From Cold to Closed | Steve Busby

[00:00:00] You be AI first by being AI last. And what I mean by that is get your processes down, get your data quality down, then do AI last, and that’s how you become an AI first company.

Welcome to From Cold to Close, the podcast for go-to-market leaders, sales teams, and revenue operations who want to turn more conversations into pipeline. We cover what’s actually working in go-to-market today from the systems and decisions behind growth to how teams use data and AI without losing sight of the fundamentals. I’m Jeremy Schiff, CEO of Bowtie. Today I’m joined with Steve Busby, founder of the Revenue Operations [00:01:00] Associates. Steve spent 12 years as the CEO of a global data and analytics company before its acquisition, and today he works with established mid-market B2B companies on structural go-to-market problems, strategy, processes, data, technology, and cross-functional execution. Steve, great to have you on, really excited.

Thanks, Jeremy. Glad glad to be here.

So before we get into RevOps, can you give me a quick background of your career? You spent a lot of time running a company, but like what did the operations experience teach you about revenue growth and what eventually pulled you towards the go-to-market architecture and revenue operations stuff you’re doing today?

Yeah, so I mean I didn’t know it at the time, but as a CEO of a hundred million dollar company, several hundred people, was doing RevOps, but I didn’t know what RevOps was. But when you’re looking at everything, your value prop, your people, how you recruit those people, [00:02:00] technology, culture, alignment, you know, of course the sales motion and sales productivity, customer service, you know, you’re responsible for all of those and that all those things collectively are how you execute your revenue strategy, aka RevOps. So, after a a long career as an operator, sort of said, “Hey, how can I help take some of this sort of holistic knowledge about the the system that is how a company operates and and help people understand and operate their system better.”

Makes sense. Were there any sort of like key learnings that came from like the time at the at when you were leading the company that have sort of become like the fundamentals to the way that you approach things specifically?

Yeah, probably the biggest thing is that everything is connected and the historic evolution of most entities is more [00:03:00] piecemeal and siloed. So, we all live in that friction world of it’s all connected, but people are thinking and operating in those those silos, but wouldn’t you you know, you need to take something like risk and compliance. I mean, they may be making decisions that impact customer experience and make it more awkward to do business. That in turn impacts your retention and expansion, which in turn impacts the CRO’s ability to hit the net revenue targets.

And you can you know, and the other thing is it it’s non-linear. It’s all connected, but it’s more of a you know, a universal circle than it is this classical you know, funnel or process that we like to to map out, you know, how everything goes across in a line and that I think AI and other things are helping people sort of think spatially and and less linearly. But but Uh, you know, my [00:04:00] advice to people would be, you know, take a few steps back, look at the entire system, and then you can start to say, “Hey, where does action uh, you know, will have the most impact, is most feasible, is behavior going to change, is this change going to be successful, can it be quantified?”

And then you can start to sort of have a up an objective basis to start, you know, where you go fix stuff cuz there’s everyone has the same problem, there’s too many things to that need addressing and not enough time and bandwidth. And you know, what do you do that’s going to move the needle, going to be measurable, going to be recognizable by the board, you know, C-suite. Um, it’s all there in RevOps and go-to-market professionals are doing this. They are directly connected to what is being talked about in the boardroom and there’s sort of this let’s just do a better job of of communicate, you know, defining and communicating the value of these activities and how they’re directly tied to EBITDA, to multiples, to, you know, the value of the company. Um, and so it we’re [00:05:00] excited. It’s early stages of that. I, you know, I think right now would from my seat see tons of sort of brilliant activity. The the things that are being implemented, the changes, the improvements, the enhancements, the speed is all amazing, but it hasn’t yet gone that last mile of saying, “Okay, let’s quantify the business impact, you know, run it through, and ultimately how does this link back into the, you know, the major goal of the value and sustainability of the business?” It’s there, but people need to start My advice is is people start thinking about doing that math.

Um, and then, you know, doing it and, you know, relatively relatively soon. And that’s when the value and importance of go-to-market and RevOps is going to explode once the C-suite sort of says, “Geez, all these people that we thought were just doing service maintenance and, you know, just worker bees getting, you know, and critical, but holy cow, they they are at the forefront of driving [00:06:00] everything that matters at this this company.” It particularly if they can affect change.

Makes sense. You made an interesting comment about sort of alignment of different people and how they can all impact each other. I hadn’t thought about it until what you just sort of articulated, but with AI making everything faster, you can sort of accelerate going in the wrong direction just as much as you can accelerate in going in the right direction if you don’t really have uh sort of alignment of interests uh sort of correct. Um sort of an interesting ramification. I hadn’t thought about that like it can make Sounds like just like the like yeah, AI can just make everything either a lot faster or like faster doesn’t mean better, right? It could drive you in exactly the wrong direction. So, um very interesting.

