BSMS96 - Signal-Based Marketing and the End of Broad ABM

Foreign. Welcome to the B2B SaaS Marketing Snacks Podcast. It's so exciting to have someone here who's not only a great builder of tools now that the relevant for our audience of B2B SaaS founders and practitioners, but also someone who's been a multi time entrepreneur and B2B SaaS startup owner, founder yourself. And I don't even know what's the definition of a startup these days. Right. Because one of the things you're working on now you've done for a while, you're actually really experienced in it, which is why I think this was a great opportunity to have you on the show and talk a little bit about that. So welcome. Yeah, thank you. Our journey hasn't come together before, but we were at the same company before at Microsoft. I was there in the late 90s, you were there in the late 80s, so I don't think we overlapped, but yeah. What were you up to there? I was in the office world. You were more on the software engineering side, right? That is correct, yes. I mean. Oh, this is bringing back memories of my Microsoft days. Yeah. I was basically fresh out of college, you know, went to University of Wisconsin Madison and then got hired in as a fresh engineer in the languages group. So early versions of their linker and nmake Nmaker is like a make tool that you put together software programs. So did that and I think I was probably more of a geek, a tech geek and got excited by distributed databases that back in the day there was a company called Digital that they were building a distributed database in Colorado so ended up joining them. So probably not a very smart thing to do from a business and overall growth of the business point of view. Microsoft was obviously on a growth trajectory, et cetera, et cetera, but that's kind of how it shaped up for me. Well, we have that in common too, Manny. I was there later, but I left literally after the stock had been flat for 10 years. So it was perfect timing. Okay, fair enough, fair enough. And then it went on a really nice steep climb for many people to enjoy. And I hope I enjoyed that a little bit too. Right. But it would have been even nicer to be there. Yeah. Hey, the one thing that hasn't changed is that when I was there, when you were there, things were changing all the time. There was so much happening in our industry and if you look at the last couple of years, that hasn't changed. Right. It takes different forms, it takes different speed levels, sometimes different abilities for us to control what's happening. But how do you see kind of the tech world, the state we're in right now in the last couple of years, what's been most interesting for you to both be a part of and maybe witness this happen? Yeah, yeah. So I think, look, and as, as you know, we've been in the B2B marketing sales tax for you know, 10 plus years. Right. The, we were one of the early guys in this whole trend from, you know, I, I think of traditional B2B marketing was, if you remember, the marketing automation tech and tools where you could primarily just build, list and send emails. I mean that, that was a core of what these tools used to do. Suddenly in 2015, 16, along comes something called account based marketing. Salespeople always knew that you gotta sell to accounts marketing people for some reason didn't understand that basic notion. They were doing batch and blast, pushing out a bunch of emails and it became a big thing, a thing to do. You had account based marketing. And so we jumped on that bandwagon, we got into something called account based advertising. So really around how do you serve targeted ads to a specific set of prospects within a company? And then about a couple of years ago, 2023, early 2024, we realized that, listen, what you really need to do is to get down to the person or the individual. Salescasts are always getting frustrated with all this ABM tech where you know, you know Cisco's on your site, you know HP is on your separately, you don't know who from Cisco, who from hp, who do you reach out to in a large organization? That's what the sales guy really wants to do. And so since they were struggling with that, what we found was in, you know, sometime in the late 2223 timeframe, we started seeing there was a new breed of data providers that were coming into the market that could allow you to understand individual buyers and their buying behavior, buying activity across the web. And so we found one of those early data providers that allowed us to start introducing what has now become the thing, which is signal based prospecting, signal based selling, signal based technology. So signal based tech, signal based pipeline growth has become the new thing. And it's kind of, it seems to be where the world is headed from what used to be account based marketing and account based experiences, if that makes sense. Yeah, that's a great point. And I forgot to do a proper introduction, really. Manny. So you're the founder of Kwanzu. That's right. That you rebuilt I think even a couple of times over the last two decades. And you were one of the early people in account based marketing. Right. When it was not even really well defined. Correct. I've always, I like your description. I've always likened it also to the earlier stages of the funnel. Right. Where marketing is about changing people's minds, changing people's behavior. You don't necessarily have the luxury yet of having a one to one conversation with someone. Right. And that's why the word marketing is appropriate. Because a salesperson, first of all, their time is too expensive, but they even wouldn't be able to really, you know, to have a specific, to understand who to have a conversation with and what to talk about. So it's kind of this notion of the marketing top of the funnel turning into sales later. But you're right, I think it was a great way also for marketing to become more relevant for enterprise sales. Right. Which it hadn't. Hey, talk a little bit about how you started. You haven't raised any capital, you've totally bootstrapped, you're now a pretty large company, so you've done really well. What does it take to stick around, do something for 20 years and keep building on the same thing? Yeah, no, look, I mean, yes, we have been through what I call pivots along the way. I mean, when we first started, we certainly weren't doing what we're doing now. And so one of the first things we did, and this was even prior to the early years of abm, even prior to that, we were still trying