Choosing Your Sales Strategy: Lighthouse vs. Landgrab

There's a moment right now to go sell big software again. We're now looking at a different way of doing business entirely.

What are the Lighthouse and Land Grab sales playbooks?

Here's the framework for evaluating which playbook you should be following. There's this very obvious one: go after the very obvious companies here in San Francisco, in New York City, in a major metro, that probably have some sort of proof or social value associated with them. Or go out and sell in Ohio, Chicago, or St. Louis. Find people who need your solution.

If you think about the enterprise networking world in 2009, people thought we were crazy. We had no chance of getting into the largest corporations in the world through a Lighthouse strategy because Cisco and HP had them all tied up. But what we could do was say, “Listen, we can configure and deploy faster, and we’re simpler to use.” That was very much a Land Grab strategy.

Too few people are willing to pick up the phone, get on the plane, and get in front of those customers right now because they feel like it sounds way sexier to sell to JPMorgan Chase than to Morgan Chase.

1. The Biggest Mistake Founders Make

I think the biggest mistake that I see founders make at an early stage, honestly, is just

Today, we're getting into the single most expensive question an AI founder faces: how you sell. Joe Schmidt just wrote a piece called “Lighthouse or Land Grab,” which gets into the 2 dominant playbooks he's observed among enterprise AI startups. Joe, tell us about the piece in your own words. What are the Lighthouse and Land Grab sales playbooks?

This piece actually stemmed from an observation I had while driving up the 101 freeway, maybe 3, 4, or 5 months ago. I can't remember. You realize that you see the same 2 competing companies—one on one side of the freeway and the other on the other side—and they're selling the exact same piece of software. For some reason, they've all decided that the only relevant companies for this piece of software are in San Francisco and along the 101 freeway.

This has gotten even more ridiculous. Obviously, every bus has been wrapped, and planes are flying overhead towing startups. I think it's all very clever, but it's all targeting the same kind of sales motion. The reality is, you don't always have to do that. You don't always have to sell to the same companies in San Francisco.

What I wanted to try to do was tell founders, “Hey, here's the framework for evaluating which playbook you should be following.” There's this very obvious one: go after the very obvious companies here in San Francisco, in New York City, or in a major metro that probably have some sort of proof or social value associated with them. Or go out and sell in Ohio, Chicago, or St. Louis, and find people who need your solution.

That was the whole point of the piece: you don't always have to go sell these notable logos. We'll see how that plays out, but that's why.

Just to get a little deeper, when does it make sense for a founder to go buy a giant billboard that you see when you're driving from SFO into the city? When does it make sense for you to do a more targeted sales activity or motion elsewhere?

The way that we tried to make this make sense was, of course, very consulting-style: we used a 2x2 matrix. I never worked at a consulting firm, but I'll do my best. We were really thinking about what axes we should be mapping opportunities against.

The y-axis is what we called buyer exposure. It's intentionally called exposure because there's the exposure of making a mistake with the solution that you buy. There's also the exposure of the solution inside your company: does the product that I'm selling to my customer end up being shown to their end customers? That's an important distinction. It's really just the overall risk associated with buying this piece of software.

That was the y-axis, and it goes from high to low. The x-axis is whether or not proof travels in any given market. If you think about the top right, it would be a market where proof travels, with high buyer exposure and high buyer risk. That's a Lighthouse market.

The bottom left would be low proof traveling, but also low buyer exposure. That would be a Land Grab market. I think those are quite different.

If you think about the standard markets that fit into the Lighthouse model, they're regulated industries. Oftentimes, there's a more constrained number of logos. If you're wrong in the industry—if the buyer buys the wrong piece of software and it ends up doing the wrong thing—it can lead to very bad things happening for your firm, including potentially getting in trouble with the regulator or even doing something illegal. That's very bad.

On the flip side, when you're looking at more of a Land Grab market, there's an established budget. People have been used to and accustomed to paying for a type of service, and you can come in there and show the end buyer the math: “Hey, my solution is better than whatever solution you're using today,” whether that's a software-driven solution or a human-driven solution.

The distinction we drew was between proof in the top right of the quadrant and math in the bottom left. That's how we thought about the framework.

And Andy, we'll get into your background in a little bit, but first, maybe it's good to categorize some of these modern-day AI startups within these 2 frameworks. I know you both work with a lot of these companies, so I'm not sure if you want to call out specific examples or talk through the sales strategies that you're seeing.