Exactly. And I think I mean there’s an interesting you know, trend happening as people sort of realize that and there’s been this great sort of application and experimentation with AI, but at some point, hey, we need a master plan. We need to see how AI deployed in a scalable way across that system is [00:07:00] going to give us the business impact we want. So, who who owns that? Right? And have we thought about, you know, how we’re deploying? And you know, you you read stuff about people going from, you know, 100 agents down to 10 and exponentially increasing because after that period of initial experimentation, hey, what’s actually making a difference? And then those 10, okay, they have a common denominator. We can start to put those It’s happening, but I guess I would love to see people proactively drive that as opposed to sort of have it happen by, you know, um more more reactive.

Makes sense. So, basically literally sort of explicitly thinking about that there’s going to be sort of an experimentation phase and then hopefully a learning and like really

Right.

like working out which ones are actually going to move the needle. It’s I’m guessing that in a lot of organizations you can’t even sort of a priori know what’s going to be moving the needle. You’re going to have to just like try a bunch of stuff and be like, oh, this approach is really dramatically moving the needle and these three things that we thought were really cool or like great in a demo, but don’t actually move [00:08:00] to your point move EBITDA or whatever the sort of core company KPIs are.

I I a great opportunity for GTM RevOps professionals to sort of say, “Great, where are we experimenting?” And let’s start to put some rigor uh around that in terms of ROI and cost and and impact. Uh and start drive making some decisions. And that again, the C-suite needs that. Yeah, I mean, they’re all you know, did the “Hey, everyone else is jumping in the pool, we need to jump in the pool.” But sooner or later, you know, McKinsey just came out with something I said they did a big global survey and I think with 6% of companies who would describe themselves as, you know, highly active adopters of AI have noticed a tangible impact on EBIT, um their net income.

Um it’s coming, but 94% are in that, you know, hype experimentation phase and need to start The math is there. I think people need to start doing it, but to your point, there’s also, you know, yes, this saves some time, but at the end of the day, you know, did it impact cost? Did it [00:09:00] impact revenues? Did we free up capacity that then was able to, you know, affect an outcome? Or nope, they just had more time for, you know, you know, doing less productive work or whatever it is.

Yeah, it’s also funny that we refer to AI like it’s one thing, but like there’s so many different things between like using ChatGPT or Claude to just like chat and like brainstorm about something or generate an email versus like something that’s going to go and like do deep research on your ICP like what Bowtie would do or go and some agentic action that you’re going to go and do, right? It’s funny that we like I’m sure all those studies lump all of those things together, but some of those things are going to be presumably a lot more impactful than others in terms of like sort of like We we just sort of act like they’re all the same thing, but I feel like there’s like three or four versions of what’s going on with generative AI that we’re all lumping together as if they’re all one.

100%. That’s why you need to look at, you know, define the deployments, however you want to define them. Maybe there’s several or or one, you know, [00:10:00] look at functions, but again, start to sort of systematically say, “Look at the playing field.” Again, it’s there’s not a lot of people at a company who are able to sort of see that whole field and then define those projects or you know, whatever you want to call them and then start to to make some initial ROI. Let’s do more of that because it’s working. Hey, let’s we learn but you know, we’re shutting that down or you know, those types of of decisions.

Um but sooner or later people are going to be accountable. You know, the people CFOs are seeing the expense on the tokens but not yet saying great um you know, where where is it in the top and bottom lines? Um

Makes sense. A theme in your work is that companies often respond to growth problems with another hire, another tool, or another tactic like sort of the AI stuff we’ve been talking about uh instead of just fixing the underlying revenue system. When you walk into these sort of mid-market companies that you’re generally supporting, what are the structural problems that you’re seeing most often and how do you figure out uh [00:11:00] which ones are really the ones constraining growth?

Um we do a a very blunt holistic assessment uh of all the core processes across, you know, the the bow tie or revenue cycle. So, you know, how how are you doing demand gen? How are you, you know, managing your pipeline? How are you onboarding? How are you retaining, man- managing churn? How does IT, you know, support the business strategy? You know, so there’s a bunch of defined processes but when you talk to employees and get the watercolor truth, uh water cooler, you know, truth uh not what gets filtered and reported to the to the C-suite and you come in as a third party and you say, “Hey, show me what you’re doing. Show me your plans.”

Um are they documented? You know, do you have a continuous improvement mechanism? Are people following? It’s a great plan but is anyone following it? So, you you need to sort of just rip it down to the studs, so to speak, but with the ability to to and part of our model and what we do is we quantify that [00:12:00] so we can take all those different tangible, less tangible systems but normalize them and come up with a common score and put it on a single page that allows a company to have that discussion that, “Hey, we’re green and we’re pretty good at demand gen, but we’ve got major leaky bucket issues and our, you know, turn and retention is is awful. And then it’s classic consulting peel the onion.

