The Real Reason Your Best Rep Outperforms Everyone Else

The magic is in your company data. The answers are in your company data. That's where the magic of AI is going to shine the light and help you be better. If you have a year's worth of data on your team, the magic's in there. Now, it's the effort of going through it and connecting it and what does it mean and analyzing and normalizing it. That's where the magic's going to be found for most companies.

All right, Jack, you are a multi-time founder, multi-time exits. I'm going to give you a question here that I want you to jump into. So we're going to call it Jumper SaaS. $30 million ARR SaaS company. Their VP of sales just told the board that performance variance between reps is totally unexplainable. Their top rep is doing 3x the quota of their medium rep.

And you know the scenario, right? And no one can figure out why. They've looked at activity data. They've run coaching sessions. They hire the same profile, but nothing's helping the other reps. You're in the room with the board. What's actually going on? And where are you going to start to figure out what the hell needs to be fixed?

Man, amen. I love this. This is not either interview or MBA school. They're asking the question, why is the thing round? And I like, I don't know, right? This one I mean, but this one, you know, you know the answer here.

This is my stock. I try to bring this up with any conversation I have. So this is it. It's almost like I said this. Look, this is so I love this question. I think this is the most real world thing. So little context, quick background: we have had tech now in the commercial side, CRM for about 40 years, right? So about the mid-1980s we started putting CRM and pipeline management and sales and RevOps and all this stuff. And if you research it, we are no better today at forecasting and developing our pipeline than we were 45 years ago.

Probably worse.

We are. I was going to say that if you Google it, Google and ChatGPT will tell you we're actually worse. We're five to ten percent worse today for public companies than they were when this started. So think about the millions and billions of dollars, time and apps that are involved in this question. So there's two questions. One I know you didn't ask, which is how do we hit forecast and why do we keep missing? And the second part of that is I have a team. This is the scenario you did. We have ten reps or whatever. Two or three of them are killing it. The others are average and below average. How do we get everybody to move up or at least make it more uniform, right?

I'm the below average one. So fix me. Dale always tells me he sells more than I do.

So I believe there's a core problem that we've been, and at FrontRace the reason one reason we started, we've been measuring the wrong thing. So we know for a fact the dashboards we had in Salesforce, HubSpot, all of them, don't matter. If it was the dashboard everyone would get to goal, right? We do calls and pipeline and emails and outreach and all these KPIs clearly are not it. And so then what happens if you lead a sales team? We all know this. If you lead a sales team, the board or the CEO comes in just like your question says, "Why is Susan crushing the rest of the team?" We're like, and then even though we have all this tech, we make something up. We're like, "Well, Susan's just better at closing. She's more personable. She has a better demo."

Better demo. No one knows what that means, but she does a better demo.

You know, so I would say this, and that was a long-winded intro to your question. We believe, I believe, in our soapbox for running large and small teams, the difference between these two people are 20 small things. It's not the big things. Everyone knows the big things. Everyone knows the pitch and the pricing and the demo. Everyone knows that. It's 20 small things. And so the magic I believe we're about to enter, this dawn, everyone talks about AI and taking jobs and some of the scary parts of it, but I believe what AI is going to be able to provide is some insight to what are those 20 things? What are these 20 little things that make the difference? We've been unable to measure those, most of those in years past, because those are things like it's the order of things. It's the timing of things. It's the gap between things. It's tonality. It's professionalism. There's a myriad of things we can dive into, but the short answer is it's 20 things that historically we've never measured or kind of said, "Oh, I don't know what that is." Susan's just better at that or Bob's just better at that. And so we love, we can deep dive anywhere you want, but that's the long awaited intro and assessment. I would say it's 20 little things. It's not the big things at all.

I love that. I think there's a lot on the coaching side of the world. Like we were working with clients all the time and I think one of the biggest skill gaps that is in the world is the leadership and the coaching styles that are happening between the sales team and the leaders. Like there's, I don't have enough time for coaching. I hear that all the time.

But conversational intelligence fixes that, Dale. I mean, come on. You don't just get Gong and fix it. I mean, I won't say the G-word, but you know, there are so many leaders and we talk to them all the time. We were doing a discovery call, Jack, with a new prospect the other day, and one of us, we always ask about coaching, right? How much time do you spend coaching your reps?

And the answer is inevitably always the same: "Well, I don't have to. I just listen to conversational intelligence, right? I just tell them to go listen to their own calls." That is not coaching people.

And they have no PIP structure. Like I've talked to so many people that do not have a PIP structure.

I don't get it. Like, so how do you educate them through a process?

Well, I think too what happens for companies, this is so many things I believe foundationally about how sales management, sales leadership has been is broken, and we're just being able to kind of say it now.

