We're joined by Patrick Campbell, founder & CEO of the world's leading SaaS profit-optimization service ProfitWell, to dive deep on all things pricing and monetization. Patrick began bootstrapping ProfitWell 8 years ago, and has since grown the business into a massive success with customers like Notion, Lyft, Masterclass, Atlassian, Help Scout, HubSpot, Cisco, Autodesk and many more. Patrick gives us a masterclass in how to think with a profit-maximization lens about pricing, feature development, growth and retention. And, as a special bonus at the end of the episode, he talks about his own entrepreneurial journey, bootstrapping the company without any venture funding, along with challenges overcome along the way. This episode has something for everyone to learn about company building — and is not one to miss!
You can listen to this episode on the LP Show.
We finally did it. After five years and over 100 episodes, we decided to formalize the answer to Acquired’s most frequently asked question: “what are the best acquisitions of all time?” Here it is: The Acquired Top Ten. You can listen to the full episode (above, which includes honorable mentions), or read our quick blog post below.
Note: we ranked the list by our estimate of absolute dollar return to the acquirer. We could have used ROI multiple or annualized return, but we decided the ultimate yardstick of success should be the absolute dollar amount added to the parent company’s enterprise value. Afterall, you can’t eat IRR! For more on our methodology, please see the notes at the end of this post. And for all our trademark Acquired editorial and discussion tune in to the full episode above!
Purchase Price: $4.2 billion, 2009
Estimated Current Contribution to Market Cap: $20.5 billion
Absolute Dollar Return: $16.3 billion
Back in 2009, Marvel Studios was recently formed, most of its movie rights were leased out, and the prevailing wisdom was that Marvel was just some old comic book IP company that only nerds cared about. Since then, Marvel Cinematic Universe films have grossed $22.5b in total box office receipts (including the single biggest movie of all-time), for an average of $2.2b annually. Disney earns about two dollars in parks and merchandise revenue for every one dollar earned from films (discussed on our Disney, Plus episode). Therefore we estimate Marvel generates about $6.75b in annual revenue for Disney, or nearly 10% of all the company’s revenue. Not bad for a set of nerdy comic book franchises…
Total Purchase Price: $70 million (estimated), 2004
Estimated Current Contribution to Market Cap: $16.9 billion
Absolute Dollar Return: $16.8 billion
Morgan Stanley estimated that Google Maps generated $2.95b in revenue in 2019. Although that’s small compared to Google’s overall revenue of $160b+, it still accounts for over $16b in market cap by our calculations. Ironically the majority of Maps’ usage (and presumably revenue) comes from mobile, which grew out of by far the smallest of the 3 acquisitions, ZipDash. Tiny yet mighty!
Total Purchase Price: $188 million (by ABC), 1984
Estimated Current Contribution to Market Cap: $31.2 billion
Absolute Dollar Return: $31.0 billion
ABC’s 1984 acquisition of ESPN is heavyweight champion and still undisputed G.O.A.T. of media acquisitions.With an estimated $10.3B in 2018 revenue, ESPN’s value has compounded annually within ABC/Disney at >15% for an astounding THIRTY-FIVE YEARS. Single-handedly responsible for one of the greatest business model innovations in history with the advent of cable carriage fees, ESPN proves Albert Einstein’s famous statement that “Compound interest is the eighth wonder of the world.”
Total Purchase Price: $1.5 billion, 2002
Value Realized at Spinoff: $47.1 billion
Absolute Dollar Return: $45.6 billion
Who would have thought facilitating payments for Beanie Baby trades could be so lucrative? The only acquisition on our list whose value we can precisely measure, eBay spun off PayPal into a stand-alone public company in July 2015. Its value at the time? A cool 31x what eBay paid in 2002.
Total Purchase Price: $135 million, 2005
Estimated Current Contribution to Market Cap: $49.9 billion
Absolute Dollar Return: $49.8 billion
Remember the Priceline Negotiator? Boy did he get himself a screaming deal on this one. This purchase might have ranked even higher if Booking Holdings’ stock (Priceline even renamed the whole company after this acquisition!) weren’t down ~20% due to COVID-19 fears when we did the analysis. We also took a conservative approach, using only the (massive) $10.8b in annual revenue from the company’s “Agency Revenues” segment as Booking.com’s contribution — there is likely more revenue in other segments that’s also attributable to Booking.com, though we can’t be sure how much.
Total Purchase Price: $429 million, 1997
Estimated Current Contribution to Market Cap: $63.0 billion
Absolute Dollar Return: $62.6 billion
How do you put a value on Steve Jobs? Turns out we didn’t have to! NeXTSTEP, NeXT’s operating system, underpins all of Apple’s modern operating systems today: MacOS, iOS, WatchOS, and beyond. Literally every dollar of Apple’s $260b in annual revenue comes from NeXT roots, and from Steve wiping the product slate clean upon his return. With the acquisition being necessary but not sufficient to create Apple’s $1.4 trillion market cap today, we conservatively attributed 5% of Apple to this purchase.
Total Purchase Price: $50 million, 2005
Estimated Current Contribution to Market Cap: $72 billion
Absolute Dollar Return: $72 billion
Speaking of operating system acquisitions, NeXT was great, but on a pure value basis Android beats it. We took Google Play Store revenues (where Google’s 30% cut is worth about $7.7b) and added the dollar amount we estimate Google saves in Traffic Acquisition Costs by owning default search on Android ($4.8b), to reach an estimated annual revenue contribution to Google of $12.5b from the diminutive robot OS. Android also takes the award for largest ROI multiple: >1400x. Yep, you can’t eat IRR, but that’s a figure VCs only dream of.
Total Purchase Price: $1.65 billion, 2006
Estimated Current Contribution to Market Cap: $86.2 billion
Absolute Dollar Return: $84.5 billion
We admit it, we screwed up on our first episode covering YouTube: there’s no way this deal was a “C”. With Google recently reporting YouTube revenues for the first time ($15b — almost 10% of Google’s revenue!), it’s clear this acquisition was a juggernaut. It’s past-time for an Acquired revisit.
That said, while YouTube as the world’s second-highest-traffic search engine (second-only to their parent company!) grosses $15b, much of that revenue (over 50%?) gets paid out to creators, and YouTube’s hosting and bandwidth costs are significant. But we’ll leave the debate over the division’s profitability to the podcast.
Total Purchase Price: $3.1 billion, 2007
Estimated Current Contribution to Market Cap: $126.4 billion
Absolute Dollar Return: $123.3 billion
A dark horse rides into second place! The only acquisition on this list not-yet covered on Acquired (to be remedied very soon), this deal was far, far more important than most people realize. Effectively extending Google’s advertising reach from just its own properties to the entire internet, DoubleClick and its associated products generated over $20b in revenue within Google last year. Given what we now know about the nature of competition in internet advertising services, it’s unlikely governments and antitrust authorities would allow another deal like this again, much like #1 on our list...
