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"We've Had All This Data for 40 Years. The Actual Outcomes Have Not Changed." · Selling AI

• Warren Kucker: Hey there and welcome to another episode of Selling AI. Today I have Jack Seine on the show. Jack is the co-founder and CRO at Front Race and he's got a resume that most sales leaders would definitely trade for. Five successful exits including companies acquired by Trimble and Thompson Street Capital. Over 200 million in sales built across his career. And what makes Jack's perspective interesting is that he's not just a seller who uses AI, he's building an infrastructure layer that he believes is missing from every sales conversation right now. His argument is that companies are rushing to connect LLMs to their data stacks and not getting great outcomes out of it. There needs to be a middle layer that nobody's building. And that's exactly what Front Race is doing. So in today's episode, Jack and I dig into why most AI agents fail in sales, what the metrics engine concept is, and actually how that helps connect AIs to outcomes, and what he calls the greater people, a world where revenue grows but sales headcount might not. So let's get into it. Jack, thanks so much for being on the show. Jack Siney - FrontRace: Hey Warren, thanks so much for having me. Appreciate the intro. Warren Kucker: Awesome. Well, walk us through a bit of your background. You've built and sold multiple companies across GovTech, public safety, and now you're in sales, performance, intelligence. What's the through line of it all? How did you kind of get your, let's say, evolution as to where you are now? Jack Siney - FrontRace: Sure, sure, appreciate the intro. Hope I can live up to that throughout the show. Yeah, I started my career in the biggest organizations. I started my career with US Navy as a civilian, worked on the F-18 Blue Angels program. If folks are familiar with that, that was interesting time. And then I worked for PricewaterhouseCoopers as a consultant. So after that, the one thing I knew is I didn't want to work for a big organization anymore. And really that led me into the entrepreneurial world, which I've been in for the last 25 years. And each one of my entrepreneurial endeavors dovetailed from the one prior. So I used my background and worked for the government. We started a software company that was in the public safety space and it's selling to public safety agencies across the company led to my next endeavor, which was GovSpend. And we were trying to help the government procurement process. so, and then now from those experiences that really dovetailed into what Front Race is and trying to help. organizations sell better and be more efficient. So one kind of piggybacked off the other trying to see real world problems that organizations were having and trying to solve those. And those simply make the best entrepreneurial endeavors, right? When you're solving a problem that you've personally experienced, so. Warren Kucker: That's an awesome background. Cool. Well, let's dive in it. Let's say it started at like the company level and let's dive into the sales process. you've mentioned you think a large percentage of last year's, I'll tell you, big AI, let's say software investments, haven't gotten the result you expected on the business size. Why do you think that is? And what do you think is actually blocking companies from getting real value out of their AI initiatives? Jack Siney - FrontRace: Sure. Yeah. Sure, so I think folks probably saw during Q1 there were a lot of studies out about what happened last year during the time. I think the number was around US companies spent about 650 million. A vast majority of those were not put into production or stopped mid pilot or mid effort. And so I think on the tech side, AI is crushing and doing amazing things and I'm not a tech person at heart. My sweet spot in the area where I focus my career is really on the business side, the sales side, the client service side. I think. That side's really struggled with AI because what happens, AI can automate and improve a lot of processes where we know all the steps. Tech fits perfect. We're trying to code and make a website or make a program or make an app. But on the business side, we know there's some stuff, there's process that we've put in little charts and graphs in our sales manual or our client service manual. But inevitably, there's a million other variables that go into that interaction of building relationships, trying to make your Spectre client happy, how to deliver, and a lot of those elements are missed in the blocks that we create and we say this is our process. So when we try to automate that with some kind of agent or some kind of standardized AI, it runs into some problems because it's missing some of the key elements along the way. And I think no doubt that's the variable that's affecting a lot of companies on the business side. Again, trying to struggling, trying to figure out we got to do something, but really what should that be and how do we improve our operations and how do we become more efficient it's really been a struggle for most CROs and or head of client service the folks on the business side. Warren Kucker: That's interesting. So I think that comparison there that comes to light is like when you're implementing AI, when it comes to let's say tech, right? Like a lot of the people aspect is kind of cut out of that process, right? You're trying to manage using compute power better, right? But when you start to implement it, let's say on the client services and you start to get in more robust kind of like product basis, what you're really doing is almost adding like a new hire. Like you have a new person on the team. This Claude is new, right? Like let's introduce Claude. And we've only been working with God for six months or a year. It's hard to figure out how to work with them, how to make it better. Sometimes it makes it worse. And so it's almost like you have this complex person to put into the loop. And so we don't know how to work with it, and we're not doing it very well. Is that an apt way to look at that juxtaposition there? Jack Siney - FrontRace: Yeah. I think part of it, no doubt, there's a personality type, a new member on your team, but also think it's the little human steps, particularly in the sales process on the business