Ep. 145 – Solving the Go-to-Market Riddle with Rick Nee - Part 1

In this episode of Selling Intelligence, Rick Nee, Chief Revenue Officer at Alcatraz, joins Mark Petruzzi and KK Anderson to unpack what happens after a company reaches product market fit and the challenge shifts from finding customers to building a go-to-market organization that can scale.

Rick explains why revenue leaders should resist bringing a fixed playbook into a new company and instead use customer behavior, sales data, and the buyer journey to determine what the organization actually needs. He shares how Alcatraz has built its revenue structure around vertical pods, creating tighter feedback loops between sales, SDRs, customer success, and other customer-facing roles.

The conversation also dives into the importance of cleaning CRM data before making strategic decisions, identifying the metrics that actually matter, and reverse engineering performance by vertical to determine where to invest people, capital, and resources.

What You’ll Learn:

• Scaling After Product Market Fit: Why the GTM motion that wins your first customers may not be the one that gets you to the next stage of growth.
• Playbooks as Starting Points: Why proven sales frameworks should inform your strategy rather than dictate it.
• Building Around the Buyer Journey: How customer needs and sales complexity should shape hiring, team structure, and resource allocation.
• The Power of Vertical Pods: How organizing teams around specific industries can improve knowledge transfer, customer understanding, and feedback loops.
• Reverse Engineering Revenue Data: How sales cycle length, deal size, win rates, pipeline coverage, and land versus expand behavior can reveal where growth opportunities actually exist.
• Cleaning Data Before Scaling: Why CROs need to validate CRM data and remove misleading outliers before using it to guide major GTM decisions.

Key Topics:

• Scaling a GTM organization after product market fit
• Building a data-driven revenue strategy
• Why one-size-fits-all sales playbooks fall short
• Vertical pod structures and feedback loops
• Sales cycle and deal size analysis by vertical
• Pipeline coverage and win rates
• Land and expand revenue motions
• CRM data quality and RevOps
• Generalists versus specialists in early-stage companies
• Using AI to pressure test assumptions and uncover blind spots
• Prioritizing high-impact GTM initiatives instead of changing everything at once

Guest Spotlight: Rick Nee

Rick Nee is Chief Revenue Officer at Alcatraz, a Cupertino-based company focused on facial authentication for physical security. As a revenue leader, Rick focuses on solving the go-to-market challenges that emerge after product market fit, using data to determine how teams should be structured, which verticals deserve investment, and where companies can scale most effectively.

In this conversation, Rick shares a practical approach to building revenue organizations around real customer behavior rather than assumptions, industry benchmarks, or rigid playbooks.

Resources & Mentions:

• Alcatraz
• HubSpot
• Claude
• CRM and RevOps data analysis
• Vertical pod GTM structures
• AGS Two Millimeter Club

🎧 Listen now and follow Selling Intelligence for more conversations with revenue leaders on building smarter, more scalable go-to-market organizations.

Mark (00:30)

Welcome back to Selling Intelligence. I'm Mark Petruzzi here with my co-founder and co-host KK Anderson.

KK Anderson (00:37)

Here's a number we're sitting with. A sales organization that goes from three people to 25 in 24 months has effectively rebuilt itself every quarter. Most leaders in that position reach for the standard playbook because it's the fastest thing available. But our guest today treated the playbook as a starting point instead of an answer and went to his own data to decide what to keep.

Mark (01:00)

Rick Nee is Chief Revenue Officer at Alcatraz, the Cupertino company replacing badges with facial authentication, backed by more than $100 million in capital and trusted by Fortune 100 Enterprises AI data centers, airports, universities, and professional sports teams. Rick, welcome to Selling Intelligence.

Rick Nee (01:23)

Thanks for having me. I am very excited to be here. this is exciting and these are topics that I'm pretty passionate about.

Mark (01:28)

Excellent. All right, first topic, solving the go-to-market riddle. You have said that stage the stage that energizes you the most is the one right after product market fit. When finding customers who want to buy is no longer the problem. Describe what actually changes for a revenue leader at that moment.