You're the Land Grab mastermind, so maybe you want to talk about some of the things you've seen.

You framed it up really well in your article. The concept of the Lighthouse being more in industries that require regulation, a lot of social proof, and so forth tends to apply to companies that are going after category creation. The category doesn't exist today, so you have to go out and prove yourself with the big names. Obviously, we have a bunch of portfolio companies out there, and you mentioned a couple in your article that are doing that.

On the other side, the Land Grab strategy involves less social proof. Especially in the AI world today, those tend to be companies that are replacing or improving workflows that already exist, where there's existing budget. Again, we have a whole bunch of portfolio companies—you named a couple in the article—that are doing that today. They're inserting themselves and saying, “Hey, we built a better way to go after this through AI.” Those are the companies going after the Land Grab strategy.

It's interesting. For those who aren't familiar with Andy's background, he's built some of the best sales organizations I've ever heard of at Samsara and Miro. I've always found these stories really fascinating and illuminating. The Samsara story around the ELD mandate, as I understand it, was basically forcing a category to happen everywhere all at once, and it was just a matter of who could go out there and do it fastest.

2. Samsara's ELD Mandate: The Perfect Land Grab Moment

Maybe, for the audience's edification, you could share a little bit about what that big why-now moment was, because we're having one right now, and how you went and captured it.

If you're in the industry for long enough—and I've got the gray hair to prove that, although I have been blonde, bordering on gray—you tend to see these big transitions. I'm old enough to have seen the internet come about, and certainly mobile and cloud, and obviously now AI. Each of those causes a transition and creates new ways to think about how you go to market—not wholesale changes, but always tools to help improve upon them.

The other thing I would say is that I can't name too many companies that have become hugely successful without some element of timing and luck.

You talk about Samsara. The company was founded back in 2015, and I joined in 2017. The idea back then, at the very beginning, was internet-connected sensors: all the value chains were going to become sensored up. How do we get sensors out there, ingest this data, and give it back to business owners in digestible and usable ways?

One of the first products that started gaining traction was these telematics units. Taking a step back, if you think about the world of transportation—long-haul trucking, right?—prior to around 2016, they had these manual logbooks. If you were driving a truck and stopped to take a break, you would write down in your logbook, “I had just driven for 4 hours; now I’m taking a 20-minute break.” Then you drove for 2 more hours and stopped for lunch.

If highway patrol pulled you over, they would ask to see your logbook and audit it to make sure you weren’t driving too long. It was a safety regulation. In the U.S., around 2016, they implemented this ELD mandate, which stood for electronic logging devices. The idea was, “Hey, we can use technology to actually track when the vehicle’s moving and when it isn’t, whether they’re taking enough breaks, and so forth.” Take the human element out of it, rather.

Over a 2-year period, that was basically implemented between 2016 and 2019, with various phases of compliance. What it did was provide this huge tailwind for anybody making these electronic logging devices, and we just happened to be one of the newer companies doing it.

And there were some very, very established players, right? AT&T had a solution. Verizon had a solution. There were a number of companies that were already in the hundreds of millions—half a billion—in revenue, doing this.

A rising tide floats all boats. It helped everybody. But if you were a new entrant into the market, like we were at Samsara, it really helped because basically the entire industry all of a sudden had to find budget to go out and buy these things. A certain percentage of them would clearly say, “Hey, let’s check out what’s new out there. Any new entrants into the field?” So it really helped give us a boost.

How did you navigate the social-proof side of that? I think the casual observer might think about that and say, “Okay, wow, this is regulated. We can’t screw this up, so you probably have to go win—I don’t know what the largest long-haul trucking company is; I’m trying to think of the ones I see on the freeway—but in any event, you probably have to go win that one.” But it doesn’t sound like that’s what you did. From what I understand, that’s not what you had to do. How did you navigate that social-proof element?

I think I would—and maybe I’m doing a little bit of a disservice to the amount of strategy that went into this—but there wasn’t a lot of strategy that went into, “Do we chase lighthouse accounts or do we go after land grab?”

Who’s willing to pay us?

We kind of listened to our customers, right? It doesn’t take too many cold calls into the largest trucking and transportation firms when you’re an 18-month-old company they’ve never heard of to hear, “We’re not buying.” You quickly figure out, hey, who can we sell to?

In 2017 and 2018, we had minimal features, right? We were just looking for: do we have—

Something that somebody wants to buy?