to solve problems in the B2B marketing space. And so we ended up building a, focusing on B2B advertising. So we were more of a B2B advertising play. We figured out how to build rich media advertising components and units and then serve it out on different media publisher websites. We looked at trying to create more of a business on the media side because we saw that there was a lot of media companies, media and advertising companies, but they primarily focused on B2C back then there weren't too many players on the B2B side. So we found some interesting problems to solve there. So that was a call of the pre origin to the ABM phase for us. So just to sum that up, that's where we really started. We built one of the first rich media ad servers that we were then offering into B2B companies and certified, fully certified on Google. So back even prior to the ABM phase, then as you mentioned, 2015, 16 is when a couple of companies came along and they started defining this notion of account based marketing. Account based, focused on the marketing side. One of the things that made that more viable or possible was increasingly the availability of data so you could understand buyers that came to B2B websites, at least at the company level. Honestly it wasn't as mature even there. So you know, you kind of knew who came but you had to wait for somebody to fill out a form. So now the point is, even before people out of form, what can you tell about them? So the first thing was to be able to understand at a company level. And that's where I said that journey went on from for several years all the way to the early 2000 and twenties. And then we started seeing new players, new data partners emerge that could tell you at an individual or personal level. So person based has become the new thing. What used to be account based. We geeked out a little bit on this. I think when we first met Manny that we both grew up in the 80s 90s in our first part of our professional career. And one to one marketing was a term that was coined in those days like by Siebel I think or someone at, in Silicon Valley, not at Oracle later became Siebel was of course acquired by Oracle. But someone came up with this term one to one marketing which basically says we understand our audience so well that we can service them at an individual level, both with the right content, the right products, the right capability, right pricing. And the reality is that, and I've knew a lot of work lately with one of my clients being in the loyalty software space where we actually we met through that engagement. Yeah. Because if I go to a Starwood hotel and now Marriott, they still don't remember what pillow I like. Right. Although I've been at the top tier loyalty program for ages and they must have a ton of data on me. But the fact is that their systems still make it. And so that's in B2C where they're relatively good at this. Right. And so B2B it's been even worse. Right. The ability of us to, to understand what is an individual looking for, not the company of course has, is a. Is a more easier to understand if you know the company is in a certain industry to have a certain amount of problems that maybe they talk about publicly that you can see in their 10k statement in their press releases. But we're not marketing to companies, we're not selling to companies. In the end you end up with an individual on a phone call. Right. Or in a meeting and, and understanding what that individual. But what will drive them to even show up for the call. Right. To carry enough and then to follow up on the call and to allow you to have a second call, you need a lot more, which you, I think mentioned. Signal. Right. Understanding. Talk a little more about. Because what I was impressed with when we met and I of course run also we have Kalungi, the marketing agency that works for a lot of the tools that you also compete with. Right. Of course, there's so many ABM tools out there. Right. But we were impressed that it felt like you had found a good way to kind of bring all that spaghetti into a way that's relatively easy to understand and didn't feel to us that we are also locked in too much, which some of your competitors do. Right. But also be relatively good at actually creating that signal. What we're looking for. You want to talk a little bit about how your philosophy and how you in the last 20 years put your current stack together. Yes, for sure. I think. Yeah. Because one of the things we realized was as over the last two, two and a half years, that's been a very deep area of focus for us, is understanding all the range of signals that are available for both marketing and salespeople and sales leaders and marketing and sales teams. And now obviously we think of it in terms of go to market teams. So the go to market team's success is really around how well and how, how deeply do you understand all the buying signals, both person level and company level, both on the website and off the website, and then to be able to make sense of it, to be able to operationalize it. And then we said, you know what, you have to first acquire the signals. Right. And then the acquisition of the signals will be from a variety of third party data sources, second party data sources. First party, of course, is the company's own website and the company's own internal tools. And there's a bunch of signals that you can get there also. But a lot of the challenges we've seen is around how do you make sense of these signals, how do you rank order and prioritize these signals? How do you then act on these signals? Through the appropriate channels. So it could be emails, could be LinkedIn, could be phone calls, could be advertising, display advertising. Right. People Also talking about WhatsApp and SMS and so many different engagement channels that are available to reach individual prospects. So that's clearly where we saw that there's a smorgasbord or a mishmash or whatever you want to call it, a variety of tools. And they all approach it differently. They all think that they're solving the whole problem and they are not. So that's what was the genesis of us thinking it through and coming up with this 10 layer AI sales automation stack which I'm happy to show you now and kind of share with you. Oh yeah, love for the audience to see that. I think you gave me a really good education on that a couple of weeks ago. And I love the term signal based selling that's become very popular by a lot of players in this space. And it feels to me