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All right, everybody, welcome back to the RevAmp podcast. My name is Mark Lerner. I’m your host and I’m joined here today by my friend Sean Lane. I’m going to give him the opportunity to introduce himself, but Sean and I have kind of been in touch and contact for several years now through different jobs that we’ve both been in, and it’s been fun from my side to watch your journey. And I’d love to hear a little bit more about what you’re doing today as well. And we’re going to talk all about operations and some other interesting stuff. So why don’t you go ahead and tell the folks at home a little bit about yourself, who you are, where you’re from, that kind of thing.
Yeah, absolutely. Do fun from my side as well too, mark, not just on yours, I promise. So yeah, my name’s Sean Lane. I am a founding partner at Minot Light Consulting. We help early stage CEOs and revenue leaders improve their go-to-market execution. And my background’s all in all things Rev Ops. So spent the last decade building Fast-growing B2B SaaS, go to market teams. Spent five and a half years at Drift, a sales and marketing software. Spent five and a half years before that at a restaurant technology company called Upserve. And so have seen the gamut in terms of growth stories, but also just spent a lot of time thinking about the processes, the tools, the systems that support those growing teams. And so that’s what I’m doing today with my two partners at mine at Light. One’s a former sales leader, one’s a former customer team leader, and as I mentioned, my background’s in ops. So between the three of us, we’ve got a pretty good chunk of the Go-to-Market Spectrum covered and excited to be chatting with you today.
Super cool. And I do have to say that before I started taking on this podcast, one of the inspirations that I went and to reference to see what makes a good Rev Ops podcast is some of the work you had done in the podcast you hosted when you were at Drift. And so I use that as a reference point as what is good and how close.
Thank you. It’s still alive today, still going. We’ve got over 120 episodes in the bank. It’s still fun for me. To me it’s a very selfish way to learn and in a great excuse to talk to smart people. And so yeah, thank you for checking it out. We’re still going strong.
Yeah, I think anyone who does a podcast would say something similar that it’s really, it’s just a really nice way to talk to people that are smarter than you and learn from ’em. That’s definitely been my experience as well. So yeah, that’s been a fun realization. So you and I, we talked before this about the direction we were going to go, and I had talked to you a little bit about some of the things that I, we at Deal have kind of been looking at in the macro sense. And one of the things that we talk about internally that we’ve been seeing is how impactful change has been over the last three years. We were kind of in a place where there was a certain level of expectation about how companies grew and you had kind of baseline assumptions that all kind of made sense for a while.
And then we had Covid hit and then that kind I think sped up the pace of change. And I don’t see that reverting back. And one of the things I’ve noticed about some of the players that have been washed out as a result where they just weren’t being flexible and adaptable to those external changes in the market was not part of their go-to-market strategy. They had a fixed idea and weren’t adaptable to anything. And so yeah, and I kind of talked about that and what we have seen in that. But yeah, I’d love to first high level get your thoughts about that concept, that thesis, if that’s something you’ve seen as well. And if you think that at least in your work, your current work, if you’re kind of seeing people acknowledge the need for that at all yet.
Yeah, I mean I think we’re all certainly operating in very different economic market conditions than we were a few years ago. I think there’s no denying that. And I think that while a lot of people had been converted and had seen the value in having strategic operations group within their companies well before covid, I think if you didn’t before then and before the market dynamic of the last two years, then you definitely hopefully have seen that value now. And I think that as companies are dealing with challenging times, having to revisit some of their core assumptions about how their business works, how their funnels work, you really need to have a world-class ops group within your company to help you to navigate that. And I think that’s the thing that I’ve found more and more both from my own experience is in-house as well as now on the consulting side, working with a bunch of different companies.