For us at that point in time, the mid-market was the place to go for a couple of reasons. Number 1, it didn’t require as much social proof, right? It was more about, “Hey, are you satisfying my need for telematics? Do you fit the requirement?”

The other reason was we could get really fast feedback on the product, right? The sales cycles were short. We could get it implemented quickly. They would deploy quickly. The bigger the account, the longer the deployments and the longer the feedback loops. So it really helped us with the product-innovation side as well, just to get as many deals out there and as many wins as we could.

Yeah. And I think this is actually really important as early-stage founders evaluate this moment in time. What we don’t exactly have is the mandate from the U.S. government saying, “You have to adopt AI,” but CEOs everywhere are saying, “You do have to adopt AI.” There are AI boards at every enterprise right now saying, “Here’s what we need to buy, and we need to do it by X period of time.”

That surely will go away, but there is this moment of crazy kinetic energy inside of big companies. So I think what Andy just said is actually a good barometer of whether or not you’re in a land grab versus a lighthouse market. Are people willing to actually buy from you? Part of the land-grab math here is: are they willing to get on the phone with you? Are they willing to buy your product? Are you going through POCs and figuring out how to get someone to use it?

If you can’t get that done, then it’s all about going and doing very deep, forward-deployed lighthouse arrangements and figuring out how to then get to your next customers. Too few people are willing to pick up the phone, get on the plane, and get in front of those customers right now because they feel like, “Oh, this is this new category moment. I have to go to JPMorgan Chase to sell my deal.”

And you said a really good thing there. Do they have existing budget? Is it a replacement product? If it is, then you’re probably going to lean more toward a land grab.

If this is a brand-new product—and there are so many of those today, right? We talk to founders every day. Companies are being born with brand-new products, and they’re going after brand-new markets—if you have to do a lot of education for your market, if they don’t have existing budget, if you’re going to have to take them through this educational journey before they can go out and justify the purchase internally, that’s probably more of a lighthouse strategy, right?

3. Lighthouse in Practice: Harvey, Decagon & Further AI

You’re taking them on this educational journey, and it’s a lot more missionary work than it is, “Hey, take that money that you’re spending with Vendor A and move it over to us.”

Yeah. Yeah.

So maybe it’s worth getting specific about some of these companies. I know in the piece you talk about Hebbia and Harvey as classic lighthouse examples, and then Stuut and Decagon as land grab. So maybe do you guys want to talk about some of those playbooks that you’ve seen, or maybe give other examples?

Yeah, sure. I can go, and you jump in. For example, I highlight Stuut in the article as the prototypical example of a land-grab company that we’re seeing in this new age. Stuut is this amazing business founded by 2 incredible entrepreneurs, Tarek and Ben, and what they are going after is the accounts-receivable market.

For listeners who may have never thought about AR, accounts receivable, basically, this is when someone owes you money in an enterprise context and you have to go collect the money from them. This is not glamorous. However, there has historically been a mechanism to do this, right? There are collections teams and big pieces of software. I won’t say their names because compliance will probably bleed me out anyway.

There are big companies that do lots of AR and sell in this market, but it’s been very manual. These human teams have to interact with this piece of software, and they have to go out there and collect. What Stuut said was, “Hey, AI is actually quite good at basically having conversations with people. It’s very good at looking at information internally and basically doing this process end to end.”

So we could reimagine this historic way of doing collections. Instead of having humans do it, we can have humans plus AI do this even more effectively. What that then opened up was the rest of order-to-cash and basically the entire accounts-receivable suite.

What they basically went out and showed all of their early-stage buyers was, “In doing this, we have the math to prove it. We will be more effective than your current solution and your current human teams at collecting, and this will do X, Y, Z for you. It’ll improve working capital by a tremendous amount. It’ll save you money. It’ll actually make you more money.”

So they were able to go out to the mid-market and just show the math and say, “Would you like to have this solution?” Yes or no. That’s a really good example of a land-grab market.

Those entrepreneurs are just unbelievable sellers. They hit the pavement better than anyone—just as good as anyone I’ve ever seen—and they’re doing a great job. Another example on the lighthouse side would be Harvey, which we highlight in our article. They did a fantastic job of winning the right law firms for this very new, very theoretically high-risk initiative, where you’re augmenting your human workforce with AI capabilities and really automating what junior lawyers would be doing on a day-to-day basis.

When they won the first few critical lighthouse accounts inside of their market, that proof traveled big time.