Purchase Price: $1 billion, 2012
Estimated Current Contribution to Market Cap: $153 billion
Absolute Dollar Return: $152 billion
When it comes to G.O.A.T. status, if ESPN is M&A’s Lebron, Insta is its MJ. No offense to ESPN/Lebron, but we’ll probably never see another acquisition that’s so unquestionably dominant across every dimension of the M&A game as Facebook’s 2012 purchase of Instagram. Reported by Bloomberg to be doing $20B of revenue annually now within Facebook (up from ~$0 just eight years ago), Instagram takes the Acquired crown by a mile. And unlike YouTube, Facebook keeps nearly all of that $20b for itself! At risk of stretching the MJ analogy too far, given the circumstances at the time of the deal — Facebook’s “missing” of mobile and existential questions surrounding its ill-fated IPO — buying Instagram was Facebook’s equivalent of Jordan’s Game 6. Whether this deal was ultimately good or bad for the world at-large is another question, but there’s no doubt Instagram goes down in history as the greatest acquisition of all-time.
Methodology and Notes:
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Transcript: (disclaimer: may contain unintentionally confusing, inaccurate and/or amusing transcription errors)
Ben: Hello Acquired LPs and welcome to today's episode on pricing, the ever important and often 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. We really like all the 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 a master class in a specific element.
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.
Who is our guest? 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. Prior to ProfitWell, Patrick led strategic initiatives for Boston-based Gemvara, was an economist at Google and the US Intelligence Community. Patrick and his company have particularly keen insights on SaaS pricing (as I mentioned), but with the thousands of companies that they worked with, they have tips that can work for just about anyone.
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, so if we have time, I think we can dive in a little bit to that topic as well. Patrick, welcome to the Acquired LP Show.
Patrick: Thanks for having me guys. Excited to chat and go deep on pricing.
Ben: I originally met Patrick at Menlo Ventures hosted this cool pricing and packaging day, and it was something that I felt under-informed about. I went and I was just absolutely blown away by the depth of Patrick, if you're thinking about this. 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.
Patrick: I appreciate that. I think it's one of those things where you start to learn about 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 monetization, especially in the subscription space.
Ben: When did you start Price Intelligently?
Patrick: It was about 7½ years ago now, right around 2012 or later in 2012. It's been a fun ride. I'm based in Boston, offices now in Rosario, Argentina and Salt Lake City. We started off strictly on pricing, which has been quite the journey especially since when I started the company. It was just me in a room and I was battling against all these like white-haired consultants basically.
David: Subscription-based services (like the whole market for them) have probably exploded over the whole time that you've been running this company.
Patrick: 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, very small projects, nothing major or anything like that. It was cool to niche down and the main reason we niche down into subscriptions and SaaS was because of the growth but also because what we found is for some reason in the world of retail, ecommerce, et cetera, they have these giant research teams, consumer insights teams, and Hallmark, there are 100 people dedicated to market research. We looked at it and we're like, they don't need us. We can probably find some product, but for some reason, all these folks who are now in SaaS and subscriptions don't know anything about this stuff. There's a little bit of disconnect that we thought we can double down here and be a solution within the market.
David: That says everything right there. Hallmark is a great, great company. Actually, in my prior life I got to know them decently well. They're amazing. They have 100 people dedicated to market research and pricing. A SaaS company that might have $100 million in ARR might have half a person. To your point, that's a huge disconnect.
Ben: I think this is a really good segue into the first topic is this overview of pricing. 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?
Patrick: If you let me get philosophical for a second, I think it would have really comes down to is if you think about fundamentally what you're doing 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, it doesn't really matter what it is.
You've created some value, and that value because we don't trade goats for wheat anymore, you're ascribing some number to it. You're saying this value is worth $10 or this value is worth $100. 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, or it's justifying the product or the price, the value that you're putting on that product that you're creating.
It's one of those things where I think that a lot of people don't realize how central it is to a business. 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. What's interesting is that when you then look at it from an analytical perspective, you start to realize, because of that central nature of pricing, you basically have a huge impact when you do something that is related to improving your monetization.
To give you some facts and figures, we redid and we consistently update this McKinsey study that was done back in the day of looking at acquisition, monetization and retention; the three big pillars in any business, especially for subscription business. What we found is that if you improve each of those levers by the same relative amount, so if you improve leads by 1% and acquisition, your ARPU or ACV by 1%, and monetization or your retention by 1%, pricing is the number one lever in terms of output.
It’s by 4X–8X depending on the types of business. 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 customer sales and marketing, but I think it's one of those things when you look at the average of 10–14 hours a year, a company is spending on pricing, probably can spend a little bit more time. You pick out your toilet paper and probably spend more time on your toilet paper and custodial supplies than your actual pricing.
Ben: It feels a lot like the typical path for startups is picking something arbitrary just to get started. 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 10–100 customers, doing some interviews, and then say, cool. We know more. We're going to launch a real pricing model now.
There's some third checkpoint that's more around maturity. I would assume between these things, companies go a year really without meaningfully revisiting their pricing.
Patrick: I think it's because of that analysis paralysis that I referenced. 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 3 years. This doesn’t change anything about their monetization, not just the price point, but packaging changes, et cetera.
That number is coming down, thankfully, over time, which I think is great because we have so much automation and all parts of growth now versus 10 years ago. 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, I would say up to about $75–$80 million. At that point there's someone or even half of a person that they're trying to dedicate to monetization. They might not know which levers, but there's at least someone focusing on it.
Up until that point, especially people think, hey, let's throw the number in the air. Maybe do some interviews, these types of things, figuring out a price point, putting the most expensive tier on the left side of the page, ending the prices and nines, and calling it a day. In reality, you have your value metric, your add-on strategy, your discount strategy, your packaging, your actual price point, and the list goes on of all these different things that influence your Average Revenue Per User or ACV.
One of the biggest suggestions I have for people when they're thinking about monetization is to 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. There's a whole host of things I'm sure we're going to get into to help with that. That's the conception that's unlocked this for a lot of people at least that indecision.
Ben: It makes total sense. One more thing on the 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 described versus when you could throw a finger in the air five years ago?
Patrick: I think it's just a density in the markets of our success as an industry because when you were starting a business 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. To have a website, you had to have a server, which is insane to think about right now.
David: No AWS, no Shopify, no Stripe.
Patrick: Yeah, nothing. We weren't debating the no-code movement, these types of things. I think that what's happened in the past two decades has been just amazing. If the three of us wanted to start our brand new companies by the end of the day, we could spin up a server, get a website, start driving traffic to that website. Products wouldn't be great. Product is still hard to build because you have to think of the right things.
What was amazing the past few decades as this cost of production came down until we focused so much on just shipping, but there wasn't a lot of stuff out there, there weren't a lot of features. It was really easy to know what to ship because you either got lucky or you were just shipping features into a void.