Different show but let's keep going, whatever. Because the coaching piece is here's what we do in management or the board says, "Hey, we want to have constant metrics and constant measurables but for people that are all different and for deals that are all different, right?" So everything's different but we want a standardized metric. We want standardized KPIs. And it's like, "No, no, Bob, you can't tell Bob to do what Mary's doing because they're unique and we want to lean into their strengths and not tell them to do the same." It doesn't work that way. The real world doesn't work that way.

This is the difference and I use this term a lot. I post about this a lot. Are you a manager or are you a leader? Managers manage to dashboards and manage to numbers. Leaders lead people. And whether you are hiring someone, whether you are terminating someone, whether you are pipping someone, whether you are talking to the board about numbers, you can't forget your job as a leader is not to lead numbers. If you lead people, the numbers will follow. If you try to lead numbers, people are going to leave.

Totally agree.

But in the intro part, it is shocking. We've all had this, whether the board or again the CEO asks us the question, and it is shocking with all the tech, all the KPIs, all the systems. We to your how you started the show, we make up answers to this question. And it's shocking that we get away with it. I've had big teams, they're like, "Why are they killing?" You're like, "I don't know." Well, like we literally almost on the fly start to make up these very, very, very subjective things.

Yeah, soft skills.

It is unbelievable that all these RevOps and all these sales systems are still in place and we still have very little concrete data to the question you asked. Why are those two people crushing and why can't we mimic it? Jack, so I want to double click into exactly what you said about the 20 little things because we were just talking through that. What are three little things that you've seen over and over again? What are those actual behaviors? Let's just pick three of them.

Yeah. So the context is everyone knows this. If you run a team, you go to your manual, whether you're in client service or sales, and you have a process chart. You hire a new person, they're good. Let's assume they're good. Forget it, you hire a couple duds. We all do that. You get a good person and you give them the process chart and you go, "Hey, these are our 30 steps, how we close the deal. Here's how we do this and then this and then we send them an email and then we schedule the demo and then we do the demo." Right, we have 30 steps, and the reality is the sales process is normally double or triple that. The real sales process reps have and we just don't have.

Those boxes. And so the first thing we always talk about is what are all the steps?

The problem is when you go ask your best people, they don't even know all the things they do. They do a thousand little things. They send a little text after the basketball game. "Hey Bob, saw your team won. Congratulations." There's a million things they do to build rapport, build connection, send an answer to an email or text question in the middle of the night. There's so many things that are missed.

One of the variables we do for companies is to not ask people. When you start to connect the data and the systems, you actually let the automation, the AI automation, tell you what the process is. What's the real process? Not what somebody tells you it is. What are all the steps? And if you have a manual, it's typically shocking—double or triple what you have in the boxes in your manual. And again, your best people, this is why AI agents, I believe, are failing. When they execute against your process flow diagram, it's missing half the steps. And you're wondering why.

I always say to CEOs when I get into this conversation, "Oh, we have it all documented." I'm like, "Okay, so when you get up in the morning and before you go out the door, write down everything that you've done before you go out the door." They miss 20 little things, right? They miss, "Oh, I stepped out of bed. Oh, I brushed my teeth." Like, they don't think about all of those little things that you're talking about. And it's the same thing in the sales process.

That's a great analogy. So to me, there are multiple things. One is what are all the steps? People greatly underestimate that, and that's the human part. That's why again the AI agents are really struggling.

Two, your best people are typically doing that process completely in a different order, right? They move it around. They're doing Z before F. And if it was A to Z, they're like, "Oh, I'm doing T the second step." You're like, "You're doing G. We don't need to give them pricing. What are you doing?" So your best people are typically doing things in a different order. That's sometimes very shocking for management.

A third one I'll give you is it's not just what's happening and the order. It's the timing between events. So we've all had this. I'll give you an analogy. Like LinkedIn, we've all had this. Somebody asks for a connection and then like eight seconds after you say yes, you get the message, right? You want to buy something, and we're like, "Oh my gosh." What's interesting if you study human behavior is it's not that they pitch right away. It's that you get the message right away. So if you just let it breathe, it's the process. How many steps? What order? What's the timing between the steps, right? Because it just feels different. If you could say send them three emails, well, if you ask 10 people, one person will send them all the same day. One will send one each month. One will send one every other week.

Let me pause you because you just said it's not that they pitch right away. It's that you get the message right away. So I think we've all been there. We get that LinkedIn blank connection request. I accept it. And then immediately it's, "Hey Adam, blah blah blah blah blah."

Right?