And then the buyers that had this tremendous amount of exposure realized, “Hey, it’s actually safe for me to buy this solution.” So those are the 2 examples in this market. I don’t know if there’s anything you’d highlight from other companies you’re working with or things you’ve seen.

Yeah, those are 2 great examples. I’m doing a decent amount of work with a company we invested in called Pylon. They’re basically an AI-native customer support company, and they’re a great example of a land grab. They’re doing a fantastic job right now of going out and saying, “Hey, we’ve got a better way of doing this.”

They’ve been climbing up the ACV ladder, but they started at pretty modest ACVs and have been working their way up just by going out and replacing. They have a fantastic go-to-market team that’s just out-executing.

4. ACV Discipline: Clear the Hurdle, Then Just Go

This ACV question is actually kind of an interesting one, and I’d be curious how you thought about it at Moroi or Samsara. There’s so much demand out there and so many different ways of building your go-to-market engine. How much did you actually think about what you were landing at with these? Maybe go back to when you were at, I don’t know, $10M or $50M in ARR at one of these businesses. Were you optimizing for that, or was it just, “Let’s basically figure out how to get enough reps in”?

Yeah, it’s a good question. The answer is you think about it a lot, and then you try not to think about it at all. What I mean by that is you want to make sure that the ACV you’re going after tops the hurdle, right? In other words, you look at your unit economics: Is it healthy or not? You don’t want to be taking deals that are negative to your unit economics.

But if it passes the threshold, then the answer is you don’t think about it. You just go and get as many of those as you can. So, if you can build a go-to-market engine, theoretically, that could live off of $15K ACV deals, fantastic. Don’t take $8K ACV deals, but go get as many $15K ACV deals as you can.

You want to just build a repeatable engine, pour fuel on the fire, and get as many of those as you can. Then what happens over time is you start inching up, right? Bigger and bigger companies like what you’re doing, and then you start stacking up the wins and going up the ACV ladder.

And can I ask one follow-up on that? This is interesting, and I'm enjoying getting you talking about this stuff. Moroi was basically a cloud networking company, and you had this clever program where you would give an access point away for free, as I understood it. Of course, that impacts gross margin, but you also have a hardware element as part of your gross-margin calculus. We don't have as many companies doing AI applications with a hardware element, but there is an inference element that impacts gross margins. How did you think about those trade-offs in the early days of Moroi? Of course, you had the same thing at Centara with hardware, too.

Yeah. So, just for the audience's edification, Moroi was basically a cloud networking company. At this point, 20 years ago, it still is a very healthy business within Cisco. It was acquired by Cisco back in 2012. The company was actually founded back in 2006. The co-founders were working on a research project as PhD students at MIT and started the business. The research project was called RoofNet. The technology they built was basically large-scale mesh Wi-Fi, and they'd install it on roofs in Cambridge. The idea was you could outfit municipalities, parks, and public areas with Wi-Fi. It was fantastic technology. Within the first couple years, they figured out it wasn't a great business model. There wasn't a lot of revenue in municipal Wi-Fi, so they pivoted into enterprise.

If you think about the enterprise networking world in 2009 and 2010, people thought we were crazy. Why would you be trying to build an enterprise networking company in 2009? Don't you know that market was won 10 years ago by Cisco and HP? But the reality was that was right when cloud was coming about, and the big innovation around Moroi was that the product and engineering folks figured out how to configure and manage this networking equipment through the cloud. Back then, it was a little bit innovative.

Anyway, our problem—and that was very much a Land Grab strategy—was we had no chance of getting into the largest corporations in the world, Lighthouse, because Cisco and HP had them all tied up. But what we could do was say, listen, we can configure, we can deploy faster, and we're simpler to use. Who cares about that? The mid-market, where they don't have substantial IT teams trained in command-line code and this kind of stuff. Our firm belief at that point was: what's the best way to get them to understand that our networking equipment is simpler to use than the Cisco they're about to buy?

And the answer is: get them to try it.

Yeah.

And so what we’d do is we’d run these webinars and say, “Hey, you attend the webinar, we’ll send you a free access point. You plug it in, try it out.” The idea was, if they tried it, the light bulb would go off and they’d say, “Wow, this is just so much easier than what I’m using. Why don’t I use that?”

It was very, very successful for a long period of time. Even as the company matured, we were very, very liberal in our trial and eval because you fundamentally want customers to experience the technology.

And realize that it’s better than the alternative.