Rick Nee (01:46)

It's a great question. So I didn't figure this out so a little bit later in my career. People ask, hey, do you want to work at a startup? And that can mean a lot of different things, a series D with a thousand customers versus a pre-series or series A, where you're trying to find that product market fit. And so I think you have to like think about where you want to be on that journey. and then if we really define what product market fit means.

I was listening to someone the other day from HubSpot and they said, product market fit doesn't mean two two customers that have bought your product and hey, we have figured this out. when I define product market fit, I'm looking at, okay, a subset of customers have not only bought your product, they're using it and you've retained them. And so then there's that there's that point, that drop, that inflection point where, okay, we now have a growing set of customers that not only are buying, but are also

staying with us. And so when you get to that part of the journey, it often requires a remodel. And the folks and the in the way that you were going to market to get those first customers is not necessarily what's going to get you to the next level. I call folks that are in that series A, I call them pirates. They're just out there, they're with the founder. They might be that founder led AE. They're literally trying to figure out what is going to stick, right?

And it often is not what they initially think. when I came to Alcatraz, they had already figured out was interested and who was buying our And so then I that what the GTM riddle, what excites me about that is then you have to take a look at it and you have to say, okay, what type of salesperson do I need? Are we an enterprise motion? Are we a mid-market motion? Are we a director? Are we channel?

do we need hunters and farmers or both? what use cases and personas and verticals should we focus on? What custom what sets of customers should we say no to? So when you look at all of that based on some of those first customers, you'll find that you're gonna have to make some changes. And it doesn't mean you just rip and replace, it means there's iterations and you're still testing. But I think

That is where I love to thrive, where you start to build what I would call truly for scale. I know that everybody likes to say, hey, scale. You know, everybody wants the But really thinking about how you're gonna build, because if you do it the wrong way, you're gonna build and attenuate out in a in a in a bad way, right? And so you wanna obviously get it right. But that's where I like to come in. I don't wanna go figure out if this product

is gonna gain traction in the market. And some people live for that, right? And if you do, then that's where you should go. But for me, it's sort of figuring out this riddle and how do

you get to the next five hundred customers or whatever set of AR, whatever your goal may be.

KK Anderson (04:14)

So

you touched on it a little bit, but if you don't mind, go a little bit deeper and walk us through the the pieces of this riddle or puzzle, like as you call it, as you see them today, and maybe even give us give us some glimpse into what you're thinking about as you're moving into to 2027 with your how you're gonna put the pieces of that riddle together for Alcatraz.

Rick Nee (04:34)

Well, I mean, first you have to start with what you think about your playbook and you think about what you know, what riddle you're trying to solve. There are there are real stakeholders with real goals that may not necessarily be the ones that you you're marching towards, but they are what they are, right? You have the board, you have investors, you have the CEO, you different different folks and stakeholders that are like, This is what we need to do.

So I think the lens that you immediately have to take as you're figuring out this riddle is what is the most efficient and effective way to get an ROI and to grow sales fast? And often that means reverse engineering the data, right? everyone talks about AI, but if you look at Claude and you pipe that into your HubSpot and you start to cue the different leading and lagging indicators.

You should be able form a pretty strong hypothesis of what you should and shouldn't do as you march down a path, which is an annual number. and and that let's face it, the average CRO lasts 14 or 16 months, depending on which data you're looking at in this as world. So I I would say if you're you're figuring out that riddle, it let's keep it simple, stupid. Let's look at

Eight to ten metrics and be clear-eyed on what we should make our immediate, what I'll call low-hanging fruit. And let's go get some quick wins as we're thinking about that remodel. Earn some trust. You can actually miss your first or second quarterly target if it's trending in the right direction with the plan, right? So I'm looking at okay, which verticals? Who do I have here that can actually

Stay with the company as we as we scale. Again, a series A pirate, a hunter, might not necessarily be the right fit for a series B. You're going to look at which use cases, the sales cycling, your win rate, your your deal size land versus expand. And then through all of that, you can start to put in place what I would call your vertical structure, which I know we're gonna talk a little bit about today, but I think

Most CROs that come into these roles at this point, I think what happens when they're trying to solve this riddle is is they see eight, ten, twelve, fourteen things that they could do and they try to do all of them when they should probably only be doing one or two of them and go get those wins and then go build out from there.

