Episode Transcript
[00:00:00] Speaker A: So we essentially merged both pricing models and simplified them so that they were essentially on the same pricing model. And what that did was it allowed our customers to choose the product that fit fit them best, not the pricing that fit them best.
[00:00:15] Speaker B: Yo, Mike Chek. What's up, everybody? You're listening to the street pricing podcast, the only show where proven SaaS leaders share their mindset and mistakes in pricing. So we can all stop guessing and start growing. Enjoy. Subscribe, and tell a friend. Now, let's break it down with your host and sought after slayer of bad pricing, Marcos Rivera.
[00:00:38] Speaker C: What's up? And welcome to the Street Pricing podcast. I'm Marcos Rivera, author, founder and pricing coach. And today's guest is someone who I would love to have on this show every time I do it. He has a rich background. He comes from an operator background. He's been in multiple SaaS companies, also as an investor. He's currently a partner with Bluestar Innovation Partners. Welcome Cameron Berrigan to the show, man.
[00:01:02] Speaker A: Thanks, Marcus. I'm glad to be here.
[00:01:03] Speaker C: Awesome, man. Good to have you here. I've been trying to get you on here for a minute, man, because you have a ton of knowledge to share. But first, why don't you tell everyone a little bit about you and what you do?
[00:01:11] Speaker A: Yeah, absolutely. So you mentioned it that I'm a partner at a private equity called Bluestar Innovation Partners, where I receive the go to market practice for our operating team. Specifically, and for context, Bluestar is actually a private equity that's essentially run in all its most senior roles by people that are founders or former SaaS CEO's. So we take a very kind of operator forward approach, which has been a really cool experience for me to get to see kind of both sides, but also be on the investment side, but through an operator lens. So that's been just a ton of fun, especially after spending 13 years in the SaaS industry after my MBA. No.
[00:01:48] Speaker C: Beautiful. Beautiful. And that's another reason why I'm such a. I think we connect so well because I was also an operator at a private equity firm. And that operator lens is so important. It brings a lot of reality to decisions and the implications of those decisions. So I love that, especially when it comes to tricky things like monetization, pricing, packaging and all that. Right?
[00:02:09] Speaker A: I think we're going to get really.
[00:02:10] Speaker C: Deep behind the scenes on that one. For me, I'm really interested in knowing a little bit more, just thinking through your investment thesis and how do you guys look for the right fit for your firm? I think makes a lot of sense.
[00:02:23] Speaker A: Yeah, I mean, that's a great question. I think, like I said, we're super operator forward. And so because we have that mindset kind of start there, we bet on people first and foremost. We bet on founders that have built something that's really special and we bet on folks that have the right kind of mindset that want to scale to the next level. And so there are a couple of kind of core elements of our investment thesis, but one of our big things is payments. That's been a big part of every aspect. We do a lot of vertical SaaS and payments is a natural kind of organic piece that gets layered into that. But then the other big pieces are we've got pretty strong m and a prowess to help our customer or help our portfolio companies bolt on additional products to expand their platforms. And then the last piece is really around go to market. And that's where I spend a lot of my time, obviously, to help ratchet things up as they invest more money into those organizations to help them accelerate on the go to market front. Got it, man.
[00:03:20] Speaker C: Betting on people that go to market motion, making sure you have the right fit m and a, all those big things, payments. I mean, that makes a ton of sense to see why you guys are so successful. But are you ready to get street with me today on pricing?
[00:03:32] Speaker A: Let's do it, Marcus.
[00:03:34] Speaker C: Terrific. Right. So a quick roadmap for everyone here. This show is based on the book street pricing. So we have a rewind, we have a play, and we have a fast forward. Right? So rewind is all about the pricing story. A struggle, a success. Let's learn something from a real pricing change and then we're going to bring it back to the present day with play. We're going to talk about some hot topics and what's working or not working with pricing, and then we're going to fast forward into the future.