And do you think there’s an element that people can learn from right now? It’s hard, though, because there is an aspect of configurability with a lot of the new AI stuff. If you just give somebody this Ferrari, they might not know exactly how to even turn it on. I don’t know how you even think about the delivery mechanism for some of these trial periods and POCs with some of the AI companies you’re working with right now.

Yeah. I think it’s become more challenging in the world of AI because, number 1, things are moving so fast. Things are changing daily. If you think about a proof of concept or a trial, the whole idea, if you’re on the sales side, is, “I want the customer to experience this. I want to prove that it works for them, but I want to do it in a period of time that doesn’t go on forever.”

And so what you have to stay away from—and I think one of the real dangers today—is these things turning into science projects, right? “I’m going to deploy this. Well, can it do this? Can it do this? Can you show me this? Can you show me this?” Of course, things are advancing every day, so the answer is probably yes, I could. But then you run the risk of these trials or proofs of concept going on forever.

And so there’s a lot of that today.

And did you—I guess, would you recommend having these auto-convert as much as you can? I don’t know—other learnings and lessons from this type of 30- or 45-day trial. And then we can even talk about the right amount of time that you’re giving people with the product.

I think the timing depends a little bit on the complexity of your product, right? If it’s going to take 2 weeks to set up, then you can’t make it a 2-week trial. But I think the 2 biggest things are: make sure you have an end date, right? It’s a 30-day trial, a 45-day trial, or a 60-day trial. Period. End of story.

And then the second one is, you have to define the success criteria up front. Here is what we are proving that we can do for you, right? In some of these companies, you can’t do a proof of concept because maybe it is regulatory, maybe there’s too much risk in there, and they’re not going to let you do it. But where you can, I think you want to make sure you have both an end date and the success criteria clearly defined.

Yeah, I think this is so tricky right now. You have to basically define the scope that you’re going after and the success criteria, but oftentimes, if you’re automating something that has never been automated before, there’s a significant amount of configuration, and that costs money. Your product could work, but it might be deployed improperly, and/or the results take longer than 30 or 45 days.

And so how do you actually address that? There's a difference between the product working and needing to work with the customer to optimize whatever they're doing with the product. Yeah, right. Imagine you're—I always go back to sales because it's easy to think about sales—but imagine you're using a sales tool.

The product needs to work, and then you need to use it and target the right customers for whatever you're selling. They're kind of 2 different parts of the equation. And so if all of a sudden you're taking risk on whether or not your product works and whether or not it's being used correctly, it's very tricky. And so I think this is actually a really important—

—topic for founders and early-stage revenue leaders today: figuring out how you're educating your customer on, “Here is the thing we are signing up for. We are not signing up for whether or not your employees are using our tool the right way.”

Who have you seen that does the best job of evangelizing and taking people through the onboarding process?

You know, who would I put in that bucket? I think Decagon has done an amazing job at this. They go in and basically evangelize that they're doing customer support better than anyone else. Then they're very good about saying, “Here are the benchmarks that we are signing up to hit,” and then they hit them in their time period.

I think some people might trivialize this, but it's very hard to do customer support effectively. This is a high-risk, exposed market; you don't want to screw this up. So I think they've done a really good job of evangelizing. I think the guys at STO—going back to the example I just talked about—and then another example would be a company that I'm on the board of called FurtherAI.

They sell into the insurance space, and they're basically evangelizing the idea of bringing AI to insurance. People have been using AI in insurance; this is not generally a first adopter of technology, but a lot of their customers are some of the biggest insurance companies in the world. It's because they're very comfortable with, “Okay, here's an AI solution that's built in a governance-first, secure form and fashion,” and then they work with forward-deployed teams at their customers to get it up and running. So those are a couple examples. I don't know if you have any—

—and that's—that last one's a good example of a lighthouse strategy, right? They've gone after the bigger insurance companies, and then you get that social proof and—

—and then you go on down the long tail of insurance.

And I think sometimes people think that you have to be from a given market to do a lighthouse strategy. Maybe there's someone sitting at home and they're like, “If only I worked at this company, I could go do this.” And it's like, no, the reality is: go build a relationship.

5. Every Big Company Eventually Deploys Both Strategies

Yeah. You know, I see you laughing because I know you like to say, “Go build a relationship with your customer.” Go find someone and show them, “Here's an earned secret. This earned secret is that AI can help your business, or technology can help your business, in this way,” and work with us on that front.