side that gets missed. And so again, think every company, any mature company has a process flow diagram and says, hey, this is how we sell. Right, is, go to their sales manual, there's 22 boxes or 34 boxes we outreach, then we send them an email, then we send them our company overview, and then we schedule a demo, and then we follow up, then we send them pricing, and then we expand our cast of characters, and we try to get a contract, and blah, blah, blah, blah, blah, right? But the reality is, the real world part of that is in between those boxes. our sales reps, our client service reps, the people side, the CEO sometimes, step in and have a myriad of interactions with most clients that... either help or hurt, they're involved in the process. They were building relationships. It's those things that, we see the news article, we send it to one of our prospects, we see something happening that could help a company that we're working with. It's all those little steps in between these kind of, we talk about these micro steps that happen, that again, build relationship, move your client to a better place that aren't in. some process flow diagram, right? It's the human part of our interaction. And so, so much of that gets lost when companies of goodwill are trying to enact an agent. Let's just say, if you're trying to put an agent in to replace maybe your SDR process or improve your SDR process, well, if your SDR is on LinkedIn and the middle of every week, they send a, just say a sports update to a client, like some client loves their Chicago Bears and they say, ⁓ look at their draft pick or ⁓ here was your quarterback out. and it's small and it seems almost inconsequential. But if it helps build relationship and it helps have that client have a great affinity toward your company, it's a big thing, right? And manifested over time, it has kind of a big impact over six months of interaction. And so that's what gets lost in my mind in all of the, let's just put an agent in or let's put AI in the process. There's another entity involved, but also, It doesn't fully understand all these little micro interactions unless you share with them, Unless you tell the tech to do those things, it gets lost. And then today what's happening last year, we're putting a lot of things in place, missing a lot of the little steps and then wondering, why isn't this succeeding? Why aren't we having great success? Why is our close rate going down? Why is the number of demos we're going down and people get really frustrated and pull the plug? Warren Kucker: Yeah, and so I think, again, we're in the infancy of using this tech. So these are like, honestly, we're probably more, we move faster than one would expect, right? But it's like brand new, we don't know how to use it and we're not getting it. So I think what you're talking about there too is that there's only two ways for like AI to get into your go-to-market process. Top-down sales leaders say, hey, we need to use it and this is how we need to use it. Or bottoms up, like individual frontline reps are using it, right? So like both have their problems, top-down. Jack Siney - FrontRace: Yep. Amen. Right. Warren Kucker: doesn't, is not a one size fits all, even just your 22 step playbook that we've had traditionally, right? Isn't, doesn't, it's like a, not one size fits all, it's like one size fits half, hopefully, right? Like if you're like half look like this and you're good, right? The human element was important. And the bottom way, like one, we don't have time, folks don't have time to do it too, even if they find something great and it's not really shared amongst the team in a way that's like best practices, right? So we're still trying to figure this out. What are like in that scenario? I think the key is like, Jack Siney - FrontRace: Yeah. Warren Kucker: when and how to use it effectively is what we'll have to figure out over time. ⁓ In that sales process now, where do you think some of the better gaps that we were being able to fill, or if you were talking to a young rep right now or a sales leader right now, be like, hey, in your sales process, this is a really cool way that you haven't thought of to interact with generative AI to make your sales and buying process better. Jack Siney - FrontRace: Sure, I agree, totally agree, yep. Sure, I think it's a great question. If I take one step back, it is shocking to me. If you go study or throw any of this in chat, Chichi and Claude, I think the following is true. immensely automated what happens in sales and client services over the last 30 years, right? Salesforce was introduced 2000, the first CRM, probably mid 1980s, early 1990s. And we are no better statistically in forecasting, reaching projections, sales team accomplishing goal than we were 35 years ago, which is shocking. If you think about all the technology we've put against the numbers, public companies, private companies, no better. And it's just so interesting. boat if somebody was said that 35 years ago you'd be like I don't know is it worth the headache so with that said no doubt AI is going to touch almost everything we do in the next 10 years and so for especially for ground level reps front line reps or even CROs, VPS sales the things that are in my mind round peg round hole are What I see a lot of people using ChatGBT, Claw, all these tools today are really the almost, I would say it's like, it's almost like a spell check on crack. It's like, ⁓ what are the, what's the right email to send? What's the right research to send? What's the right background information you can aggregate to be better informed when you talk to a client? So those things are, it's what you see happening in banking. Whatever an analyst could do. Whatever research is being done, to me that's round peg round hole. AI is going to make that amazingly good. It can find everything about a company. Can it write a better email than you? Probably. Can it do research in a tenth of the time that you could do it? Those are all amazing. Now it's about, how do we apply that? And where do I stick it in? the thing that we've all experienced if you've used AI long enough is in my mind, AI is about an 80 % solution. Right, it's good, but if you don't double check it, it will hallucinate, find things that aren't true. think Deloitte, Touche was embarrassing last year. They had a whole report that went out