Does it matter? Would it matter if that message came a day later? Would people still have the visceral reaction of "you pitched me right away"? I actually have a meme that I send to people who pitch me right away and it's like two men standing at a urinal, and like whatever. Would it matter if it was a minute later? Because I think we all expect to be pitched, right? Generally speaking, if some stranger connects with me on LinkedIn, maybe you're not going to pitch me, but I would say seven times out of 10, I expect you want to pitch me something. Do I care if it's not 30 seconds later?

Well, I would say most people feel better the more time there is. But every business is different. We help companies measure that because it's different. The 20 things that we talk about are different for every company and impact. Are you selling a $10,000 thing, a $500 thing? Are you selling an enterprise solution? Are you selling a one-off solution? Are you selling to the rep? Are you selling to the whole company? So all those things matter in the context of it. And then it depends on what the ask is, right? But we all don't like right away. So then it's like, "Hey, can you stick something between? Can you give it a little time? Can you send me something personal between?" So those are all variables, and every company's different. They're their own little organism. And so trying to identify those 20 things, the impact of them, what matters, what doesn't matter—it's different for every company, every vertical, every product, every offering, every price point. We start to shine a light on those to give every company what are the 20 things for you that matter, because it's going to be different between your company and the next company and for all those reasons I mentioned above.

So I agree with everything you're saying. My question though, I want to play a little bit of devil's advocate. Managers are coaching the same reps day in and day out, right? Every single day, Dale is managing the same nine people. He knows everything about them. Why the hell doesn't Dale or Billy or Bob know what these behaviors are? How do managers not know this?

Well, I think it's a fair question. I would just say if you have kids, we think we know our kids. And so if you've raised kids from eight through 18, you know somewhere in between you lost touch, even if you're a goodwilled parent. My wife and I—I was a football coach for my son and my wife worked in their high school—and still my kids got away with some things. You look back and you're like, "How did that happen? Where was I?" I was in the school. They did what you know, they got in trouble. You're like, "No, not our kids."

No, our kids are perfect.

I just show that analogy. But especially in the business world post-COVID, so much stuff that happened in the office happened organically. Maybe folks saw you if you sat in a bullpen or the teams all sat at least near each other. Some work function that was close to yours, you got to hear and see and share ideas and water cooler talk and blah blah blah. Well, most companies today are maybe in the office part-time or never, and teams are scattered. So when we used to hire a great rep and say "go shadow Dale," he's following around for two or three days. Well, that's impossible, right? Dale's in his home now. You can't send someone to Dale's living room, and you know, Brad or whoever. So it's obvious to say we should know what our people are doing, particularly post-COVID, particularly at their house, particularly in a world that's more complex, more digital. It's really hard. It really is hard. All the systems out there are good—no shot at Gong, HubSpot, Salesforce—but to connect them all and get down to a micro level and actually see the data points when and what's happening is very challenging. It's been very challenging for many, many years. But that's where the magic is. It's not the big things. Salesforce and Gong, they're great at capturing the big things like, "Did you mention a competitor? Did you bring up pricing?" Well, great. But if those were the things, everyone would hit goal. Your team would hit forecast. It's not those things. It's all the tiny little details. So how do we start to both measure them? I'll just say this: no one today has perfect data. No one has it. And so you start to lay out version one. Here's your data and where the holes are. And do you care about the holes? If you do, let's find a way to measure them. But sometimes you don't care. Sometimes you're like, "Hey, my people have face-to-face lunches. I'm not going to measure that." Well, cool. You can decide that as a company. Where do you want to measure? What all do you want to measure? And start to make decisions based on that. If you measure everything, you measure nothing.

I do agree with that. But it's funny, you know, as you're talking about the little things, I'm thinking of the little things that I do that to me are common sense. To you as, you know, a great CEO or Dale, are probably common sense. We have a CEO that we work with. He came from SpaceX. He is a huge SpaceX fan. He's also a huge car fan. So, you know, I saw the SpaceX launch. I texted him the other day. I was driving down the road and I saw a Ferrari that I know he really likes. I took a picture and snapped it to him on the weekend. And part of it certainly is to build that relationship. A part of it is it's a similar interest. But to me, like that's second nature, right?

I'm going to do that. What we don't realize is it's second nature to me might not be second nature to Billy Bob down the road. This word will get you in trouble in management as a leader. That's common sense. Everyone does it. And you're like, that. My wife had a retail store and we went to a training for a free franchise. They used this example: you can hire a Goodwill young lady to work at her store and tell her to clean the windows. But if you just go tell her to clean the windows and don't show her how to clean the windows, you might get anything. They might be streaks. They might only clean part. You have to show them what it is because what's second nature and common sense for you—we all come from different backgrounds. Look at our political environment. Look at the topics. You see things. I like the other person feels what. I don't want to comment on this, but whatever the other side says.