Mark (06:41)

Excellent. So Rick, most earlier stage CROs and are in a standard shape. They come in, there's a sales director of some sort, an SDR, customer success person. What do you what do you keep from that initial structure and shape? And where do you immediately give yourself permissions to kind of blow it up and start again?

Rick Nee (07:01)

So a few things. I love this question. And I would say 10 years ago I was probably at fault for what I'm gonna tell you say not to do. but I guess as you get older and you've been through this a few times, you you learn you learn from those mistakes and you and you try to do the right thing moving forward. And and for me, you see this a lot with job this you see this a lot with job roles, open CRO roles or VP of sales roles. It's like we're looking for someone with a playbook.

And it's like, okay, great. Well, the playbook for cyber company A or physical company B doesn't necessarily mean you're gonna take that playbook and it's gonna be a perfect overlay. And if anyone says that, I have a playbook and it will I can just turn this thing on, then you should run the other way. I think there's a lot that we've learned in the industry. I think there's more data.

There's more networking opportunities. There's podcasts like this where there's lots of nuggets and things that you can extract from, right? I was listening to one six months ago and a CRO had said, hey, you should really look at your webinars and doing them this way. And I thought, that's a great idea. I haven't haven't looked at that. So great. So that, you know, you you're gonna take some of those new things and add it. But I would say any playbook that you're gonna bring in and assume it's gonna work somewhere else. Let's say it's 50.

To 70% applicable, which means there's a pretty big could be 50%, it could be 30%, that you're gonna have to call audibles and and lean into what the business needs, right? so for us, vertical pod, everyone's gonna tell you, hey, you're gonna need a sales director, you're gonna need an SDR, you're gonna need success person, you're gonna need, you're gonna need this.

I think, yes, I think the I think the clarity of role is very important. But you know, for us, it's been SDR sales directors. we have our inside sales rep that look that is doing some of that success stuff and some of the renewal stuff. We have channel account managers that are doing a little bit of a a different role than you would see in other orgs where they're helping us drive lead generation, but not necessarily deals. and we've had to like lean in heavily. We have found through our data.

That service and support is super critical to retaining and expanding customers. Sounds obvious, but when you have an early Series B company and you have cash and you're making investments, the easy button is to say, I'm just gonna go hire more sales directors. I'm gonna go hire more SDRs. I'm go. And I think before you do that, you should understand your buyer journey and look at the complexity of what you're selling. And my last company, out of the box cloud cyber tool.

The post and pre-sale support on the technical side was not as great. And so the the answer was you should accelerate sales directors and SDRs. Here, we are selling a physical security solution that's very simple to deploy, but based on what our customer wants with that, and if they're doing an on-prem deployment or they're gonna they want us to be baked into their environment, those are a little bit more complex. And so we have found we need.

Just as many folks post-sale as we do pre-sale. again, that was not something from my playbook. So I think you have to look at the buyer journey. You have to look at what's working, where customers are happy, where things are sticky, and and go there. And and don't be afraid to question those that are overly dogmatic on hey, you need to be using these AI, these nine AI tools, and you need to have a person, a success team that's this big based on the series or revenue or.

Then you should I should always start with the well, why? What are they doing?

What are they not doing? What what is this role doing? And so I'm a big believer in giving folks enrolls multiple things to do, to stretch them where they might be doing renewals and mid market sales, or they might be doing success and post sale this or deployment and and pre-sales engineering, whatever. I just I think you have to look at what's right.

And the gift that keeps on giving there, Mark, is a lot of thought leaders in the in the go-to-market space will say, Well, you need this size team and you need to do this. And then I think the answer is, well, I have limited capital. So I have to I have to make the most efficient, effective investments here. And often that means a series B where

You're asking people to do multiple things. And then it's into a role that's not the traditional customer success role. It's not a traditional renewal specialist. They're doing multiple things. I think the more you grow up and you go to Series C, Series D, or IPO, then specialization probably becomes more and more relevant, right? but I think at B, you still want folks that are a bit of

generalists in some of the roles that they're doing so that you can get more from the team if that makes sense.