[00:03:58] Speaker A: So what's next?
[00:03:59] Speaker C: What's next around pricing?
[00:04:00] Speaker A: Then we're going to wrap it up.
[00:04:01] Speaker C: With my favorite question of all times, which we're going to learn a little bit about Cameron and his favorite jam growing up.
[00:04:07] Speaker A: All ready to go? Let's do it.
[00:04:09] Speaker C: All right, man. Cool. So let's start off with a pricing story. Please share with me. Don't leave out anything on the steps you took or if you maybe had a few trips along the way. Those are great learning moments.
[00:04:21] Speaker A: Go right ahead, man. I'm going to reach way back into my past for one of the earliest pricing situations that I had to kind of work through, and I own pricing now at three different companies, SaaS companies, before moving into private equity. And one of the first ones I was faced with, it was a real challenge. As I mentioned, I've worked a lot of VC and PE backed companies, and in the PE world, obviously, a big part of almost any play you run is that you're going to have to do a fair amount of bolt on m and A. And so I've been part of 38 different transactions across those portfolio companies that I've worked at over time. And so one of the things I was getting acclimated to was how to drive a commercial integration of new acquisitions. And my first early on experiences with this were all around ancillary products that were kind of attached products around a core product. And that's a pretty simple problem to solve. You're able to take an existing pricing structure, usually simplify that a little bit, and it's easy to kind of layer on top. There's the question of bundling, which I want to talk to you more about later, but even without bundling, you can do that pretty easily. The problem or the situation we were faced with in the example I'm talking about right now was basically us acquiring our way into a down market version of our core product. And that's a very different problem to solve. And so essentially what we did is we had the market leading product for enterprise and bin market, and we purchased the SMB market to basically bring that into the fold. And we thought initially we could solve that by creating great sales, swim lanes and lead routing to ensure that customers of a certain size and scale were going to that down market player. And obviously, the inverse is true for mid market and enterprise. What we found that didn't work. The market was voting with their feet and they were essentially finding their way to the company that they wanted to, to the product that they wanted to. And in some cases, they were actually, we were selling against ourselves and we were finding ourselves in a situation where there was channel conflict. We were actually seeing ourselves negotiating against ourselves, eroding our own pricing, eroding our own margins. That was kind of the challenge that we were facing.
[00:06:40] Speaker C: It's not solo to you guys. I've seen other companies trying to make the same move. One in particular bought a company up in Canada, down market player. They picked them up and that that same channel conflict started happening in the early days, too. And we took, actually took a little while to resolve that as well, to untangle that web. And so I'm curious, how did you, how did you start sniffing that out, did you, it, was it from deal exceptions? Was it over discounting each other? Was it was the win rates were changing. How did you, how did you detect that?
[00:07:11] Speaker A: It was interesting because it was one of the scenarios where, you know, there's different ways to do kind of a commercial integration, but we basically parked this acquisition off to the side and ran it in parallel. And the first step we took was starting to merge lead pipelines and then basically rationalize those pipelines and then redistribute them back out to the company, to the product that we thought made the most sense. And that was how we tried to be the arbiter of which customers were going to get routed to which product. But as I said, the market goes to their feet and they were finding their way into reps at the different company and they were circumventing that lead routing process. And so, you know, just a little bit of naivete on our part to assume we could actually control that. And that's, I think we had to learn an important lesson there.
[00:07:55] Speaker C: It's interesting how water flows, it'll always find it's those cracks in ways that it wants to go to. Right. So I'm really interested. So now that you found out that, uh oh, this triage thing that we're trying to do here in the middle is not working, what did you do next?