with fake references and fake stuff to one of their clients. And so it's good to use, but we have to double check it. It gives you a solid 80 % out of the gate ⁓ answer, but you have to go through and weed through it, tweak it, make it your own, double check it, and confirm the things that it finds. And so... To me, the initial part right now is any basic analytic stuff it can do. Everything beyond that, again, on the business side, it's been a struggle for people to scale so far. Warren Kucker: Yeah, no, I think there's two separate points and one that is actually near and dear to my heart right now. So we'll go with that first one for a moment. So I completely agree. I don't know this to be the case. I've said it about 30 times now and maybe it's becoming true. For real dollars, I don't know if sales quotas have moved since the late 80s. So if your quota in 1988 was probably like $300,000, then now we're at a million. So in real dollars, we haven't made. Jack Siney - FrontRace: Yeah. Yeah. Warren Kucker: the selling process and really more importantly the buyer's journey any more efficient. And I actually feel like it's because most if not almost all of the tech that we've developed has been about letting the rest of the organization know how sales was going rather than allowing making it easier for the sales rep to sell. Right. And so the good example would be like Salesforce right. Hey let's use Salesforce as a forcing function for selling process right. Like so. Jack Siney - FrontRace: Yeah. Yeah. Warren Kucker: This will guide you through a typical process, answer these questions, gate between pipe. And this was great, this is good, it was great. And the rep has to update it and that'll force them to be better sellers. Well, I don't think it did, right? In theory, that worked out well, but I don't think it forced them to be better sellers. I think it forced them to throw out Salesforce, right? So it's just too static, right? I do think now the pivot with what AI can do with context being pulled from the conversations. Jack Siney - FrontRace: Mm. Amen. Warren Kucker: and surfacing up the right insights, the right people allows us to do that with reps. But then secondarily, we also should get all work off a rep's plate that is purely to update the rest of the org as to what sales is doing. So, Rob, I'm sure you I want to know my forecast based on all the conversations I've had, not asking the rep, right? Like, don't ask the rep to forecast anymore. Get all admin off and give them tools to be better sellers. ⁓ Does that check out with what you think or is that completely off base? Jack Siney - FrontRace: Yep. Yep. No, I think it's true. think one of the reasons salesforce.com has exploded is, and I've used a series of CRMs over the years, as soon as the company gets to some size, you always have to go to Salesforce because other parts of the company, like you said, need to see what sales is doing. So they either get handed what's been done, they need to forecast, finance needs to do invoicing. it's like, and most people know, I would say most sales reps want like a pony and Salesforce is like a stallion. has all the things, every module, it can get... Warren Kucker: pray. Jack Siney - FrontRace: Very daunting, but I agree and I think the magic of AI, we've spent all these years ⁓ measuring and trying to do dashboards and all these kind of KPIs, but they're not, they haven't been measuring. What actually drives success? Why when you have two reps, when all their metrics look very closely aligned, why is one outselling the other one three times or four times? And you can ask any VP of sales or CRO and the answer they normally give to the board or to the CEO when they get asked is normally a lot of fluff. know, I don't know, well, Susan, she's better at sales, she had a better network, she's a better communicator, whatever it is. And it's been left that way for a lot of years. And now I think AI is going to help kind of blow through that door and start to give us some real analytics about what really drives this disparity. Why is when the basic metrics look the same, why is somebody outselling another rep or closing or retaining at 3X when all the historical metrics looks the same? And I think that'll be one of the most amazing parts about AI going forward. Warren Kucker: Yeah, totally agree. And then, so that's a good dovetail, and so let's talk about our next topic. So Front Race in particular, it's a complex product and driving really good insights. One of the cores is this metric engine that you think is kind of key to leveraging AI in your go-to-market flow. Can you tell us more about that metric engine, why it's important, what it is, and how that particular lever could help us sell better? Jack Siney - FrontRace: Yeah. Yep, sure. I think folks, two things, two paradigms I would share. By the way, the vendors are out there, FrontRace integrates with all the vendors. So this is not pro one CRM or against this other tool or what have you. So we're really ⁓ system agnostic. But as an example, for anybody that's used ⁓ one of the enterprise CRMs, HubSpot, Salesforce, you name it, and you're trying to do pipeline, for example. Those tools will not let you, you try to follow a deal from the day it originated, if your sales process is six months, how has that deal changed over time? When did it go up? When did it go down? Why did it go up? Why did it go down? When was the pricing? When did the pricing change? And what were the variables to that? It's almost impossible with the tools to see how a deal changes. And you mentioned, which I agree with, get the sales rep out of doing the pipeline because sales reps, we're biased. We always think it's coming, right? Unless somebody hung up the phone and Warren Kucker: breed. Jack Siney - FrontRace: told us the kick rocks, we always think it's coming next week. So there are a set of analytics that can look at deals neutrally, what a wide variety of variables, and be able to give a much better forecast about is that deal really coming in? And only... Yes or no, but why and start and the analytics behind that. And so those are the variables we believe are really important. So how that gets to this question about front race and our metric engine. So one of the reasons historically, if you just plug in AI and some simple queries into your company data, it will work