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 Google AdWords were a penny a click, and then remarketing ads opened up, everything opened up. What's happened in the past few years are costs are still going to go down, memory and things like these are going to get cheaper and cheaper, but we're reaching a little bit of a flattening, where we figure out all these really cool ways to ship code faster and how to make dev teams productive, but nowhere on the margins. The other thing that's happened is the last major marketing channel that's opened up was 2015. It was Snapchat, which is not really relevant to everyone. Yes, there's been innovation and things like that, but it hasn't been like there was 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 2–3 competitors, direct or indirect. All of a sudden, if you started a company today, the average number of competitors you'd have and allotted from verticals that we looked at would be about 15. They would not be good, they wouldn't all be great, but in addition to that, customer acquisition costs because of all those channels, not just reinventing themselves, that's gone up about 70% in the past 7–8 years. The customer you got for $100 7–8 years ago is now $170–$180.
The value of software, unfortunately, isn't as magical. 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 going to have a conversation with you. What this is all led to is you now need a balanced growth strategy. You're still going to spend 50% of your sales and marketing that just a fact of high growth, but you got to think a little bit more about pricing, a little bit more about your retention, because what we've noticed in the data is, you pretty much need to be good at acquisition to just survive at this point from a startup fast growth perspective. In order to actually get those big gains, you got to have some good monetization. You got to have some good retention.
Ben: Wow. It's as good a place to dive deep as any. You say good monetization, good retention. Let's dive in on good monetization. Pricing models. You mentioned the website with three plans, the smallest on the left, the biggest on the right. What's the high level overview of types of pricing models that a company could elect to use?
Patrick: It used to be if you think about most products, we have one product, one price. Think about a retail product that we're selling. A lot of the advice in SaaS and software was good, better, best. You should have three plans. Not everyone's created equal. It was great advice for the time, and it's still good advice, but what's happened over the past two decades is billing systems. I know it's not the sexiest topic, but billing systems have finally gotten to a place where they can charge on different things, email, consumption, users, these types of things.
I know it sounds so pedantic right now, but 20 years ago, if you wanted to charge on anything, but per user it was really hard. How are we going to measure the amount of engagement? How are we going to measure the number of emails? It was expensive to measure. What's 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 cohort, companies started in the past five years (let's say), they're using what are called value metrics. Basically, it's some measure of usage or some measure of value. With retention products, we price based on how much money we recover for you, and we can measure that and we can get the customer to agree with it. HubSpot, obviously, is a big B2B example. They price based on basically the number of contacts that you have in your database, because presumably with more contacts, you're getting more value.
What happens is you have a couple of models. There's you just get the software, the perpetual model. You have a differentiated package. There's no measurement of value metric, but you get these features in package A, these features in package B, these features in package C. There's a pure value metric model, everyone gets all the features, except there's this consumption metric in some way, and then there's a hybrid.
On top of all this are add-ons and things like that that people can deploy. Those are the four main models and most people are in the latter two. There are still about 40% of SaaS companies, subscription companies out there that are just doing feature differentiation, there's no measurement of a metric. Those companies are starting to die out. They're mostly incumbents, or they're changing very quickly because they have the billing system and the wherewithal to change things up.
David: As you're talking especially that last bucket makes me think of Zoom. Zoom is price per seat, but there are so many add-ons that you can pay for and all sorts of bells, whistles, features and I'm sure they're thought about it, but they must have invested a ton in their billing and customer database technology to be able to do that.
Patrick: 100%. That's why we can get into billing systems if you really want to partner with these folks, but that's why what I like to tell people is once you get around $3–$5 million in ARR (Annual Recurring Revenue), you got to invest in a billing system. It doesn't have to be the Cadillac in the market like Zuora.
All roads do lead to Zuora, though. Zoom uses Zuora because they need so much flexibility. The larger point there, which I want to point out, is like add-ons are one of the most underutilized strategies in B2B and D2C. One of the most interesting things is, 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, there will be dynamism in subscription and SaaS pricing in some way in the next 20 years, because we're going to be able to somehow measure your willingness to pay based on your profile, we're going to measure your willingness to pay based on your profile, and we're already doing this in inside sales in some ways. That's a little far out there, though. Even segment-based pricing is tough right now.
Ben: You mean 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 one price for that person, because we know exactly the value you'll get out of.
Patrick: Yeah, kind of like the travel industry. A lot of people will say it will never happen because of this or that, and normally, those objections come for what if they talk to each other? That already happens in enterprise software, it already happens in a lot of our consumer products, so if you take one step back from there, it's segment-based pricing. There's a world where there's definitely some big questions here about measurement and things like that, but that the LTV (Lifetime Value) from that SEO channel customer is so much better than the lifetime value from that Facebook channel customer.
What you end up doing is, 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 it gets more volume, or whatever the decision comes with the data. Where we are right now, just to talk not about the future, but where we are now is you can do a different persona base, profile, or however you're measuring your different segments of your customer base with different packages. They might come in with your base plan and then based on their use of the product, you can offer them certain add-ons, and then you can offer them the value metric. As they go up, they're paying more.
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 what people are paying. That's the goal 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. There's a lot of ways to do that right now, and in the future, it'll get easier with tooling and stuff like that.
David: How should companies think about the freemium, trial, or the free aspect of what they're doing? I would be shocked if you say anything other than free and freemium is a major innovation in pricing, but I'm so curious to hear your thoughts.
Patrick: This is semantics. I like to try to separate it from pricing. We were talking about this earlier. Freemium is one of those religious topics, but people don't realize freeware has been around forever, not just in software.
Patrick: Yeah. There are all kinds of stuff where you're like, 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 on these types of things.
What I like to say is that freemium is an acquisition model. It's not a revenue model. You need to think about it as a premium ebook, basically. I think every company is going to have freemium in some way because if you just think about rising costs over the years, it's going to come to a point where those ebooks 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.
I think the beauty of freemium and to be completely and actually honest, I used to write articles about being very anti-free as the pricing guy. Freemium was an innovation because what you're doing is about that value, and some of those customers coming to you maybe higher up in the funnel, or they're just maybe not ready for primetime, but they still like you and they still want to 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. 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, there are a couple different types of freemium. You either put a limit, so 14–21 days into that freemium plan. They're hitting that limit. It's like a faux free trial as we call it.
Or like ProfitWell, it's forever free (our metrics product). Eventually in six or seven months, you find that little button inside there and you're like, I don't like that this metric is going down. Let me get this demo so I can get this product that improves this metric. That's why I always say it is part of pricing, ultimately, because it's a plan, but I think people need to think about marketing first rather than anything.
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.
David: It becomes full circle back to marketing.
