles around that.

24:51We can do automated outbound in terms of like LinkedIn email. And then we have a dialer that allows people to dial. What I'd say is the secret sauce. And this is what we've learned over the years. The secret sauce isn't necessarily like the AISDR functionality of just being able to do everything in one tool. The secret sauce is really how do you leverage your unique data plus third-party data to have a much more targeted list and to have the data that understands how to help you craft the message that's going to be the right person, the right value prop at the right company at the right time. And that's really what differentiates people who are successful without bound from people who aren't.

25:31Daniel Saks: We have tens of thousands of people who have followed the show. Are you one of those people? You want to be a part of the group. You want to be a part of those tens of thousands of followers. So hit the follow button. We'll probably weave the story in as we go, maybe on tangents, but like I do want to make sure we get enough time on quarter market, on outbound specifically, because I think there's just so much value we can probably extract there. So imagine you're an investor, right, in a company. So you have like, you have a stake, right? And they're like, listen, we want to start an outbound function.

25:58Like we've got some amount of product market fit because that's always an issue. I mean, if the thing you're selling nobody wants, nothing's going to solve that for you, right? But it's like, listen, we've got this product. Customers are happy. Retention is decent. We've got an amount of inbound. You know, we're working on that. But outbound is beautiful because if you figure it out, you can just control it, right? Like you really can dial that up. The numbers around it start to get pretty predictable if you can figure something out. Where do you start, right? Like what are some of the obvious questions that you would ask?

26:25Like we're going to have a 30-minute conversation and I'm a founder. that you've invested in and wants to do outbound, right? Like, we'll go from there. Obviously, I have enough to pull out. But just from a starting perspective, like, where would you start? Yeah, so step one for any company is know your TAM. So you have to understand and build a comprehensive TAM map that would articulate, okay, for my business, here are the segments that I can go after. Here are the exact companies. Here are the people at those companies. And to have that living TAM map is actually a very costly or difficult exercise.

26:56In fact, when I was at AppDirect, I remember maybe at our Series C, we hired Grant Thornton, a firm, and we paid a few hundred thousand to build this TAM map that showed, okay, here are the industries you can go after, telco software, manufacturing, here's the estimated market size. Today, with tools like Lambase, you can have Claude build that TAM map for you. And as you mentioned, there is a key, which is like how do you prompt it to do the right things? And a lot of our efforts are helping our customers understand the perfect prompt. but if you already have a lot of context in your cloud code you could literally uh go to cloud code and say use land base to build me a comprehensive tam map and it's going to look through your call recordings it's going to look through your crm it's going to look through your win loss records it's going to look through your website it's going to look through your competitors and it's going to say okay here are the top segments that you should go after here's the tiered prioritization of them um and then it can do a lot of research and qualification So a lot of times traditionally in prospecting, if you just ask Apollo, like, hey, find me manufacturing companies in Ohio, they're not going to actually be the manufacturing companies you want.

28:04There's going to be a lot of fluff in there. It's going to be really confusing. So what we can do is actually go in automatically and do research to understand, like, is this the exact person or story that you would need? So for example, with land-based, while we service manufacturing companies like Honeywell or ABB or Schneider Electric, we weren't going into the traditional selling arms. We were typically looking at what are the IoT initiatives that they're underpinning. And you can't do that type of work on ZoomInfo or Grata or Crunchbase. You have to do a lot of manual research. And that's why in the past, reps were left to do this on their own.

28:39It'd be very time-consuming and manual. But with Lambase and Claude, this can be done centrally by the head of RevOps, by the CRO, by the CEO, if it's a smaller company. And having that visibility to your TAM map gives you all the power in the world to understand how you forecast, how you think through your pipeline, how big your TAM is, and if you have to build adjacent TAMs, how well you're penetrating your initial TAM. And just as I mentioned, the key to product market fit is identifying these tight beachheads in which you can dominate. So with AppDirect, it was initially large telcos around the world, and then it moved into adjacent fields.

29:14What's super important is understanding, like, are you penetrating that? So like Peter Thiel through Mithril was one of our investors at AppDirect. He always talked about the idea of dominating a small niche market that can really grow and then finding adjacent markets or adjacent products to be able to expand. That's what I really refer to as this magnetic momentum. So having a TAM map allows you to do, it's a total addressable market. It's allowing you to understand, okay, for my initial segment, how well am I penetrating that? How much more should I hit at it? You can even find out through Landbase where your competitors penetrated versus you.