Yeah. The other side. You go, "What's their position?" You know what I mean? And you hear it and you're like, "Did they? Are they even in the same universe that I grew up in?" And so imagine that in the business world where there's so many nuances. Look at all the sales methodologies—Sandler versus Miller Heiman versus Challenger Sale versus all these theories about what's great. And it just gets lost in the wash—all the little details.

And the magic—I'll just show this because it can be very complex and overwhelming. The magic, whoever said it—Larry Ellison—sent it to all these AI LLMs. They're using open data. So whoever you love, whether you love OpenAI or not, it doesn't matter. The magic is in your company data. The magic going forward, the answers are in your company data. That's where the magic of AI is going to shine the light. If you have a year's worth of data on your team, the magic's in there. Now it's the effort of going through it and connecting it and what does it mean, analyzing and normalizing it. That's where the magic is going to be found for most companies.

100%. Let's shift a little bit and talk about activity intelligence versus outcome data. And so I would love for you to give us a real-life example of a company that changed something based on activity intelligence that you saw and got a measurable result out of it. I guess the first thing is describe it for us. And then the second is, how do we measure that?

The easiest process for people to relate to are things to stop doing, right? Because no one purposely screws up their deal, right? Like no one goes, "Today I'm going to lower the probability that we close this deal." No one does that, right? We're working hard and good will. And so I'll tell you one example that I mentioned a couple times: we had a client. As we analyzed all their micro data, when they sent a seventh text, their CRM was able to monitor. When they sent a seventh text, they never won. That was it. They never—so the reps in today's remote world—I don't want to bother you. Pick up the phone. No one's in the office. I don't want to call your sell, right? It's a real challenge to go to market. Everyone knows this. People do a lot of texting. And so for one company we have, when they sent a seventh text, they never won the deal. That was—that's the point of annoyance.

That was it. They—it was over. And you're like, so then you obviously want to talk about one to seven. You better use those very discreetly. But it's a great example. So those things are really much easier for us to measure. What are they? Winning looks like a certain thing, right? Winning has a certain set of characteristics, and we always focus on that. But I'll just tell you this: losing is easier to fix because you say, "Just stop doing this. Stop."

Hey, every time we have companies, every time you log into this system or try to use this functionality you pay good money for, you lose the deal. Your win rate—I mean, like, we've added this thing about how to do outreach or texting or automated email. You're like, "You know, every time people use that system your win rate goes down 6%." You're like, "What?" Yeah. Yeah. You added that to your thing three years ago and every single time you're going down. And people are like, "What?" And so losing also has a set of traits that are relatively uniform. And so how do you stop doing it? Hey, you keep sending that PDF that talks about a competitor or a certain functionality. It actually—those deals have a lower probability of closing. You're like, "Get rid of that. Get rid of that document." And so again, going through those things—no one again, no one purposely screws up their deal. But the ability to quickly go, "Let's stop doing these three or four things," can have a dramatic impact on what companies do.

Here's something I keep seeing with sales teams I work with: generic sequences don't work anymore. We've all gotten so good at turning out the noise that even your own buyers are ignoring you. The problem isn't your reps. It's that your sequences are static and your signals are somewhere else entirely. That's why our clients use Nooks. And the thing that stuck with me is that their sequences actually stay fresh because the signals update them automatically. Right buyer, right moment with no manual babysitting. If your outbound feels like it's shouting into a void, go check them out at nooks.ai/bridge.

Dell and I talk a lot about garbage in, garbage out, right? Whether it's garbage out, whether it's data. So two questions: how do you make sure that FrontRace isn't just surfacing garbage faster? And then tying to that, what are you actually seeing and doing that other tools are missing?

Why FrontRace?

Yeah. No, it's great. The magic of FrontRace, humbly, I like to describe it almost like a layer on top. Almost like if you're pouring paint over top of a flat surface that has a lot of holes and stuff, over a road. We're like a layer that goes on top of what you have. So for companies, we don't want you to replace anything, right? I—we tried to build this companies, the solution I always wanted, which is don't pay us up front. Let us give you some results before you ever ask for a dime. And so keep what you have. If you have AI pilot layers, whatever you want, keep doing it. Don't stop. As you're doing, we're going to come in and it's like a little layer on top. We're going to connect your data, which we have a history on it. Normalize the data so an apple in your CRM is an apple in your bidding system, which is an apple in your video conference system, whatever you call it. So normalizing the data, then we're going to put the process flow together. But we're not going to ask—most companies ask. They go around. They ask the employees ten times. They ask the best people: "Who's your best person? Bob, let me go ask Bob what he's doing. Let me sit with Bob for three days. Let me look at all this stuff." I don't want to bother any of the people. We're going to—when we connect the dots, we have a piece of AI that tells you, automates what the process flow is and documents it. So we're not going to ask anybody. And then we give the details back to the company. Is anything perfect? I would never say FrontRace is perfect. But what's great about it is the raw data. Here's what your people are actually doing. Now you may not like it and it may not be pretty and it may not be what you think it is. But here are the facts—good, bad, and ugly—of what your team's doing. And so I think those are unique variables. So going to your question, why FrontRace over other things? There's some things we have developed we believe are proprietary. AI is amazing, but we all know this: AI hallucinates, AI drifts, it will make stuff up.

