Pricing: everything you always wanted to know but were afraid to ask, with ProfitWell CEO Patrick Campbell
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Hello, acquired LPs, and welcome to today's episode on pricing, the ever-important and oft-neglected topic. We decided we really wanted to get back to the LP show's roots, tackling a specific element of company building.

We really like telling stories and we really like all the sort of interviews and histories of companies we've been doing. But we do plenty of that on the main show and really wanted to dive into kind of a masterclass in a specific element. I think our goal is by the end of the episode, you're all nodding your head and agreeing, oh my God, I have not paid enough attention to pricing and take some of our guests' practical advice to heart. So...

Who is our guest? Well, we have with us today Patrick Campbell. Patrick is the CEO and founder of ProfitWell, which you may formerly have known as Price Intelligently, which is one of their product names still today.

It is the software for helping subscription companies with their monetization and retention strategies. ProfitWell also provides free turnkey subscription financial metrics for over 20,000 companies. And prior to ProfitWell, Patrick led strategic initiatives for Boston-based Gemvara and was an economist at Google and in the U.S. intelligence community.

Patrick and his company have particularly keen insights on SaaS pricing, as I mentioned. But with the thousands of companies that they've worked with, they have tips that can work for just about anyone. So ProfitWell is a really interesting company and also a great example for all the bootstrappers out there of a very successful bootstrap company. They've rapidly grown. They do over $10 million in revenue. And so if we have time, I think we can dive in a little bit to that topic as well. So Patrick,

Welcome to the Acquired LP Show. Yeah, thanks for having me, guys. Excited to chat and go deep on pricing. Yeah. I originally met Patrick at Menlo Ventures, hosted this cool pricing and packaging day, and it was something that I felt kind of under-informed about. So I went, and I was just absolutely blown away by the depth of, Patrick, of your thinking on this. And I don't think it's hyperbole to say you're truly one of the best people in the world to dive deep on this topic with us. Yeah, I appreciate that. I think it's

It's one of those things where you start to learn about it and you realize how much you don't know. So there's still a lot I'm learning myself, but I think it's a good day to evangelize the monetization, especially in the subscription space. Yeah. And when did you start Price Intelligently?

It was about seven and a half years ago now. So right around 2012 or later in 2012. And so, yeah, it's been a fun ride based in Boston offices now in Rosario, Argentina and Salt Lake City. But yeah, we started off strictly on pricing, which is, has been quite the journey, especially since when I started the company, it was, you know, just me in a room and I was battling against all these like, you know, white haired consultants basically. Yeah.

Well, and like subscription-based services, like the whole market for them has probably exploded over the whole time that you've been running this company. Yeah, we used to target not just subscription and SaaS companies. Our first customers actually were

some SaaS companies, but then folks like Hallmark, Reebok, a couple of other brands, like very small projects, nothing like major or anything like that. But it was kind of cool to kind of then niche down. And the main reason we niched down into subscriptions and SaaS was one, because of the growth, but also because what we found is for some reason in the world of like retail, e-commerce, et cetera, they have these giant research teams and consumer insights teams. And like Hallmark, there were a hundred people dedicated to market research.

So we looked at it, we're like, they don't need us. Like there's nothing, you know, we can probably find some product, but for some reason, all these folks who are now in SaaS and subscriptions, like they don't know anything about this stuff. And so there's a little bit of a disconnect that we thought, oh, we can double down here and, you know, be a solution within the market. Well, that kind of says everything right there, right? I mean, like Hallmark, Hallmark's a great, great company, actually. Yeah.

in some of my prior lives I've gotten to know them decently well but like they have a hundred people dedicated to market research and pricing and you know a SaaS company that might have a hundred million in ARR might have half a person like to your point that's a huge disconnect yeah if that right yeah

Well, I think this is a really good segue into sort of the first topic is this sort of overview of pricing. So, Patrick, pricing is obviously one of the most important levers in a business. Can you talk about why and why people should be so much more obsessed with it and dedicate so much more time than they are?

Yeah. And if you let me get philosophical for a second, I think what it really comes down to is, you know, if you think about fundamentally what you're doing, you know, in a business and it doesn't matter if you're a subscription company, not a subscription company, if you're a nonprofit retail product, doesn't, doesn't really matter what it is.

you've created some sort of value, right? And that value, because we don't trade goats for wheat anymore, you're ascribing some sort of number to it, right? You're saying, hey, this value is worth $10 or this value is worth $100. And so at the end of the day, when you think about your business, basically everything you're doing is driving a customer to a point of conversion where it's justifying the product or the price, the value that you're putting on that product that you're creating. And so, yeah,

It's one of those things where I think that a lot of people don't realize how central it is to a business. Now, this is also what makes it complicated. And there's so much analysis paralysis that comes with pricing because it means that sales is involved, marketing's involved, products involved, all these other folks are involved. But what's kind of interesting is that when you then look at it from kind of a, you know, analytical perspective, you start to realize because of that central nature of pricing, you

you basically have a huge impact when you do something that related to improving your monetization. To give you some facts and figures, we redid this McKinsey study looking at acquisition, monetization, and retention. You know, the three big pillars in any business, especially for a subscription business.

And what we found is that if you improve each of those levers by the same relative amount, so if you improve leads by 1% in acquisition, your ARPU or ACV by 1% in monetization, or your retention by 1%, pricing is the number one lever in terms of output. It's by 4 to 8x depending on the types of business, right?

And I'm not going to say that you're still going to probably spend half your budget and half your time, if not more, on acquiring customers, sales, and marketing, right? But I think it's one of those things when you look at the average of 10 to 14 hours a year a company is spending on pricing.

you probably can spend a little bit more time. You know, you pick out your toilet paper and probably spend more time like on your toilet paper and custodial supplies than you on your actual pricing. Yeah, it feels a lot like the typical path for startups is pick something kind of arbitrary just to get started. And that's a finger in the air thing where you're probably underpricing. I would guess people tend to underprice generally, but the first one is definitely underpricing just to get people to try your thing. And then they get

smart after looking at 10 to 100 customers and doing some interviews and then say, cool, we know more. We're going to launch a real pricing model now. And then there's some third checkpoint that's more around maturity. But I would assume between these things, companies go a year really without meaningfully revisiting their pricing. Yeah.

I think it's because of that analysis paralysis that I referenced that a lot of people, they actually, the average amount of time that a SaaS or subscription company in particular takes to update their pricing is actually about 2.7, right around three years.

This is to change anything about their monetization, not just the price point, but packaging changes, et cetera. And that number is coming down, thankfully, over time, which I think is great because, you know, we have so much automation and all parts of growth now versus, you know, 10 years ago. But I think what's really important to point out is that I think a lot of people don't realize the different levers they have with monetization.

Because when you talk to most founders, it doesn't matter. Like I would say up to about 75, 80 million at that point, you know, there's someone or like even half of a person that they're, they're trying to dedicate to monetization. They might not know which levers, but there's at least someone focusing on it.

But up until that point, especially people think, you know, Hey, here's throw the number in the air, maybe do some interviews, these types of things. But it's, you know, figuring out a price point, putting the most expensive tier on the left side of the page, ending the prices in nines, you know, and calling it a day. Right. And in reality, you have your value metric, your add on strategy, your discount strategy, um,

your packaging, your actual price point, and the list goes on of all these different things that influence your average revenue per user ACV. So one of the biggest suggestions I have for people when they're thinking about monetization is start to think about it less about the price point and more about anything that influences the revenue per customer that you're bringing in. That's part of your monetization strategy.