29:48And this is all really helpful for an executive team, for a board to understand how to navigate. So for example, at Landbase, one of our recent pull areas has been what we call fractional SDRs. So these are top callers that maybe left, you know, a big company as a BBR and went out on their own and they find their own customers. But for these fractional SDRs, they need to spend time list building. And that's very time consuming, very difficult. So there are these like power sellers or fractional SDRs, Fletcher Cox, Jesse Rupa, Tony Brophy. These are like, you know, people who have huge LinkedIn followings and are seeing a lot of success in calling.

30:27what we found is we enabled one of them to use our CLI. Then all of a sudden, they're like, I'm going to talk to more of my friends. Now we have like this whole influencer network that's using it and promoting it. And then it's impacting their downstream channel. So that's an example where the fractional SEO market's very niche. It's not big enough for me to say that I'm going to be a$10 billion company from. But the pull in that market is strong. So I can say, how well penetrated are we on these fractional SDRs? and what's the next adjacent market that we can move to where we can capture a higher contract value or have a bigger TAM.

31:03And then how do we penetrate that market? Going back to like how I started the conversation when you said like, what does product market fit feel like? I don't believe the product market is fit is something that you don't have and then you have and you always have it. And it's just like easy. I believe that you're always fighting to find product market fit in adjacent categories. And the way you can feel it is the pull. So the example of, you know, us with fractional SDRs is important. And how do I navigate that? It's using land-based, but I have my TAM map. I understand that fractional SDR is actually a pretty small segment of my TAM, but I'm dominating that.

31:37And because of that dominance, I can then go into the next market that might still be a smaller niche market, but I can dominate that too, instead of being too wide. One of the things on TAM is like with this breadth and niche, like one of the challenges I see is I've got, I mean, there's companies, a startup company, sounds like customer success, AI for customer success. Or like everybody has customer success. Like my world is everybody. So you can segment however you want. The upside is you're not going to run out. I mean, you can go crazy on volume and just go. I've got other companies that are like, I sell to a market that's still a big market, but it's like maybe there's thousands of leads if you really think about it.

32:12And like you will run out. Does that mean outbound just doesn't work? Or it's like you have to do it a different way? How do you think about the relationship between how many accounts there could be and how you therefore should treat outbound? Yeah, so I think like the best outbound companies are ones that have massive TAMs and massive value props. So they have their own pull. I'd call like Rippling, Ram, Fricada, they're probably the powerhouses for sophistication in outbound prospecting. And they have the credibility to go out there and they have the hook that's gonna be very strong. I think for most companies, that's not the reality.

32:44They either have a small TAM, which means you have to be much more careful on how you activate that TAM. or if they go after too wide of a TAM, they're going to fall into issues where the pull is not strong enough and therefore they have a lot of people marketing the spam and therefore the campaigns get burned and they don't see a lot of success. So what we believe is you need to go with precision. And even if you have a small TAM, oftentimes that small TAM could actually be large companies with many people and you have to figure out, okay, who within this company do I go after? So traditionally there was like ABM motions, account-based marketing.

33:20So what we've found is you can use land-based to intelligently approach account-based marketing. And even though your TAM might just be a thousand fortune 1000s, within those 1000s, there may be millions of people that you have to figure out who am I going to navigate to. And the titles are not obvious or indicative of who owns what the outcome is. So that's where you want to bring intelligence to the forefront to say, okay, who should we go after in which priority? Have they talked about this on LinkedIn? Is their job description open for the pain point that I have that we can solve? And that level of precision can make you as a seller or founder-based seller or a SDR team or AE far more efficient because you're going after the right people at the right time with the right value problem.

34:04So that's kind of step one is kind of build that TAM and understand what it is and what kind of game you're playing. What would be step two? Yeah. So key thing with that TAM is to score it and prioritize it and understand who are the top accounts in which you want to put a lot of effort to traditionally called account based marketing. And what we even do is we say, okay, for our top tier A accounts, I'm the one that's going to do the outreach, because they're so strategic and important. And we're going to put effort to go in person and meet them because the contract value can be big. The next tier would be people that my team can go after.