[00:08:09] Speaker A: Yeah, so I think at a certain point we said, hey, there's a degree to which we can influence this. We have to create an environment in which we're making structural changes that are, we can't determine exactly where a customer is going to go and what their evaluation processes of software. In fact, we need to let them figure that out for themselves and we need to support them and allow them to educate themselves along that journey. But structure things in such a way to where it makes sense for them to choose one path or the other. And from what we saw, the biggest thing that we could solve to actually make that work was to rationalize pricing across both products. And so that was the first thing we had to go tackle to make sure that we got that right. And so as we dug into that, what we found was, hey, we essentially did, not to get too geeky on this, but we basically did some heavy kind of cluster analysis in terms of where we saw customers coming in on both sides with both on the enterprise mid market product and on the SMB product, and saw what were the standard price points we saw for certain kind of unit ranges, which was the big value metric or pricing metric. And we were able to run a couple of tests to see what was the price sensitivity for the SMB player. How much further could we nudge that up? And with that data, we ended up creating some breakpoints where we said, hey, what if we put the SMB and enterprise market product on the exact same pricing schedule as the SMB product, but we create a higher degree of gradation to where it's smaller tiers on the lower end for all products. But as you get bigger and bigger and bigger, the price jumps get bigger and bigger and bigger. So we essentially merged both pricing models and simplified them so that they were essentially on the same pricing model. And what that did was it allowed our customers to choose the product that fit them best, not the pricing that bit them best.
[00:10:02] Speaker C: That is genius there. And you're talking to the biggest pricing nerd of all, right? So you can get nerdy with me, like, all day long. Don't let the hat fool you, man. I love this stuff. Right? So the clusters are a really great way to start detecting the patterns, right? And I think those patterns are going to what helps you draw that line? And I call this harmonizing models. Right? So you take the two models, you harmonize it into one, which allows customers to jump on a spectrum and choose across a spectrum versus this or that, very stark differences. And so it makes the decision process a lot easier. It also makes the upsell motion interesting, too. So I'm curious to know what happened when you created this sort of blended, harmonized model.
[00:10:40] Speaker A: Yeah, I think what we found was, again, I think the testing here was really the big thing with the SMB player to say, hey, what is price sensitivity? How much further can we push that up? And within which segments of unit count, which was, again, that metric that we were keying on, has the most of the least price sensitivity. And so essentially what we found was based on how we merged, or to use your term, harmonize, the two models we ended up finding was channel conflict completely disappeared. We got to a place in the background where we trained the sales teams to where they actually all could sell the exact same products. That took time, obviously, but with that happening in the background, what essentially it became was, hey, you come in, you talk to one sales rep, you look at the products, they do discovery to help understand what the right prescription is in terms of product, and they guide you to that product. And if you want to look at the other product as well, you can do that, but you're not going to make a decision based on one being less expensive than the other, you're going to make a decision based on what's going to best fulfill your use case. That was not just a win for the company, it was a huge win for the market, because we weren't trying to do something artificial anymore, but we were allowing them to choose the path that worked best for them. And we also made it work on our side from an economic standpoint. So it was one of those scenarios where it was an everyone win kind of situation.
[00:11:59] Speaker C: I love it, and those are rare. You have to fight for those in many ways. Right? You do. I love that a lot, because I think it does set the right tone from the get go. Right. If you make it easy for the client to make decisions, I always say the first question on a customer's mind when they see a pricing page or they see some pricing is, please don't make me think so hard. Right. Or the first statement I would say, right, don't make me think hard. Let me make this decision without a lot of brain power and cognitive cycles to try to find what's gonna work for me. And I think you took that to the forefront of this whole decision making and said, let's let them make the best decision for themselves possible. So you made it clear across the spectrum what each of these things do, what problems they solve, who they're for. That kind of allows them to go in and make that choice themselves, and by the way, evaluate different choices and say, I'm kind of in between these and let's see which way I wanna go. I think that's a key thing there. Play this a little bit forward. As you're seeing now customers come in, you're seeing the channel conflict completely go down. And now that the model seems to be working, what are some of the signals that you're like, hey, I think we need to do this more. We need to keep iterating.