like an empty vessel a little bit until you see it. And I felt when you did your demo for me, it felt that all these tools that either they buy cookie data or they allow CRM data to be captured and organized, or they allow your team to enter customer insights, they all feel so still not noisy. And the whole signal creation is a really good part. Hey, it's time. I just wanted to pop in for a second and let you know about something we've been running. If growth has started to feel a bit inconsistent and it's hard to know where to focus next, we're doing something called the T2D3 Growth Workshop. It's a 45 minute working session where we look at your go to market approach and build a custom plan for driving pipeline and growth. You can scan the QR code on the screen or head to kalungi.comworkshop to apply. All right, let's get back to the episode. So I think what we are talking about now, Stein, is the kind of a 10 layer framework of what we're calling an AI driven sales automation architecture. Right. It's a layers of tech with some unique capabilities that you need to kind of build out the entire process. So if we kind of go top down, at the very top, you've got your signals, so you really need to aggregate all the buying signals. So first up is de anonymizing individual site visitors down to the person level. So you've got, you know, this tech is relatively new, the ability to de anonymize on websites. It works for the US market, it doesn't work overseas. Right. And we'll talk about GDPR and data compliance and privacy concerns and this and that. That precludes some of this tech being available more broadly. But certainly the US market is a large market where being able to identify website visitor down to the individual is pretty valuable. You've got off site intent signals, which is again across 90,000, 100,000 different media websites, tens of thousands of domains, understanding again prospects who are engaging on those sites on topics of interest, content of interest again at an individual level. So now you can bring them back and they become off site intent leads. So individual leads that can then be pursued, fresh leads that you can pursue every 24 hours. Website leads again. Typically, you know, every few hours you can get fresh leads as you can go. Action. Social monitoring again is where you can start understanding prospects, customers, analysts, influencers and so forth on social channels who are maybe writing about, posting about topics that are relevant to your business. So now it's about having that information available on a daily digest or every 24 hours. So now you're in your company, you can have the leadership go engage with certain key people. You can have individual sales teams and account execs and sales leadership who engage with certain other people. You can have your marketing team engage with certain other people. So basically a structured way to go and organize, engage with prospects, right? And all parties on social channels. You can go beyond LinkedIn, you can look at Reddit, you can look at YouTube, you can look at, you know, Twitter X and so on and so forth. The other kind of signals would be company level signals. So think about, I think you called out earlier. It's more possible now. We have newer data providers that are literally crawling the web and they're aggregating all the web data. So now you can have APIs that you can go and understand which companies have a new store opening that maybe I should go pursue, who's got some new projects or initiatives where I might have a Solution, who's issued RFPs in the last 24 hours or last week. The point being there's a lot. And then who's got fresh job posting, job listings in certain areas, who's got new leadership that's come in in the last 30 days in a C level role, who's had a funding event, the list goes on. But the point is the company signals, the person signals. Then from there you really need to aggregate these signals into, you can decide how you want to operationalize it. There are some newer tools that are now available. One tool that's getting fairly popular called Clay. You also have your marketing automation tools or you can even drop them into relational databases or a Google Sheets layer, which is the data layer to bring it all the signals together. What comes up next, of course, is enriching all this data to make sure you have accurate information of a variety of personal level data that's needed for you to be able to make it actionable. You need to then think about rank ordering and scoring these signals. So that's a whole Scoring and qualification layer. And then you can think about message sequences to go reach out to each of these individual companies and prospects that you now said, okay, these are the ones worth pursuing based on the capacity that I have to go operationalize this. You can then set up a sequence of messages, emails, LinkedIn phone messages, but the messages themselves, we recommend a human in the loop review step, which is why you see there is these approval cues. You've got your message review boards and then from there the next logical thing to do is to think about the channels where these messages would need to be pushed out into the market. You might use some tools that can send out the LinkedIn sequence, sorry, email message sequences, LinkedIn message sequences you would also then want to consider and certainly, you know, easier for not the smaller organization, but mid market and large organizations can look at budget allocation around display advertising, paid media, right? And so forth. Especially retargeted advertising for the prospect that have already come into their website and have engaged on their site that fit the profile, fit the ideal customer profile and the Personas that they should be talking to at that target organization, right? If it's a high value target, you can do physical nudges, you can do gifting as one way so that they actually know who you are. There's a personal relationship building that happens, prospects maybe that are not ready to engage. You can put them into a newsletter campaign, you touch them maybe once a month, once every other month. And then for people who are engaging directly on your website, you now have voicemail drops, you can have direct callbacks and so forth. And then from here what gets interesting is you will see responses come in. You might see some, might even go as far as scheduling meetings. But some of the others we are starting to see even automation of