And there's a whole host of things I'm sure we're going to get into to help with that. But yeah, that's the conception that's unlocked this for a lot of people, at least that indecision. Yeah, it makes total sense. One more thing on the sort of high level before we dive in. I've heard you talk before about the startups today and the challenges they face versus competition relative to three years ago and five years ago. Can you share some of that data and why it's so much more important to think about

pricing in this detailed and holistic way you just sort of described versus when you could throw a finger in the air five years ago. The density in the market's a product of our success as an industry, right? Because, you know, when you were starting a business,

you know, now it's probably 20 years ago, if not a little earlier or a little later, your biggest barrier to building a business was the technology, right? To have a website, you had to have a server, right? Which is kind of insane to think about right now, right? No AWS, no Shopify, no Stripe. Yeah, nothing, right? We weren't debating the no code movement, you know, these types of things, right? And I think that

What's happened in the past two decades has been just amazing from if the three of us wanted to start our own brand new companies by the end of the day, we could spin up a server, get a website, start driving traffic to that website. Product wouldn't be great. Product is still hard to build because you have to think of the right things. But what was amazing the past two decades is this cost of production came down. And so we focused so much on just shipping.

But there wasn't a lot of stuff out there, right? There weren't a lot of features. And so it was really easy to know what to ship because you either got lucky or you were kind of shipping features into a void. Now, while this was all going on, all of a sudden you started to see these marketing channels just open up every quarter. I don't know about you guys, but I remember when I first discovered business that, you know,

AdWords were a penny a click, right? And then remarketing ads opened up and then, you know, everything opened up. Well, what's happened in the past few years is we're kind of reaching, you know, costs are still going to go down. Memory and things like this are going to get cheaper and cheaper. But we're kind of reaching a little bit of a flattening, right? Where we

We've figured out all these really cool ways to ship code faster and how to make dev teams productive. But now we're on the margins. The other thing that's happened is the last major marketing channel that's opened up was 2015 and it was Snapchat, right? Which is not really relevant to everyone. And yes, there's been innovation and things like that, but there hasn't been like there was, you know, in the early 2000s, let alone in the early 2010s.

What's happened is we've seen competitiveness go from a place of five or so years ago, you had maybe two, three competitors, direct or indirect, to all of a sudden, if you started a company today, the average number of competitors you'd have in a lot of different verticals that we looked at would be about 15. And they wouldn't all be good. They wouldn't all be great.

But in addition to that, customer acquisition costs because of all those channels, like not just reinventing themselves, that's gone up about 70% in the past seven, eight years. So the customer you got for $100 seven, eight years ago is now 170, 180. The value of software, like unfortunately software isn't as magical. Like you used to be able to put a login screen on a database and you were a God. And now if it doesn't have good design, good support, I'm not even gonna have a conversation with you. What this is all kind of,

led to is you now need a balanced growth strategy. You're still going to spend 50% of your on sales and marketing. Like that's just a fact of like high growth, but you gotta think a little bit more about pricing a little bit more about your retention. Uh, because what we've noticed in the data is you pretty much need to be good at acquisition to just kind of survive at this point from a, uh,

startup fast growth kind of perspective. And in order to actually get those big gains, you got to have some good monetization. You got to have some good retention.

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Well, it's a good place to dive deep as any. So you say good monetization, good retention. Let's dive in on good monetization. So pricing models. You mentioned the website with the three plans, the smallest on the left, the biggest on the right. What's sort of the high-level overview of types of pricing models that a company could elect to use? So pricing models.

Used to be, you know, when you think about most products, right? You know, hey, we have one product, one price, you know, think about like a retail product that we're selling. And then, you know, a lot of the advice in SaaS and software was, hey, good, better, best, right? You should have three plans, right? Not everyone's created equal. And it was great advice for the time. And it's still good advice. But what's happened over the past like two decades is billing systems. I know it's not the sexiest topic.

But billing systems have finally gotten to a place where they're, you know, hey, we can charge on different things, right? You know, email consumption, users, these types of things. I know it sounds like so pedantic right now, but 20 years ago, if you wanted to charge on anything but per user, it was really hard, right? Like, hey, how are we going to measure the amount of engagement? How are we going to measure the number of emails, right?

And it was expensive to measure, right? And so what's kind of cool now is we're in this world where we could essentially charge on mostly anything. What that's led to is most of the new wave, you know, the new wave cohort, like companies started in the past, like five years, let's say, they're using what are called value metrics. So basically, you

Hey, it's some measure of usage or some measure of value. So with retainer, our retention product, we price based on how much money we recover for you. Right. And we can measure that and we can get the customer to agree with it. HubSpot, obviously big B2B example, you know, they price based on, you know, basically the number of contacts that you have in your database because presumably more contacts, you're getting more value. Right.

And so what's kind of happened is you have a couple of models, right? There's like just, hey, you just get the software kind of like the perpetual model. You have a per user or let's just say, you know, a differentiated package, right? So there's no measurement of a value metric, but, you know, you get these features in package A, these features in package B, these features in package C.

There's a pure value metric model, like everyone gets all the features except, hey, there's this, you know, kind of consumption metric in some way. And then there's kind of like a hybrid. On top of all this is there's add-ons and things like that that people can deploy. But those are kind of the four main models. And most people are in the latter two. You know, there's still about 40% of like SaaS companies, subscription companies out there that are just doing like feature differentiation. There's no measurement of a metric there.

those companies are starting to kind of die out. They're mostly incumbents or they're changing very quickly because they have the billing system and the wherewithal to kind of change things up. Yeah. I mean, I think about it as you're talking, especially that last bucket makes me think of Zoom, right? Zoom is like, it's a price per seat, but there are so many add-ons that you can pay for and all sorts of bells and whistles and features. And I haven't quite thought about it, but they must have

have invested a ton in their like billing and customer database technology to be able to do that. Yeah. A hundred percent. I mean, and that's why, you know, the, and I, we can get into billing systems if you really want to partner with these folks. But, um, but that's why what I like to tell people is once you get around three to 5 million in ARR, um, or annual revenue, uh,

You got to invest in a billing system. It doesn't have to be the Cadillac in the market like Zora. All roads do lead to Zora, though. Zoom uses Zora because they need so much flexibility. But I think the larger point there, which I want to point out, is add-ons are one of the most underutilized strategies in B2B and in D2C. And one of the most interesting things is that what you're trying to do from a theory perspective is every consumer is different.

And if we play this out long enough, like there will be dynamism in subscription and SaaS pricing in some way, you know, in the next 20 years. Right. Because, you know, you're we're going to be able to somehow measure your willingness to pay, you know, based on your profile. We're going to measure your willingness to pay based on your profile. And, you know, there's we're already doing this in like inside sales in some ways. Right.

That's a little far out there, though. And even segment-based pricing is tough right now. You mean like unique pricing per user? Based on all the data a company could have on that person, they come up with a one-to-one. There's like one price for that person because we know exactly the value you'll get out of it. Yeah, kind of like the travel industry, right? Now, a lot of people will say, like, oh, it'll never happen because of this or that. And normally those objections come for...

Well, what if they talk to each other? Well, this kind of already happens in enterprise software. It kind of already happens in a lot of our consumer products. And so if you take one step back from there, it's segment-based pricing. So there's a world where you know, and there's definitely some big questions here about measurement and things like that, but you know that the LTV, the lifetime value from that SEO channel customer is

is, you know, so much better than the lifetime value from that Facebook channel customer, right? And so what you end up doing is, hey, well, I'm going to actually increase my price on the Facebook customer because it's just not worth serving them or lower my price because maybe, you know, gets more volume or, you know, whatever the decision comes with the data. Now, where we are right now, just to talk not about the future, but like where we are kind of now is, you know, you can do

different persona based or profile or, you know, however you're measuring your different segments of your customer base with different packages, right? So they might come in with, you know, your base plan, right? And then based on their usage and their use of the product, I should say, you can offer them certain add-ons and then you can offer them the value metric as, you know, they go up, they're paying more. And so all of a sudden you don't have infinite packages that are one-to-one,

But you start to have a lot of permutations of, you know, what people are paying. And that's kind of the goal, right? Because you don't want everyone paying the same amount. I don't want the Disney company paying the same amount as Johnny or Jane startup. Right. And so there's a lot of ways to do that right now. And, you know, in the future, it'll get easier with tooling and stuff like that.