It's like, "AI says Dale's great." I don't know what the hell.

I'll say I agree with you.

Yeah, perfect. That model is good, but it's the Dale model. I just want to take one step back on the tech side. What AI is doing is amazing. It can code and create things. I'm not on the tech side, so I want to set that aside. But on the commercial side, there's a lot of variability. Mark Cuban said a couple days ago, if you run the same question with the same data in different LLMs, you'll get at least two different answers every single time. And if you push back on your first answer, it'll completely change its answer, which is bad. That's really bad. And so if you're going to say, "I'm going to base my job and my team's hiring and the forecast we're going to do based upon it," that gets scary if the answer is always going to change. And so FrontRace, we developed a couple modules. We believe keep the AI. Let you do complex queries because you can do a basic query like, "Who was my top rep last month?" That'll—

Come out fine. What were the number of demos we did? It's fine. It'll run those. But if you say, "Who is my top rep last month who had the most demos and the most call minutes?" That's when you start to get three or four variables, and it gets very challenging to keep the AI on point every time.

And so the way we have this thing called the metric engine, which we measure items, put flags in the sand so those data points are the same all the time so the AI stays aligned for each query. It doesn't just allow it to go every time and go, "Net new, let me just see what I come up with today," because Monday's different than Tuesday and I feel different. So we have a metric engine and this time machine where we monitor those variables over time to keep the analytics in order.

And so those are some unique things that we do with the data, and for companies that are really unique and have helped them leverage AI and actually put solutions in that work today. But also the key is, the things we use today in the AI world are going to be obsolete a year from now if we keep up the same rate of improvement. Like, you don't want to commit to today's AI. Today's AI is going to look like AOL. It's going to look so outdated very soon. And so you want to have an analytical foundation that allows you to plug in one solution today—this is working for us, we like it—or it's not. And then when the next thing comes out six months or nine months from now, you're able to take that thing out, plug a new thing in, and still analyze, "Is this good for us or is this not good for us?"

And so that's what we want to do for companies. Tell them what's happening, normalize their data, tell them their process flow, and then give them a foundation to analyze what's happening in their company, good or bad, as they change different solutions as the technology continues to evolve. And so those are some of the unique things we try to help companies with.

I think some of the biggest challenges people are having is just the amount of data. And it sounds like a lot of what you're doing is making it digestible. And as you're saying, normalizing it, because I think when I've talked to a lot of the revenue officers and CEOs and just people in general, they don't know where to start. They have so much data. They get super freaked out. They're like, "Where do I start?" And so I like the normalization of the data because I think that's interesting.

We have a client that uses HubSpot and Airtable, and it's like a complete mess. It's crazy because they're using HubSpot for one thing and Airtable as their source of truth, and it gets super messy because data is getting dropped in the middle and it gets really difficult. As we're going through AI and creating AI as a multiplier for these behavioral patterns, what are two or three items of data?

So we talked a little bit about, hey, the seventh text you drop off very quickly. What are a couple of data points that people would not realize are creating challenges in their GTM or revenue process that we couldn't see even two years ago?

Yeah, it's a great question. My immediate answer, I would default into what we talked about earlier, which is like the order and timing of things. We believe that has the biggest impact. But one of the unique parts about AI—this is going to sound big, starred on it. It's going to sound pithy—but is has really been much more accurate with AI and will continue to get better, which is measuring the soft skills involved in sales: tonality, professionalism.

Can AI really grab tonality yet? Like, I haven't seen it do very well on it.

So what's really interesting is that we have a series, probably about 20 of these subjective quality-type metrics. And so from our perspective, our viewpoint on this is we try to tie it to: did they win? Not a lot of people are like, "Bob was very professional and Mary wasn't." Well, that's not the right context. The context is: did they win the deal? Because professionalism in New York is very different than professionalism in Montana, which is very different than professionalism in Georgia.

Adam curses on most of his sales calls. Jennifer doesn't. But who is Adam talking to? Like, we could be talking to a totally different persona, right? And so we try to measure those things in: does it result in wins? Not any training program, not "Hey, we were trained in Miller and this is how they do it." You're like, "No offense to Miller, I don't care. Did we win?"