responses. So that's what we mean by the layer 8 where we talk about AI email conversations. So again there's a human in the loop to review the message and then you can automate it more and more over time, whether it's emails, whether it's LinkedIn and so forth. And then I know you've seen this Stein, which is now with AI, it's possible to build some very, very rich customized profiles. Especially if you have a handful of a few hundred very high value accounts where you're trying to close large deals, you know, quarter million to million dollar deals, then you really want to invest the time to have very rich deep account research, understand literally individual buyers that are part of a buying group or buying committee and then even start mapping out the way you will message out to the individual based on their pain points, based on their hard partner issues. And that's what really you seeing as what we call personalized outbound messaging. And moving on from there once now, you know you've got prospects that are actually engaging. You're now ready to do the handoff to your SDR and BDR team. That's what you see down here. So those leads have been approved. They're now going to call it ready for SDR action. And then you go further down from there and then you can start deciding who gets to pick it up. You'll do territory assignment, you'll do SDR handoff and so forth. So that's kind of is the complete 10 layer AI sales automation workflow. Yeah. This is so helpful. Mani and when I think of my audience, right, our listeners, most of us, including the people at Colungi, we run marketing programs for companies that are under 100 million ARR, between a couple million ARR, maybe 50, 60 on average. And having a lot of the options here and optimizing for what your specific needs are is really, really powerful. And thank you for walking through kind of these layers. I think it's really, really useful. Yeah. And the next thing we are working on just in FII is really now peeling the layers of the onion from here. Like how can you actually make this happen more and more easily? How can you then button it up where you can actually have proper data flows that occur from layer to layer to layer? What do you do with certain tools that come in that can maybe do one layer and then another layer, but then they've got gaps along the way. Right. And what we're starting to see is this is becoming the framework with which we can go in and have a conversation with the C level leadership, with the growth and demand gen and sales leadership to figure out how do we actually make it happen in your organization? Yeah, that's a great point. Because all of the tools, they will be only as good as whether they're used or not. Right. And whether they're used in the right way. So combining the technology with the right level of onboarding and education and also incenting, I've always learned this is specifically with managing partner channel programs and things like that. Incentives only get you so far. You have to make it easy. Right. You have to reduce the friction. Yep. And connecting these things together in a really easy way. By the way, we've all been very impressed the last couple of weeks with Claude being able to orchestrate a lot of different Tools, Right. How do you see that? Not for, not Claude specifically, but how do you see that evolve how things like agents and other ways make it even easier to use all these tools together. And I know Quantum is also helping with that, right? Yeah, yeah. So I think it's very interesting what, as you mentioned is happening because if you looked at what you just saw in the 10 layer stack that we drew up there and we walked you through, there is certain components that really are the source of college signals data, or even account and contact and thermographing and technography, different kinds of data. So a variety of data sources. Then there's certain others that have a different role to play of having business logic within them, like an N810 which has workflows and so forth. Right. And then you've got certain other tools that are the delivery tools. Now what people are doing is a lot of the data type of source, type of tools are now starting to offer as you know, model context protocol or MCP servers that when you have an MCP server, that kind of front ends those kind of tools, you can have a way to connect into those tools from within a cloud AI LLM environment. So from cloud you connect into those tools, use simple English language prompts, and then using those prompts, you can then have a variety of them that you can string together and do different actions across those tools. So that's certainly something we're seeing more and more of. The other thing that we are also starting to see is the workflow tool like an N810 make and so forth that you just saw. Those workflow tools that encapsulate business logic again are then able to make API calls and calls into MCP servers and then be able to connect all those tools and then the workflow tool becomes kind of the center, if you will. So it becomes the one that ties together almost like a context layer. You can also start thinking about externalizing a context layer and the context is then like a shared context across all these individual tools. So I hope that makes sense. But that's certainly where we are starting to see the world kind of moving in that direction. By no means is it there yet. It's still the good old. From tool A, let me connect into tool B, from tool B to tool C. But externalizing the data flowing in and out of these tools and that having a common context layer and then a common workflow layer is just, we're just starting to see that happen. Given that signal, signal based selling, signal based marketing is such an Enormously valuable part of your ability to be relevant, to have a great sort of ROI on your marketing and sales. How do companies who buy these tools make sure that they hold ownership of that core signal right versus it? Living in a combination of all these data sets and maybe sometimes hard to get it out. Any kind of best practices there? Any thoughts for people? I mean quite honestly we find that half our time is really in educating the customer, educating the buyer on how to understand the value of these signals and how to operationalize the signals in the right way. Even a step up from that is even kind of doing a common guided discussion alignment with the customer around how should they be even thinking about who their target