How should companies think then about related to that, the freemium or trial or like the free aspect of what they're doing? I would be shocked if you say anything other than like free and freemium is like a major innovation in pricing, but I'm so curious to hear your thoughts. Yeah. So I think that people, and this is semantic, I like to try to separate it from pricing because I think too many people are

And we were talking about this earlier, like freemium is kind of one of those religious topics, right? But people don't realize freeware has been around forever, not just in software, right? Shareware. There's always, yeah, right? There's all kinds of stuff where you're like, okay, I'm going to give you this part and to get the rest of the chapters, you have to sign up for this magazine to get the Charles Dickens books, these types of things, right? Yeah.

What I like to say is that freemium is an acquisition model. It's not a revenue model. And you need to think about it as a premium e-book, basically. And I think every, you know, not to get out there again, but I think every company is going to have freemium in some way, because if you just think about rising costs over the years, you're going to have to think about it as a premium e-book.

It's going to come to a point where like those e-books aren't working as well as they used to. Content just isn't working as well. And you want to nurture that lead and own that lead. And so I think the beauty of freemium and to be completely and actually honest, I used to write articles of a very anti-free, you know, as the pricing guy. Right. You know, freemium freemium was an innovation because what you're doing is remember, it's about that value. Right.

And some of those customers coming to you who are just maybe higher up in the funnel or they're just maybe not ready for prime time, but they still like like you and they still want to kind of engage with you because maybe they'll want to purchase at some point in the future.

You need something to give them and giving them content. There's so much distraction out there and things like that. And the beauty of freemium is you're basically lowering the activation energy for that lead or that potential customer to come in. They start using the product and then depending on the model you use, and there's a couple of different types of freemium, you either put a limit. So, you know, 14 to 21 days into that freemium plan, they're hitting that limit. So that's like a faux free trial, we call it. Or

Or like ProfitWell, it's like it's forever free or metrics product. And, you know, eventually, you know, in six months or seven months, you find that little button inside there and you're like, oh, yeah, I do. I don't like that this metric's going down. Like, let me get this demo so I can get this product that improves this metric. Right. And so I think that's why I always say like it is part of pricing ultimately because it's a plan. But I think people need to think about it marketing first than anything. And

And what I will say just for some of the folks listening, if you are just starting out and you do not have a top 25 growth hacker, I don't know what we're calling growth hackers these days. I know growth hackers out of vogue. It's become full circle back to marketing. I know. Yeah. But if you, yeah, that's, that's really funny. I like that. But if you don't have that person, you should not be doing free out of the gate.

And someone who's truly that good. We all think we're that good, but like someone who's like the Balfours, the Casey's of the world, just because they're the ones who can actually sustain that. The most successful freemium models that we've seen, they weren't started until like three, four years into the company. What makes them good? I know it's a little derailment. For someone that's like, I guess, never been around an A-plus growth person like that, and they kind of feel like a lot of the people that they've worked with are good. How do you know?

I don't know if I'm the one to answer it, but here's kind of how I think about it. It's an odd discipline to not go in until you're certain. And that's what I found with really good growth folks. So Brian Balfour, a good friend of mine, he runs Reforge. I don't know if you've heard of the growth program. I've known him at HubSpot, Viximo before that, because he's a Michigan guy, but he was in Boston when I was in Boston. And he

When I talked to him about this, I kind of, I didn't pose that exact question, but I talked to him about like, Hey, what makes someone good at growth? And what he talked about was, you know, the discipline not to, to basically chase a bunch of things, right? Like most marketers, if when you really meet them, they chase things, even if they have like a quarterly like plan. Basically what ends up happening is they like, Oh, this is what I did in my last company. Or, and this is the same thing that happens with pricing, right? You know, Oh, I did this in my last company. We need a Facebook strategy.

Oh, it's very different. Right. And so what Belfort will do is he, he does this whole growth loop, right? And that's what most of them do. And they do a ton of research, ton of hypothesis testing. And as soon as they know that this is the thing, they go all in just unabashedly. So this is the Berkshire Hathaway approach to growth. Totally. And then there's a whole, there's a whole long tail, right? Of just like the discipline to run these loops and constantly be running these loops and loops are basically, okay, we're proactively,

pushing experiments every week or every end days or whatever it ends up being. And I think that's like being that diligent about, you know, and I think we're calling it actually full stack marketer, I just realized. And so being that diligent about being a full stack marketer is really hard to find someone. There's definitely more than 25 of those people in the world, but I think it's just in the early days with freemium to bring it back to freemium,

You're just adding distracting leads. That's all you're doing. You don't even know your beachhead customer. You don't know the viral coefficient that you need. You don't know what is the thing that's going to create the network effect. You don't even know if you need a network effect, right? That's really where it comes down to. And most of the time that people are successful at FreeBM three, four years into their business, they know how to convert a paying customer to, or a free customer to a paying customer. And they also know, hey, like we're just trying to open the top of the funnel at this point.

It's a premium ebook. Like we're just trying to open the top of the funnel because we know how to move people through the funnel and we just need more leads. So you mentioned, we don't know if we need a network effect. So the one way that I've always tried to slice, should you do a trial versus should you do forever free is if your product has a network effect or a data moat where the more data that comes into the platform or the more people on it, the better, then you should have a forever free plan to try and get that data.

the value of all that data or all that connectivity. But if it doesn't, and every incremental customer is, doesn't deliver new value for that next customer, then just stick them on a trial and ask them for money after a few weeks. Is that right? Is that how you think about it? Whether someone should do forever free versus trial? So in the context of freemium, yes, but I want to, I want to just clarify, um, I don't think you should do trials anymore. Like at all. There's always exceptions to, Oh,

Oh, no, same way. This is great. Gross generalizations. But I don't think you should do trials anymore because you should do the faux free trial that I was describing. And here's why. So let's talk about Superhuman, Yesware. Let's talk about like Yesware, right? So Yesware was one of the first email tracking products. So you send an email, you can see if someone opens it. Great for salespeople or whatever, right? Yeah.

So what they did is they gave you, and I don't remember the exact numbers, so don't quote me on it, but they said, okay, our target customer, they're going to burn through 100 opens or tracks or whatever they called it within 14 to 21 days, right? So we know that if we give them 100 per month for free, those people who are target customers are essentially going to self-select, right? They're going to get something at that 101st track that says, hey, you got to sign up.

And they're either going to sign up and then you got to deal with churn or retention, right? Or they're going to go, cool, I'm going to wait till next month, which means they probably weren't an actual target customer or a target buyer persona or a deal customer profile, whatever framework you want to use for buyers. Now, if I had a trial, let's say I gave them the 14, 21 day trial, I'm still getting people who sign up who probably aren't ready for prime time to convert. But what ends up happening is that at day 15, all of a sudden I start spamming them. Hey, you got to sign up.

It ended. Can't use the product anymore. Can't use it. And then I have a 14 day drip of trying to get them to convert. Well, that person probably isn't going to go from a non-ideal customer to an ideal customer in those next 14 days, but they might six months from now or three months from now. So faux free trials, what it allows me to do is allows me to nurture that lead until they're ready. Right. Cause they could, they could say, Oh, I got the 14 days, you know, I can't use the rest of this month. Um,

I'm going to sit back. I'm going to start using it again next month. And then they're going to do that for a couple of months. And maybe by month four, they're like, you know, I actually want to use this. What ends up happening is you can start looking at their usage and you can go cool. Anyone who gets over this usage, we're just going to automatically start adding the tracks. Right. Or on day 31, they're just going to start getting those notifications again. They're like, Oh yeah, I remember that. Yes, we're a thing. Right. It puts the onus of conversion more on the user than on the business. Right. So,

And this is from an investment standpoint for you guys when you look at this. You can't look at that first 30 days of conversion in a freemium model and be like, oh, this company is great or this company sucks. You have to look at a cohort of

of those free users? Like how many are converting within a six month window, a 12 month window, a three month window, depending on the business, because that then you're like, oh, wow, there's gold in these hills because they're still converting down, down, down the path. Basically, it makes me remember, you might say this is a little bit of a different dynamic, but

And Zoom, when we did our episode, we talked to Santi. When they were doing diligence on Zoom, they were like, oh man, they have a churn problem. Like all these customers are signing up and then they're churning. But then when they zoomed out on the data, they were like, no, no, they're churning, but then they're coming back. And if you looked at it in a six months, 12 month period, you're like, oh crap, we thought there was a churn problem. There's actually like no churn problem. Yeah, 100%.