If you don’t have folks who are looking at it through a critical and objective lens to understand, okay, these are the things we thought were going to come true about our business, these are the things that are actually happening, how do we now react? And I think a lot of times in ops, people are so set on say, okay, this is going to be our very specific set of goals and we cannot waiver from these goals. These have to be the things we stick to. And I think that there’s a balance there. Yes, you want to get everyone on the same page, you want to get everyone to commit to a certain direction and you want to get a certain timeline that people are going to say, okay, we’re going to at least commit to these goals for a quarter. But I think what we’re finding is you also have to be nimble enough to be able to adjust when those things do present themselves in terms of new market conditions, new business realities. If you just stick to those same set of goals, you’re going to wake up in three, six months and realize, oh my gosh, what were we doing for the last three to six months? And so I think ops teams have to play a role there both in the annual planning, strategic planning for the company, as well as the ongoing goal setting and execution.
Cool. Yeah, I think it’s a really great way to distill it down in terms of the way companies could structure implement ops teams and to the Go-to market organization. When we’re talking about the concept of building for scalability, right? You’re working with a company that’s earlier stage and you want them to be from the start, have the DNA to be able to be scalable, but also take into consideration that decisions made today are based on assumptions that may not be true however long in the future. How does one approach that, how does one kind of plan out that structuring?
So first of all, I think that the CEO, the founder, the revenue leaders, whoever it may be in an early stage company, those folks can set that tone that you’re talking about, can embed this kind of data-driven or ops centered thinking in the company from a very early stage so that you don’t have to go back and undo a bunch of stuff years later. I think people are sensitive to that now in terms of making the wrong hire or putting the wrong system in place or not putting a system in place at all. Because ultimately you lose a lot of time by not having that focus on early. So to answer your question, the way that we think about it and the way that I would design an ops team to think about it is in three buckets, planning, execution, and insights. Those probably have exactly what you think they do in them, mark, but I’ll talk about ’em quickly.
So planning is everything that happens before any of your customer facing team members are even in their seat. We’re talking about let’s just stick with go to market operations here. So that’s things like territory planning and sales, book of business planning, post-sale decisions around what parts of the market you’re going to go into, comp, design, headcount, quota capacity, all of that lives in that planning bucket. Execution is all about the day in the life of all of those different customer facing team members. So what does an SDR do every day versus a mid-market AE versus an enterprise CSM? What are the systems and tools that support that day in the life? What does the customer journey look like? Handoffs in that customer journey. So thinking through all of that and then insights should be the bridge between the two. And that’s in addition to kind of the core reporting that OPS is usually responsible for in a company that’s also the place where you can be more proactive in terms of the analysis that you’re doing, the insights that you’re bringing back to the business.
And so planning, execution and insights should kind of all feed one another. And then to your point about scalability, if you put all three of those ingredients together in an effective way, you should almost have gates set up in your business that tell you when you are ready to scale. So an example of one, and one of the ones that I use as kind of a north star metric for any sales organization is productivity per rep. And I think in the thesis that you were describing at the beginning, there was a world before where you would hire a bunch of people, you would say, okay, each rep’s going to provide 600 K in bookings for the year. And so therefore if I just multiply 600 K times the number of people I hire, that’s how much money my company’s going to make that year. And then we find ourselves in this unfortunate situation where there’s layoffs and people are shrinking their teams because those expectations aren’t coming true.
And so I think a better way to handle that now is you have to prove out the productivity assumptions that you have. And even if you create a hiring plan, let’s say for the entire year, that doesn’t mean you have to fulfill that plan if you’re not meeting the productivity expectations that you have. So an example of something that we used to do was I would sit down with the CFO VP of sales every single quarter and say, okay, for each segment of our business, are we ahead of our productivity expectations? Are we behind on our productivity expectations? And so if the SMB team is beating productivity expectations, great, move forward with your hiring plan. Keep going. If enterprise is in the red and you’re not yet at your productivity expectations, don’t hire, stop, figure out what’s broken in that part of the business, get those folks successful before you start to grow that team. So that’s one of the ways that I would think about just making your entire process more scalable and it gets down to understanding the nitty gritty levers that are available to you in your funnel to make those productivity expectations come true.