buyers are, what their target, not just accounts, but the individual buyers, buyer Personas, buying groups, buying committees, and how are they going about making their buying decision and the purchase process. So the deeper the understanding there, the more we are able to better help them and help and guide them as to which signals actually make sense for their business. Social signals may not make sense if their buyer is not that deeply engaged on LinkedIn or on some other social channel like Reddit. So Eric, website signals seems to be kind of the one that most people agree is interesting because it's people actually have taken the step of coming landing on their website, them visiting certain product pages, solution pages, pricing pages, demo contact pages, again helps with some rank order and prioritization of certain prospects saying okay, these person are probably more interesting than this other one who didn't go there. So what we found is it's just a lot of education to be honest, because people do get overwhelmed with the entire range of signals that are available these days. By the way, a story. We were out of time I think when we met the first time. When you made this comment you mentioned Reddit and this is a story from my early days after I did two startups after Microsoft Acumatica and then Mightycall and then after the second one we had an exit with a Russian investor, Yandex, the Russian Google. This was a long time ago, about 12, 13 years ago I did a little bit of consulting and I met with a startup founder who was just starting with a company doing management of IT Peripherals and right now they're a unicorn Atira. They had multiple rounds. They're very very successful Israeli based startup. When I helped Gil the founder, his team was four people and I helped him with his first pitch deck with the first website interviewing a couple customers and it was all about signal and the one thing he did in the first couple of weeks, which I think till today was pivotal for the success of his company, was he engaged as the founder with Reddit communities. Because the rawness, but also the quality of the signal that you get there when you talk with the community, you're trying to be part of them and you have to show up very genuine as a contributor to help to answer questions in a very transparent way was a great part of him being successful in the early years with atira. Talk a little bit. Because I'm super intrigued by Reddit and things like it, GitHub or things like Quora, all these places where people have high quality conversation and insights, especially in B2B talk. A little bit of how you see that, that type of content being captured by the tools that Kanzu provides and others and how we use that as marketers and sellers. Yeah, no, I think, look, I mean, human connection, human contact is not going away anytime soon, right? I mean, and the quality of what you can learn by direct engagement, it just can't be beat. Right? Reddit obviously, as you said, has created that microcosm, that community where there is a lot of authentic communication happening. The other things we are seeing, certainly, and we are fairly active in this, is there are other, call it private owned communities you might have heard of Pavilion, for example, which has about 10,000 marketing and sales leaders that are in there. And we are also part of that. We help run one of the slack channels on Pavilion, which is signal based GTM channel where we find that there's a lot of engagement and conversation that happens in a lot of the zoom sessions that happen of community members coming together. And because they're all part of the community, there's a little more trust that's built in among those folks just because of the fact they're part of that community. So those end up being quite valuable, just direct engagement with a larger group there also at a channel level. And then we've also seen that there are other communities that are springing up these days which are WhatsApp communities. You've got, for example. I'm part of a couple of communities. There's like a thousand plus founders of Indian origin building SaaS and AI and tech companies. There's another one which has got founders along with GTM operators, GTM leaders that are part of another community. All of these end up being pretty interesting sources for signals, that's for sure. I mean it's. But some of it does require you got to show up and you got to engage. How much of that can be automated I think some of that is starting to get automated. I know about people coming up with clever ways of staying engaged in different Slack channels with notifications and knowing that okay, I got to jump in here to have a conversation. Jump in there to have a conversation. Which is part of what this whole social monitoring is about. Monitoring the activity on social and then jumping in where you should be having a conversation. The same thing with Reddit for that matter. You can be there all day long, but you got to know when to jump in, where to engage on where somebody is talking about something relevant to your business. Hey, it's time. Quick note. Before we keep going, I just wanted to mention something we've been working on and are offering for founders who are thinking seriously about growth and pipeline this year. It's called the T2D3 Growth Workshop. It's a focused 45 minute session where we review your go to market approach and build a custom go to market plan so you're clear on what to prioritize next. If that sounds useful, you can scan the QR code on the screen or head to klungi.comworkshop and apply all right, let's get back into it. When you compare this is going to be a little maybe sensitive for you because I but so whatever you're comfortable with but when you compare what you do because I feel your tools are very accessible, they're very affordable and I want to say cheap because that's not. They're very valuable and but when you compare what you do with some the sales forces of the world and all the tools that are at that kind of level, what do you feel is the is the reason for people to maybe go with some more of the best of breed tool set that you just showed us and how you've done a really nice job combining that give me kind of the pitch to go with the but the newer options. But also you're not new of course to this. You've done this for 20 years. But maybe not the sales forces of the world. I'm not calling out all the other ones. Right. But there's so many big ones in this