[00:13:08] Speaker A: Yeah, I think there's two things that allowed us to build on that. When it's your core product and you have ancillary products, if that's not working, you can't start to think about tier two, tier three considerations in terms of other attach rate products and things like that.
Once we got, again, to use that word, harmony there, we were able to say, okay, great, the core product squared away. How do we start thinking about other creative solutions in terms of creating bundles that we can sell, to attach the other ancillary products, to not just the enterprise and mid market product, but now also to this SMB product that was new to the ecosystem, and was just now having access to those ancillary products. So we're able to look really seriously at driving up ARPU for that product as well. And that was a big difference maker because that was a product that was in terms of its maturity stage and its like maturity lifecycle was just earlier stage. And they hadnt really looked historically at attaching those ancillary products because they didnt have them. That was the big thing that we built on from there. So that was kind of .1.2 then was they also hadnt really seen annual price increases.
That was something that, because we reached a point of stability, we now had the opportunity to do that too. And so we were able to come in and capture a price increase on that product as well. Obviously, that's always great because it goes straight to your bottom line and that worked really well for us.
[00:14:35] Speaker C: It's a pretty common lever too, that from a private equity perspective is pulled pretty quickly. I call that very low CAC revenue coming in hits the bottom line directly. That's fantastic because I think the big lesson for a lot of folks thinking through here is how to help customers make these decisions, make it easier for them. And if you're finding that you're forcing them to go one way or the other, or if you're stepping in and trying to help force them one way or the other, chances are they're going to find their own path anyway. And you're introducing a lot more friction than necessary. If you can give us like the one, the one takeaway from that story, what would you tell another SaaS operator out there?
[00:15:12] Speaker A: I think if you feel like you're trying to contort your business and you're trying to do something unnatural or make the buyer journey unnatural, you're doing something wrong. It's going to take more work to try and orient around the way the buyer buys and simplify things for them. But if you do that, you're going to find a way to win for them that's going to allow you to win as well.
[00:15:32] Speaker C: I love that a lot, man. I hear a lot and see a lot of just literature on keep it simple, simplicity. Keep it simple, but keep it natural. It's kind of what you're saying. It's a natural decision making process. I think that that's a big lesson for a lot of folks to reset and keep that in mind as they're thinking about their pricing and packaging. Phenomenal story there, but there were a few things at the end of that that I think will help us leap into present day we'll be moving from rewind to play. You mentioned attach rates, you mentioned annual increases. And so I'm thinking about as your mind a viewpoint from an investor and looking at how do we create value and grow these companies, right. I think a very big one, this goes back to my Vista days as well, is how do we take a product that maybe is sold here and another one that sold there, but there's like obvious synergies between them or there's obvious, you know, ways that that two plus two is five and how do we create bundles and how do we, you know, increase attach rates where it makes sense. Now, one big thing I always look out for is selling bundles for the sake of bundles is usually not a good strategy. Typically the bundle has to either solve the use case greater, either also lend some other types of scale, which is your ability to either roll out faster. And another one is, well, now that we have these two things in one, we can actually see and unpack insights that we couldn't before. So there's lots of those things I think great bundles give you. But just thinking your perspective on bundling and the private equity, are they getting it right? Are they getting it wrong? What's your point of view today on that strategy?
[00:17:03] Speaker A: Yeah, so Marcos, I've known you for a little while now, and I think we've had some interesting conversations on this over the last couple of years. I think that forget private equity for a second and let's just look at SaaS. Generally, when I look at SaaS companies that are multi product, I think that we're so often trying to optimize for a distinct product, PNL. And sometimes this is the way that we're organized internally as well. If different people have different ownership of different KPI's, what I find is that it is really difficult to get make a bundle work in a SAS environment. And oftentimes it's because we have trouble getting in our own way internally. And again, in terms of like allowing buyers to buy the way they want to buy, oftentimes they're expecting an economy of scale, but they're also expecting an economy of scope if they're going to be trying to buy multiple products from you and bundling for bundles sake. Sure, I understand that. But there needs to be some sort of an incentive for them to purchase more products from you. And sometimes that needs to be an economic incentive. And I find that this is one of those areas that I see in SaaS company after SaaS company after SaaS company, where it turns into a paralysis by analysis situation that prevents us from actually being able to bring bundles out into the forefront that makes sense for the market because we're oftentimes getting in our own way around individual product line p and ls rather than focusing on what's going to maximize value for the customer, because if you do that, you're going to maximize value for your company as well. And I think that's the gap that I see.