34:35And they're in the sweet spot. And then there's lower tiers in which, hey, it'd be nice if they reach out to us, but we're not gonna we're going to do that on autopilot using the AISDR functionality of you're prospecting out on LinkedIn or email, but maybe not giving calls or not spending in-person time. So the key is prioritizing your reps time because to drive pipeline, you know, the limitation is always going to be your time and capacity. You want to make sure that you're focusing on the right things. Let's talk about one and two. Yeah. So like the ones that you've decided, because that's very common, like almost every founder I work with has some accounts that are like, whatever enterprise means to them is like, these are the ones that would just change the game for us.

35:12So I'm going after them. But what does excellence look like in that world? Like for you, you're like, these are my 10 accounts, whatever that is, maybe it's 50. But I mean, I'm curious, how many accounts is that? And what are you doing with each account? Yeah, so I think the key for excellence here is making sure that it's genuine. So you're reaching out to the right person, right time with the right message. But you've put a lot of thought into the value crop. So in those accounts, we actually use AI to create case studies where we can go in and we have different elements. So we can pre run a TAM map for these CEOs in our case, right?

35:43And we'll say, here's what we've seen as your TAM. Here's the hard to reach TAM. Here's how we can help you get there. Here's the business case that's customized of how you get there. We create these little like landing pages in some cases that are customized pilots in a way to showcase, hey, here's the data that we can get for you that you can't get elsewhere. And we would do that only for the top accounts because there is a cost to running that. We also have checks and balances where humans would have over time, like looked at that, reinforced it, edited it. And then it gets to a point where it's pretty precise without human intervention.

36:14And that's the level of focus that I have. So for example, like over my career, and people sometimes say like cold email, does it work, does it not? I mean, I had Michael Dell cold email me, Aaron Levy cold email me. Some of the best opportunities I've had have been going outbound and emailing people. So the key though is it needs to be right person, right time, genuine interest. The other thing which correlates to this feeling of magnetic momentum or product market fit is it's much more powerful if you can have someone come to you. So I gave the example of we launched Bell and because of that, we talked about it.

36:48And then AT &T and Comcast came. I think one of the things that I've seen is the big secret sauce in a lot of companies growth is you work really hard on one company. You evangelize that case study, but then you go and you share that case study with others. So one of the outbound motions that works very well is to showcase, hey, we understand who you are and who you're targeting. We've serviced similar companies to you and had this level of success and articulating that very succinctly. How are you doing that? Like walk me through like the specifics on that because the idea makes a lot of sense.

37:19But just, you know, are you getting a warm intro to someone? Are you like running into them at a conference? Are you just like straight up cold outbound being like, hey, we work with XYZ. Like, you know, like does anybody even read that? I mean, what's the approach to get that message even just listened to on the other side? Yeah, so it's surprising that if you have cloud code and cloud code or codex is like indexing a lot of your stuff, your calls, your Slack, your CRM, it's going to know a ton about what's working, what's not and who you should go after. And we also put all of our customer case studies in skill files in our cloud.

37:52So what I'd recommend is like a step one for a company. And this could be really any company of any size. But it's how do you give agents context to your win loss to your customers, your call records, the agents can very effectively reason over your data to be able to say, okay, this is what each person needs. But you do need to put in place checks and balances to make sure that the output is strong and it doesn't come across as a slop. So we work with our partners, depending on their level of technical maturity, to think through skill files and templates and ways to identify how to best activate their outbound motions.

38:28But it's possible today to have really good understanding of like who your best customers are and why and therefore other customers that look like them that should have similar value um and you know cloud code or codex can just do that for you they can apply with our with land basis data plus your data they can understand okay here are similar companies the ones that you're going after today here are similar people use this case study data and and go after them and you're going after them like just here's a cold email here's here's a case study over cold email for example for your 10 accounts yeah it could be so normally we do omni-channel outreach, it's called email and it's LinkedIn from the top accounts is coming from me for lower tier accounts, maybe coming from our SDRs.

39:08But for our top tier accounts, I'd also be offering, you know, potentially like an in-person meeting or a contact or seeing them at an event. We do conference campaigns. So I'm speaking at Pavilion NYC in September. Landis has the data on predicting who's going to be at the conference. We could do pre-outreach to tee up those meetings. So I think the key theme, depending on your level of cloud or AI maturity, is you can orchestrate a lot of this centrally in cloud code if it has the right context. And you can do what would have previously taken teams of hundreds of people and you can do it really effectively.