I'll also say that every small company wants to become a big company. I don't know too many very large, successful companies that at some point in time haven't deployed both strategies. You might start off with land-grab, but then you mature and have a lighthouse strategy, or you start with lighthouse and then get big enough that you can go broad into land-grab.

So I think for founders, when I get this question early on—

Do what makes the most sense for your business right now. What does that mean? Go out and talk to customers. Find out where the earliest and easiest sales are and pursue that strategy. It doesn't mean you're completely punting on the other one; it just means come back to it.

And in both of the last companies that I worked for, both Moroi and Samsara, we started with land-grab. But as soon as we matured and started getting up into enterprise, then what do you do? Well, you verticalize. All of a sudden, it's, “Great, who are the top 5 transportation companies? Who are the top 5 warehousing companies? Who are the top 5 public-sector companies?” Then you want to go take those down.

You can morph into a lighthouse strategy. You just want to do what's most efficient and most effective for the stage of the company you're at.

Can you talk a little bit about one of those key markets that you unlocked when you went from land-grab early to lighthouse in a given market? How did you set up that team? Or was it just you—the founders—going into this new market? Maybe a little bit about some of those deals that you closed. I'm just curious how this played out with the sequencing.

Well, I think at both Moroi and Samsara, the sort of earliest example of lighthouse was when we verticalized. In both those instances, it was basically into public sector. At Moroi, we were going after school districts.

Interesting, because that was low-hanging fruit: anybody who's ever sold to school districts knows that they all talk to each other and know each other. You want to find the biggest school districts in each state, and if you can take that down, every school district underneath them asks, “What did that one buy?” Great—all of a sudden the social proof is there.

Now, why use a lighthouse strategy in, say, school districts, or in Samsara's case, when we went into public sector—when you started selling to cities, counties, and states? Why shift? Because the sales motion is fundamentally different, right?

The sales cycles are different, the way you sell and the decision-makers are different, and the way they procure is different. Asking the same sales team to shift from selling to a mid-market customer or an enterprise customer over to selling to a city, a county, or a school district—it's just different. That's a point where you might want to shift and say, “Okay, great. Once we're verticalized, we want to shift to a lighthouse strategy.”

What would you say are the differences between great sellers in lighthouse models versus great sellers in land-grab models? Are there any differences from what you saw, maybe when you're opening new markets? Is there a profile that was most effective?

It's always difficult to generalize. I think in a true lighthouse strategy, and when I envision lighthouse, it's like, hey, we're going to go after the financial sector.

Here are the top 15 accounts in finance, and here are their logos. How many can we get into this quarter, next quarter, next quarter, right? That's a lighthouse strategy.

Generally, you want more seasoned enterprise sellers that know how to work within those accounts. They understand the sales cycles. They understand the procurement cycles.

In more of a land-grab strategy, where you're just saying, “Hey, we have the best technology. We're replacing this workflow. We're replacing this product,” you just want very aggressive—hire for attitude and aptitude, right? You can go earlier in career. You just want those people to get out there and hit as many of those customers as you can because, at that point, it's like you're hitting a big market and you just want to stack wins as fast as you can.

Yeah. And my unsolicited advice to any early-in-career seller or potential seller right now is that there's never been a better time to work at some of these companies in our portfolio.

That's absolutely true. It's a super fun time to be in the market.

Yeah. I wanted to ask about maybe a third kind of selling or product diffusion that we haven't talked about, which is developer, bottoms-up, more grassroots adoption. Is that something that you guys are seeing? Is the idea of the seller becoming—I wouldn't say obsolete—but, for a particular kind of product, just less relevant now?

Like a developer saying to their CTO, CIO, or whoever, “Hey, this is great. Let's just get this,” and there's less of a sales motion needed?

Yeah. I guess definitely not. There's a bunch of PLG that's still happening today. I think people are buying things in a consumer fashion all the time, and I think that there are new buyer behaviors being discovered. Of course, we were big investors in Cursor, and everyone saw how that played out, and there are a bunch of other examples of this.

However, if I take a giant step back and talk about where we are in this current cycle, I wrote this long piece called “Trading Margin for Growth” about 1 or 1.5 years ago, or whatever it was, talking about the cycle. If you think about why, basically, in the last 12 years before 2024—or 10 or 15 years before 2024—you saw so much PLG, it's just kind of where we were in the software innovation cycle.

A lot of the big cloud platform businesses—if you think about CRM, HR, IT, and security—a lot of those big platform businesses were founded in, call it, the 2000 to 2008 or 2010 period. Those businesses went out and solved the big platform opportunities.