space. Yeah, yeah. Look, I mean what is happening is if you think about what happened seven, eight years ago, is the traditional ABM companies like six sense or a demand base. They did a very good job articulating a whole lot of what they articulated the value they could provide to the customer. And they did a good job of positioning themselves, branding themselves and getting themselves landed at many Companies in a SaaS platform tech model costing Literally tens of thousands, even up to 100,000 plus in terms of annual license fees. But what has happened is the marketing leader, sales leaders have gotten smart, right, over the last couple of years that company level signals are just not good enough, especially coming off their own website. And so they've been unable to justify their value. So we are starting to see many of those customers actually when they come up for renewal, they're trying to now look at more the more modern signal based tech and tools that go down to the individual or person level. So we are certainly getting our share of people who are on demand based on fixtrends coming in. Hey, can you help us define a more modern AI GTM tech stack that has your tech plus other tech? So that's why you saw the reference architecture that I just put up. You don't see ABM tools in there, right? Because honestly part of their struggle is they haven't even built a business model and a commercial model and a platform that's available. These newer signal based tech and tools, by and large you'll see they sell on a usage or subscription model with credit based pricing, not the traditional module based pricing where you got to pay 3,000amonth for this module, 3,000amonth for the next module. Literally you get credits. So it's consumption based and it grows over time based on consumption. True for us, true for clay, true for many of the other signal based tracking tools. Most people understand what first party signals are, right? Someone visited your website, your own content, you can track things, etc. Someone opens your email, the off site intent piece is a little less intuitive. You're tracking prospects across maybe partners that you have deals with, you buy data, maybe you get access to data in other ways, third party sites. Or maybe you pay for certain ads at a different website and you get data in exchange for that. All the way to when you sponsor, you have a booth at an event, maybe they send you the list of the people who come there, which is very analog, right? But it's also third party data. Talk a little bit about how this actually were, how you think about off site versus owned signal, et cetera. Yeah, so I think you're right. I think people need to understand the distinction between first party, second party, third party. People talk about that. As you mentioned, first party is who's engaging on my own website, who's engaging with the emails that I send out, what information do I have about prospects based on my sales team actually having conversations with them. And so I might have meeting recordings, call recordings that are Then saved back in my CRM and if I can analyze that I can get some information. I have historical data about my customers, my my renewals and my upsell and cross sell and who's the potential for renewal. All that is first party data that can be used to even the potential referrals relationships of my own sales team and people that they can go after. All that is your first party universe. Second party is really think of it as the directory sites. So they list a bunch of software vendors and providers and then they track who's visiting their website and then they feed that back to the vendors and the software tech providers to say here's a list of 20 companies that came to your directory listing on my site and they might be interested in what you have to offer. Why don't you go reach out to them so that second party like your G2S and trust areas and others of the world. Now third party is pretty much a catch all. And so the third party comes in many different flavors. Now the ones that we are able to do at a personal level, as you saw, the personal level intent is based on a tracking tag that has been placed on 90,000 or 100,000 different media websites. So these are media publishers with articles and content pieces on different areas of content. And as a prospect goes and consumes content from multiple different websites. We are collecting all that data. We got 20 billion records coming in into a snowflake backend every week. Then we got some AI ML stuff going on that's going to figure out is there a change in terms of an individual prospect and their visit behavior in terms of specific domains that they're visiting in the last seven days? If you go to weather.com every week, that's not a change in behavior. You're going to weather.com to check the weather. But in the last seven days, let's say you went to five different domains and all of those domains have a cluster of common topics like web content management or cloud security. Then we are going to say you probably are interested in cloud security. Or if you go visit a bunch of sites and they all have the branded keyword of Salesforce, well you're looking for something from Salesforce at this point. Maybe Salesforce CRM. Right. Or maybe you're looking for a particular other brand. So it can be branded keywords or it can be other topic keywords and category keywords. And then we're looking for those kind of patterns of behavior of content consumption across a set of sites and tying it back to the individual and bringing that back at a personal level. So that's the third party signals that could be. One source of signals is third party media websites. People visiting a social channel would be another source of third party signals, remember? So that again falls into third party category. And then to your point, you may get people clicking on emails from a media publisher that again you would consider a third party. We see less of that these days. That's your traditional content syndication leads and so forth. Right. And then you, of course, you know, you also have, I would say those, those would be probably the biggest buckets or categories of third party signals. Really cool. Yeah. When you think of the. So I'm a marketer, right? And I've also been a sales leader many times, but in marketing, I still go back to that one to one marketing concept we talked about earlier. And apart from the things you can find about people, you also have to catch