Patrick: I know, yeah. That’s really funny; I like that. If you don't have that person, you should not be doing free out of the gate, and someone who's really that good. We all think we're that good, someone who's like the Balfours and the Caseys of the world, just because they're the ones who can actually sustain that. The most successful freemium models that we've seen weren't started until 3–4 years into the company.
Ben: What makes them good? I know it’s a little derailment. For someone that's never been around an A plus growth person like that, and they feel like a lot of the people that they've worked with are good. How do you know?
Patrick: I don't know if I'm the one to answer it, but here's how I think about it. It's an odd discipline to not go in until you're certain. That's what I found with really good growth folks. Brian Balfour is a good friend of mine. He runs Reforge (the growth program). I've known him at HubSpot, Viximo before that, and because he's a Michigan guy, but he was in Boston, when I was in Boston.
When I talked to him about this, I didn't pose that exact question, but I talked to him about what makes someone good at growth. What he talked about was the discipline not to basically chase a bunch of things. Most marketers, when you really meet them, they chase things. Even if they have a quarterly plan, basically, what ends up happening is they’re like, oh, I did this in my last company. This is the same thing that happens with pricing.
David: [...] Facebook strategy.
Patrick: Oh, it's very different. What Balfour will do is he does this whole growth loop, and that's what most of them do. They do tons of research, tons of hypothesis testing. As soon as they know that this is the thing, they go all in just unabashedly so.
David: This is the Berkshire Hathaway approach to growth.
Patrick: Totally, and then there's a whole long-tail of just the discipline to run these loops and constantly be running these loops. Loops are basically pushing experiments every week, every end day, or whatever it ends up being. I think we're calling it actually full stack marketer, I just realized. Being that diligent about being a full stack marketer is really hard to find someone. There are definitely more than 25 of those people in the world, but I think it's just in the early days of 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. That's really where it comes down to. Most of the time that people are successful in freemium 3–4 years into their business, know how to convert a free customer to a paying customer. They’re also just trying to open the top of the funnel at this point. It's a premium ebook, we're just trying to open this up the funnel because we know how to move people through the funnel, and we just need more leads.
Ben: You mentioned we don't know if we need a network effect. 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 the value of all that data, all that connectivity, but if it doesn't, and every incremental customer 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?
Patrick: In the context of freemium, yes, but I want to just clarify. I don't think you should do trials anymore. There are always exceptions to gross generalizations. I don't think you should do trials anymore because you should do the faux free trial that I was describing. Here's why.
Let's talk about Yesware. Yesware was one of the first email tracking products. You send an email, you can see if someone opens it. It's great for salespeople or whatever. They said, our target customer is going to burn through 100 opens, tracks, or whatever they called it, within 14 to 21 days. We know that if we give them 100 per month for free, those people who our target customers are essentially going to self-select. They're going to get something at that hundred and first track that says you got to sign up. They're either going to sign up where you got to deal with churn or retention or they're gonna go wait until next month, which means they probably weren't an actual target customer, a target buyer persona, or ideal 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 primetime to convert. What ends up happening is that on day 15, all of a sudden, I start spamming them, you got to sign up. It ended. You can't use the product anymore. You can't use it. Then, I have a 14-day drip of trying to get them to convert. 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, what faux free trials allows me to do is it allows me to nurture that lead until they're ready.
David: Right, because they could say, oh, I got the 14 days. I can't use the rest of this month. I'm going to sit back. I'm going to start using it again next month. They're going to do that for a couple of months. Maybe by month four, they actually want to use this.
Patrick: Or what ends up happening is you can start looking at their usage and you can go, anyone who gets over this usage, we're just going to automatically start adding the tracks. Or on day 31, they're just going to start getting those notifications again. They're going to go, oh, yeah, I remember that Yesware thing. It puts the onus of conversion more on the user than on the business. 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 this company is great or this company sucks. You have to look at cohorts of those free users. How many are converting within a 6-month window, a 12-month window, or a 3-month window depending on the business? Then you're like, oh, wow. There's gold on these sales because they're still converting down the path basically.
David: That makes me remember. You might say this is a little bit of a different dynamic. When we did our episode and we talked to Santi when they were doing due diligence on Zoom, they were like, oh, man, they have a churn problem. All these customers are signing up and then they're churning. But when they zoomed down on the data, they were like, no, they're churning but then they're coming back. If you looked at it in the 6-month, 12-month period, you're like, oh, crap, we thought there was a churn problem. There's actually no churn problem.
Patrick: 100%. That’s what’s so interesting.
Ben: 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.
Patrick: Yeah. That's why I call it a faux free trial because of that hundred visits. That's how you set how much you give for that freemium is my ideal customer profile. I want them to convert in a certain time period. Maybe it's 30 days. Maybe it's 45 days depending on the enterprisiness typically of a product. You set that usage at that mark. Obviously, within those 14, 30, or 45 days, you're doing everything you can to get them to use, get to those milestones to be really invested in the product.
Ben: I like that as a nice bow on how to think about your pricing model at a high level. Now, let's get into actually pricing it and picking numbers. I'll ask this in a loaded way. In our discussion of how to test whether you are pricing well, can you just A/B test prices?
Patrick: If you have the ability. What I mean by that is the traffic and the completes, 100%. Amazon can do a price test for a majority of their products in 30 seconds. Here is the thing. There's a lot of stuff that's been written on A/B versus multiple variants, one-tailed, two-tailed. All kinds of stuff go back to your statistics course. The problem is the concept of testing experimentation lulls a lot of us into a full sense of security of, we’ll just A/B test it. You hear that all the time. We’ll just test it. 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. Really what we do with the pricing product is quantified customer development. We're doing customer research. We're just doing it with a lens of monetization. What we find is how many people are actually doing any research? This was a gambit of Johnny and Jane’s startups all the way to Fortune 500 companies in this data set. Most companies in product organizations and marketing organizations are talking to really 10 or less customers that are non-sales capacity in a given month, which is not a lot if you really think about it in terms of research.
The pushback we always got was, we don't talk to our customers, Patrick. We don't do that but we do A/B testing. Half of the data set, zero tests per month including marketing tests. They don't even test subject lines in a lot of cases. I know that sounds bonkers because people listening to this podcast are probably not in the general. They're more in the elite theoretically. What I want to say in terms of testing is, if you have truly significant and authentic tests, go for it. I think that works out well.
Here’s the problem for the majority of us especially in B2B. We probably don't have the traffic to get enough completes to even just do a simple A/B test, let alone all of the different pieces that come with changing up a price. If you look at a traditional SaaS pricing page, let's say you got three tiers and you got five different feature differentiations, that's somewhere around 85 different variations of tests. It's one of those things where we just don't even have traffic for A/B, let alone the 85.
What we recommend doing is, if you don't have that traffic, it's totally fine. Do research. That will basically take the problem space down. When you have that output, maybe then you do an A/B test or you're not going to have any traffic to do even an A/B test with the majority of B2B companies. You have to do a little bit of a time test and just make sure you're measuring the KPIs.