Yeah, and that's what's so interesting. Just to make sure I understand the...

faux part of the free trial, you're basically gating on an engagement metric or a usage metric rather than a time metric for the free trial. Yeah. That's why I call it a faux free trial because it's, you know, that hundred visits and that's, that's how you set how much you give for that freemium is my ideal customer profile. I want them to kind of convert in a certain time period. So maybe it's 30 days, maybe it's 45 days, depending on the enterprisiness typically of the

product. And then, you know, you kind of set that usage at that mark. And then obviously within those 14, 30, 45 days, you're doing everything you can to, to get them, you know, to use or get to those, you know, milestones to, to be really invested in the product.

Cool. Well, I like that as a nice bow on sort of how to think about your pricing model at a high level. Now let's get into like actually pricing it and picking numbers. So there's sort of, I'll ask this in a loaded way, but in our discussion of how to test whether you are pricing well, can you just A-B test prices? If you have the ability...

And what I mean by that is the traffic and the completes, 100%. Amazon, they can do a price test for majority of their products in 30 seconds, right? But here's the thing. A-B testing, and there's a lot of stuff that's been written on A-B versus multivariate, one tail, two tail, all kinds of stuff. Go back to your statistics course, right? The problem is

The concept of testing experimentation lulls a lot of us into a false sense of security of, oh, we'll just A-B test it, right? You hear that all the time. Oh, we'll just test it. And then no one ever sets up the test correctly and completes it. We did a study. We haven't talked about this data in a long time because we were really curious because really what we do with the pricing product is quantified customer development, right? We're doing customer research. We're just doing it with a lens of monetization, right? And we're doing it with a lens of monetization, right?

And what we found is like, well, how many people are actually doing any research? And, you know, what we found is that most companies and this this was the gambit of, you know, Johnny and Jane startups all the way to Fortune 500 companies in this data set. Most companies and product organizations and marketing organizations are talking to really 10 or less customers in a non-sales capacity in a given month.

which is not a lot if you really think about it in terms of research. And the pushback we always got was, well, you know, we don't talk to our customers, Patrick. Like we don't do that, but we do AB testing. Well,

Well, half of the data set, zero tests per month, including marketing tests. Like they don't even test subject lines in a lot of cases, right? And I know that sounds bonkers because, you know, the people on this, listening to this podcast, they're probably not in the general, they're more in the elite theoretically. And so what I want to say, like in terms of testing is if you have truly significant and authentic tests, like go for it. I think that works out well, but here's the problem for the majority of us, especially in B2B is

We probably don't have the traffic to get enough completes to even just do a simple AB test, let alone all of the different pieces that come with changing up a price. So if you look at a traditional SaaS pricing page, let's say you got three tiers and you got like five different feature differentiations, that's somewhere around 85 different variations of tests. And so it's one of those things where we just don't even have traffic for AB, let alone the 85. So what we recommend doing is if you don't have that traffic, it's totally fine.

do research, and then that'll kind of basically take the problem space down. And then when you have that output, maybe then you do an AB test or you're not going to have any traffic to even an AB test with the majority of B2B companies. So then you have to do a little bit of a time test and just make sure you're measuring the KPIs. And you'll know like, hey, this has changed things. Maybe you don't know, like, could it have been a little bit better? Should it have been a little bit worse? But you at least know based on tracking those KPIs as you implement things.

And yeah, it's going to be a risk because you're not going to know until you put it in the market. But with enough research, you're at least hedging as much of that risk as possible. And what would you say is a... Well, this is also a super loaded question. We were talking a little bit before. What would you say is a viable minimal sample size for doing that? Oh, there you go. Sample size, right? It's a measure of variance, man. It's super tough because it's not about...

beginning of the trials or the beginning of the freemiums. Because that's the other thing you have to think about. In a subscription or recurring revenue business, technically, you're going to have to track this data all the way through like probably first 90 day retention. And it's not the signup, it's the completes. So it's the actual purchases here. It's not like, hey, this many people click this one and this many people click that one.

It's well, they signed up, they paid us after the freemium or the free trial, and they were with us 90 days. So what I also find is that you, you just slow your tempo down too much.

So, again, going back to the research, to give a direct answer to your question, like depending on the circumstances, you can calculate these things. And there's tons of data. We wrote a book on statistics for SaaS executives. That's what we call it, just to kind of educate like our base. But, yeah, it's one of those things that there's a lot out there to kind of calculate those exact numbers. But that's the thing to think about. It's the completes and then it's the cohort that you have to look at. And that gets really complicated over, you know, a year.

Okay, so we're saying, look, we can't do this ultra quantitative thing because we just don't have enough completes. And it would take a really long time to get all the way to complete for 90 days or even longer. So let's do some research. What's the, like...

Hey, I'm starting a startup. I'm picking numbers out of the air. I've talked to a few customers. I know they want this. They've told me they'd pay for it. We haven't really gotten clear on what they would pay for it. Like what type of research should they do here? What questions should they ask? And how much is qualitative versus quantitative?

Yeah, I think in that scenario, it's going to be almost even if you do some some A-B testing because there's like signal like you can change some stuff up and do see what people click on. And that's signal, right? It's not the whole cohort like I described, but you at least can then make some decisions. And the one thing I will say is that even with multivariate testing and research, you

You got to always understand the limits of your data. I think that's a big deal. Like we were kind of talking about this before where, you know, people, they, they really like to agree with the data that, that agrees with what they think. And then even if the same data set, there's something that they don't agree with, the data was a problem there. Right. And I think it's, you got to know, like, if you're going to make a 10 million, a hundred million dollar decision, you're going to have to collect some, do some research. If you can do testing, you have to do the testing. If you're in the, in the world where you have zoom or Slack or Amazon, you absolutely can do testing, which is great. And,

If you're a startup and you're making a perceived million dollar decision, but you don't have a lot of money to spend on research, like it's okay to be qualitative. You just have to understand the limits and then check back in in three months, six months, et cetera. So, but to answer your question directly, which was around like what type of research to do, there's some models of, hey, put it up there, see what people click.

I'm a bigger fan of just literally going to the human beings that you're trying to sell to and talking to them. And I think this is the biggest misconception is that people are like, well, people aren't going to tell you what they actually are willing to pay.

And it's like, well, that's, you know, yes, you're not going to know until you actually hit publish and you look at some of the data in three months, but there are ways that you can have this conversation that lead to really rich data that allows you to make decisions. And so there's a couple of models that you can use. So I'll talk about those two models a little hard in podcast form to go deep on them. But, um, and then I'll talk about like one caveat when it comes to, you know, making sure that you, you look at this research in the right way. So the two models that we recommend, um,

And this is from an efficiency standpoint. You could go do conjoint analysis if you've heard of that. Conjoint is super expensive just in terms of time and costs. And there are models that get you close enough, at least in my opinion, in my analysis, that costs a tenth of what it costs to implement those types of surveys. But remember, you got two axes when it comes to value of anything. The first axis of value is the relative value of the features or the attributes of that product. The other axis is the willingness to pay or the price.

price. So one tool or one kind of methodology that anyone can use, there's a bunch of like information, Wikipedia articles, stuff like that on this, is something called max diff to look at the value of features. So this is where I go to you and I say, hey, I got these five attributes, or you go to the person who's been demoing or using the product or beta testing the product and say, hey, there's these five aspects of product A. What's the most important

What's the least important? And I can do that on a phone call, right? I can do that scalably through a survey. But the beauty of that is you're forcing them to make a decision. Choose most important, choose least important. Because most of our surveys are terrible. Like everyone hates surveys. And the reason we hate surveys is not, it's not like statistically, they're so good if you do them right.