fine. If you say, Hey, who has the best number of minutes or the biggest pipeline or any basic query, it'll be fine. As soon as you want to start to do a deep dive into your company's data and start to add three or four variables, a la on the sales team. If somebody had the biggest pipeline with the most number of meetings and what's their close rate over a three-month period, that type of query, if anybody's tried that, will normally generate... less than accurate results. You'll get a result. But if you go back and try to validate it, one of the nuances of the AI technology, it will start to hallucinate. And I'm not a tech person again, but it's really creating this coding, this behind the scene and the joins that it will do. It'll start to connect data that is not accurate. And so that is the problem in taking a ⁓ basic LLM and applying it to a data set. So what front raise what we wound up doing to fix that problem address that promise that we start to put concrete we called a metric engine to each one of the variables. So we have over 150 variables that we put a hard metric to start to quantify. It's a specific number that it can then start to then the tech can attach those variables and attach numbers to numbers over time. So not only do we hard code it we track it over time and we call this time travel so you can follow a deal. how it changed, why it went up, what caused it. But the magic is, this thing as you mentioned, called the metric engine, where we put hard data points, hard metrics behind anything that someone wants to measure or think could be a factor in them closing deals. And when you start to have the hard numbers and say you measured over time, then you can start to do real analysis that comes out with real answers based upon your corporate data. Warren Kucker: That's awesome. Let's dive just a little bit deeper. Maybe let's put our CRO, VPS sales hat when you're thinking on here. I think one thing that I've always struggled with is when you really get down to it, most mid-size orgs, I imagine the largest sales orgs out there don't have this problem, but let's say the mid-size, the data gets to small sample size really quickly, especially when you're starting to look at across reps or across industries or across product lines. Jack Siney - FrontRace: Sure. Yep. Warren Kucker: So you have a $10 million, let's say startup, a $50 million startup. You probably have like six product lines and 11 different customer types and you don't want to admit it. So like it almost breaks down pretty quickly where I can get like, great, this is the number, but heads up, this could be like, this is a small sample size now. What I'd love to hear is like one, is that a problem that you encounter in decent amount when you're looking at these metrics? And two, as like a sales leader yourself, what are some examples, some like insights that you've kind of like illuminated that maybe are non-traditional? that's like great, like on both sides. Maybe like you came up with an insight, it was super small sample size you should ignore or another insight that's like great. Like this is actually really foundationally helpful. That's, and it's novel, it's new now. Jack Siney - FrontRace: Sure. Great question. Yep, that's great. So if I take one step back, so what FrontRace does, we approach a company, we just put a little layer you mentioned on top of whatever they have. So you don't have to change anything, keep all your systems. And so we'll start to attach the data and normalize it. That's the background of our tech team. And it's amazing. And then we start to take AI and non-AI analytics, apply that. And so we believe the magic. We talked about, we've had all this data for over 30, 40 years. The actual outcomes have not changed. So then it's like, It seems like we historically have not measured the right variables. Whether it's a big team or a small team, I'll just give you a list of some of these applicable, and then I'll give you one real world example. things that are more pithy that people get wrapped up around, hey, what was the professionalism in my call? What was the tonality in our interaction? Those are like. We can measure those and then tie them to they go to success, but I'll come back to those. They can seem a little pithy. Things that are more hardcore are the following. What's the patient score? How much is someone talking in a call? Gong does a lot of this and not talking in a call. What's the time between when the client talks and then you respond? What's the order of how things happen? Not just how things happen, like we mentioned those 22 boxes. What's the order? Because typically again, why is somebody 3X over the 1X person? Sometimes it's the order of things. Sometimes it's the gap between those things. It's not necessarily the order. It's how long did I wait between those actions, right? Sometimes every action, we know this in sales, what's that thing, every action gets a reaction? When we have a winning deal, there's simply a set of things that are correlated. So what's the correlation between when one thing's happened, what happens to the next thing? Allah, we added the CEO to our cast of characters. Now does the deal change? Does the price change? What are the relationships? What were the relationships when the deal started? Was this a cold deal that came in via marketing? Did we get a warm intro from a third party? Is this somebody on staff knew that person, right? I'll give you one more. What about, what's our pipeline? How are we doing this quarter, right? Those are variables that affect it. really well and when we're typically we're doing really well we're less inclined to discount the deal we're less inclined to be more aggressive when we're behind notably we get a lot more typically most organizations get a lot more aggressive in pricing who sits in on the deal who sits in on the demos how do we do the proposal all of those things affect success Right? And so I'll give you one real example. We had a client who thought he was very frustrated, CRO, that he felt his sales reps total, they were having a lot of success. One of his best sales rep, type A. Soon as the client said something, sales rep would kind of have a standard go-to comeback. Really frustrated. He's like, hey, it's got to feel more conversational. It's got to feel more relationship. So we would measure that