You'll know this has changed things. Maybe you don't know if it could 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. It's going to be a risk because you're not going to know until you put it on the market but with enough research, your lease is hedging as much of that risk as possible.
David: This is also a super loaded question we're talking a little bit before. What would you say is a viable minimal sample size for doing that?
Patrick: There you go, sample size.
David: There we go.
Patrick: It's a measure of variance, man. It's super tough because it's not about the beginning of the trials or the beginning of the freemiums. 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 probably the first 90-day retention. It's not the signup. It's the completes. It's the actual purchases here. It's not like this many people click this one and this many people click that one. It’s, they signed up, they paid us after the freemium or the free trial, and they were with us 90 days.
What I also find is that you just slow your tempo down too much. Again, going back to the research, to give a direct answer to your question, depending on the circumstances, you can calculate these things and there's tons of data. We wrote a book Statistics for SaaS Executives, that's what we call it, just to educate our base. It's one of those things. There's a lot out there to 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. That gets really complicated over a year.
Ben: We're saying we can't do this ultra-quantitative thing because we just don't have enough completes. 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. 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. What type of research should they do here? What questions do they ask? And how much is qualitative versus quantitative?
Patrick: I think in that scenario, it's going to be almost even if you do some A/B testing because there's signal. You can change some stuff up and do see what people click on. That's a signal. It's not the whole cohort like I described, but you at least can then make some decisions. The one thing I will say is that even with multiple variant testing and research, you always have to always understand the limits of your data. I think that's a big deal.
We were talking about this before where people really like to agree with the data that agrees with what they think. Even if it's the same data set and there's something that they don't agree with, that the data was a problem there. You got to know. If you're going to make a $10 million, $100 million decision, you're going to have to do some research. If you can do testing, you have to do the testing. If you're in the world of Zoom, Slack, or Amazon, you absolutely can do testing, which is great. 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, it's okay to be qualitative. You just have to understand the limits and then check back in three months, six months, et cetera.
To answer your question directly, which was around what type of research to do, there's some models of, put it up there and 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. I think the biggest misconception is that people aren't going to tell you what they actually are willing to pay.
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. There are a couple of models that you can use. I'll talk about those two models a little hard in podcast form to go deep on them, and I'll talk about one caveat when it comes to making sure that you look at this research in the right way.
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 cost. There are models that get you close enough, at least in my opinion and analysis, that costs a 10th of what it costs to implement those types of surveys. Remember, you get two axes when it comes to the 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.
One tool or one methodology that anyone can use, there's a bunch of information, Wikipedia articles, stuff like that on this, is something called MaxDiff to look at the value of features. This is where I go to you and I say I got these five attributes. Or you go to the person who's been demoing, using the product, or beta testing the product and say there are five aspects of product A. What's the most important? What's the least important?
I can do that on a phone call. I can do that scalable 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. Everyone hates surveys and the reason we hate surveys is statistically, they're so good if you do them right but we suck. We just suck as operators. We send these 45 question surveys. We email them to people. The first question on the survey is what's your email address? That's a terrible situation to be in. Don't plan the survey.
David: Nobody wants to answer that.
Patrick: Just to give you some data. In our price style just offer, it's survey-base, we've sent about 80 million of these things at this point. We've looked at this. If you have a non-compensated survey—there's no compensation given—it's got to be less than four minutes, not only because your response rate goes down but the quality of responses tanked. Even with the responses you're getting, it's people who want to win an iPad.
It should be 30–60 seconds which is 4 or 5 questions depending on the length of the questions. If you do that, you can send these surveys once every 3–6 weeks. That's what we’ve found. You have to be careful with a batch of people who are always answering survey questions. You want to always put more people into that batch. MaxDiff is really good for features.
David: When you say your five features, MaxDiff is being the highest versus the lower.
Patrick: Yup. Most important, least important. It's important to follow that specific instruction. Rank order doesn't work well because the one and two ranks are typically intellectually honest from the respondent. Three, four, and five, they want to move on. There's a lot of signal at least important. As founders, we always have this vision. As operators, we have this vision of what we see. We want to go do everything we can to put that vision into place. If I know that the least important thing is the thing that I thought our whole centered marketing around needs to be, I probably need to readjust or really dig into the data.
On the pricing side, what we want to do is we want to take advantage of how people think about value. As human beings, economists, and psychologists who have studied this for years, we think of that value as a spectrum. We know that this water bottle here is worth less than this computer that I'm on. If you put me in the desert for three days, all of a sudden, without water, that value is going to flip. This is because we've purchased these products before but also with my circumstance, a whole host of things.
We have to ask in the right way. Again, it's not perfect. One of the most efficient ways we found is using what's called the Van Westendorp model, which is I asked you, at what point is this way too expensive that you would never consider purchasing it?
David: I think we talked about this on our Superhuman episode.
Patrick: We’ve had plenty of conversations on pricing which is great. At what point is it getting expensive but you never considered purchasing it? At what point is it a good deal? At what point is it too cheap that you question the quality of it? That last question is really important especially for any European listeners. European countries or founders typically underpriced their product so much. I think there's a little bit of little brother syndrome to the US in a lot of ways.
This Ukrainian company I was talking to, $20 for their product per month and their premium plan. I was like, “Hey, man. You got to up that to $100 at least. I don't even need to test it. It's getting up there for your premium plan.” He's like, “I can't imagine because $100 is a lot of money.” Their customers are all in the US. Back to the Van Westendorp model, the beauty of this is if I go ask 30 people, it's not going to be quantitative. I'm not going to make a $10 million decision on it, but at least understand my $100 product and my $1000 product. I can up basically the respondents to increase the integrity.
One thing I will say to Van Westendorp is, the innovation was the question or were the questions. The standard calculations aren't amazing. They're great if you're just doing qualitative. If you have so many responses, they really triangulate.
Ben: In those standard calculations, there's something about trying to get to the 40% threshold where you want. That's the thing you were referring to in the calculation?
Patrick: Yeah, because what you do is you just graph the answers to each question. Theoretically, you find where the intersections are. It creates this little diamond of where we should be. Whenever you have a model that theoretically can be used for any industry, in any sales model, and all this other stuff you got to adjust it if you're going to make a larger decision. What we did for our software is we took the questions and that's how we run it. We have some modifications depending on the application. It leads to the questions and then we threw out how they calculated it. We did a bunch of stuff in order to have our own IP frankly.
Just to give you a little bit of a litmus. Our software was at the point where it's plus or minus about 3% of reality. We check it with commodities and things like that. Van Westendorp is just standard. You'll probably be about plus or minus like 20%–25% of reality which again if you're making a $10 million decision, it's a little much but if you're just a Johnny or Jane startup just starting out, that's fine. Just get it out there.
David: We can plus or minus 25%. You are in the 99% of early stage startups.