[00:18:33] Speaker C: I think that's a huge gap that you see there, the p and L ownership. So there's a, there's almost a natural incentive or disincentive to bundle when you're trying to guard your own p and l guard your own margins, right? Because if you do decide to put a couple products together and the economic incentive is a big part of bundling, right. Nobody likes a bundle that you just end up paying the same price or more, right? But you know, who takes the hit, right? Who takes that? Who takes that hit? The attribution and all that, right? And then that becomes a little bit of infighting there where we're more valuable than you, but you're more valuable. And so that can be a little bit, I would say counterproductive in that ever. Right.
[00:19:08] Speaker A: When I think of bundle killers that.
[00:19:11] Speaker C: P and L ownership or that sort of internal goal focused of the bundle versus the external goal focus of the bundle can get into the way. I also see where like, not just bundles that completely mismatch like coffee and a hamburger, those things don't really go together. But you think about bundles that may really increase time to value. So if you sell these two products together, you go from a two week ramp up to a six week ramp up that can get a little bit dangerous in terms of a lot of complexity before they get the value. But going back to what you said, getting in your own way, the first thing you have to unpack is a can we create a bundle from an external point of view that's going to solve either this use case better or serve these types of customers better. I always say that every package has a purpose and that includes bundles. If you can define why this combination exists from an economics perspective, you can work off the attributions on the back end.
I think p and l driven pricing can get very dangerous and slippery real quickly.
[00:20:17] Speaker A: Yeah. And I think where I found this to be the most true is where different products have different pricing metrics. And sometimes there'll be a product in the mix that's variable while one is driven by usage and trying to model out. The economic trade offs across those p and ls can get really hard, and it's really tough to, what I, the way I say, to spreadsheet out. And so sometimes you have to make a decision based on just like a logic proof, and you have to believe that it's gonna, it's gonna move, and you gotta test it to find that out. But sometimes even getting to a testing phase can be tough because people are afraid of what that's going to mean again for their product. You know, it's true.
[00:20:51] Speaker C: It's true. One area that I've seen that really can help ease that a little bit, that tension is in most cases, you know, product a and product b. Before you put them together in a bundle, there's always some discounting going on in a and b, especially in larger b, two b worlds. And oftentimes what I say is we're repurposing that discounting as a bundle incentive. And I would actually reduce the discretionary discount. So I would put the bundle together, we'll build in a discount, and then I would take your discretionary, say it's like 25%, I'll knock it down to 15, you know, and I'll just basically saying that the incentive is to get the bundle. And so the value we're giving away in a discount, which I know people poo poo at me all the time about discounting. I think if you use it strategically.
[00:21:32] Speaker A: Enough, it can help you. Right.
[00:21:34] Speaker C: Others say, thou shalt never discount, but I think there's a place for it in the b two b world. That's my stance and I'm sticking to it. But the idea here is if you repurpose the incentive, so to speak, and reallocate those calories, I like to say oftentimes you actually could lift Asp, especially if you're over discounting in some areas. And then that true bundle can actually solve the problem better. I've seen it where you're discounting 40% here, you're discounting 40% there. You put these bad boys together, you give them 15% off for the bundle. Maybe there's a little bit of 10% discretionary floating around. And now you went from 40% off to 25, which is essentially 15% more price.
[00:22:13] Speaker A: Right.