what they tell you. Right? And it's one of the reasons I think LinkedIn is still one of the most important sources of information, because it's where people keep their own data up to date. Right. When you think of contact monitoring and people moving from one job to another and then matching that to maybe a lead that you have that went dormant last year, but now this person may be moved. How do you kind of, of use that type of signal in kind of a pipeline optimization, marketing campaigns, etc. Yeah, look, I think the reality is we have found that literally it becomes one of the key roles of the growth and demand marketer ends up being making decisions on a relatively short cycle. Think of it as every 30 days of saying that here are three or four key signals we're going to focus on for this month. Kick off what we think of it as micro ICP lists, which is 300 prospects, 3 to 600 prospects that fit a certain type of prospect. They could be people who have changed jobs in the last 30 days or 60 days. People who have companies that have had some kind of a trigger event of some sort of. So essentially you got to pick one primary signal and then a few key signals execute a series of what we call micro campaigns and try to engage them with that as one of the key messages or core messages. Experiment with those and see which ones are really resonating, which ones are working. Some of them may be something you could action, if you will for another 30 days or maybe 30 days in the next quarter. Some of them you'll end up swapping out because this one doesn't seem to be working for your target icp, target Persona, target audience. So there is no magic bullet here. What we found is literally how to experiment with a few different tactics and few different kinds of signals. And then over time you'll start to realize that this combination of signals seems to be a steady flow, seems to deliver a steady flow of, you know, prime prospects that you can really look to convert. Right. Taking from first meeting into a opportunity and then all the way to a closed deal. Yeah, no, those are great, great examples. When you we mentioned GDPR before, right? How do you see the, the privacy regulatory environment and things like legislation change, especially for the North American market, maybe following some of the things that happen in Europe and how do people inoculate it? How do you make sure you own enough of the insights, the signal so you're less prone to being hurt by that. Any thoughts, any best practices there? Any recommendations? Yeah, look, I think certainly from the perspective of the companies, the buyer, as you said, the companies with anywhere from few million all the way to 100 million plus ARR and up all the way. We have mid market clients too. They're all concerned about making sure that any of the data provider partners or any folks with tech like ours who work with data provider partners, everybody that they're working with is truly being conscious about following all the right practices in terms of data capture, data sharing, data dissemination out to the customer, on and on. So having proper consent management, basically making sure that they clear out and stop actioning data for which they don't have permission from the prospect is really, really critical. So we definitely make sure of that. Certainly with the data partnerships that we have, we are obviously having conversations with our partners, make sure that they follow all the rules and regulations, number one. Number two is if you go to our own website, we've got privacy policy, terms of service, gdpr, CCP addendums, and then we also have the required forms, if you will, for people to be able to opt out. Now somebody opts out, we make sure that we notify the data partner saying hey, we don't want this person anymore from you. For us to be able to further provision that to our clients, we notify the clients who are using that data for them to also make sure that they have proper permissions or the person has not opted out of theirs. Of course the clients have their own consent management systems when they reach out using this data. Because the regulations, as you know in the US are a little bit different from Europe, right? In the US it's a default opt in until they opt out. And in Europe you have to have opted in in order to write to them. Other than, of course, if the communication is through LinkedIn, then get some DM daily message limit and so on in LinkedIn because under LinkedIn terms, terms of service, they would have agreed to take in messages, right? Comes in through LinkedIn DMs. Now, social monitoring is actually a very interesting way in overseas markets and global markets to engage with prospects in a way that you're not falling afoul of any regulations. Because if somebody posts on LinkedIn and they're sitting in Europe, you're allowed to comment on their posts on LinkedIn, right. There's nothing wrong with that. So that's why social monitoring becomes a very, very useful capability, certainly in the us, but more so in overseas and global market. Because you have only so many ways you can reach a prospect overseas. How do you see many? The use of agents being partly helping your team to do the kind of actual posting and the responding to these things relatively fast, et cetera. How do you turn the signal into action with all these new tools to help with that? Any thoughts on that? Yeah. So the thing is, it's a little tricky because certain actions are less likely to hurt your brand or your personal reputation. Like if you go and like a post, right, somebody has posted because you now know they posted on a topic you care about. You can go and like it, but that's a little bit safer. But if you are going to go and actually comment on the post using AI, that's how you've heard the story about AI slop and AI. Poorly written AI. That's what I mean by it gets risky. So you're better off trying to be authentic. Now if you're a busy C level executive or if you're in senior leadership, just limit the people you're going to engage with. Let them be fellow C level leaders, let them be C level prospects and so forth. And so you're kind of engaging executive to executive. Does that make sense? So that's what we would recommend. But then really surface the most interesting post to engage on and make it a short list for the right people within your organization. So let your executive leadership here engage with their peers over there at an executive leadership level. Let your