39:43But the key is giving the agents the right context to enable your humans to have the best outcomes. What's a good expectation on like, let's say you're doing this stuff right. We're talking cold, outbound, right. in terms of response rates, right? Like what kind of volume do you need to operate at even just to see any level of success? So it's really tough out there on email. I think there's a lot of people on LinkedIn who say, oh, I have like these high response rates, but we see aggregate and millions of volume. I think in general, you're looking at a 2 % response rate even on a good list for email because of spam and deliverability.

40:15But if you have a tight list and it's pretty strong, you can get to 8 % to 10%. And then hypothesize that stronger companies with big brands like a Rippling or Ramp might be in the 20 % range, but that's very rare. And they've spent a lot of time on customized outreach. I think for connect rates, it's similar where industry connect rates, people talk about 8 % to 10 % as being normal and great. Connect rate being what? Like connecting on LinkedIn or are you talking about connecting in a meeting? No, phone connect rate. So if you're a dialer for however many calls, how many pickups there are. And in general, we find a lot of companies that are sitting at like 2 % connect rates, they struggle.

40:54then if you have the right list, you can uplift that to 8 % to 10%. A lot of these fractional SDRs that I was talking about, Fletcher Cox, Tony Brophy, we were able to 2x or even 4x their connect rates, which follows on to book meeting rates. And the economics for this is incredible because if you were an SDR spending 30 % of your time list building and then maybe a lot of time doing extra research, you know, originally like call it 94 % of the people you're calling are not picking up, it's tough. But if you automate all your list building, you have this automated TAM map, and then all of a sudden you're getting 4X Connect Uplift, and every day you're booking way more meetings.

41:29So that's the power of what we're doing is we're using agents and agentic AI to make sure that as a seller, you're getting better shot with the people that you're targeting. And what's the answer to it in the sense that if you've got, like, how many accounts are you personally going after? I would have 100 in my top heat map, and I would limit it not just to accounts, but to the people within the accounts. So I'm going after the exec sponsors, but then I have my team that would go after the people on the ground. So my outreach would be more to a CEO or potentially a CRO. And then my team would map in different levels.

42:03How far would you take it? Like, just to follow up on that, you're going after a CEO. You hit him up three times. Like, would you just hit him up X times over each quarter? So we've seen all the data on this. You could do different. It's called a sequence. So we enable omni-channel sequences, meaning hit them up first, you know, with email, then a call, then LinkedIn. connect with them on LinkedIn, but don't send the message until later. We've done testing on all of it. And what we found is generally three sequences is going to get you 90 % of it. If you go to five, maybe you get an extra 10%, but you risk people flagging you for spam.

42:33So I'd say like the sweet spot is probably three, maybe four, if you have the right message. And then I'd say that what people underestimate is that they could send emails and not get email responses, but people do see it, and then you become a familiar name when you call, you can reference that email. And one of my first jobs back in the day, this is when I was in college, was a wealth manager at Royal Bank of Canada. I worked for a wealth manager doing old school prospecting. And he literally gave me a physical phone book and said, go find rich people in a zip code and start calling out. At the time, what I learned is that if you were to just say, hi, I'm Daniel Sachs calling on behalf of Ami Shor from RBC.

43:14You know, do you want to talk? It would be like a weaker signal. But what we actually did is send physical mail first and we'd say, hey, I'm calling from RBC. Did you see the message we sent you with like a portfolio review offer? And then they say, oh, maybe I saw it, maybe I didn't. But that facilitates a better hook for a conversation. So I think the key thing is you can warm people up to the calls by using multi-channel touches. And the key thing here is always to just build trust and credibility. So what I'm doing with my whole team is encouraging them to build brands within LinkedIn. And I find that my sales team members that have bigger LinkedIn following are the ones that get better credibility because people look them up right away and want to work with them.