Well, you know, what what is the business objective of your CS function? Well, it’s to delight customers and we measure it by NPS scores. Okay. Um that is at odds with a financial objective of, you know, CLV and and retention and expansion. So, tell me about the people you’ve hired. Well, you know, we hire them because they’re delightful and they’re patient and they’re kind. And okay, have they been trained on sort of commercial aspects and, you know, what the triggers and things? Are you using technologies to sort of, you know, help score and identify either at risk or opportunistic customers? And it’s always pretty self-evident once you’re in there. And people know it.

It’s just is there a collective [00:13:00] knowledge that it’s there, but I sort of say one of the things we do is is diplomatically put these big issues on the table. Uh and sort of ask the question, are you this is holding you back or it’s preventing you from realizing your full potential? Are you ready to do something about it? And if just like my name’s Steve, you know, and and you know, I have a drinking problem, which I I’m just saying using an A analogy, you have to do that as the first step to admit you have a problem or else you will not recover. And we will do our best to get companies to say yes, we have a problem in CS or yes, we have a management problem in sales or yes, we have a technology issue, you know, they’re brilliant technologists, but they’re disconnected from the business and they’re making decisions without vetting, you know, all stakeholders and getting all the requirements down. I mean, we everyone’s seen versions of this movie all over the place.

Um but, you know, knowing at a company all right, you know, whatever, there’s 20 things that aren’t perfect, but how do we get [00:14:00] through those 20 and get agreement on the two or three that board, C-suite, front-line employees are all going to say, yes, I will put my shoulder behind that. I I this is a great idea and, you know, we can unify around a plan. Without that, you know, the three legs of that stool, it ain’t it ain’t going to happen.

Makes sense. We were just sort of like pontificating a little bit earlier about like how AI can amplify the problems or rather than fix them, uh especially if you have like weaker processes or bad data, some of the stuff you’ve just been covering. What do you think separates the companies that are actually getting measurable ROI from AI from companies that are just like experimenting and like what do you think the CEO or CRO or chief marketing officer should be doing uh and measuring to know that they’re like really making the difference?

Yeah, I think they have uh sort of acknowledge that we’re coming at it slightly differently, right? It’s sort of bottoms up that [00:15:00] there is a process, right? The the the the the way we acquire customers, right? The cost at which we acquire customers, the cost at which we serve customers, you know, what whatever it is and there’s, you know, dozens of those, but saying, you know, that that is a process. Is it defined well enough? Is there sufficient adoption of the process? And if the answer is no to either one of those,

don’t do AI yet. It’s it’s it’s not going to help. So, the organizations that sort of understand and I I’ve used the sort of the Ricky Bobby, you know, if you’re not first, you’re last, you know, you you be AI first by being AI last. And what I mean by that is get your processes down, get your data quality down, then do AI last and that’s how you become an AI first company. And a lot of people are saying, great, but if you deploy again, everyone’s heard this, AI on top of bad process, bad data, you’re just going to amplify that. So, it’s the companies that have I whether it’s wisdom or the maturity to [00:16:00] sort of say, hey, let’s you know, look at our bow tie, understand where we’re good, bad, you know, um indifferent, you know, what what what and know, okay, this is where the zone we’re going to focus and someone is is leading that to say, all right, let’s first look at the underlying process, define some objectives, then AI is a way to achieve the improvements you want on that process, and it’s a lot more measurable, right? Because it’s coming from a from a plan. And that tends to work and tends to be sustainable. Um And it’s interesting because at most companies, you know, that that effect of, you know, let’s buy a tool, deploy it, and you know, hope for magic, you know, Burlesquey Matt versus that sort of process-driven AI lasts to be AI first, you know, a lot of it depends on the function and the individuals. How, you know, how ambitious they are, how talented they are, and it’s all part of that experimentation experimentation phase, [00:17:00] but someone needs to start saying, hey, Suzy and Fred over here are really doing it right, so how do we take that and then start to horizontally do that same process across everywhere. Um but you got to start making decisions. It just can’t be, you know, great, everyone get access, and here’s your tokens, and just go start banging away. You got to You got to have a conductor to the symphony.

It also sounds like finding like sort of like the key uh the key people that are like executing in a way that’s aligned with what you’re looking for, and then trying to sort of evangelize that approach.