KK Anderson (11:21)

And you said pod. And I imagine as well in in your world, where I think it's probably becoming more normal and more accepted to have a facial recognition, security instead of just a badge. You know, everyone's just been carrying badges for a hundred years and we're used to swiping our badges, to get into every building and to do everything. but I imagine in that pod structure, then there's a super close relationship between

you know, your inside sales team and your C S that's in that pod and your AE and like what are we what feedback are we hearing from the market? Like what

Rick Nee (11:50)

Yeah.

KK Anderson (11:51)

objections are we getting? What obstacles are we facing? Like I bet that's

Rick Nee (11:54)

That's

yeah, I that that's exactly right. That's why I love the power of the vertical pod. It's it's really a feedback loop at at its core. That's

KK Anderson (12:04)

Right.

Rick Nee (12:04)

really what it is, because there is so much good information on a hundred person startup team. And I could guarantee you that fifty, sixty percent of that knowledge transfer doesn't happen because of the unintended silos that are built.

That was sort of my genesis into the vertical pod. Verticals, I believe, buy and have different cycles and and things of that nature. But really, KK it was to speed up the feedback loop. And an SDR. So I actually I have the SDR, the inside sales rep, and if we have a success person actually reporting to that sales director, and other

In other companies, they might have those reporting to the function leads. But what I'm actually trying to do is I'm trying to look at that customer journey from a new logo intro meeting to a large expansion opportunity. I'm trying to make sure that that knowledge transfer is happening all the time. And then they can adjust their discovery, they can adjust their new logo targeting, they can

make introductions or present new use cases to similar customers. That all

KK Anderson (13:06)

Right.

Rick Nee (13:07)

happens when you're doing the vertical I don't really get when when folks tell me, well I'm the I'm the enterprise rep and I'm the mid

KK Anderson (13:13)

Yeah.

Rick Nee (13:13)

market and I sell to everybody. Perhaps that does make sense to be fair. it probably does. I'm sure it does.

KK Anderson (13:19)

Not in your world. You know, a university looking for security is gonna be very different than in an airport, right? Wouldn't don't you

Rick Nee (13:26)

Right. Yeah.

yeah. And I have learned I have learned so much from our sales directors on that. But you're right, like a a higher ed higher ed population where, you know, everyone's carrying a mobile phone and the concept of a badge is sort of foreign to a lot of them. versus a data center where it might be two or three factor where every single room or row or wherever you're going in a data center.

you're doing multiple multiple authentications to get somewhere, those are very, very different.

problems or things you're trying to serve. as your sales director, imagine jumping from a higher ed one where he's worried about students losing badges all the time to a triple, triple three factor use case where it's government sensitive data, data and and the the team is just used to and has to do a certain set of workflow things just to get to their job. They're just very, very different.

KK Anderson (14:18)

Yeah, really interesting. And last thing I'll say before we move into the next topic around kind of reverse engineering that data is that I would say, Mark, and correct me if I'm wrong, but we're you know, we're so lucky we get to talk to CROs every day on this on this show. And almost all of them have been pivoting to a vertical

Rick Nee (14:37)

Yeah.

KK Anderson (14:37)

pod structure.

And I think it's because of the feedback loop, but it's also because of this trust recession that we're in and being able to be more human and be more differentiated and really get into subject matter expertise. Like it seems like it is the hottest topic over the last couple of months. Mark, do you agree?

Mark (14:53)

Yeah, I do agree. I I think it's been building longer than just the last few months. I think it's been really building over ten, twelve years. And I especially saw that in the software industry, especially enterprise software.

KK Anderson (15:06)

Mm-hmm.

Mark (15:07)

So yeah, but definitely there's a newfound momentum in that as well.

KK Anderson (15:11)

Yeah.

And I think maybe even just for a mid-sized series, A through is what I really what I'm referencing and and the verticalization, but I think it's the right call. Okay,

Rick Nee (15:20)

Yeah.