Patrick: Yeah. One note that I'll make is the most important thing with any data, I would argue. Segment, segment, segment. The aggregate is interesting especially when you track it over time, but you get to segment it down. I think the biggest pushback is there's a lot of people who can't talk to customers about pricing. You shouldn't just talk to customers. You should talk to prospects. People have never heard of you who are your target customer base. 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. The people who 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 the complete opposite. People won't pay more. It's like, have you ever tested pricing? No. Well, you've anchored yourself into thinking that your products are only worth this much because that's what you put three years ago when you started the company. Now all of a sudden, we actually do need to raise the price on new customers to this level. We need to find a plan to take those existing users and get them to a higher level price. There's a couple ways to do that obviously.
Ben: Before we get into that because I'm very curious about grandfathering strategies there.
Patrick: Very religious topics.
Ben: Yeah. I never hear people say ‘grandmothering’ but I suppose for gender equity. Listeners, we're going to put links to both MaxDiff and Van Westendorp in the show notes here. I don't know, Patrick, if you have a page on that. I'm sure we can find some really good blog posts on each. I'm also going to link a screenshot of a slide that I have in a deck from you that I think is an awesome matrix of that graph you described.
X axis is relative preference magnitude in terms of ranking what's the most important feature or what's the least important feature. The Y axis is the willingness to pay. I love this notion that in the right top quadrant, where everyone wants to be, that's your high value and willingness to pay. You call them differentiable features.
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. If you think about the bottom right, that's your high value but low willingness to pay. That's your core feature set. 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. Anything in that bottom left, you call trash land where there's low value.
Patrick: Only in marketing not for a product. Don't worry.
Ben: Yeah. If there's low willingness to pay and low value, that gives you a really obvious signal, we shouldn't even be developing these features.
Patrick: In some cases, yes. We just started noticing a lot of trends on priority support. Never 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 certain segments so we wanted to visualize. Even if we’re just not even collecting data but just mentally think about it, where do we think our features are and things like that?
One thing I will say is features do move between these quadrants as well. If you think about two-factor authentication, it used to be an add-on, then it was a differentiable feature. It was a core. We’re starting to show it up in trash now. That's something that's important. You're going to have to probably build some trash. That's why it's a little sensational to contract.
David: Because everybody just expects it now. It's like, if you don't have it, I'm not even going to consider you.
Patrick: 100%. Like the login screen that would show up in trash. That's the most outlandish feature. A lot of security stuff has gone around the quadrants. Things like Active Directory, those have stayed in the add-on world, which is interesting. Obviously, your core features are probably always going to be in core. It's been interesting to track some of these features over time just because as the market has gotten denser and more features are out there, it's been super fascinating.
Ben: Really interesting. Let's return back to your three years into your business. You've managed to 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 had been on that same price point the whole time. You want to be nice to them because they were nice to you early. 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?
Patrick: I want to be careful with right and wrong. Again, a religious topic with grandfathering or grandmothering, let's be gender-neutral or inclusive, I should say. Here’s the thing. It is a really great idea when everything is in a terrible stage which always feels that way in certain aspects. You're just starting out. It's a really fun idea to be like we are never going to do these things. We're never going to hire salespeople. I hear that from a lot of fun apps. It's like, well, no, the mid-market enterprise of people who really like your software. You can probably hire some salespeople even Atlassian and its lack of sales.
Ben: But PLG, come on. It's going to take us the whole way.
Patrick: I know. In certain ways, it will. I think the secret is you really have everything at that late stage or the growth stage. In terms of grandfathering and grandmothering, it's one of those things where people love to say we are never going to raise prices on these folks and that's that. The problem isn't from $0–$10 million ARR. If you want to be just an indie business, which I respect and it’s awesome, if that's your path, that's awesome.
It's the new corner store. It's a software company which I think is great. Then, you don't have to upgrade people. You don't have to force them on your plans. It's totally fine. If you’re trying to be a $100 million company, it is extremely rare that you find a $100 million company that's somewhere between $10 and $100. 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 $0–$10. You're scrapping to get the market share. All of a sudden, you have that market share. You have this existing customer base. You're like, well, let's build a new product. It was hard enough to get the first one for these people to buy alone the second one. 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.
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 on the value that people are getting. Has your value increased while your brands improve? Your stickiness is improved. Your UI is improved. The actual feature set you're giving away is improving? It's a whole host of things. It's less about, don't do it; do it. It's more, do it in the right way.
I can share a template of a bit generic like email that we recommend using, but it's one of those things you can apply and it goes through the four or five steps we recommend. One, do what's called a grandfather discount. You've seen this in a number of ways. It's like you've been so loyal. Thank you so much. You've been awesome. You've been with us for 4½ 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. Remind them of that personalized value and then tell them, hey, you've been so loyal. 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.
I probably wouldn't go that far and lay it on thick; I was doing that just for effect. That's the big thing. I think one of the nicest hacks with raising prices is PS: if this materially impacts your business or if it's a B2C product, please let us know and we'll work something out. That PS is for two types of people. For people like me who are 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, 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. This is totally fine.
It's also for people that's actually impacting. They can email and be like, hey, cool. You can just gain so many relationship points and be like, hey, not a problem, founder, exec, or whomever. We're going to give you actually nine months on that grandfather discount. If that's still a problem, let us know. It's not about being a jerk. It's about how things cost money. They know that things cost money. That's the big misconception. People don't know that things cost money. You just have to do it in the right way.
Now, a couple of caveats, if you have a massive TAM (total addressable 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 for customers. We gave up $10 million because we grandfathered him. I'm like, okay, man. That's cool. You didn't have to. You could have gotten all $10 million. But that's fine because the help desk is a massive market, he can punt on that decision.
Ben: With Nick specifically, I've used Help Scout now at four companies. I'm sure the first ones grandfathered in but I've stood it up in three other companies now that have gotten full rack rate.
Patrick: And I think that that works out well. It's one of those things, though, that doesn't have to all be mutually exclusive. You probably would have had that brand equity to use them anyway because it's a great product, even though you weren't paying as much at the original company. The other caveat is, you have to have done your research before you raise the price and you can't have terrible NPS or CSAT scores. We've seen a few people try to raise prices. Their customer satisfaction scores were in the tank and it was terrible.
David: That's the wrong time to raise prices.
Patrick: We're like, what are you doing? Why are you doing that? That's the thing. A little minor caveat is anyone who receives greater than 50% increase in price, they deserve a phone call or they deserve some different communication.
Just to give you a little anecdote, one of our customers, they are a platform. It's not a very positive story so I can't tell you who it is. Their customers make money on the platform. They had a cohort of customers. They've raised a ton of money, like $100 million plus venture raising. They basically had a cohort of customers. They spent a ridiculous amount of money acquiring. That basically was costing them $12,000 a month just in infrastructure costs and they were paying $30 a month for the product. They were in a situation where they had this giant cohort.