When Adam curses, we win. And when he doesn't curse, we lose. And then what territory is that?

But Jack, let me ask you a question, though. When Adam curses, he wins, and when he doesn't, we lose. Does it mean that when Dale curses, he wins, and when Dale doesn't curse, he loses? It could be the exact opposite based on personality.

Amen.

To your point that you said earlier, just because it works for Adam doesn't mean it works for everyone else. We have been unable—going back to earlier, we said, "Hey, how do? Why couldn't we measure these things earlier? Why do these things get missed?"—well, the reality is, when you think about the company wants certain metrics and KPIs and measurables, right? We bought all these systems, we want to measure stuff. The reps are all different based upon their personality, where they were, their experience, their training, their age, right? And then every deal is different—how much money they have, how many people they're going to deploy, what region of the country they're in, what vertical they're in. So those are three major variables, three major sets of variables, and they're all moving all the time.

And like, we want to just place a straight line and go, "Here's how we do every deal." And you're like, "No. No. Adam curses like a sailor, and that works for him. And Katie is like Mary Poppins. She never curses and talks about how to bake bread, sourdough bread, and that works for her." Well, great. Well, then we have to go back to your point earlier. We have to coach them that way. We have to emphasize certain things. We have to realize that we can't tell Adam to stop cursing and talk about sourdough bread, and tell Katie to stop talking about sourdough bread and start cursing. It doesn't work. But that sounds ridiculous and we all laugh about it, but that's what we've been doing for the last 20 years, haven't we? We're like, "This is how we do it here. This is how we do it in X Corporation. This is what we do. And so you follow this training." And it's like, "No, that's actually not great."

And you have to be able to find it. And that is the Monday morning move. So we have this thing on GTM Center called the Monday morning move. What takeaway can you take from this show and actually put it into play Monday morning?

So what's the unexplained gap, right? Find the rep on your team who's hitting quota. No one could explain why. Don't look at their numbers, but look at their actual week. What are they doing Tuesday at 9:00 a.m. that the median rep isn't? What are they saying that's different? What's the one specific behavior that you could then try to triangulate? And that's your playbook right there.

But you got to remember, you have to tie it back to that specific rep. But if you can't find it and can't answer that for every single rep, that's the gap.

Agree or disagree?

Prove me wrong.

I agree with I agree. But don't ask them though. They're not going to tell you. Like, you have to send somebody in or use automation. Don't. If you. We've all done this.

Yeah. No, don't ask them. You have to go look at their week. You have to go figure it out, right? The person in 3X comes in. We all do this. "Oh, Mary, you're killing it. Can you come train the team?" Mary comes in and does an hour-long training. No one knows what she said. They think it's nothing, and nothing changes, right? She can't even articulate why she's doing it. So you have to really invest into it.

Now, bring one of my other soap boxes, which is: listen, people are so rushing into AI right away. They're like, "Oh, I'm going to fall behind. I'm going to fall behind." My biggest encouragement to people, Monday morning feedback, would be like, "Stop rushing into AI. Get your house in order. Get your data in order. Understand your process."

What you said: like, get your house in order. Then once you—you said garbage in, garbage out. Once you have a great handle on your data, your process flow, then you can start to plug in AI. But if you just stick an AI agent on a process you don't understand with bad data, it's not going to work. You'll be in a worse position. You're going to sell less and you're going to be frustrated. You're going to be like, "AI sucks. It's not any good." It's like, "No, no. You're just."

It's not the AI that sucks. It's your stuff that sucks.

Right. Totally, 100%.

But you don't have a process. You didn't build a foundation. Like, this is an age-old problem from the get-go. Forget about AI. Like, your GTM strategy sucks because you never built the foundational elements to make it successful. Like, let's just call it what it is.

Okay. In the old days, human beings would fill the gaps. And now if we try to automate, there is no.

The human intuition, the human, you know what I mean, would make up, say, "Hey, this. They. The company trained me for this, but this is what we really do, you know what I mean?" That thing of "this is what we really do" gets lost if we don't fully understand it.

Yeah, I love it. I love it. Let's jump into our uncensored questions a little bit. Let's get a little bit down and dirty with some GTM stuff. One question every CEO should ask if their GTM is broken.

So I think, Dale, what you're trying to say is one question asked to know if their GTM is broken.

No, one question that the CEO should know to ask if their GTM is broken. Like what's that question that's in their mind?

It seems like a very multi-threaded question. So a CEO walks into head of sales or somebody on the business side and says, "Hey, our go-to-market is broken."

Why? And just stops there.