KK Anderson (15:21)

so let's go into reverse engineering data before you, change the model. And when we say model, we mean your go to market, you know, puzzle pieces or riddle, if you will. and

we chatted in the prep session and you've vindicated that, there's enough tools now. There's AR, there's AI, there's CRM, there's all kinds of data out there that you can reverse engineer and and form a strong hypothesis quickly. Like what is what does that actually look like for you? Like what data are you looking at? What are you reverse engineering? Like how are you using that to solve your riddle?

Rick Nee (15:52)

I first, like just a blanket statement. I'm always surprised, and I would bet this is for at least half of series A, maybe transition into series B, that no not many have taken a a a true look at the data in and really tried to form a hypothesis on it. Of course, everybody looks at the data to some degree, but there's there's a few caveats and one.

By time you inherit a CRM system, if you're coming into a series B, you have to question the integrity of it, first of all. Right. p field have been added, fields have been taken out, and now we have AI which could spit out all that data, and you know, a lot will tell you that data's dirty. and and it it just is. And so

KK Anderson (16:28)

Yeah.

Rick Nee (16:28)

you got that, and you have perhaps a few folks that are investors or board members that say, This is why we invested, and we believe.

Early that this was the type of customer in the DL size. And then the data says something different. So I I would encourage and I recommend to anyone that's coming into a a product market fit, how I defined it, where you know you get customers who are starting to buy starting to buy and starting to actually retain, before you really plug in all of the data to start looking at these different KPIs or leading or lagging indicators.

You have to clean it up. And so that sounds like a very, very painful task. And if and we're fortunate now, we have a RevOps leader that is helping with that. But the way I did it for the first six months here in the last two roles that I've had is export, look at export all the win-loss data on a spreadsheet, and then go get those outliers and get them out of the data. There's just weird things that

you don't know

or that have inflated or and go get to the median. Go get to go figure out what your sales cycle length really is. Go build your taxonomy of basic vertical structure. go do all of that. And the hypothesis is that I was able to form by doing a cursory or just a basic cleanup of the data. And then instruct your RevOps or your sales ops team to say, okay, now that I've cleaned X, Y, and Z.

Can we go make these fixes in our CRM so that moving forward, this is a little bit quicker? So I would always encourage people, you gotta you, you have to do some cleaning up. And if you're not willing to roll your sleeves up as a CRO at series A, series B to do that, then I don't I don't actually don't think you should be in the job because you know you come from a big company or series D or you know, yes, doing

a few hundred million in the R, all that sort of.

Done for you. But I think at the A and B level, you've got to roll your sleeves up. And then you have to look at the data. And there's a few data points where you look at them initially and you're like, you know what? It's the integrity is just not there. So that's still a hypothesis. But I can see the DL size. I can see which verticals are buying. I can see the sales cycle length now that I've removed outliers.

You know, yeah, what you know, if you have some sales cycle,

yeah, if you have sales cycle length, you have a hundred deals over five years that were all closed in a day, you're like, wait a minute, nobody, what's going on here? it was just somebody was rebuilding a quote, and so now it looks like it was the sales cycle. They finally put the right

KK Anderson (18:40)

They finally put it in C R because their manager said they

Rick Nee (18:44)

they finally put it in CRM. Exactly, right? So remove all of that stuff, right? So but sales cycle length, deal size, which verticals you're buying.

Pipeline coverage by pipeline coverage by vertical, by rep. you could start to look at all of that, number of new logos, the percentage of LAN versus expand, how quickly from LAN to expand. And through that, you start to see what I would say the the most important KPIs that you need, win rate, right? So we have a certain pipeline coverage number.

That is not as aggressive as what the industry says because of our win rate. And so again, after you clean the data. So once you have all that, the next level is then to say, okay, I see what the data is telling me, but now let's actually go a step further and let's look at what the vertical data is telling me.

KK Anderson (19:33)

Mm.

Rick Nee (19:34)

The vertical data will have different.

Performance. Some verticals are going to have very long sales cycles, but the deals are bigger. Some are much quicker, but the deal is smaller. some require a more technical resource that it in in these things that whatever. And so you start to look at that and you say, geez, I think I I think I needed

to hire this type of person and they need to focus on these verticals. But maybe these these verticals, I can tell you right now, the persona of my sellers are different based on the verticals they're in, what those verticals need. And so again, that's the power of the verticals, is that what I initially knew was a communication loop. And to Mark's point earlier, like this has been an eight, 10, 12 year vertical, people have been sort of banging on this door.