43:55My team has tons of outbound calls going all the time and I get snippets of them and I look at them for QA. But just this morning, there was like one of our target accounts was reached out by one of my SDRs. And the guy said, well, let me just make sure you're legit. I'm going to look you up. and he goes like looks up land dates, looks up the guy's name, Max Wu. And Max has 10 ,000 followers on LinkedIn. And he's like, oh yeah, you're legit. You're a thought leader. I see this, I see you're funded by, you know, Series A company. That builds trust. So the more you can do to build trust is what's going to drive the efficacy of the cold outreach.

44:27The example that I give there is like Michael Dell cold email me as email was michael at dell.com. And I like double shot saying, is this really him? But fuck, yeah, I'm going to respond. But if it's a unknown SDR from a really weak company, there's not a chance that I'm ever going to read that message. So you have to think of ways to build credibility. And often that time, that's just leveraging and building an online profile. So, you know, the CEO, you as a CEO, or even you as your sales team can be credible thought leaders that people want to spend the time to talk to. I think, you know, the lesson there for me, at least is like, you have to find a way, because it's true, anything that you get that you feel like is cold outbound, it just, my default is ignore.

45:04Just ignore it. How do you turn something so that it's, for whatever reason, just slightly above cold outbound, right? Obviously, if you have just like, you know, you're Michael Dell, it's like, okay, cool. Like this person's reaching out to me directly. Like I'm, it's a no-brainer, right? But like anything you can do, like you said, you know, warm it up through email, whatever, have a like online visibility so that people are like, maybe I've seen that name before. I feel like I know this person or like, just anything like that already puts you in a different ballgame and you're going to see new response rates.

45:32Yeah, no, exactly. Yeah, people often say, oh, cold outbound doesn't work. I don't pick up the phone. But you'd be surprised at how many people really do. And if it's the right person, the right message at the right time, it's credible. And look, honestly, I've hired people based on them cold emailing me. I've worked with a lot of vendors based on cold emailing me. So I think it's a very effective channel. There's just too much lack of trust and there's too much proliferation of AI slop and overload and spam. So if you're being untargeted, I think the benefit actually, so what's happened in the last year, which could be seen as a headwind for our company, but I actually have seen it as effective, is there was a point where there was so much AI slop and so much spam that we're all overloaded.

46:13And there was a shot that like, hey, this is never going to work just because it's just our inboxes are flooded and no one's going to ever tune into this. But I think what's happened in the last year is the spam filters have gotten way better at filtering out bad messages and putting in good. And what we've seen from managing a lot of email deliverability and LinkedIn messaging is that it's not just if the message is generated via AI or not. That's not how they distinguish it. It's actually the relevance and the credibility of the domain. One of the things that we did to add a ton of credibility is that you can get your domain authorized to get a blue checkmark in your inbox.

46:49So you need a lot to do that. It took us like a year to get. But now whenever I send an email, it's going to be a verified blue checkmark. And that's done a lot to increase conversion rates. And then other techniques that we have is definitely having better LLM indexing, as you said. So if someone's going to be searching, how do I find or target this person? They'll say, hey, use land-based. Simple question. Just on sequencing, you talked about three kind of steps. It gets you 90 % of value. How quickly does that reset? Like I do three and then in the month, no reply. Okay, cool. I put you in a pile.

47:18At some point, I'm going to hit you up again. Is that in six months, in a year? Like what's the default there? It depends on how often you run through your list. So for example, one of my team members was doing outreach to the GTM owners at Private Equity to support their portfolio. And maybe it took a couple of weeks to burn through the list. And what our AI would recommend is probably, okay, let's go back to the ones that are engaging that have, you know, we can see that they're opening the emails or they're following up, but the rest can go dormant for call at a quarter and then we can go back after them.

47:50And if you have this live TAM map, then you can see who you've penetrated. So within each of these sub segments that you have, I would want to look at, okay, if I want to dominate fractional SDRs, How many are there? How many have I touched? How many have responded? How many of them are with competitors? And in the world of like a small enterprise TAM, that knowledge is power. So knowing, okay, I have 100 enterprise companies that I can go after in manufacturing. We've talked to 70 % or we've reached out to 70%, you know, call it 50 % have either said no or said yes. You know, of the ones that said no, they told us why.

48:26Maybe it's like we're working with a competitor and it's a three-year contract. And then you can mark like, okay, in three years, you know, or call it two years, so you have time to prep, go back. And if you're working within cloud code and you have all this indexed, cloud will do this for you based on the way you can set up land base. So I think if there were like, call it maturities of sales development, you know, the old school way would have been go call from the phone book, like I described manually dial. You know, the next would be you're using a Zoom info to do the research, you're maybe doing manual web research, and then you're manually sending an email or LinkedIn or a call.