further. Over six months, we measured, we called it a patient score. Once the prospect or client started talking, how long before the rep responded and how long did they talk? The net net of that analysis, none of it mattered. The CRO was bent all around the axle about it. It was literally inconsequential. If the reps responded right away, didn't matter. If they waited, didn't matter. How long the response was, didn't matter. How short the response was, didn't matter. None of those variables. And this was a training he put in place for two months about when they talk, we do this. When they do this, do do do. And so again, it can sound very in the weeds, but I'll just tell you this. I just wanna repeat this. Over decades, we've been measuring all these kind of big metrics. It's not in the big metrics. The difference between your this rep that's selling 1x and your rep that's selling 3x, it's 20 small things. It's not one or two things. If it was one or two big things, we'd all do it. Most people in sales are type A's, Tell me to be successful. Let me go study bot. Warren's great. Let me sit with Warren. I'll just repeat what Warren's doing. It's not that. It's 20 little things along the way that makes this rep. and for years and decades, we've missed those things and kind of gave it lip service and let it left be unmeasured. Let it be unmeasured. And now we really have the ability with AI and some of the metrics to start to really deep dive and kind of take away that black hole of sales. always thought Sally's just really good. And you're like, it's got to be more than that. Or we are doomed. We just spent all this money in our tech stack. You're not for not much reason, right? Warren Kucker: Yeah, so I mean, there's actually two core thoughts there I think intersect really well ⁓ on those lines. So to take it back to my original question, which you answered was like, great, you end up with a small sample size problem a lot, right? So what you answered, somewhat indirectly, but very well is like, great, it's. The way you get away from a small sample size is you look at behaviors instead of point-in-time actions, right? So the example I always come back to in this scenario is my sales enablement person at a company several companies ago came to me and was like when we use this PDF in the sales process, we have a 40 % win rate and when we don't we have a 5 % right? I'm like, well that doesn't make that much sense. That PDF isn't really, it's a long sales cycle. It's a PDF, right? So like logically statistically doesn't make sense. A lot of people would be like. Jack Siney - FrontRace: Yeah, yeah, I know. Warren Kucker: Grab onto that, cool, everyone grab that, right? Which is not the wrong answer. But really the correlation was there is one rep who sold better than everyone else and she used that PDF more than anyone else, right? So was like a correlation, not causation, it was small sample size. But when you start to look at behaviors, behaviors are not point in time, they're constant, right? So like everything you described is a behavior. And so these happen thousands of times during a sales process, not four times during a sales process. And they're almost, they're less relevant at like a Jack Siney - FrontRace: Yeah, it is. ⁓ Warren Kucker: what type of company and who is doing it kind of way, right? When you're looking at who you're selling. And so you get to aggregate those and end up with an analytics stack. And so then the second piece of that that I think is really like fascinating is how do you then like enable the behavior stack? And it seems like you're able to do this over your decades of experience compared to when you go into an individual company to see what works. What's like the mix there, right? Do you find that like Jack Siney - FrontRace: Sure. Warren Kucker: There's individual, you go into an engagement and it's like at your company X is true and it's really not true at most companies or do you find there's a lot of overlap in terms of like successful sales motions that have commonality between that data. Jack Siney - FrontRace: Yeah. Sure, by the way, sorry for your earlier question. Scale-wise, for us, the magic is what... There's really two variables. It's number of people you have on your team and then historical information. if we have, we run into a company with say just five reps, but if they have two years of historical data, we can give them great insight, right? But if you have three reps and only information, data for the last three months, you're like, I'm not sure how, what is that in the world of stats, how statistically viable that is? But again, I think if you have five people and a year's worth of data, you can have enormous insights into that process. Warren Kucker: All yeah. Yeah, right. Jack Siney - FrontRace: of you. ⁓ Yeah, the other part of kind of where and when and what are we looking for? For us, I would just say... Since COVID, we used to like, before COVID, things were so different. You could, you could mimic a rep or follow them around. You know, we, we've taught them this before and get the best of post COVID with work from home with so many organizations. It is extremely hard to start to figure out what does success look like and how do I share it? So picture this, you're a CRO, you go through the whole hiring process, you have a star, you know, they're a star. They had two other companies, they've been great. You're going to onboard them and you're trying to share best of, of your company and what they do and how they. it you're like I don't know. Here's our sales manual. Above, here are the stats. They can go look at it. And what are those things that make them great? If all that's happening in their living room, you probably have their pipeline. You have some, emails you can go look at. You may have some recorded calls. You may have some recorded video conferences. And you're like, star I just hired, go watch all that and pull, glean from it what you want. I think that is a very hard model. And I think that's what a lot of companies are countering now of like, everything's been a little glitchy since COVID and it's trying to have, what are those things? And I think what we try to do for companies is the things that are driving success, we find are typically unique at every company and it's not. Do people have to make a set of calls and do some outreach and