Is there a stage, a gate at which the menu changes, what’s on offer, what levers you have to pull change and you kind of shift your thinking and the way your strategic kind of model?
For sure. I mean, I think first of all, people ask me all the time, when should I even invest in ops, right? And I think once you are making that transition away from a founder-led sales model, you have some sort of predictable repeatable sales process and you’ve found some level of product market fit, you’re ready for ops. And that’s the moment where you can say, okay, what can we do to bring more yield out of the team you’re hiring? And I think just to pause there for a second, that’s kind of the whole point of the job. The whole idea is that hiring someone and paying a full-time salary for an operations person will yield you more dollars than the amount you’re paying for that person. That’s something that I think sometimes people just take for granted. Like, oh yeah, of course I’m going to hire X number of ops people.
Every single dollar you attribute to ops salary needs to result in more dollars for the company, more efficiencies, more yield. And so I think that’s important. And then to answer your question, yes, you have to change the lens through which you look at your business as your business grows. The way I like to think about it is you want to be careful to map the maturity of your company with the complexity of your systems and your metrics. So for example, if you’re a super early stage company that is primarily an outbound driven business, you probably don’t need to build a super complicated multi-touch attribution model for figuring out how your pipeline is driven, right? You’re just not ready for that yet. And as you grow, the types of metrics you look at might change. So if we’re really focused on win rate and average sale price and productivity per rep, then maybe as we get a little bit bigger, we start to pay more attention to things like renewal rates and retention and lifetime value and LTV to cac, right?
You have to kind of grow up into some of those metrics. And I think if you try to be more complex than you need to be early on, it can be a bit of a distraction. There are exceptions to these rules. You’ll find super mature companies that are super immature in their systems, and you’ll find really early stage companies that have super complex systems, but for the most part, you can kind of map where your company is based on of its stage and then ultimately the maturity and complexity of the systems that you need to support that stage.
Yeah, awesome. Yeah, I’ll take it kind of the opposite. When should you be wary of Frankenstein, Frankenstein-ing your own solution? We are not going to spend the time to find a real CRM. We’ll make one in Google sheets or blank in Google. Google Sheets tends to be the thing where all bad ideas end up trying to be worked on your own. At what point, even if it’s sort of working, right, you’re making it but put a little stress on it, that thing breaks pretty quick. Where are the gates? That’s something we can’t brush past, we have to fix, we can’t work out of, we can’t gloss over this. We can’t fit half measures on this thing.
So first of all, this is a hard question for operations teams to answer because the answer is always we want everything and you have to prioritize and you have to pick the parts of your business that you are with being imperfect. And there’s always things that we think could be better. And that’s just the way ops folks are wired. And so the way I think about it is you’re going to have Band-Aids inside of your systems. What I would always coach my team on is don’t build a Band-Aid on top of another Band-Aid, right? Because those are the things where you’re going to have where breakages, and then you’re ultimately going to have to go back and do a whole bunch of cleanup. So what’s the better version of that? To answer your question one at the very beginning, you want to keep things as simple as possible.
If you map out, and you should do this, map out your customer journey from beginning to end. Look at all the different milestones, all the different touch points, all the different handoffs between different roles, and then think about what are the milestones along that customer journey that you want to measure? And again, what you are ready to measure. So to start, it can be something as basic as, alright, how many meetings do we book? How many of those meetings take place? How many real opportunities do we create? And how many of those become customers? Those can be the foundational milestones that you build. And those are also the things that you probably don’t want to go back and change the definition of later on because then you’re in this whole world where you have to retroactively change everything. Definitions change, it’s an enormous paint. And so picking the kind of foundational building blocks of what you want to measure at the beginning will help you for a long period of time.