And so the only way to really break in at the enterprise—whether enterprise sales or mid-market enterprise sales—was to build some sort of wedge product, wedge in with this product, and say, “Hey, I’m going to solve this part of your suite for you,” and then try to expand over time. This land-and-expand model became super in vogue, but it was really based on where we were in this adoption cycle.

There were, of course, other people who said, “Hey, I want to go build a new CRM. I want to go build a new HR system. I want to go build a new ITSM system.” But the reality was that going from on-prem to cloud was a big enough shift for people to switch to something new. Going from cloud to cloud for CRM, though, I don’t care if the button is green or blue. I don’t care if there’s one little feature difference. I’m not going to switch.

6. Why Now Is the Moment to Sell Big Software Again

You can compare that cycle, where we were looking at everything for the last 15 years—which was all PLG, all the time—and it’s incredible compared to where we are now. There’s this crazy kinetic energy inside of companies where they’re saying, “Hey, it could be something as fundamental as CRM. It could be as fundamental as HR or ITSM. We’re now looking at a different way of doing business entirely.”

This is not a skeuomorphic, one-to-one replacement—green to blue. We’re now thinking about how humans are going to be doing something completely different and way more high-value. We’re going to be doing way less of the same kind of mundane, rote work, and instead agents are going to be doing that. That’s the opportunity right now, and it’s why, instead of talking about—of course, we’ve got to talk about PLG and all these other sales models—there’s a moment right now to go sell big software again and to go sell platforms. It’s because of this moment, and I think people need to be studying the models from 15 years ago of how people built this and the ecosystems around it in order to have success.

Yeah, I think that’s right. I will say that the consistent trend, as long as I’ve been doing this, is that every year and with every technology transition, buyers become more and more educated. The buyer today fundamentally has a better idea of what they want than they did 5 years ago, 10 years ago, or 15 years ago.

That does lend itself more toward, if you can hit that buyer when they’re in decision mode, you’re going to have a better chance. It doesn’t necessarily have to be PLG, but it can be more self-serve. It should be an easier sell than it was 10, 15, or 20 years ago, when you had to take them on this entire education journey: why you need this, how it works, and how you’re going to use it.

They’re just so much more educated now on what they want to buy. Your job is simply to convince them that your company is the right solution for that.

Amen.

Yeah. I guess the lighthouse definition just gets pushed ever outward, or you just have to keep conquering new territory. I’m curious—I assume a company just can’t stay a lighthouse forever. You even alluded to this, Andy. What’s the average amount of time that a company can chew off those bigger logos, and what does that transition moment look like?

Yeah, theoretically, you could, right? If you were a company dedicated or committed to a multiproduct strategy, you could keep coming out with new products and keep going after more verticals. You could theoretically do that, and I think there are probably some examples we could come up with of companies that did that.

But, in general, if you start with a lighthouse strategy, you’ve built the social proof, and you’ve gotten these big names, then what you want to do is run the category underneath it. If I’ve gotten the top 5 financial companies in the world, I want to run down the list after that.

That fundamentally becomes a little bit different of a sales motion. You’re spending less time with the huge organization, the big logo, selling, and you’re spending more time—less time on the social proof and more time on, “Hey, here’s a reference if you need it. Otherwise, this is why my product’s best. Buy it.”

Yeah, and to Andy’s point, there are certain companies that actually do just stay lighthouse the entire time. The best example might be Applied Intuition in our portfolio. There’s a very set number of people who are buying that kind of autonomous software, and a certain number of car manufacturers and so on and so forth in the world.

Not to say that those are the only people they can sell to, but these are finite markets, and so you then have to treat every one of these with immense care because they are huge ACV opportunities. They’ve obviously—I think they’re arguably the best in the world at doing that. So, yeah, that’s a good example of that.

Why would a founder misjudge what game they’re playing? How have you seen founders misjudge whether they’re doing lighthouse or land grab? I mean, it sounds way sexier to sell to JPMorgan Chase than to, you know, Morgan—[laughter]—Chase.

I think the biggest mistake I see founders make at an early stage, honestly, is spending too much time trying to figure it out. They spend too much time on the strategy. Strategy is important, but you should spend 1% of your time on the strategy: pick it, and then spend 99% of your time trying to execute.

Rather than sit back and say, “Well, should we do lighthouse or should we do land grab?” get out, talk to your customers, figure out which ones are willing to buy your product and the features and services that it delivers today, and then chase that path.