Well, but I know that the go-to-market could be very broad, and so it's hard to pin that down because it could be: Are we lacking at the top of the pipeline? We don't have enough leads. Is it like when I look at it, that looks fine, but midway through we drop off? Or just at the end, our sales stink, you know?

And so I think following that question through, it's going to be in at least those three buckets, maybe probably more, but it's very different if it's the top of pipeline—we don't have enough leads—or "Hey, while we're in it, not enough make it through," or "Hey, that all looks good. We got a bunch of leads. The pipeline's good, but we're just not selling this quarter or this year." Those would all be very different.

And it could also be on the retention side, right? You may be selling a bunch. Your NRR may be great, but the GRR is not good, so you're not renewing customers. So like there are multiple things in that thread, and I think it depends on what your goals are as well, because I think the other thing we don't do well as an organization is set a goal for the GTM organization and make sure everyone's going towards a north star. And I think that becomes very challenging for organizations as well.

By the way, if it's retention, go talk to the product team. Get out of my office. That's not my problem. People don't like the product.

You're going to get Dale on a tangent.

No, it could be your sales team selling into the wrong ICP.

Yeah, totally good.

You know, in grad school they give you this book, something about operations. I forget the name of it. Almost every MBA program. They move the bottleneck. You know, the whole point of the book is they move the bottleneck, and I think the same thing happens a lot of times in go-to-market. It's like we'll fix one part, and then the next part gets busted or can't handle the volume. And so it's very important, I believe, for companies to ask: What is the exact question? Is it a lead gen top-of-funnel issue? We don't have an ICP. We're selling to the wrong people. We don't have enough volume. Is it our process? We don't demo right. We don't manage it right. We don't price it right. Or is it at the end? We don't have the right contract. Those are really different problems and issues, and if you think one's the problem and then you solve a different one, it could get really complex. So identifying where is the bottleneck. And typically when you fix one part of it, it will then illuminate another issue in the entire go-to-market process.

It's like the toothpaste problem, right? You squeeze toothpaste on one side, it goes out the other side. If you close that side, it goes somewhere else.

All the time. All the time.

Let's go to uncensored question number two. This one's a little bit controversial. Curious your answer. Currently, what's the most overrated metric in sales performance right now? Where are sales leaders and CEOs saying, "This is where to focus"? That it's like, dude, that is so low on the radar of things you should be looking at.

I love this question. Ready? I would say pipeline size. Your pipeline size.

Tell me more.

Think about this. For years we tell the AEs whose job it is to have a big pipeline and to make sure it looks a certain way. They manage their own pipeline. How many AEs, how many salespeople, have fortitude enough to close a big opportunity that they worked really hard on and had great momentum? That almost never happens, right? If you look at it, they just keep kicking the can down the road. They just change the value. And so one of the views of data we give is very illuminating: taking a deal and you see all the activity on it over time. When you start to see the activity, you can actually see this deal is dead. You can see there's a lot of activity, and then it died, and now we're just sending emails and attempts.

Just checking in, right? And then you look at the pipeline. The value goes up, the value goes down, the value goes up. The close date has changed here, here, here. We keep moving it out. The probability was closed at 90, now it's 70, down to 50, up back to 60. Like, we tell most companies to tell this sales rep to manage their pipeline. Are you insane? That's one of the big things that AI can also start to automate for you and give you insight. They manage their pipeline, and imagine if you had a digital assistant that's also managing the pipeline and will give you an accurate number based upon that rep's legacy, company deals, and how a deal is really close? You can put a real probability and a real close date on your numbers. It can be really illuminating. But the whole thing of just letting the sales rep do their pipeline is ridiculous.

I love that answer because I think it is so true. We have this fallacy of 4X and all this, and you're creating numbers just to make numbers up.

Okay, next question. You've had seven exits. What's one thing you got wrong on your first exit that you actually got right on your last one?

Gosh, I like my start to my answer is exits are challenging because everyone is looking at the side of the elephant. It's—they're all looking at the elephant, but depending on whether you're a founder, are you an investor, have you been at it 10 years, are you at the end of the road, are you just taking over—it's like it's all true. So, um, you do learn. It's a great perspective. Each deal you try to improve and take what you learned. I'm not going to do that again.

Our second exit, we thought we were working on—hey, let's have some overlap. Let's not have it be so sudden. Our first one, we kind of were there and then we left. Then let's have some overlap. But I'll just say the overlap wasn't great either. So, you know, the old and the new. The exit process is amazing. Most people build a company. Eventually they get hired, or you're moving on, or you have a new idea you want to do something. It's amazing. But that process—that's why most mergers and acquisitions are really challenging. Trying to merge cultures and companies and people is really, really, really tough. And it's not right or wrong, but again, everyone looking at a different side of the elephant has different viewpoints on what they want and what they value. And so I'll just say that dynamic is really challenging.