49:03I think then the next maturity would be call it go into clay, pull in data sources, have your TAM, push that out. I think the next frontier is just being native in cloud code or codex where you give it all the context and it's going to run this for you live. And it's going to activate your TAM for you. And the power of that is incredible. And you would have previously needed a way, way bigger team to be able to activate that whole TAM. What's one of the most common mistakes around outbound go to market that you see? Outbound is not, it's just like product market fit, actually. Outbound is like product market fit.

49:36It's not something that you have, and it works forever. You always have to be constantly experimenting. So chances are, with outbound, the first things that you do, whether it's the message, the channel or the target, it's going to be wrong. And you should be see yourself as like rapidly experimenting at low volumes until you have that pull. And it's really not good to scale weak value prop or weak target because you're just going to get flagged as spam and your email campaigns are going to be burned and you're going to have no success. So I in fact tell a lot of startups, don't do outbound until you have a really strong digital presence where people can look you up or look your company up and see, hey, this is really working.

50:15So I think the biggest pitfall startups have is they'll approach Spray and Pray Outbound early and set it all up and then say, hey, it's not working and then give up on it for years. Well, let me ask you the flip side of that. Like imagine I said to you, there's a company, has product market fit, like just take it as given. People like the product. Outbound is not working. What is default for you? It's like, this is probably why, obviously you haven't looked at it and there's different, but like generally speaking, what's the thing that they probably are not doing as well as they could? The main thing, yeah, it's probably if you put all of that context into Claude and it can see your call notes and your connect rates and it can see your CRM records and win-loss, Claude can tell you, you know, here's why it's not working.

50:58It's because of you're going after the wrong person, wrong message, less signal. It's too competitive. So for certain markets like recruiting, if you're going out to a company and saying, hey, I can help recruit for you. There's so many other recruiting messages that it just gets fallen in the mix. So there's certain industries where this is tough. And that's where AppDirect has indexed, or sorry, LandBase has indexed all this data and trained on it. So we can tell you with context and cloud code, like, hey, yeah, the issue that you have here is you're going after the wrong ICP, or it's too broad of a TAM, or you're going after the wrong person within the right company.

51:33Or, you know, this is a market in which It's just overburdened with outbound and therefore it's really going to be hard to differentiate. So you need to spend time with a unique value prop or hook. So I think the key is if you feel like you have product market fit and you're trying outbound and it's not working, you got to experiment a lot. The other thing that I found is that if you have the average SDR that's been around for the last few years and they were built on the era where they spend 30 % of their time filtering in Zoom info and call it 30 % of their time on LinkedIn and email and like very little ton calling, you're going to have not a lot of success with calling.

52:10So what I find is like calling is an art and people who like love and breathe calling, you can feel their energy and they're going to be, you know, dialing, they're going to be on it. And that's probably 10 % or less of the SDR pool. So what we see is that email and LinkedIn are good, but they're not going to be the best channel today. The best channel today often is calling, but you need a DNA of a caller. So if you're a founder, what I would say is you can automate the TAM mapping, the email, the list building, using tools like LandBase and CloudCode, and then you can focus on hiring SDRs that are going to be like these great callers.

52:44And that's much better than just hiring an average SDR and telling them do everything and they do it the old way. And that just doesn't scale. Love it. Well, Dan, thanks for jumping on the show, man. It's been great. Yeah, love chatting with you. And feel free to reach out to me, daniel at landbase.com, or you can see us at landbase.com or my LinkedIn.

53:03Daniel Saks: So picture this. It's months from now, years from now, and one of your founder friends, a really close founder friends of yours, guess what? Their startup went bankrupt. And it turns out if you had just shared the product market fit show with them, they would have learned everything they needed to to find product market fit and to create a huge success. But instead, their startup has completely failed. You have blood on your hands. Don't let that happen. You don't want to live like that. It is terrible. So do what you need to do. Tell them about the show. Send it to them. Put it on WhatsApp. Put it on Slack.

53:37Daniel Saks: Put it where you need to put it. Just make sure they know about it and they check it out.