What was great is that part of this cohort was making a lot of money on the platform. It's a group of this cohort that was making a million dollars a year or more. What the CEO did is he called every single one of these customers. It was a long list, but he said, “Listen, here's the situation. You've been using us for X long. You've made this much money and you've only been paying us this. That's on us. That's what our price was. Unfortunately because of the situation, I have to raise your price to $3500 a month.” 90% of those calls, they were like, yeah, okay, like yeah, I get it. Obviously, I don’t want to pay more, but sure.
Now, the rest of that cohort, unfortunately 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 $1200 of cost, but a lot of them, they said that kind of fire us 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 had spent so much money acquiring them that it was a huge waste of capital.
Ben: If their unit economic negative customers, then it’s a bummer for the low [...].
David: Yeah, but Patrick [...] I mean it's all some cost, but you spend so much money acquiring them, it’s a terrible use of capital.
Patrick: 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 your unit economics into this analysis of pricing as well. The reason ProfitWell was free is we get a network effect and now there's like a really good narrative around why we made that decision, but the impetus to 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. I wish we would’ve seen the writing on the wall. BI analytics is a terribly hard space.
Everyone starts off, we're going to democratize this across the space, and they're like, nope, Fortune 500, because the tension is terrible and we need to get this through the door. What we found is basically our two segments. One we were going to break even on, just when it came to CAC and lifetime value and then the other, we're basically going to be underwater by 50%. We're going to pay twice as much as lifetime value. What happened is we discovered our competitors didn't know this information. They weren’t collecting this data. This saved us about 18 months when we tried to calculate it.
It was one of those things where we were definitely either giving up on this product, we're going up market and we weren’t in a venture-raising kind of motion, so it probably doesn't make sense to do that, especially for BI product that’s going to require a ton of engineers to build all kinds edge cases, security features and things, or we have to figure out if it’s free viable. That's what we ended up doing through some other research and things like that.
David: That's such an important decision to make, but I can imagine especially for you guys being bootstrapped by these decisions that impact capital—you've referenced a couple times, is it a $1 million decision, is it a $10 million decision—that's real. You have only so many resources based on your cash that you're generating at the business and how you reinvest it. Obviously, every company should think this way but in the environment we've been in for the past 10 years, a lot of venture-backed companies are doing things like you were describing, like let's go out and spend a lot of money acquiring this set of customers, and not think about that.
Ben: 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 in the episode, but being a bootstrapped company, how many times have you made the decision to stay bootstrapped? What was your calculus and starting the business that way and what's your calculus and keeping the business that way?
Patrick :This is one of those religious topics as well, where everyone is like bootstrappers suck or VC suck. At the end of those conversations, it always depends. In the beginning, it was just complete naivete, I'm a first-time founder and I knew what funding was, but I didn't know how to raise money and all the articles out there. I just thought through why is this a viable option and we did have the opportunity to just raise a small seed round in the early stages, 6-9 months into the business. That's when I started, like I went to enough events. Everyone craps on events but they're really a great place to learn, especially when you're so new
But I think that what we found is that our lifetime value and our ACV were high enough, that we were able to bankroll the business. What happened with us is this is a 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’ve 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. 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.
I think that's really kind of our little story about bootstrapping, and then over the last 7½ 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 are the problems we’re trying to solve related to money? No. 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 up the sales team things like that. Money would've helped, of course, but then money comes with a lot of expectations, obviously, which is important, because that's what you get in exchange for the cash.
Then it became, okay, we know where we're going, we know what we’d spend the money on. Are we being held back by the money? No. That's where it gets a little sticky because are you being held back? You could accelerate with it. In the beginning of last year, we went on a few dates (if you will) and as all founders do—our baby is worth more than maybe other people think and all this kind of stuff—we've always been a little insecure because we have this tech-enabled service and everyone's like, oh, it’s consulting. We're always like, it's not consulting. It's not consulting. They're like, the margins must be terrible. Everyone makes all these assumptions about businesses.
I've learned how to not make assumptions about people’s businesses (unless I ask) because everyone's always like, well your margins are terrible, How do you know? Actually our gross margins are better than most software companies, 81%. It is insane. Our tech-enabled service company and then our peer software products have basically pure software margins. Actually, this is kind of funny. Our retained product gross margin at 79%, so it's less than our tech-enabled service product, which is kind of insane.
Ben: Is Price Intelligently a tech-enabled service?
Patrick: Yeah, Price Intelligently is a tech-enabled service because there’s a people element. Basically, I don't know if I mentioned this but basically people were like, hey, I really like this data but I need to talk to human because pricing is a little complex, and everyone's involved there’s politics and we—
David: Well, that’s also the kind of thing. 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.
Patrick: Yeah, a ton of people and that's really what started with this confidence gap and we try to close down a software and it's just not there. Now, we're kind of shifting our model in the next couple years, we have a road map to start doing things more automated, similar to our retained product and we think the market is finally ready for some of that stuff. Not the dynamism we're talking about but a small step towards that.
To close out the bootstrapping thing, we found people who got what we're trying to do, got that we wanted this big vision, wanted to be a big company and all sort of the fun stuff. We had one person get really aggressive with the term sheet before we even were talking. It was the valuation we wanted, but we knew we're going to get hurt with the terms just because they were so aggressive.
Long story short, we've dated a few times and we just haven't converted to raising cash. I think we’ll raise cash at some point. It's really rare you see a company do more than $100 million in revenue who hasn’t raised cash. I don't know if I answered your question at that point, I just kind of ruminated on our bootstrapping woes basically.
Ben: No it's great. Frankly, it's the calculus that I think a lot of listeners are thinking through, either who are currently working out of venture-backed company in 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 sort of chill little bit longer and accept some slower growth? 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 sustain your lifestyle while building your vision. Everyone's got a different way to slice it, but I always think that perspectives are helpful.
Patrick: What I'm excited about with this environment and I'll say that now because things haven't cratered but we'll have to see how things go and maybe I'll revise this (that's the ugliness of recording early). I think that what's kind of interesting is I'm excited for equilibrium to kind of come back a little bit. Valuations have always been going to be going up because now money's really plentiful, which is great, but also companies are now plentiful. It's just a different environment and I think it's dangerous to compare too much to like 2001 or 2008, these types of things, but what I will say is, whenever you have too much extreme in certain markets or even the government or politics and things like that, you never win.
It's when there's an equilibrium. I think one thing that we've missed out on with the VC partner are all the things that come with great venture partners or PE partners, which are, “Hey, we're going to help you hire key hires.” We're not great hiring execs, 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 hire firms and stuff to help us, but we wouldn't have to worry about that. We don't have as many advisers except for fellow founders and things like that, who look at the market differently. I think there's a lot of value there.