There are no bonus points for hard-earned revenue. You don’t get extra multipliers on your revenue if you get the big logo or something. Go after the customers you can, and then constantly improve your product. After the first year, if you’ve hit all your revenue milestones, you can look at it and say, “Could we be more effective doing this?” Maybe. But don’t spend too much time in analysis-paralysis mode.

Yeah, totally agree with that. I totally agree with that. Joe, you had some fun questions for Andy. I have a lightning-round question.

Lightning round. Lightning round. I’ll see what other ones I can come up with off the top of my head. The first one is maybe the weirdest place you ever closed a deal.

We’ve had some customers who have taken us to some funny places. I’ve closed deals on fishing trips. I’ve closed deals out at shooting ranges. I’ve closed deals at ballparks. I think those are all unique—anywhere that wasn’t a meeting room.

A pair of Chili’s. [laughter]

Probably over the years—

Over a couple million?

Dollars, certainly. At Samsara, we’re selling to logistics and transportation companies—truck yards and that kind of thing, sanitation sites. There are some—

When you’re doing land-grab motions, I think the permeating theme is just to be willing to go and sell wherever. Andy, if you could go back and tell yourself one thing when you were building out these teams, or early in your career, what would you tell yourself?

Early in my career? This is the advice I give a lot of people early in their careers, and it was a mistake I made early on. The only thing you should really be focused on when you’re starting your sales career is finding the best company you can possibly find to work for.

I made this mistake early in my career. I was chasing where I could make the most commission, where I could make the most money, what the hottest technology was, and where I could get the biggest title. At the end of the day, none of that matters. What you want to find is the great company that’s going to grow. If you do that, it’s like a career elevator: you will grow with the company.

But you can’t let your ego get in the way. Don’t say, “I want a director title,” or, “I want this big of a base salary,” or, “I think I can get this much of a commission rate.” Just go find the best company you can work for.

Totally agree. What’s one role you think companies should hire for earlier than they normally do in the sales world?

It really depends on the company and, specifically, how comfortable the founders are. If you’re a founder who’s very comfortable with sales, you can wait longer to hire a sales leader and that kind of thing. So it’s a little bit of a generalized question, but I would say sales operations is probably one that I see companies waiting a little too long on.

I’m not a proponent of standing up a gigantic revenue operations organization.

And it can be literally one person, but you need somebody who every day is thinking through territory alignment, named lists, commission schemes, setting a sales constitution—all that kind of stuff becomes really, really important. When you get into scale mode, you want all that stuff largely figured out. You don't want that stuff to become speed bumps otherwise.

You want somebody thinking about that, and it's generally not going to be your sales leader, because they're thinking about, “How do I hire the next person? How do I bring the next deal on?” So I'd say sales operations or revenue operations.

Yeah. Maybe one sentence or two sentences on how you think about what percentage of sales teams at the early-stage companies you're at should be hitting quota—

—and, like, sales comp thinking.

Oh, 100%.

Yeah, 100%. Well, I think you have some interesting comments about basically trying to keep them low, get everyone kind of rabbing and—

I mean, listen, I think in the early days, sales teams run off of momentum, right? You want to hire winners and give them a chance to win. So, yes, you want to be able to bring people in and set reasonable goals. It's got to be profitable for the company. The unit economics have to work. You can't change the math.

At the end of the day, if you're an early-stage company and you've got a great product, you want to hire the best possible sales talent to get that product or solution out to market. Yes, and the way you do that—the way you attract those people—is to give them a chance to hit quota.

Totally.

So, yeah, I think some of these companies today where 40% or 50% of the team is hitting quota are probably doing themselves a disservice. Either their quotas are too high, or their hiring profile is off.

Especially in the early stages, cost of sales isn't as important, right? When you're a public company and you've gone out and conquered your market, nobody looks back and says, “Gosh, 6 years ago, your cost of sales was really terrible.” Nobody cares about that. What they care about is: Did you get on a path where you could be successful?

Well, I think something that's cool about this conversation is just how timeless a lot of the wisdom is. It just seems like these frameworks and ways of thinking about the industry are pretty consistent throughout the different software cycles and eras that we've seen.

Anyway, Joe, Andy, thank you so much for joining us. This was great, and we're excited to have you guys back on.

So, yeah, got the GOAT. Thanks for having us.

Thanks, Andy. Fantastic.