have so many demos? Yes, there's no doubt. I'm not throwing the baby out with the bathwater, but that's not what's driving success because if it was, then you'd make forecasts every quarter, every month. That's not it. Each company, what we found, year and a half of this, it's one or two little things. that are unique to each company. We have not found a through line that, everybody just does X, because it's based upon the product, as you mentioned, the vertical, how much does it cost? There's a myriad of variables, but we have found the light at the end of the tunnel. There are typically two or three variables that are non-traditional that can have a big impact for a company. I'll give you one. We have one organization where a sales team, That was amazing, the impact of this. Once they sent a seventh text, so their CRM would be able to monitor text, once they sent an eighth text, they never got the deal. That was it. They were owed for like thousands. It was unbelievable. It was just unbelievable. And so you could tell that was their call reluctance, deal was going south, then they just text somebody to death. And so it was a great training for the team to be like, hey, when we're disconnected, we don't have the right cast of characters. person's going silent. The answer is not to keep texting them to death because then that deal is burned and never comes back. Right? And so it's going through the data every time we deliver it. There's always one or two things that are shocking to the company. They're like, ⁓ who knew? You mentioned the PDF example. That was really a driver. But is it the real driver? And trying to analyze that in totality ⁓ is a big endeavor. Warren Kucker: Yeah, no, that's a great call out. ⁓ I think the part you're alluding to as well is that point in time process things that do well in sales can be replicated. I think sales and marketing are the perfect supply and demand juxtaposition where it's like, soon as something works, everyone does it, and then it doesn't work anymore. But the thing that can't change is what you're talking about, the analysis of those micro behaviors, those exchanges. Jack Siney - FrontRace: Yeah. Yeah. Warren Kucker: getting the right stakeholders in the room, interacting with them correctly, truly trying to find a solution to their problems, and hopefully being that solution one out of four times. Those types of things is what we've been spending so much of our enablement time on the steps, the skills, the knowledge, and so little on the behavior side. And so I feel like the behaviors is where I think AI could really help analyze the myriad of micro interactions to help drive positive things over time, like years. Jack Siney - FrontRace: Amen. Warren Kucker: of development as a salesperson to nudge us in a direction. Yeah. Jack Siney - FrontRace: ⁓ true. So true. know, so many people now are doing that. Whatever platform you love, Cloud, ChatGVT, Plexi, whatever. All that stuff. Larry Ellison said it great recently, which is... That's all one of the same open data set. The magic is in your data. It's your company data. There were some reports recently about until you get that house in order, AI is only going to do so much for you. But again, all those tools, if you're just keeping the open data set, they're all looking at the same internet-based set of data. The magic is in your company's data and the companies that are punting on that and be like, well, we'll get back to that or we'll figure it out later. You're missing. The answers are typically there and it's just having the diligence and the desire. It kind of almost feels like a step back, right? Hey, let's go back and get our data. Let's get it out of the silos. Let's standardize it and figure out what are our best people doing the best. Warren Kucker: Yeah, and so that leads us to another big barrier that is happening right now to this level of success. So I think there's two types of solutions for AI that execs are kind of analyzing right now. They're like point solutions. They cost not that much per month. They're not a fundamental sea change in how you work. They improve a specific process, right? They're cheap, they're efficient, and they sometimes could have maximal gains. I'd say with the right effort, there's good gains to be had, but sometimes they could be minimal. Jack Siney - FrontRace: Yeah. Yes. Yep. All right. Totally agree. Yep. Warren Kucker: Then there's the sea change you're talking about, the access to your data and how we function as an organization being fundamentally different. And I think that's where Front Race kind of fits more, right? This is a decision to like look at how you manage, to market in your organization fundamentally different over the next three to five years. That's a harder leap with the uncertainty we have right now. So from both perspectives, you're selling this product, but then also the looking at how the buyers are viewing your product. How would you like advise that a seller looks at that? Jack Siney - FrontRace: Yeah. So, so. Warren Kucker: Like how do I get like a sea change in someone's hand in an effective way? Jack Siney - FrontRace: Amen, I agree that AI is so noisy right now. Three solutions, right? There's, hey, there's the free $20 stuff. God bless, keep doing it. Let's all get smarter. Let's revolutionize the world. Every product in the world says they have AI now. Whether they're tech or not, if you go to any website today, there's some method on their homepage of AI. It's crazy. And then there's net new standalone AI ventures like we're doing. And so very noisy. Warren Kucker: Yeah. Yeah, right. Yeah. funny. Yeah. Jack Siney - FrontRace: I would say, this is kind of with my little sales hat on, front race, one of the unique parts of what we try to do is we don't want to approach any company and say, stop what you're doing, we're the answer, we're the holy grail. In fact, we do just the opposite. We say, hey, listen, keep doing what you're doing. You should pilot things. Go look at stuff. What we say to company, let us come in, don't change anything you're doing, we're just going to connect what you have today. No risk, don't buy anything new, don't add. Let's connect what you have, let's look at the data and start to do analytics. so front-race, we never want to be on this cutting edge of AI. These tools out here are going to change