But we suck. We just suck as operators. And we send these 45-question surveys. We email them to people. And the first question on the survey is, what's your email address? That's a terrible, terrible situation to be in. And so don't blame the survey. Nobody wants to answer that. Oh, my gosh. And just to give you some data, so our price technology software, it's survey-based. We've sent, I think it's actually about 80 million of these things at this point. And so we've looked at this. And if you have a non-compensated survey,

it's got to be less than four minutes, not only because your response rate goes down, but the quality of your response is tanked. So even the responses you're getting, it's people who are like, oh, I want to win that iPad. Yeah, just like click, click, click, click. You know, the click, click, click, right? And really it should be 30 to 60 seconds, which is four or five questions depending on the length of the questions. And if you do that, you can send these surveys like once every three to six weeks. You know, that's what we've kind of found. Now you've got to be careful with like,

you know, there's a batch of people who are always, you know, answering survey questions. You want to always put more people into that batch. Um, but yeah, so max diff is really, really good for like features. The other tool that we suggest using max diff being, which, uh, amongst what you say, your five features, max diff being the highest versus the lower, like what, uh, most important, least important. Right. Um, and that's, and it's important to like follow that, that specific instruction, um,

Rank order doesn't work well because the one and two rank are typically, you know, intellectually honest from the respondent. Three, four, and five, they're just like, I want to move on, right? And there's a lot of signal and least important, right? Because as founders, we always have this vision, right? And as operators, we have this vision of like, this is what we see, right? And we want to go do everything we can to put that vision into place.

If I know that like the least important thing is the thing that I thought our whole centered marketing around needs to be, I probably need to like, you know, readjust or like really dig into the data. Now on the pricing side, what we want to do is we want to take advantage of how people think about value. And as human beings, economists and psychologists have studied this for years, they found we think about value as a spectrum.

We know that this water bottle here is worth less than this computer that I'm on, right? And if you put me in the desert for three days, all of a sudden without water, that value is going to flip. And this is because we've purchased these products before, but also my circumstance, whole host of things.

So we have to ask in the right way. And one of the most efficient ways we found to ask, and again, it's not perfect, but one of the most efficient ways we found is using what's called this Van Westendort model, which is I ask you, at what point is this way too expensive that you would never consider purchasing it? I think Ravel talked about this on our Superhuman episode.

Yeah, yeah. Rahul, yeah, Rahul. Well, you've had plenty of conversations on pricing, which is great. And so, and then at what point is it getting expensive, but you never consider purchasing it? At what point is it a good deal? And at what point is it too cheap that you'd question the quality of it? And that last question is really important.

Especially for any European listeners, European countries or founders typically underprice their products so much. I think there's a little bit of like little brother syndrome to the US in a lot of ways. And also like Eastern Europe, like this Ukrainian company I was talking to, $20 for their product per month and their premium plan.

And I was like, hey, man, you got to up that to like $100 at least. I don't even need to test it. It's just you need to get up there for your premium plan, right? And he's like, I can't imagine because $100 is a lot of money, right? But their customers are all in the US, right? But back to the Van Wissendorp model, the beauty of this is if I go ask 30 people,

I can get, you know, it's not going to be quantitative. I'm not going to make a $10 million decision on it, but I at least understand that my a hundred dollar product and my thousand dollar product, and then I can up basically the respondents to kind of increase the integrity. And the one thing I will say is, is Van Westendorp, the innovation was the questions or were the questions, the calculations, the standard calculations aren't amazing.

Um, they're great if you're just doing qualitative or if you have so many responses, like they really triangulate. Cause those standard calculations, there's something about trying to get like, there's some 40% threshold where you want. Yeah. Yeah. That's the thing you're referring to in the calculation. It just gets, yeah. Just when you do, cause what you do is you just graph the answers to each question and theoretically you find where the intersections are. So it creates this little diamond of like, this is where we should be. But the, the, the calculations it's,

you know, whenever you have a model that theoretically can be used for any industry and any like sales model and all this other stuff, you got to adjust it if you're going to make a larger decision. So like what we did is for our software is we took the questions and that's kind of how we run it. And we have some modifications depending on the application. We took the questions and then we kind of threw out how they calculate it. And we like redid a bunch of stuff in order to, to kind of have our own IP, frankly. And what you'll find just to give you a little bit of a litmus, like

we're our software. We're at the point where it's like plus or minus about 3% of reality. And we check it with like commodities and things like that. Van Westendorp, just standard, you'll probably be about plus or minus like 20, 25% of reality, which again, like if you're making a 10 million dollar decision, that's a little, that's a little much. But if you're just a Johnny or Jane startup, just start out like that's fine. Right? Like just get it out there. Plus or minus 20, 25%. You're, you are in the 99th percentile of either,

early stage startups. Now the one note that I'll make is the most important thing with any data, I would argue, segment, segment, segment.

Do not look at the aggregate. The aggregate day is interesting, especially when you track it over time, but you got to segment it down. And I think the biggest pushback people are, there's a lot of people who are like, you can't talk to customers about pricing. And we're like, well, you shouldn't just talk to customers. You should talk to prospects. People have never heard of you who are target customer base because what should happen when you do price testing is,

People have never heard of you, but are in your target base, are willing to pay the least. And then the people who are, you know, have been with you for 12 months should be willing to pay the most, assuming that they're the same type of person. Almost all the time when we work with companies, it's complete opposite. And people are like, well, people won't pay more. And it's like, well, you've, have you ever tested pricing?

No. It's like, well, you've anchored yourself into thinking that your product's only worth this much because that's what you put three years ago when you started the company. And now all of a sudden, we actually do need to raise the price on new customers to this level. And we need to find a plan to take those existing users and get them to a higher level price. And there's a couple of ways to do that, obviously.

Yeah, before we get into that, because I'm very curious about sort of grandfathering strategies there. Another religious topic. Yeah, I never hear people say grandmothering, but I suppose for gender equity, yeah. So listeners, we're going to put links to both Max Diff and Van Westendorp in the show notes here. I don't know, Patrick, if you have a page on that, or I'm sure we can find some really good blog posts on each.

I'm also going to link to a screenshot of a slide that I have in a deck from you that I think is this awesome matrix of that graph you described. So x-axis is relative preference magnitude. So in terms of ranking what's the most important feature, what's the least important feature. And then the y-axis is the sort of willingness to pay. And so I love this notion that in the

right top quadrant where everyone wants to be, that's your like high value, high willingness to pay. You call them differentiable features. And then when you want to figure out what should be an add-on, that's over in the left where it's not everyone's relative preference, but there is high willingness to pay for it.

Now, if you think about the bottom right, that's sort of your like high value, but low willingness to pay. That's your core feature set. Like you want to make sure that since there's only low willingness to pay around that, that's not going to move the needle for you when you're putting it on as an add on. And anything in that bottom left, you call trash land where there's low value and only in marketing. Yeah.

Not in our output for our product. Don't worry. Okay. Okay. But yeah, if there's low willingness to pay and low value, like that gives you really obvious signal on, oh my God, we shouldn't even be developing these features.

Yeah, in some cases, yeah. So we developed this actually, we just started noticing trends, a lot of trends, right? Where priority support, never like the most important feature relative to other things, like obviously the core aspects of the product, but there was a good group of people who had high willingness to pay for it, like certain segments, right? And so we wanted to kind of visualize, even if we're just not even going to collect data, but just mentally think about it, where do we think our features are and things like that? And the one thing I will say is,

Features do move between these quadrants as well, right? If you think about two-factor authentication, it used to be an add-on. Then it was a differentiable feature. Now, well, it was core. And we're starting to show it up in trash now. And that's something that's important that you're going to have to probably build some trash. And that's why it's a little sensationalist to call it trash. Because everybody just expects it now. Yeah.