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 company-side to resettle a little bit on what this relationship looks like. Now that money is still somewhat plentiful, might not be writing checks but it's still there. We've kind of gotten over that initial hump of a VC has to be more than just money. It'll be interesting to see. We're not going to raise money until this settles down a little bit. We might not ever, but at least we're open to it, which is more so than a lot of the bootstrap crowd is like, you all are evil or something like that.
David: I'm simply curious, just to pull on 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 started with the ambition to start a software company. What did your founding team look like and how much capital needs did you guys need to fund to do that? If I'm starting now, if I'm a solo nontechnical founder, maybe I can do stuff with no-code, but maybe I really need some developers and maybe I should raise some money for that. Or maybe I need to put some capital, infrastructure or whatever. What did that calculus look like for you guys?
Patrick: You're giving me PTSD flashbacks. I think that I had a terrible founding story, but it's not an uncommon founding story. I made all the terrible mistakes. I didn't really know any co-founders. My co-founders were part time. We definitely do not set the vesting, terms and all that kind of stuff up nicely. It wasn't like anyone was trying to take advantage of it, anyone or at least that's the least charitable interpretation. I think most charitable is, none of us knew what was going on.
Really, what happened was I was pretty much a solo founder working 18 hours a day in a room alone and these guys would occasionally help at night, occasionally on weekends, definitely with advice if I needed it, but (at least, in my opinion) it didn't feel an equal situation. There's a lot of resentment that probably could have been solved if I was a better executive, where I could do an expectation setting and we should have dated a little bit more before we founded a company and a whole host of things. They're still on our board, everything's amazing now, and they've been so helpful over the past 7½–8 years but it was a terrible founding story.
Ben: Were you an engineer? Were you the only one coding or were you outsourcing engineering?
Patrick: No, this is where it's even more terrible. My background was kind of in the metrics and math, but I'm more like a data science engineer. I wouldn't even call myself that now because that's an actual engineering job right now. I'm nowhere near full stack. I know what code is and I can fix bugs. In the early days, I was fixing bugs but there were times where I was like, “Hey, are you guys committed to fixing things when needed?” I would go to one of these guys’ apartments—again this is the dramatic story, but it’s very understandable how these things happen—“Hey, you said you were going to work on this.” “I had a long day at work, let’s just drink some wine and hang out.” I'm sitting there and I'm like, I got to get this done for a customer, and this type of thing.
It's just because expectations weren’t set and communication wasn't solid. Again, there wasn't a taking advantage of or anything like that, but that was troublesome. I think that to answer maybe the specifics of the question, we basically didn’t need a ton. What I did was I cashed in my 401(k), no kids, no wife, anything like that at the time. I cashed in my 401(k), which again, I was 25, so it's not like a massive amount of money. It probably wasn't good for my future, but I think it's like $14,000 or something after the major taxes. Maybe that was before the tax. It was around $10,000, I remember that and living in Boston, it's not a lot of time.
I've lived on ramen, not actual ramen, but lived the ramen lifestyle and basically, I gave myself nine months and within nine months, if I can't pay myself something, we'll figure it out then. Because I come from a very blue-collar background, really poor as a kid and what gave me the conception of I am willing to do this, is (1) I was the classic mantra of we only got one life, but (2) you can always find a job. It might be being a barista at Starbucks, might be digging a ditch, but you can find a job to get to the basics.
Thankfully we started getting revenue within those nine months and then I heard our first team member because it's just me and then this guy, Peter Zato, who, from a traditional sense, is more of a co-founder than anything. Co-founder by name, they were like advisors and initial folks, but that’s how it shook out. I would say that 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, just because at that point I’d have a mortgage or something and that kind of thing. I think it's not for everybody and I recognize that that style bootstrapping is very specific to when you're young and dumb or you're in a good place in terms of—
David: Well, you could probably [...] calculus in terms of do you have your personal runway, what are the expenses going to be to get it off the ground? It's funny. Your story is almost exactly—I don't know if you noticed—the same thing with the Atlassian founders. They just graduated from college and they were like, we could go work at McKinsey, that we would make X amount a year to do that. What if we give ourselves a year and see if we can get to the same salary that we would pay ourselves?
Patrick: Well, that's a whole nother story because this is something that’s interesting in a bootstrapping business, or let's say you're in the agency or something like that. A theory that I have is some of these folks that I see start paying themselves too much, it’s my opinion, and what ends up happening is then they go into like, we’ll just be that agency and then they want to be the $100 million company. And there's that disconnect.
What we did is I went to zero on salary as well as savings within this time. Again, no obligations except for myself, which is thankful and I didn’t have student loans; I have a scholarship. Again, these are all these things that our generation has to deal with now, so I'm just making sure that I'm pointing out that I was blessed in these scenarios.
Then salary became $3000 a month and started at a very meager salary. It took me three or four years to actually make six figures. I think that was really helpful for us because it allowed us to hire certain folks that we never would've been able to hire and probably took some time off the clock.
Just a piece of advice. Don't look at the first year only, look at the first four or five years because there are better ways to make money and if money is the most important thing you, go work for McKinsey. Go become a $250,000 a year consultant. That's totally fine; it's great. It's not founding a company, but we all don’t have to be founders.
Ben: Patrick, thank you, not only for the great discussion on pricing, I mean I feel more educated but in sharing your story. I think it's just one of the best things about doing the show is getting to really hear the real stories from people like you.
Patrick: Yeah, 100%. Thanks for having me, guys.
Ben: Yeah, where can folks find you on the Internet?
Patrick: Just firstname.lastname@example.org. It might take me a bit to get back to you, but definitely get back to everyone at some point. Then, just Patrick Campbell on LinkedIn, that's kind of where I post a lot of stuff. I’m always up for helping and always up for chatting.
David: What types of companies should get in touch with ProfitWell?
Ben: Yeah, I know you have this free pricing audit, can you talk a little bit about that and if that's interesting for folks?
Patrick: Definitely. With free pricing and also retention audits now, so we're sitting on so much data that we can give you some really good benchmarks very specific to you and not just like, hey, you're vertical, but hey, there are companies that similarly flow in terms of their growth and churn everything as to you, or if similar [...].
Just email email@example.com and I can get you hooked up with those. The most elegant way to do this is if you hook up the ProfitWell for free with Zuora, Stripe or whatever, it takes two minutes. You can basically get that really easily and more specific. If you're a big dog and have so much security and compliance stuff, it’s totally fine. Just get on the phone with us and we can back into it for you without having to hook up as well.
I’m happy to help as I said and any question, we probably have written something on the question you have, too, so don’t be afraid to email me and we can send you over that information or that data to be helpful.
Ben: Yeah, there's so much content. If you want to dig more into any of this stuff, be it on the Price Intelligently side or the ProfitWell side, you've certainly talked about it.
All right. Well, everyone, thanks for listening. Patrick, thanks so much for joining. See you next time.
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