constantly. We've already seen it over the last two years. It's sick, right? We want to be, we're one step in to help you constantly analyze what is your data saying? What tools do you have? And we'll analyze it if you want to automate your SDRs. Well, great. What tool did you choose to automate it? What's the impact that's having on your organization, right? We believe going forward for the next three or five years, it's making sure do you have a platform that lets you look at the data. Analyze it compare it and track the outcomes. That's the magic. It's not Everyone has an opinion about what's the right sales model or the right? sales training or What what process we track it? Did we win right? Is it causing you to win more and then also the things that you've lost? Let's analyze that what what's causing you to lose and so we are my humble opinion I believe front race is the thing going back to what you said. It's so risk adverse. It's like don't Don't do this big swap out. Let's just add a little layer on top of what we have. And by the way, we'll put our money where the mouth is. You can try it for a month. You don't have to pay us. Let's look at what you have. And then you can start to make smart decisions about this last 10%. What do we want to automate? What's automatable? What does fit the good AI use cases? What doesn't? Because there's so much human interaction today that might change in the future. We want to stay one step in. from the cutting edge tools, because I think they always are going to change. But we want companies to have a baseline of data of what's happening, wins and losses, and make strategic decisions. So that's what we say to the executive teams that we interact with. Hey, keep doing what you're doing. Don't stop your pilot. Let us put a thing in place and start to make you smarter every day. And then you can do it that way you want. You want to automate the whole thing? You decide over the next year? God bless. And then let's measure that automation. you just jump over the bridge and get rid of your team and automate the whole thing, that can be really daunting. I don't think there's a need to do that anymore, but let's make sure you have a tool that measures what's the impact of what you're doing and is it improving or hurting your net results. That's what we try to do for companies is to lean into exactly what you said because there's so much out there. Let's get a baseline, as you mentioned, a layer, and then you can add to that and put things into it as you want. Don't do anything drastic, because it could look very different two years from now. Warren Kucker: Great, awesome. Cool, maybe last question then. So you kind of talked about the great upheaval, right? And the idea is that companies are going to grow revenue and margins without having to scale a headcount because of this tech, right? It's actually kind of like the opposite of what we talked about earlier where we haven't moved efficiency since the 80s. Now, if this great upheaval were true, there's going to be a sea change event there. ⁓ Jack Siney - FrontRace: You said that? Yeah. ⁓ yeah. Yeah. Warren Kucker: How do you feel that changes the future of go-to-market or how sales leaders should look at go-to-market in that space? Jack Siney - FrontRace: Sure. Yeah, this is one of my personal desires, just watching change management, watching what's going to happen, right? And there's certainly enough content out there on both sides. AI is going to be the best thing ever, make us amazing and the best new technology we've ever dealt with, or AI is going to bring societies we know it to a grand, you know, to a halt. is going go away, capitalism and what have you. And so I think in my mind, the reality is that... The struggle, and I don't know how it plays out, probably some good moments and some bad moments, or you know, we've talked about, which is... We've never seen historically the market, public market crushes CEOs when they do these rifts, right? They, hey, you must over hire, you don't know how to manage your business, why would you have to fire 20 % of your staff? You did something wrong if we're at this spot. And over the last six months, six to 12 months, we've seen an exact 180 of that paradigm where CEOs and public companies are actually being rewarded, they're doing these layoffs, they're tribunate to AI. The market we've seen recently has upticked those companies eight, nine, ten percent in their market cap and that to me is a really dangerous outcome. Not because the world's going to come to an end and da da da, are we going to turn the entire economy, TBD right up that's beyond my pay grade or beyond my mental stimulation but I do know that We're all lemmings and if we see, ⁓ crypto so hot, let everybody get to crypto, goes off. But now public CEOs see, ⁓ my gosh, the recent trend is if we, the companies that do riffs, not only is our payroll lower, our market cap's going up. Percentage wise notably you have to believe that every boardroom and every CEO is having that conversation now Hey, should we just gutter, know, Jack Bosa's gutter at 10 % and not only will we not only will we not get hit for it we're actually gonna get an incremental benefit and it'll give us more liquidity and it that to me is gets into a kind of a scary loop and where that ends, know, that could be a race to the bottom but That to me is, it's 100 years from the Great Depression, that's the great upheaval term. We went through the Great Depression 100 years ago, a lot of things were out of control. Now it's, can we get AI up and running and can the market adjust to it sometime around 2028, 2030 so that it's accretively better for all of us? Warren Kucker: Yeah. Jack Siney - FrontRace: TBD the timing the timing has to be really good, but right now it seems like we're gonna we're gonna rush to some of these I could do it with less people and I don't think companies have seen that again outside the tech group play out well yet, so And your scrolls, yeah Warren Kucker: Yeah, it's an interesting position, right? And obviously there's a lot of unsureness there, right? Like on one hand, so I think from like a CEO or executive leadership standpoint, the layoffs are almost seen as a forcing function, right? Like, great, I'm not, we're not gonna get better. Like no one's just gonna get better on their own. So I'm gonna cut 20 % of the