It's like, if you don't have it, I'm not even going to consider you. 100%. So like the login screen that would show up in trash, that's the most outlandish feature, right? But like a lot of security stuff has kind of gone around the quadrants. Things like Active Directory, those have like stayed in the add-on world, which is kind of interesting. And then obviously your core features are probably always going to be in core, but it's been interesting to track some of these features over time.

just because, you know, as the market's gotten denser and more features are out there, it's been super fascinating.

Really interesting. Okay, let's return back to you're three years into your business. You've managed to, you know, triple in your first year and then triple again in your second year. Things are going well, but those first customers that were with you, they've been on that same price point the whole time and you want to be nice to them because they were nice to you early. And frankly, you think they might churn because your ICP has changed. They may not necessarily be that perfect customer for you anymore. So you never change the price. That's probably the wrong thing to do. What's the right thing to do?

I want to be careful with right and wrong. But I think, you know, again, a religious topic with grandfathering or grandmothering. Well, let's be gender neutral. I think that, or inclusive, I should say. I think that, here's the thing. It is a really great idea when you are in the

Like everything is terrible stage, which, you know, it always feels that way in certain aspects, but you're in the, like, I'm just starting out and it's a really fun idea to be like, we are never going to do these things. Right. We're never going to hire salespeople. I hear that from a lot of fun, you know, apps. And it's like, well, you know, the mid market enterprise, the people who really like your software. So you're probably getting to hire some salespeople. Right. Even that last year in Slack have sales. Right. But PLG, come on, PLG. It's going to take us the whole way. Hey,

Hey, in certain ways it will, right? Like I think, you know, the secret is always like you really have everything, you know, at the late stage or the growth stage, right? In terms of grandfather and grandmother, it's one of those things where people love to say like we are never going to raise prices on these folks and that's that. The problem isn't from zero to 10 million ARR.

So if you want to be just a lifestyle, I don't want to use lifestyle where we call them indie businesses now, you want to be an indie business, which, which I respect and it's awesome. And if that's your path, like that's awesome, right? It's the new corner store, right? Is, is a software company, which I think is great. Then,

Then you can never, you don't have to upgrade people. You don't have to like force them on new plans. That's totally fine. If you're trying to be a hundred million dollar company, it is extremely rare that you find a hundred million dollar company that's somewhere between 10 and a hundred. They did not raise prices on people and they didn't do it multiple times. Because if you think about it, you have a good market share from zero to 10. You're kind of like scrapping to get the market share. Right. And then all of a sudden you have that market share. You have this existing customer base and

And you're like, well, let's build a new product. It was hard enough to get the first one for these people to buy, let alone the second one, right? And then you're like, well, we'll do add-ons. Well, that can take you a long way, but it's not going to take you the full way, right? And the thing I like to remind people is go back to that philosophy of what price is. It's a measurement of that value. It's the exchange rate and the value that people are getting. Has your value increased? Well, your brand's improved, right?

stickiness has improved, your UI has improved, the actual feature set you're giving away is improving. It's a whole host of things. And so it's less about don't do it, do it. It's more do it in the right way. And so what we recommend, and I can share like a template of kind of like it

it's a bit of a generic like email that we recommend using. Um, but it's one of those things you can apply and it kind of goes through the, the four or five steps we recommend is one do what's called a grandfather discount. And that's basically, uh, you've seen this in a number of ways. It's like, Hey, um,

you've been so loyal. Thank you so much. You've been awesome. You've been with us for four and a half years. You're using this new feature. You're using this feature all the time. We've made you $18,000 over the past year. Like remind them of that personalized value and then tell them, hey, you've been so loyal. We're going to give, we're going to raise prices on everyone new. Not you, everyone new. You're going to keep your existing price for the next six months as a reward, right? And I probably wouldn't go that far and lay it on thick. I was doing that just for effect, but I think that-

That's the big thing, right? And then I think one of the nicest hacks with raising prices is, P.S., if this materially impacts your business or you, if it's a D2C product, please let us know and we'll work something out. And that P.S. is for two types of people. It's for people like me who I'm a bootstrap founder. I don't want to spend money on anything. I don't want to do that. But I'm going to look at that and I'm going to go,

you know, yeah, this guy or gal is right. They've been so valuable. They did add that feature that I really love. I'm not going to be a jerk. Like this is totally fine.

And it's also for people it's actually impacting. So they can email and be like, Hey, cool. And then you can just gain so much relationship points and be like, okay, Hey, not a problem. Not a problem. You know, founder or exec or whomever, um, we're going to give you, you know, we're going to give you three months. We're going to give you actually nine months on that, that grandfather discount. And then if that's a problem still, like you let us know. Right. Cause it's not about like being, you know, a jerk. It's about,

Hey, things cost money. They know that things cost money. Like that's the big misconception is like people don't know that things cost money. And so you just have to do it in the right way. Now, a couple of caveats. If you have a massive TAM, Target Adjustable Market, you can get away with grandfathering if you really want.

I have this debate with Nick Francis from Help Scout all the time because he's so like for our customers. Right. And we gave up ten million dollars because we grandfathered. And I'm like, OK, man, that's cool. You didn't have to like you could have gotten all ten million. But but that's fine because help desks massive, massive market. He can punt on that decision.

Also, with Nick specifically, I've used Help Scout now at four companies, and I'm sure the first one's grandfathered in, but I've stood it up in three other companies now that have gotten full rack rate, so...

Yeah, totally. And I think that, yeah. And I think that that works out well. Right. And that, that it's one of those things though, that these, these don't have to all be mutually exclusive, right? Like you probably would have had that brand equity to use them anyways, because it's a great product, right? Even though you weren't paying as much. Right. And so at the original company, and then the other caveat is you have to have done your research before you raise a price.

And you can't have terrible NPS or CSAT scores. We've seen a few people try to raise prices and their customer satisfaction scores were in the tank. And it was just, you know, it was terrible. Yeah, that's the wrong term to raise prices. And we're like, what are you doing? Why are you doing that? And so that's the thing. And then a little minor caveat is

Anyone who receives like a greater than 50% increase in price, they deserve a phone call or they deserve a, you know, some sort of different communication. Just to give you a little anecdote, one of our customers, they are, you know, a platform. It's not a very positive story, so I can't tell you who it is. They're a platform, so their customers make money on the platform. They had a cohort of customers and they've raised a ton of money, like $100 million plus, you know, venture raising.

They basically had a cohort of customers they spent a ridiculous amount of money acquiring that basically were costing them $1,200 a month just in infrastructure costs. And they were paying $30 a month for the product. So they were in a situation where they had this giant cohort. Now, what was great is that part of this cohort was making a lot of money on the platform. So they had a group of this cohort that was making a million dollars a year or more. And so

And so what the CEO did is he called every single one of these customers and it was a long list, but he said, listen, here's the situation. You know, you've been using us for X, you know, X long. You've made this much money and you've only been paying us this. And, you know, that's on us, right? Like that, that's what our price was. Unfortunately, because of the situation, I have to raise your price to $3,500 a month.

And 90% of those calls, they were like, yeah, okay. Right. Cause I'm making a million dollars. Like, yeah, that's right. Yeah. I get it. Like, yeah, obviously I don't want to pay more, but sure. Now the rest of that cohort, unfortunately they weren't, you know, they weren't making money.

Or as much money. And so there was a couple of slices there that they were able to raise prices to a point that actually got over that $1,200 of cost. But a lot of them, they just had to kind of fire as customers. And it was really bad for the business because they couldn't find a way to bring the infrastructure costs low enough. But they'd spent so much money acquiring them that it was just a huge waste of capital.