And those are the ones that you should spend time and energy and effort on defining well the first time. And then there’s other stuff that you can probably change later on. You’re going to change the way you think about target accounts over the course of your business. You’re going to change the way you think about lead distribution. You’re going to change the way you think about segmentation or firmographic scoring. Those things are inevitably going to change. And so I think in addition to keeping things simple, the second piece I would say is you really want to think long-term. What are the things that are foundationally going to always be true? And what are the things that probably won’t change over a course of period of time? And then the other thing I would think about, and this is something that is also pretty difficult, but we naturally want to move towards things that are quantitative and the things that we can absolutely measure.
And a huge part of the customer journey, a huge part of the customer interactions we have is qualitative. And so one of our goals at Drift was we had this kind of internal mantra that a customer should never have to repeat themselves. And so you see this, I’m sure all the time, right? You go through a sales process for something, maybe you are buying, you give the sales person a whole bunch of information about your business, your use cases, what compelled you to want this tool in the first place. And then you get to your post-sale onboarding kickoff call, and they ask you all the same questions that you’ve already answered and put a ton of thought and detail into during the sales process. It’s infuriating, and it’s also a really bad customer experience. And so as you think about, okay, what are the things we absolutely need?
There’s some qualitative information that needs to get passed through this customer journey as well, and there’s more tools available now to help you with that. You can use AI to summarize calls. You don’t have to rely on the handwritten notes of the rep, which we know are on a notepad somewhere and not on the CRM. So there’s a whole bunch of ways I think you can do it that prioritizes the most important things that you need at that moment. And it’s hard, like I said, you have to make those trade-offs about what is critical and what are some of the things that we can build later. Yeah,
I’m smiling because yes, I’ve been on that end of conversations and I find it endlessly frustrating when I’ve already had the first call and then I speak with the next person and they’re doing discovery again. It’s like, guys, we did this already. I would take it a step further and that I think that buyers today, B2B buyers expect that some of this stuff without them telling you, because there’s so many tools out there that kind of tell you what CRMA company’s using based on whatever signals they have out there and all this stuff. And I don’t know if that’s been proven out, but that’s my kind of gut feeling because there’s so much data out there, and the bigger your engine, your growth engine, the more opportunities you have to listen to those things. But kind of bringing it back and talking about the critical pieces of, let’s call it kind of the technology stack for ops for Go-to-market, along with the changing dynamics, we shifted from a world where it was growth at all costs.
Everybody gets to choose their favorite little do hickey and for their specific niche in the company, and budgets are kind of whatever that flipped on its head pretty quick. And not only have budgets been constrained, but also there’s been a much more rigorous look at the existing stack and how you can, what’s duplicative, what’s redundant. And there’s a lot of stuff I think that is redundant, but taking things back to the core, what are the pieces of the technology stack that you maybe you can try, maybe take somewhat of a risk on a newer technology or work on do something internally, and what are the core pillars that you have to make the costs can’t be the biggest constraint you have to really consider what this is going to do for your growth?
Yeah, that’s a great question. And I think any company right now that is questioning whether they are a nice to have or a need to have in that tech design that you’re talking about, it’s going to have some challenges because if you’re questioning it about yourself, your customers are questioning it about you as well. So the way I would think about it is going back to what I was saying about mapping out your customer journey, you want to think about what do you need to instrument within that customer journey, and where does technology help you, not just by default. I heard so-and-so has this category of tools, so therefore I should have it as well. Technology should support the existing customer journey, not the other way around. I think a lot of times people try to shoehorn a specific tool into their process because again, maybe it’s the hot new thing or somebody recommended it to them.
You need to have a problem that you want technology to solve better than a manual process or a human could solve it for you. In terms of the stuff that’s foundational, the way I think about it is across that entire customer journey, there are kind of two foundational components that should always be there and never change. The first is the CRM use Salesforce. HubSpot doesn’t matter. The second is some sort of data warehouse, and you need to have a strategy for that. And this is one of those things that, again, early ops leaders, early data-driven CEOs can embed in the DNA of the company. My first boss at Drifts, really smart guy named Will Collins, he was taking snapshots of our Salesforce instance from the time we were less than 25 employees. And so that was always embedded and then that data was available to us.