workforce, show that we could do it with 80 % and everyone will do more, right? So it's like a forcing function. It's lazy leadership, if you ask me, right? Jack Siney - FrontRace: Yeah. Yeah. Yeah. Warren Kucker: The opposite comparison doesn't make it any true that I talk about when I engage with companies is like, if your financial advisor came to you and said, used like AI last year on your portfolio and we went from a 7 % return to a 14 % return, right? So I'm now doubly as official with my portfolio, right? I wouldn't be like, cool, let's take the money out, right? Like I'd be like, no, no, that's great. you're like, now that my team should be 20 to 30 % more of. like efficient on a daily basis. The people are now leveraged. Now there's a ceiling on how much work can be done, but I think that's lazy leadership in that perspective. It doesn't mean that's not the direction you're gonna go, right? And the sales side in particular, again, we talk about nothing's moved in terms of like quotas in 30 years, tech hasn't helped. What would be interesting is that at its core, what salespeople were trying to do is like... Jack Siney - FrontRace: Yeah. Yeah. Warren Kucker: get people to be like, have a solution to a problem that you have and you should spend some time solving that problem right now because there's an impact. That's all we're trying to do in the middle, right? Like in a perfect information world, you wouldn't need salespeople. I have a problem, I go figure it out, I buy a piece of software or do something different in a process and I solve the problem. The salespeople are the problem solvers, middlemen, connectors, right? What I think, yeah, please. Now please do. Jack Siney - FrontRace: Yeah. The magic though in that, the magic in that fight gets you out, like is, I think in the marketing world, that's the magic. you think about this paradigm, I know from my company, when I get a referral, it's a layup. know, when somebody's used my stuff, refers me to a friend, the friend's already pre-sold almost, and the process is a million times easier, right? And so then it comes down, if AI can get us to better marketing so that the, we don't, all of of us, historical marketing and sales have been, I gotta talk to a hundred people. Warren Kucker: Yeah. Yeah. Jack Siney - FrontRace: to get 20 conversations or get 20 B1s to get 10 demos to sell five, right? And like imagine if we can use the AI and the technology and some of this gets into data privacy of like, no, I only have to talk to 20. Cause I've already doubted the 20 that have already said I'm struggling with X and you're an X solver. that, then we're round peg round hole. And I'm not sure, I still think people want, you mentioned the financial planner. Warren Kucker: Yeah. Yeah. Jack Siney - FrontRace: Do that, wanna automate it and not have Bob who I can go talk to? I don't know, right? But I think then, I think there's a lot of people because people still wanna talk to people and especially the more money you're spending. You don't wanna necessarily just do it in some automation world, ⁓ but if we can get to better marketing so that I talk to less people, that then makes the process so much more efficient, right? Warren Kucker: Yeah, right. Yeah, I agree. I think you always gonna want to buy from a person. want to speak to little things. No, but bigger things. Yeah, right? I cuz I cuz there's also a post relationship that's on Automatable as well, right? Like after I buy your expensive software, that's a major part of my business We're gonna be working together for a while sales is the entryway into that right? But on the flip I still I mean one out of ten websites I go to the website and I could figure out what they do and who they sell to right? so like it's really we're still at a point where it's like Jack Siney - FrontRace: Right, it's more money rather than Warren Kucker: We're going after such a big market, it's never a size. I almost never know what someone does when I go to their website. We could fix this problem in a better way now that makes really the buyer's journey way more efficient. And then we could, that's when you'll see quota per rep go up, right? Where we'll get out of those things. Jack Siney - FrontRace: Yeah, we get frustrated. Have you ever had a problem with Google or Facebook and try to, you can't get ahold of a person, right? You're like, I mean, they can really cut. I've had one or two corporate issues over the years and it just, it's a black hole. You're like, well, our page just got turned off. You're like, who do you call? Do know what mean? You're like, oh my gosh, so painful. Yeah. Warren Kucker: No, no. Yeah. And in that scenario, it's really easy to switch. Like now I'm going to switch to somebody else because I don't know somebody there. Right? So I totally agree. So that's definitely the evolution that we're going to have to get through, hopefully artfully over the next few years. And we continue the trend of brand new tech creating work other than destroying work. So let's fingers crossed we'll get there. Great. Well, Jack, I really appreciate taking the time today. For our listeners, where can people find you? You post on LinkedIn? You write any articles, anything like that? Yeah. Jack Siney - FrontRace: Amen. Amen. Yeah, I'm LinkedIn, Jack Siney. Yeah, Jack Siney, I'm on LinkedIn. I have a notable LinkedIn presence and FrontRace.com is our company. yeah, I mentioned a little earlier, one of the things we'll do, I want to say in the most humble, loving way, I think a lot of people are locked up. The AI thing has people, don't know what to do and how to do it. And we've tried to create an environment where, we'll let you, don't take our word for it. Here, go use it. No obligation. If you don't love it. Don't get it, you know what mean? Not like a free pilot, hey, you can try for a while, but I think people are really lost in the AI world and wanna be a, you get to a peaceful spot, because we're all, like you said, it's all gonna keep changing over the next three to five years. So how do I do incremental things to help me be better at the process? That's really what we're focused on, so. Warren Kucker: That's a great approach. Well, Jack, I appreciate taking the time. It's been a really thoughtful conversation and thanks for being on the show. Jack Siney - FrontRace: Thanks so much, appreciate it. God bless.