I mean, if they're unit economic negative customers, then like it's a bummer for the logos. Yeah. But Patrick, like you said, like the bummer is like, I mean, it's all sunk costs. So like, forget it. But like you spent so much money acquiring them. It's like, oh, it's like terrible use of capital. Well, there's a good lesson there. And I know it's a little apart from the point that we're going on is that

you should bring in unit economics into this analysis of pricing as well. So the reason ProfitWell is free is, yeah, we get a network effect and now there's like a really good narrative around why we made that decision. But the impetus to like going for free or even having the discussion was we were going to charge for the metrics product. We discovered that all of our conceptions of what we thought willingness to pay was for an analytics tool

And we should have seen the writing on the wall. BI and analytics is a terribly hard space. Everyone starts off, we're going to democratize this across the space. And then they're like, nope, Fortune 5, because retention is terrible and we need to get this through the door. Well, what we found is basically...

our two cohort, our two segments, I should say, one we were going to break even on just when it came to CAC and lifetime value. And then the other, we were basically going to be underwater by 50%. So we were going to pay twice as much as lifetime value. And what happened is like we discovered like our competitors,

They didn't know this information. They weren't collecting this data. And so this, we say this saved us about 18 months when we try to calculate it, but it was one of those things where we were like, we're definitely either giving up on this product, we're going up market and we weren't in a venture raising kind of motion. So you're like, eh, it probably doesn't make sense to do that, especially for a BI product that's going to require a ton of engineers to build all kinds of edge cases and security features and things. Or we have to figure out, you know, does free, you know, is free viable. And that's what we ended up doing through, you know, some other research and things like that.

I mean, that's such an important decision to make, but I got to imagine, especially for you guys, like being bootstrapped, like these decisions that impact capital, you've referenced a couple of times, like, is it a $1 million decision? It's a $10 million decision. Like that's, that's real. That's like, you know, real, like you have only so many resources based on your, you know, cash that you are generating at the business and like how you reinvest it. Obviously every company should think this way, but you know, in the, in

we've been in for the past 10 years. Like a lot of venture-backed companies are doing things like you were just describing of like, oh yeah, let's go out and spend a lot of money acquiring this set of customers and not think about that.

Well, David, you bring up an interesting point that I want to make sure we dive into here with Patrick. It's probably our last big segment here on the episode, but being a bootstrapped company, how many times have you made the decision to stay bootstrapped? And what was your calculus on starting the business that way? And what's your calculus on keeping the business that way?

This is one of those religious topics as well where everyone's like, bootstrappers suck or VCs suck, right? And the end of those conversations is always, it depends, right? And I think that for us, we...

Yeah.

six to nine months into the business. I think that, cause that's when I started like, Oh, this is, you know, I went to enough events and everyone, you know, craps on events, but like, they're a really great place to learn. Right. Especially when you're so new. But I think that what, what I kind of, what we kind of found is that our lifetime value and our ACV were high enough that we were able to kind of like bankroll the business. And what happened with us is we

This was not all, this is like very hindsight-like. It's not really foresight at the time. But I think that if we were to raise money in the early stages, we would have went really quickly right into a brick wall because we were going in different and incorrect directions.

and we were doing it slower than we would have with cash. Now, this isn't to say anything against raising money. It was my idiocy and ignorance that was the reason we're going the wrong direction, right? And so I think that's really kind of our little story about bootstrapping. And then over the last seven and a half years, we have lots of fun conversations and our whole litmus, and I think it's the standard litmus for thinking through these things has been, okay, well,

Are the problems we're trying to solve related to money? No, right? Like in the early stages, they weren't. It was, where do we go? And we're making enough money to kind of learn each day. We're not trying to blow out a sales team and things like that. And money would have helped, of course, but then money comes with a lot of like expectations, obviously, which is important because that's what you get in exchange for the cash. And so, and then it became, okay, well, we know where we're going and we know what we'd spend the money on. Are we being held back by the money? And it's like, okay, I don't know.

No. Right. And that's where it gets a little sticky. Right. Because you're like, well, are you being held back? You could accelerate with it. So the beginning of last year, we did, you know, we went on a few dates, if you will. And, you know, we ended up having someone who was, you know, and we also, as all founders do, our baby is worth more than maybe other people think and all this kind of stuff. And we've always been a little insecure because we have this tech enabled service and everyone's like, oh, it's consulting. And we're always like, it's not consulting. It's not consulting. Right.

And they're like, well, like the margins must be terrible. Like everyone makes all these assumptions about business. I've learned how to not make assumptions about people, businesses, unless I ask, because everyone's always like, well, your margins are terrible. And we're like, how do you know? Actually our gross margins are better than most software companies are 81%. It's insane. Right. I'm on our tech enabled service company. And then our software, pure software products have, you know, basically pure software margins, which are, you know, actually, actually, this is kind of funny. Our retain product,

Gross margin is 79%. So it's less than our tech-enabled service product, which is kind of insane. Is Price Intelligently the tech-enabled service? Yeah. So Price Intelligently is the tech-enabled service because there's a people element. And basically, I don't know if I mentioned this, but

And basically people were like, hey, I really like this data, but I need to talk to a human because pricing is a little complex and everyone's involved and there's politics. And we... Well, it's also the kind of thing that I can imagine you feel so nervous. You're like, I don't want to make this decision without talking to somebody who knows what they're talking about. A ton of people. And that's really what it started with is like...

this confidence gap. And we tried to close that with software and it's just, it's not there. Now we're kind of shifting our model in the next couple of years. We kind of have a roadmap to start doing things more automated, similar to our retained product. And we think the market's finally ready for some of that stuff. Not the dynamism we were talking about, but like, you know, a small step towards that.

But to close out the bootstrapping thing, we basically, we found people who got what we were trying to do and got that we wanted this big vision and wanted to be a big company and all this other fun stuff.

We had one person get really aggressive with a term sheet before we even, you know, we're talking. And then we were like, eh, like it was the valuation we kind of wanted, but it was, we knew it was going to like, we were going to get like hurt when it went into terms just because, you know, they were so aggressive. And so long story short, we've, we've dated a few times, but we just haven't, you know, converted to, you know, raising cash. I think we'll raise cash at some point. It's really rare. You see a company do more than a hundred million in revenue hasn't raised cash. Um,

but yeah, I don't know if I answered your question at that point. I just kind of ruminated on our, you know, bootstrapping woes basically. Um,

No, it's great. I mean, I think it's, frankly, it's the calculus that I think a lot of listeners are thinking through, either who are currently working at a venture backed company and trying to decide if that's the path they would go and starting something on their own, or a lot of people who are hacking around on something, have a little bit of traction and trying to decide, especially in this climate, like, do I go sell a story? Or do I do I sort of chill a little bit longer and accept

slower growth or, you know, maybe it's not even a viable business yet at all. And it's not about the growth speed. It's just about being able to, you know, sustain your lifestyle while building your vision. And everyone's got a different way to slice it, but I always think that the perspectives are helpful.

What I'm excited about with this environment, and I'll say that now because things haven't cratered, but things aren't, you know, they're not, we'll have to see how things go and maybe I'll revise this. That's the ugliness of recording early, right? But I think that what's kind of interesting is, is

I'm excited for like equilibrium to kind of come back a little bit, you know, valuations like, yeah, valuations have always been going up because now money is really plentiful, which is great. And but also companies are now plentiful. Right. So it's just a different environment. I think it's dangerous to compare too much to like 2001, 2008, these types of things. But what I will say is whenever you have too much extreme value.

in certain like markets or even like the government with politics and things like that, like you never win, right? It's, it's when there's an equilibrium. And I think one thing that we've missed out on, um, with a VC partner are all the things that come with great venture partners or PE partners, right? Which are, you know, Hey, we're going to help you hire key hires. Um,

we're not great at hiring execs. Like we just haven't been, and we've tried. And I think that we haven't spent enough time on it. We can get great and, you know, hire firms and stuff to help us, but you know, we wouldn't have to worry about that. You know, we don't have as many

except for fellow founders and things like that who look at the market differently. Right. And so I think there's a lot of value there. And what I'm excited about is I think that now that things are going back to a little bit of equilibrium, it's going to get the investment side as well as the company side to kind of reset a little bit on what's this relationship look like now that money is still somewhat plentiful. Um,

Might not be writing checks, but it's still there. And, you know, we've kind of gotten over that initial hump of, hey, a VC, you have to be more than just money. So I don't know. It'll be interesting to see. We're not going to raise money until, you know, this kind of settles down a little bit. We might not ever. But, you know, we're at least we're open to it, which I think is more so than a lot of the, you know, the bootstrap crowd is like, yeah, y'all are evil or something like that.