[00:22:13] Speaker C: Sorry for the math craziness there. But you see what I'm trying to do, right, is sort of reposition that. So that's one thing I've seen work out in the bundle, in the bundling world. The other thing, too, in bundles. And I want to hear your point of view on this one? Because this one is, I see folks go back and forth on it a lot.
[00:22:28] Speaker A: Yeah.
[00:22:29] Speaker C: And so I always say that in the bundle, there's a school of thought that you should just marry the metrics together. So instead of charging for X and charging for y, just charge for one thing. Now, I kind of dig the simplicity of that, right, because you're just kind of worried about one thing and it flows, but not all products. Like, it doesn't make sense for all products in my view. And so your comment about usage based kind of really was tickling my mind a little bit. Right. Because you could have a bundle and you could maybe simplify the price and then either flat price for both or whatever, but then you can also introduce the scaling usage metric behind, and I think that's okay. Like, I don't think that's over complicating things, but I want to get your point of view on mix and matching, having more than one metric in a bundle.
[00:23:11] Speaker A: Listen, I think it is really hard, especially when there are, when there are different products where you can't necessarily predict the usage with a high degree of certainty. I think that's where I've really run into the biggest issues. To me, it's this concept that I refer to a lot of as like, you know, there's, we all know of ARR and MRR, but there's, you know, as SaaS companies incorporate more product lines, they generally incorporate some variable product lines. So I call it AVR and MVR, average variable revenue and monthly variable revenue. And so depending on what that variability is, it can dramatically change the economic equation of any customer. And so the sacrifice you'd be willing to make for the more predictable revenue line in a bundle, you have to be able to account for that variability in those variable lines. And so the equation changes based on how high the peaks are and low the troughs are and kind of a sine wave of that variability. And so to me, that's really where it's got to start because you can try to size that and you can get a kind of average, right? And try and use that as your plug to say, here's what the overall economic impact on a per customer on an ARPU basis is. But sometimes that will change over time too, based on market conditions. For example, like travel is down right now. So companies that are serving the travel industry will see, or, sorry, vacation, rental travel specifically. They'll see things that are tied specifically to stays or occupancy. Those things are going to decline where the fixed cost items are going to stay the same. So you expose yourself to some risk there as well. So I think it's hard, but it's a question of not just in period variability, but it's also like seasonal variability and market condition variability and how much you want to expose yourself to risk on those areas.
[00:25:00] Speaker C: Yeah, that's a very good point here on both. And I think the beauty of a bundle is if you can get a product that actually promotes the usage of the other, if you know what I mean. If you're able to get one to the other, that's actually one of my favorite types of bundles there. But I think the analysis has to play out. You're right. If there's a ton of variability, that could get tricky. In some cases, you can have some allocation or entitlement included and then allow them to bolt on more for those peaks and things like that and so on. That only solves part of the problem. You also widen the window to help with a little bit of accountability. So that MVR, you're looking more on the AVR basis, the annual versus the monthly variable revenue. And that way it accounts for some of that noise.
[00:25:41] Speaker A: But you're right. You're right.
[00:25:42] Speaker C: It is tricky and it is hard, man, I could talk about this with you probably all day long, man. So from a bundle, I think the big key here is it's something that's really thoughtful. It's a bundle. It's not something you just slap together, throw it out there and see what happens. But I think you should, if you are seeing some of these signals that, hey, there's some p and l fiefdoms going on and they're owning it. I think as a SaaS operator, as a leader, you should step in and try to reframe the whole reason for bundling and drive a lot more of that because bundles have been shown time and time again to really increase not just ACB, but also retention and also just overall good economics for the business, I think you should focus on it as a SaaS leader out there. All right, man, let's take this home here on the fast forward front, what do you think is next in all this pricing, packaging, growth, monetization? What do you think is the next big wave? I think it's interesting.