And so the way I think about it is the CRM is going to give you visibility into everything that’s happening in your business at that moment in time. The data warehouse gives you visibility into everything that’s ever happened in your business, ever. And so those are the two kind of foundational elements that I think every company needs. Where you go from there, whether you choose to use more of a platform approach or more of a piecemeal individual point solution approach, doesn’t really matter as long as you focus on the different parts of the customer journey where you see friction. And so if you see friction around creation, then that’s a place where you need to make a solution. That’s the way I think about it. And then once you have those things in place, you need to also think about what might break. If you have a whole bunch of different integrations and tools coming together, something inevitably will break.
And so you need to proactively think about, okay, how can we create some sort of alerting system for ourselves so that when something does break, we know by lunchtime as opposed to three weeks after it breaks. And so there are tools you can use to create those alert systems. Another thing that we do a lot is we help companies to create what we call a danger dash does exactly what it sounds like. It detects danger. And what that is, it’s a series of reports, again, throughout the customer journey that report on things that we would not expect. So let’s say for example, you have some sort of lead distribution tool in your stack, and any lead that comes in that has a behavior score greater than 20 gets distributed out to the team, my danger Dash report would show me all the leads that are greater than 20 that have not been distributed to the team. And then it’s really fast for people to go in and diagnose what’s been broken and then ultimately take action. And so putting those foundational building blocks in place, anticipating where things are going to break, following along with what needs to be done throughout the customer journey. That’s the way I think about designing the tech stack right now.
And I would be remiss if I didn’t bring up the two letters that is just ever present everywhere. So there was, I would say certainly at the end, middle to end of last year, we were in ai. It felt like that scene in being John Malkovich where he drops into John his own, and everyone’s just like malkovich mal. That’s how it felt like with ai. It was everywhere as a company. We went to HubSpot inbound. It was every session I went to a Salesforce event in New York City. Salesforce seems to have is now an AI company according to them. So I think that there were a lot of people that are scrambling like, oh, we need ai, and don’t really even know what that meant. And my concern there is that some of the dynamics I saw play out with some other kind of flashy terminology without people really thinking critically and then kind of change everything to incorporate it and realize it’s really not the silver bullet. So how do people find that balance and what does it mean to incorporate ai? Is it necessary? Is it, yeah,
Yeah. So first of all, I fully agree with you. We’ve reached the point where it’s time to move past the buzzwordy hype and into actual use cases, right? Yeah. I actually really strongly believe that ops people are incredibly well positioned to leverage all of this new technology that is becoming available to us. And the reason that I say that is S, like I mentioned before, was created in order to drive more efficiency, more outcomes, more yield through less people. AI is the exact same thing. And so if what your job is every day is how to create the most leverage possible for your internal audiences, you should apply that same thinking to the AI tools that are available to you. We talked about how do you maybe summarize AI calls, right? That’s a good way to think about it. Maybe you use it to help you build your next firmographic score based off of a whole bunch of data you have about your existing customers.
Ops people, I think are uniquely positioned to help do the work that they’re already doing faster through the use of these technologies. And so that’s the way I would think about it. Right now. I just had, speaking of my podcast, I just had Scott Brinker who leads the ecosystem at HubSpot. He’s the one behind those beautiful MarTech map graphics that come out every year. And what he basically said to me is the key to using some of these tools is he calls composability. And the way that he talks about it is all these different tools can now connect to one another in a way that you couldn’t before. And you can also leverage the data sets available to you in a way you probably couldn’t before. And ops folks get to be the ones who kind of inject their creativity into how all those different things connect.