My best advice is probably a clean cut. You're like, "Hey, you all—God bless what you did, and here's where we're going to go forward." I think that overlap part, especially as you go higher—higher up—is really, really tough to align.

Because there's no egos up there, right? You have no ego at the top.

Amen. Amen. Same thing.

Zero ego. So funny.

What tool, process, system, other than Frontrace, has done the most across your career to actually bridge that revenue gap and why? What's accelerated revenue in the organizations you've been in? Like, what's the one thing? If you were talking to someone who is striving to achieve seven exits, what's the one tool, process, or system that's going to help them accelerate?

My two-part answer is precoid. It was definitely some of the automated outbound call systems that could have an amazing impact on your ability to reach people and talk to people. Some of these connect-and-sell type systems, you know, it'll automatically dial. They're so amazing where they would clean up the number, dial the number, and you could literally go through an enormous number of connections really quickly. And that was an amazing tool to help us reach people. You couldn't do it all day—eight hours a day. It would wear you out when you're trying to hyperfocus to build pipeline or reach people. Amazing tools. Those still exist today. I would say they're still super productive. They are. But we all know now most people are not sitting at their desk.

# Transcript

Now, going back to those numbers—they're typically someone's cell phone. No one likes being pammed on their cell phone impromptu with a work solicitation. It can be super choppy for most people. So, to me, the value on those has changed. And now, to me, we're in this transition period of what is going to—you guys probably live this, see it a lot—what is the new go-to-market pull funnel outreach mechanism that works for you? And maybe that's text, maybe that's LinkedIn, maybe some of it's still email, maybe it is calls. But I think one of the reasons the economy and companies have not kind of almost restarted the engine post-COVID—pre-COVID, it was calling. You knew if worse came to worse, you could call people. They were in the office. You could reach people. Whether they were annoyed or you were annoyed, you could at least know you always had that as a foundation to go back to. Right now, it seems really vague, and depending on what company you are and what market you're in—whether it's again text, email, LinkedIn, calls—it's really challenging. AI automation, all these tools that'll fill your ICP and make you feel more complete. It's tough.

I think if we go back to like the original—like where people lived—was always introductions and getting lead introductions from other people and figuring out a way, a better way, to get hot leads through introductions of other people. Because people are ignoring so much of what you were just talking about: the email outreach, the phone calls, the text. I get cold texts on my phone all the time. How do you even get my number? Right. And so I think where we're seeing the most value and push today in go-to-market is the warm introduction somewhere. And a lot of our companies that we've been working with put programs in place just for that advisor advocacy—they call it all sorts of things—but that warm leads strand is probably the fastest way to drive revenue.

**Yes, yeah, I totally agree with that. Yeah, I think one unique part about AI on the commercial side is going to—not yet. We're not ready yet—but I believe over the next 10 years, think about it. Most outreach teams are this: reach out to 100 people, 30 you actually get a hold of, 15 you can actually talk to or have some back and forth with. Maybe you book five. There's some number, right? It's like 100, you get 20%. We've been doing that for decades in sales: reach 100, get 20 or 30 of those, talk to 15, hopefully five agree to look at your stuff. Some number like that. Whatever your numbers are for your company. I believe AI will deliver in one day. Not yet. You're not going to reach 100. Imagine if you only reached out to the 30—the 30 that were actually, you had the best signals, they were in your market. Like that'll be the magic I believe AI can deliver for companies. Where I don't have to contact 100, these 70 are wasted anyway. They're not interested. They don't care. But with AI, as people have more signals and we leave more trails along what we do on the internet, well now, hey, just reach the 30. Those 30 are in your sweet spot. Get the 30 and focus. That will change what we do in go-to-market. It'll change how we outreach. It'll get rid of this volume thing and let us be more targeted one day. What? We're not there. But I believe that's the future promise of AI marketing.

We made this last uncensored question very easy for you: Dream vacation destination.

And don't say Houston.

No, not don't come to Houston. Anywhere with a warm beach, tropical, South Caribbean—that is my sweet spot anytime.

I love it. Jack, thank you so much for joining the show. Where can we direct people to learn more about Frontera Race?

Sure, easy. Frontera.com—F-T-R.com. In the upper right, it says "Join the Race." We'll actually do a free pilot for you. Or you can actually find me on LinkedIn. I'm there almost every week. My last name is S-I-N-Y, Jack Simon. PM me on LinkedIn and we'll connect there as well.

Awesome, man. Thanks for joining the show.

Thank you for joining the show.