rank and file kind of director level or junior level staff engage with the corresponding staff on the other side. And those are some ways to kind of approach that whole process. We're going to have to wrap up here. This is a super interesting conversation. So I wrote a book called Syntropy last year that was all about signal more, as in how marketers have a responsibility to constantly find the signal in the noise and make it really clear, drive that clarity so that we don't add to the noise as marketers. Because especially with all these AI tools, it becomes so easy to amplify the wrong things. So thank you for building a lot of tools that help marketers and sellers find the signal and distill it from all the different data points that they get. When you are from your vantage point as a technology geek and innovator and builder of these tools, how do you see AI and tools like this evolve in helping constantly use technology to keep that signal clear instead of just generating more data? Any thoughts on that? Yeah, look, I think one thing, just looking ahead, I mean, I'm kind of curious to see if this is where the world kind of goes in that direction. At the end of the day, what are we all trying to do as people trying to offer something into the market? We're trying to connect to somebody who's ready to buy. On the other side, what do the person on the other side, who's the buyer? What do they want? They want to engage with providers and vendors they trust who are going to offer them something they want when they want it. So it really becomes a question of from the seller point of view, a lot of the activity really is around building trust. Can you build trust with the buyer? They may not be ready to buy now. Can you build trust? What does it mean? It means engaging with them in communities as and when you can. It means giving them high quality content that builds your trust and your credibility. Whenever they might be looking for that content, they find it through AI search engines, they find it on social channels, they find it and they hear about you on YouTube, on and on. And then the question is, over time, will we see an optimization of the buyers and sellers being able to find each other when they're ready to engage? It could be the buyers themselves, or maybe some of that may get delegated to agents. Imagine a buy side agent engaging with a sell side agent and the buyer. Sell side agent. And then the buyers are themselves basically notifying that agent that this is a vendor I want to be in touch with. This is the one somebody I think I want to put on my shortlist. So I see that whole buying selling process evolving and changing. It's a little more ad hoc now. It's a little more serendipitous. You got to show up with the right ad in front of them when they're Ready to buy. It may become more organized, more structured in that, you know, if like you meet someone, you say, this vendor is someone I like. You tell your agent, hey, I want to be in touch with this guy when I'm ready to buy. And the agents are all getting more intelligent. They're getting, you know, they track your longer term institutional memory across the group of buyers in a buying committee. And then they are the ones who will go out and do the shortlisting and look at the latest version of the product or solution and say, you know what, based on your criteria, which is typically that RFP that they issue, but there's no more RFPs. It's just a criteria that's been defined. These are the guys who should be on your shortlist as of now. And then you get a chance to play as we all kind of every day I discover new things that AI does that amaze me. Right. What is your biggest aha in the last couple of weeks? Something that really impressed you that you did that maybe our listeners can benefit from money. It's like what we talked about. We just had this morning. We had an AI GTM talk session and I had one of our guests come in and say, you know what? Remember I came and gave a talk four months ago in October. Everything has changed. Whatever I told you then, that's not how I'm building. So it was all about micro ICPs and micro ICP list building. He's completely changed his process to using cloud with a command line interface and connecting to all these different systems we talked about early in this session. And so the entire world has changed. And he said, I've earned like so many hours back in my week since then because of the new way that I'm doing things. So I think for all of us, it's about productivity and how can we double and triple how we use our time and what we do with our time with all these. Yeah. When we're getting also a little bit older, Mani time is the most valuable thing we have. That's correct. And it's amazing. I always, I've been always someone. I wake up in the morning and I have 10 ideas of things I want to do. Things I have come up with an idea that I would love to share. Right. And it's so cool that these tools now allow you to do that without any friction. Right. You can write an article really quick as long as you of course create really good signal. Right. Otherwise you're just creating noise for people. Yep, yep. But yeah, it's been it's, it's magical. It's amazing to live in this era of where, where we get so much new tools and capability to have our minds be either shared with more people, be also challenged more. Right. And it's wonderful speaking with you. Anything else you would love to share with our readers or listeners? I should say, look at me, I'm getting old. No, I think, I think my final thing would be we are at a time, but we just got to always, always be learning. We just got to learn. World is moving fast and learn, learn in real time and find the best, smartest people that you can find and learn from them. That's all we can do. What a great place to end. Thank you so much for spending time with me, Mani. Absolutely. Thank you for having me. Bye for now. All right, that's a wrap. Thanks so much for watching and sticking with us through the episode. We really appreciate it. And just one last reminder. If you're looking for a clearer plan around your go to market strategy and where to focus to drive pipeline and growth, the T2D3 growth workshop is available. It's a short working session where we'll review your approach and build a custom go to market plan for your business. If you haven't already applied, scan the QR code on the screen or head to kalungi. Com Workshop. Thanks again for watching and we'll see you next time.