I'm super curious just to pull in this digression for one more minute, because I think this would be instructive to a lot of our listeners who are thinking about this. When you guys started, you're starting, you know, the ambition to start a software company. What did your founding team look like and how much like...

What capital needs did you guys need to fund to do that? Because if I'm starting now, if I'm a solo non-technical founder, I'm like, well, maybe I can do stuff with no code, but maybe I really need some developers, so maybe I should raise some money for that. Or maybe I need to put some capital in infrastructure or whatever. If you're willing to say, what did that calculus look like for you guys? You're giving me PTSD flashbacks right now. So I think that I had...

terrible founding story, but it's not a, it's not a, uh, uncommon founding story. So I had, um, I made all the terrible mistakes. Um, I didn't really know my co-founders. Uh, my co-founders were part-time. We definitely did not set the vesting and terms and a lot of kind of stuff up nicely. It wasn't like anyone was trying to take advantage of anyone, or at least that's the most, the least charitable interpretation. I think the most charitable is none of us knew what was going on. Right. So I

Really what happened is I was pretty much a solo founder, working 18 hours a day in a room alone. And these guys would occasionally help at nights, occasionally help at weekends, definitely with advice if I needed it. But it was...

It was a not like, at least in my opinion, it didn't feel like an equal like situation. And there was a lot of resentment that probably could have been solved if I was a better executive where I could go, all right, let's do expectation setting. And we should have like, you know, dated a little bit more before we like founded a company and a whole host of things. So, and they're still on our board. Everything's like amazing now. And they've been so helpful over the past, like, you know, seven and a half, eight years, but it was, it was a terrible founding story.

Were you an engineer? Were you the only one coding or were you outsourcing engineering? No, this is where it's even more terrible. So my background is in econometrics and math. I'm more like a data science engineer and then not even like, I wouldn't even call myself that now because that's an actual engineering job right now. Like I know when we're near full stack, I know what code is and I can like fix bugs. So in the early days I was fixing bugs, but there were times where I was like, hey, I

You guys committed to fix things when needed. And I would go to one of these guys' apartments. And again, this is a dramatic story, but it was...

It's very understandable how those things happen. Hey, you said you were going to work on this. Oh, I had a long day at work. Let's just drink some wine and hang out. And I'm sitting there and I'm like, ah, I got to get this done for a customer and this type of thing. And it's just because expectations weren't set and communication wasn't solid. And again, it's not a... There wasn't a taking advantage of or anything like that. But that was troublesome. But I think that to answer maybe the specifics of the question...

we basically didn't need a ton. Like what I did is I cashed in my 401k, no kids, no like wife, anything like that at the time. And so cashed in my 401k, which again, I was 25. So it's not like a massive amount of money. Yeah. It's probably, you know,

wasn't good for my future, but it was about, I think it was like $14,000 or something after the taxes, major tax hit, or maybe it was before the tax. It was around 10 grand. I remember that and living in Boston, that's not a lot of time. So, you know, lived on ramen and

not actual ramen, but like lived ramen lifestyle. And basically, I mean, I gave myself nine months and I was like, Hey, within nine months, if I can't pay myself something, we'll figure it out then. Right. I can always, and really what allowed me, cause I come from a very blue collar background, really poor as a kid. And what gave me the conception of, Hey, I'm willing to do this is one, I was like, you know, classic mantra of, you only got one life, but two, it was, Hey,

hey, like you can always find a job. Like it might be being a barista at Starbucks, might be digging a ditch, but you can find a job to like get to the basics. And thankfully we started getting revenue within those nine months. And then I hired our first team member because it was just me. And then there was this guy, Peter Zotto, who, you know, from a traditional sense is more of a co-founder than anything. My co-founder by name are more, they were like advisors and initial folks, but yeah, that's kind of how it shook out. And

Um, I would say that, you know, I was definitely in a good place. I was blessed where if I had obligations with family and stuff like that, I probably would have had to wait another five years to try something. And maybe I never would have tried it. Um, just because, you know, that at that point I'd have a mortgage or something and that kind of thing. But yeah, I think it's, it's not for everybody. And I, I, I,

I recognize that like that style of bootstrapping is very specific to like when you're young and dumb or like you're in a good place, you know, in terms of, well, you can probably make that same calculus in terms of, yeah. Like what do you have? Do you have personal runway? Yeah.

What are the expenses going to be to get it off the ground? Like, can you? Yeah. It's funny. Your story like is almost exactly. I don't know if you know this, but the Atlassian founders, the same thing. They just graduated from college and they were like, all right, well, we could go work at McKinsey that we would make X amount like a year to do that. What if what if we give ourselves a year and see if we can get to the same salary that we would pay ourselves like.

Yeah, well, that's a whole other story because this is something that's interesting about like I think in a bootstrapping business or like let's say you're doing the agency or something like that. I think, I don't know, a theory that I have is like you can – some of these folks that I see, they get a little too –

They start paying themselves too much is like my opinion. And what that ends up happening is then they, they go into like, well, let's just be that, that agency. And then they're like, yeah, but I want to be the a hundred million dollar company. And there's that disconnect. So what we did is like, I might, it took me, like I went to zero, uh,

on salary as well as savings within this time. I mean, again, no obligations except for myself, which, which, you know, thankful. And I didn't have student loans. Thank God I had scholarship, right? Like, again, and these are all these things that our generation has to deal with now. And so I'm like, just making sure that I'm pointing out that I was blessed in the, in these scenarios. But yeah,

And then salary became three grand a month, like, and started at like, you know, a very meager salary. And then for a good three, four years, it took me like three, four years to actually like, you know, Hey, like I'm going to make like six figures, that type of thing. And I think that was, that was really helpful for us because it allowed us to hire certain folks that we never would have been able to hire and probably took some time off the clock. And so just a piece of advice, like,

don't look at the first year only like look at like the first four or five years because you know, there's better ways to make money and if money is like the most important thing to you like go work in McKinsey go go become a $250,000 a year like, you know consultant that's that's totally fine. It's great. You know, it's not finding a company, but we all don't have to be founders. Well Patrick, thank you. Not only for the great discussion on pricing. I mean it I feel more educated but in sharing your story, I mean, I think it's a

It's just one of the best things about doing this show is getting to really hear the real stories from people like you. Yeah, 100%. Thanks for having me, guys. Where can folks find you on the internet? So just Patrick at Profitable.com. It might take me a bit to get back to you, but definitely get back to everyone at some point. And then just Patrick Campbell on LinkedIn. That's kind of where I post a lot of stuff. So yeah, always up for helping and always up for chatting.

And what types of companies should get in touch with Prathowell? Yeah, I know you have this free pricing audit. Can you talk a little bit about that and if that's interesting for folks?

Yeah, definitely. So yeah, we free pricing and also retention audits now. So we're sitting on so much data that we can give you some really good benchmarks, like very specific to you and not just like, Hey, you're vertical, but Hey, there's companies that similarly like flow in terms of their growth and churn and everything is to you or have similar ARPU and ACV. And so, yeah, just email patrick at profitable.com and I can get you hooked up with those. You either, you know, the most elegant way to do this is if you hook up to ProfitWell, you know, for free, it

with ZoraStripe, whatever, it takes two minutes. You can basically get that really easily and more specific. If you're, you know, big dog and have, you know, so much security and compliance stuff, it's totally fine. Like just get on the phone with us and we can like back into it for you without having to hook up as well. But yeah, happy to, happy to help, as I said. And, you know, any question, we probably have written something on the question you have too. So don't be afraid to email me and, you know, we can send you over that information or that data to be helpful.

Yeah, there's so much content. If you want to dig more into any of this stuff, you guys, be it on the Price Intelligently site or the ProfitWell site, you've certainly talked about it. All right. Well, everyone, thanks for listening. Patrick, thanks so much for joining. See you next time.