[00:26:36] Speaker A: SaaS in general is just reaching a stage of maturity, especially with all this genai stuff coming in. There are things we don't know, we don't know right now. And I think it's an exciting time to be working at B two B SaaS. But it's also a time where things are going to be changing pretty dramatically on the, both the revenue and the expense side of the business as it relates to that. And so I think as we look at opportunities for more efficiency within these businesses, and also enhanced growth levers with higher degree of efficiency, it changes the cap equation for us.
It also just changes the underlying cost and unit economics for product delivery and things like that. And so this is one of those areas where I'd say it's not something that I have clarity on yet, and I think, I don't think any of us do, but I think what's going to be really exciting is to start to read the tea leaves and see how new opportunities emerge, what that means for pricing, because it inevitably will have an impact on that. And I'm looking forward to seeing that.
[00:27:34] Speaker C: Awesome, dude. Awesome. So listen, I actually think that you're right on a lot of those key things. I also look for a number of, as Genai, like you mentioned, starts coming into play, there's going to be, there's a little bit of a struggle. I was talking with some other folks about this too. About, well, is AI making things more or less expensive now? In one way, yes. Summarizing a meeting in 2 seconds is great. And doing some of the other cool things and suggesting things that we do that used to take longer.
[00:28:02] Speaker A: Fine, makes sense.
[00:28:03] Speaker C: Economic hours saved, all that good stuff. The processing power for AI is at this stage of its life cycle still pretty darn high. Now, I expect that to go down over time, just like Moore's law and everything else, right? Things will start getting cheaper later, but we're at this interesting stage where the, I think discovery and adoption cycle is much faster than everything we've ever seen before. I think the previous one was like Instagram and TikTok and how quickly they got attraction.
[00:28:28] Speaker A: Right.
[00:28:29] Speaker C: But also how that marries with the cost. I think what that forces, in my view, is very targeted use cases of where there's obvious value and where you can monetize it. And then what'll happen is it'll just start expanding from those as the cost curve comes down.
[00:28:46] Speaker A: Right.
[00:28:46] Speaker C: So you're going to see a very quick, I would say sprint up, and then it's like, uh oh, okay, yep. Let's make sure this seriously adds a lot of value and we can point to it and understand it. And then it'll slowly, the cost curve will start to come down and then we'll start seeing more proliferation. So there's this like little bit of a, you know, kind of up the hill slowness I would see. And then it'll start ramping up again a lot faster. So let's see if that actually plays out from that perspective. But man, you came and you dropped a ton of great knowledge today, I think from your operations review from your investor view, like all those big things, I think a lot of SaaS leaders can take a lot away from you. So thank you for coming on the show and getting street with us. Now, one key thing and one last question I have for you.
[00:29:27] Speaker A: Are you ready for this one?
[00:29:29] Speaker C: Let's get to know Cameron a little bit better.
[00:29:30] Speaker A: I need to know what your favorite.
[00:29:32] Speaker C: Jam was growing up doesn't have to be nineties hip hop, but if it is, bonus points.
[00:29:36] Speaker A: Cameron. Yeah, I'm not going to go the hip hop route. I did grow up in LA, though, and I grew up surfing. So a non negotiable was you had to like Sublime and so I grew up really liking. Yeah, yeah. So I really, one of my favorite sublime songs is probably the most popular one. It's Santeria, so I know not far from you, right? So I imagine you can identify with this one a little bit.
[00:29:58] Speaker C: No, some of my best friends are surfers. There's nothing wrong with sublime and loving that growing up. I love it and it gives us a little bit of insight on you as well. So thank you again for jumping on here today. And team, you need to take these lessons and apply them in any way, shape or form that you can. You learned a lot of great knowledge gems from Cameron, so please move it forward. And remember, stop guessing and start growing. Until next time, thank you and much.
[00:30:25] Speaker B: Love for listening to the street pricing podcast with Marcos Rivera. We hope you enjoyed this episode and don't forget to like and subscribe. If you want to learn more about capturing value, pick up a copy of street pricing on Amazon. Until next time.