It started to catch my attention when publicly traded companies like Cloudflare and some others said, Hey, we're outperforming because we have the structure. So of course there is a there's a revenue piece, but the the piece that that I would say in the last year that's stuck with me with the verticals is not only the feedback loop and the outperforming in revenue, but actually

What is needed in those verticals based on what that vertical data is telling you? And I can I it some of them look the same, right? Or pretty close, but some of them are wildly different. And when you're thinking about near and far-term revenue targets, you need both. You need those bigger swings that are going to take longer, and you need to make certain investments and certain comp plans and certain types of people for those. And then you need someone else that can do what I call the run rate quicker business.

And that's a different set of folks and investments. And so that's that's what reverse engineering data means to me. I look at it every 30 days and every 90, and I encourage any revenue leader to do this. I take a Friday afternoon, probably six Starbucks iced coffees, and I just

KK Anderson (21:12)

Yeah.

Rick Nee (21:14)

I I I block my calendar for the day.

and I basically say to myself, okay, I'm a venture capital private equity investor. I'm gonna go deep into this. I'm gonna look at cohorts. I'm gonna look at verticals. I'm gonna look at time series trends. And okay, this is still looking what we thought, or this one's starting to get more interesting. So I think 30 look, 60 look, and then not every 90 year, and maybe at the six month mark.

You're really digging because that's when you're starting to think about 2027, right? You're starting to think of okay, I need to start thinking about my budget and my plan for next year. And I should have enough of a signal from six months to know where the puck is going to some degree. Of course, things change, but that's what I mean when I'm talking about reverse engineering the data. and I think you have to do it. I think you can work with your sales or rev ops leader, but I think you have to be in as the as the chief revenue officer.

KK Anderson (22:02)

Roll up your sleeves.

Rick Nee (22:03)

Yeah, you gotta roll

Mark (22:03)

Yeah.

Rick Nee (22:04)

it up and

And with Claude, which is my favorite AI tool, and again, they're all great. the prompts you can get very creative contextually with the prompts as you're sort of pressure testing your own bias or your own, you got the data, but you then you can kind of try to convince yourself based on the data that this is always right. But like, no, tell me where tell me where I'm not looking. What are the blind spots? What about this? And and you'll start to see other things willing.

start to uncover. And so it to me it's a fun exercise. If you like data, it doesn't happen often. Yeah. The aha

KK Anderson (22:31)

Mm. We love data. We love data here at AGS, that's for sure. Mm-hmm.

Rick Nee (22:35)

moments,

Mark (22:35)

Yeah.

Rick Nee (22:36)

they don't come often, but when they do, good or bad, you're like,

KK Anderson (22:39)

Yeah.

Rick Nee (22:39)

okay, that this is a very compelling thing that I need to have a discussion with the senior leadership team about.

KK Anderson (22:44)

And I'm sure your board appreciates

Mark (22:44)

Perfect.

KK Anderson (22:45)

that. Mm-hmm.

Rick Nee (22:46)

Yeah, definitely.

Mark (22:47)

So Rick, I think this is a good place for us to pause for episode one and move into episode two. The idea that a vertical can carry its own economics and that these economics are what earn you the next four people is worth sitting with a little bit longer.

KK Anderson (23:04)

So reading the data before you change the structure is just as I mentioned, the same discipline that we employ here at AGS, and specifically inside our two millimeter club, which is a small group coaching residency of sales managers, leaders from non-competitive companies that come together in a data-driven coaching program where they learn to identify using data.

And coach the small shifts in seller behavior that add up to exponential movement and pipeline. We have eight-week cohorts that launch monthly. If you're interested, you can apply at www.get-ags.com forward slash two millimeter club, two mm club.

In part two, Rick takes us into the talent side of his go-to-market riddle, how he turns sales directors into industry voices, why he promotes from SDR seat instead of hiring senior talent in, and what a 90% retention rate actually takes to hold.

Mark (24:04)

That is part two. We will see you there.

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