And so the more that becomes available and easier for us to use, I think ops is going to have to play a critical role because everyone’s going to go out. And what’s going to happen is everyone’s going to try their own tool. Everyone’s going to try their own AI model. Everyone’s going to try their own version of chat GPT or make their own GPT, and then all of a sudden we’re going to have the exact same problem that we had four or five years ago, which was you have this crazy tech stack bloke and no one’s thought about how it all comes together. And so that’s I think where ops is going to have to come in and say, look, this is our unique data set. This is how we bring all these things together. And if we’re leveraging AI to help us along the way, great, but it still has to come back to that kind of customer journey and the data that’s available to the company. Does that make sense?
Makes perfect sense. And I think that’s really the ops gets to play that role of, hold on, let’s check the euphoria at the door and think critically. And the scenario that continuously plays in my mind, because I saw this happen, and I’ve talked to people whom it happened, I would say two years ago, up until, I don’t know, 6, 7, 8 months ago, a similarly kind of euphoric word and term that was out there is PLG. And not to discount the whole idea, I think it’s great, but I think there were a lot of companies for whom that model is probably not ideal, who felt pressure because the word was everywhere that VCs were like, you have to go PLG, you have to go PLG. And I know of some that completely shifted their entire structure, their go-to-market strategy, their sales, everything. And then the ground shifted under them, and they did not have the ability to kind of handle that change quickly. Their change management philosophy was fine. It was like a point in time. This is the change we’re making. So obviously we don’t know what we don’t know. We can’t foresee what’s going to happen. But as an ops leader, how does one kind of ensure as best you can, that those kind of scenarios don’t happen? That there’s a mentality of continuous change, accepting that the market dynamics might dictate and that we can’t overcorrect or put all our eggs in one basket, or we have to think this about this critically.
Yeah. So I’ll add two commonalities that I see between the AI trend that you just described and the PLG trend. The first is something I think optimal can embrace about both AI and PLG is that it can challenge all of our historical ratios and staffing expectations about how many people you need to drive X number of results at your company, right? In theory, both AI and PLG should make you more efficient. And so you shouldn’t need as many people and as many resources to drive the same number of results. So I think that’s kind of commonality number one. Commonality number two is what we were talking about around the data. If you are effectively using PLG within your business, you have this treasure trove of data about the usage of your product by some of these users that should indicate to you when you should insert a human being versus not, right?
And I think AI will be the same thing. The proprietary data that companies have within their products will be their unique differentiator. And so to me, I think if you think about the capacity of teams and also the data underlying them, that those are similarities to me when it comes to both PLG and ai. And then I think really to answer your question, the mentality of the best ops folks that I’ve ever worked with is better, better never done. You’re never going to hit a state of complete. There’s always going to be incremental improvements that you can make to a system, a tool, a process, or just the way your company goes to market. And so you ask about how do you deal with ambiguity? The whole job is ambiguity. If you don’t like that, you’re not going to enjoy this type of job, you’re not going to enjoy this type of work. But if you embrace that and you love and you thrive in those type of situations, to me, there’s no better gig to have. So better never done, and you won’t be disappointed.
Awesome. So as we round out our time here, because time flies when you’re having fun, before we say goodbye, why don’t you tell the folks a little bit about how they can learn more about what you’re doing, consume some of your content, maybe some of your upcoming plans for that content? Yeah, yeah,
Absolutely. So first of all, would love to connect with anybody on LinkedIn, Sean Lane on LinkedIn, connect with me and we can kind of continue chatting from there. Operations with Sean Lane is the name of the podcast, super creative title, but very also easy for you to search wherever you get your podcasts. And then if you want to work with us over at mine at light, you can check out email@example.com. So those are the places to meet me.
Thank you so much, Sean. That’s great. And I’m looking forward to hopefully having you back on the podcast in a few months.
All right. Awesome. Thanks Mark. Appreciate the time. Bye-Bye.