Right. And I’ve I’ve worked with many clients where we all know this person at companies. They’re just they’re they’re genius, right? They get it. They’re Energizer bunnies. They’re deploying AI within their function, and everyone’s saying, more, more, more. And you go to the CEO and you say, you need to take that person because they’re only benefiting sales, or they’re only benefiting marketing, and give them a new hat and a new title, and say, you you know, you’re in charge of workflow transformation. Um and and go, right?

[00:18:00] You can start changing your org chart, but to free up some of to your point, free up some of that creative talent where it exists to let it, you know, have more effect on that entire interconnected system.

So, doubling down on that, you’ve also written a lot about how the next generation GTM leaders are going to be operating across sales, marketing, customer success, finance, product, like data, technology, all of it. Uh which is a very broader mandate than just the CRO or even RevOps role like today. Um who do you think is best positioned to grow into that role and what skills or mindset are missing from most CROs today that would be like helpful for people to invest in?

Yeah, I I love this topic. I think it is the next frontier of opportunity and the main beneficiaries are going to be good RevOps and good GTM professionals that are junior and can, you know, learn the, you know, maybe their [00:19:00] you know, knowledge of certain functions and the ability to manage and lead and and drive change at scale. Um it’s going to be easier for them to grow up into that role than it is for the classical CRO and the CRO job, I think, is going to change a lot, but up to this point, if you read a CRO job spec or look who’s in the seat, it’s someone who was, you know, exceptional at sales or exceptional sales manager, worked at a rocket ship company. Great, we want to recreate that magic here.

They weren’t hired for their go-to-market engineering skills, their change management skills, their leadership skills, um you know, cross-functional, and and and but so they’re missing it, right? And I So I don’t see a lot of talented sales managers being able to evolve and acquire that you know, change management, entire revenue cycle skill set. Much more feasible that, you know, the people coming up uh from, you know, RevOps and GTM, but at the same time, the, you know, CRO job specs are [00:20:00] starting to change, the profile. People are saying, “Nope, we we Here’s what we really need is someone that can oversee the entire revenue engine, which is product, which is a lot of process, it’s a lot of technology, it’s AI. This isn’t just about, you know, the classic, you know, sales territory quota management, management stuff. And the other interesting thing is is for those people that have it that the really talented GTM RevOps superstars that are incredibly marketable, when they go in now and talk to a company and they get hired, they usually end up with a C title.

Um because it’s it’s what they’re going to be doing, right? If they get the job they want, which is a you know, I do want to affect change, you know, I do want to have some authority. Uh I do want to be around the leadership table. That’s not, you know, VP RevOps. That is a COO or new paradigm CRO. Uh

Yeah, I’m even wondering if there’s going to be some sort of like new title or like it’ll be It’s interesting. I don’t It’s not clear to me if it’ll be a CR like the CRO will evolve or they’ll [00:21:00] be like uh I don’t know. Like uh like the chief operations officer changes in terms of their role or there’s literally I mean, right now it’s like chief AI officer usually means something hyper-technical. I’d imagine that it could mean something more aligned about like how do you align all of these um different positions in a way to like get the most efficiency. But yeah, it’s very interesting. I think uh that’s what makes it fun, right? This uh definitely not stagnant time frame.

No, it is I am so excited for people that have chosen RevOps or go to market because of the opportunity and it may not be why they chose it originally, but it is it is there and they are getting such great training and exposure. Um And back to your point, I’ve had a couple of clients and we’ve recommended this because they did get to exactly where you were as, you know, this is new, what do we call it? And said chief transformation officer. The the [00:22:00] the Think of it as a never-ending continuous business transformation that captures the AI essence of transforming processes and improving them through through AI, but also the people, you know, behavioral, you know, org chart. I mean, everything is is changing. So, how do you, you know, put a put a label on that? Put someone responsible for? It’s a big big big job.

They’re going to need a lot of teams and a lot of people, but I see that as an a beachhead for a lot of opportunity.

Makes sense. I mean transformation and change is all the accelerating. So, having someone who’s just in charge of worrying about that is is makes a lot of sense. See, this was great. The thread I keep coming back to is that like the better the GTM performance is really going to start with visible activity. It starts with um with clearer strategy, better processes, better data, better decisions, and then it sounds like the way that we translate and evangelize those decisions, especially in the world with AI.

Um Uh I think that’s also an interesting [00:23:00] connection to like what we’re doing at Bowtie where like helping teams more be more precise about who’s worth engaging and what where to spend your time and money downstream cuz to your point, if you set everything else right up, everything else will still like sort of follow. So, thank you so much for joining us. Um everyone listening, if your team’s trying to create more pipeline, starting to look at uh the quality of the opportunities entering your revenue engine, not simply the quantity. Uh if you got something out of this, uh share it with your team and follow along for more conversations like this. See you on the next one, and thanks again, Steve.

Thanks, Jeremy. It was fun.