Monetizing SaaS: Episode 8 with Pat Doran, Head of Revenue at PriceIntelligently by Paddle

Well, Pat, it's really great to have you here. It's been so good getting to know you over the last year, year or so. You've had this really interesting career. You've worked in sales for companies like Constant Contact, Gannett, Paycom, ProfitWell, which is now Paddle. You're currently running revenue for Price Intelligently. You've been with ProfitWell, Price Intelligently, Paddle for roughly 5 years. So I think it's fair to say that you've seen pricing and packaging firsthand, the good, bad, and the ugly across hundreds of companies. Hundreds, if not thousands, of SaaS companies. Before we go into pricing and packaging, can you just tell us about the steps in your career and how you got to now?

Sure. Yeah, uh, thanks for forcing me to relive my highly illustrious career. Um, it was funny, it actually made everything I look at now is through pricing and packaging lens. So now I'm reflecting. Um, yeah, I started— I, I went to school down North Carolina, Wake Forest, got a business degree, uh, did a couple interesting internships there, and ultimately got into sales, kind of following in my father's footsteps. Don't tell him that. Cut my teeth on the inside sales floor at Constant Contact. Went from there to, was basically at that point a newspaper company. Now Gannett, part of USA Today. Moved on to Paycom, another sales role, and then eventually forayed into ProfitWell/Price Intelligence/Paddle. A lot of P names flying around, including my own. Uh, really not, not, not totally in pursuit of like pricing as a specific discipline, but like, like I imagine a lot of folks getting into pricing or any next move is, uh, it was an opportunity to solve a very cool problem with, uh, big-time go-to-market operators and, uh, following a couple leaders that I, that I trusted and believed in. So that's been the trajectory, uh, and can definitely share like specific anecdotes around how pricing was leveraged in, in different spots in different ways. And how it influenced my experience on the front lines, which I'd say like most folks in pricing, in my experience, come from either like an academic backdrop or sort of a consulting backdrop, and not so many of them are, are from sales, uh, and those are the folks ultimately deploying good, good pricing and bad pricing in the front line. So it gives me a slightly skewed perspective on the thing, which I hope is a good thing.

Yeah, you really do have this very interesting vantage point. I mean, you've been able to observe lots of different companies at lots of different stages and kind of think through the market forces that are operating on them. When, when you zoom out, when you think about, you know, building software companies and, you know, are there market inflections or big changes that you have become particularly interested in given the seat that you've occupied?

Yeah, um, and this is where I, I kind of reflect on if I pit, uh, my time at Constant Contact against my time at Paycom. For both of the companies of which I, I couldn't close a window. So we can isolate any sort of like market inflections of pricing and, and attribute it to my lack of salesmanship. But, um, it was interesting to see once upon a time at Constant Contact, their, their pricing was a huge differentiator for them. It was a super simple $20 per month, easily conceived by the buyer, uh, and a 60-day free trial made them feel warm and fuzzy, helped them fill the, the marketing funnel really easily, easily and actively., and they had a big old bench of inside sales folks that could execute against that. Versus my time at Paycom, very different, like opposite end of the spectrum, where we, the last thing we brought up was price and it was a premium price. We looked to build a bunch of value through more of an outbound motion. Uh, and ultimately like the, the culmination of that process was here's the price that makes sense for you based on the value I've developed. So interesting to see. And I think like that tracks with the, the time that passed between, which was 3 or 4 years where Once upon a time, pricing was really simple and it optimized for simplicity and got folks into the marketing funnel. It's since evolved and in some cases been bastardized into more complex, but ideally more value-based where you're building up a bunch of value to build into price. So that's like, as it connects back to a little bit of my career arc in terms of inflection points in the market more broadly. Have you heard about AI? Uh, that's, it's, it's stupid, but like, that's, that's what's top of mind for us as of late. Like, if you're not waking up every day in cold sweats thinking about AI and how it's going to disrupt your business or how you'll use it to disrupt someone else, you're probably shot. Uh, and then like a lot of folks, I'm just seeing like a big old fat trend towards profitability. Um, so not surprising. I'm sure you've heard it a couple thousand times via LinkedIn, but like, if you don't have an eye towards profitability, you're also probably behind the 8-ball versus look at it as like pump cash into the business and hope that revenue comes out the other end.

Very good. I have heard of AI. I have heard of profitability. You're right.

Raggy.

Those are good. Okay. Monetization, pricing, packaging. I want to go deep with you. Let's start. Cool. Let's start with monetizing software as an idea. Why is monetizing software so complex operationally for software companies?

Um, you primed me with operationally, um, but I think it's complex for a lot of reasons. Like, I'd argue strategically too, if I can put my strategy hat on for a second. Um, it's complex in part because there are so many levers to pull. Um, like, if I think back to my, my time then at Wicked Local, now Gannett, we were basically slinging newspaper ads. And so it's pretty simple. It's like, do you want 6x9 or 5x8? Do you want color, black and white? And they said color. I said, heck yeah. Um, you know, uh, and then it was like maybe we threw a bone on the, the number, or like the amount of circulation, uh, and we may have value-based against that. But really there are only like a couple axes, and that's, that's existed, uh, in, in pricing models for eons, uh, since we started selling wheels and hammers. Where it becomes complex with I mean that when it comes complex with software is there's just like a ton of levers to pull. There's a ton of vectors of value you can deliver. And so in turn, it adds the complexity. So like if you think about there, and you know this intimately, but, um, there are different pricing models you can charge for. There are a thousand different segments, especially if you sell through like a product-led motion. You can sell to anyone under the sun. So who am I optimizing for? Uh, there are different features you can of course offer and paygate. And then there are price levels out the wazoo. Um, and all of that to back to your point of operationalization, uh, becomes super tough to instrument because you have to build it into, um, your marketing collateral and how you show out in the world and making sure that, that, that threads into your general story and narrative, right? And if you're a premium position, but your price says something else, then you're, you're probably shot. Uh, it has to be instrumented into your sales team and, and collateral trading, uh, consistency such that you have a go-to playbook. And then the actual product itself and the supporting tech stack. So if you can't track usage in your product, but you're charging on usage, then it's probably fugazi. And if your tech stack doesn't support it, that it either makes for a bad buyer experience because they can't get access to parts of the tool they need without seeing some uptick in price or a bad, say, business experience because you're not capitalizing on the pricing that you're pushing out to the world because you have no mechanism for tracking or, or entitling, etc.

Yeah, really good. So, you know, let's say 10 years ago in software, seats are probably a really common value metric. That feels like it's changing, you know, quite a bit with the introduction of usage-based pricing over the last, let's say, half decade, probably accelerated by AI.

Yeah.

What are the most common value metrics that you guys see as you go out and consult with companies, and, and how should companies select and evolve their value metric?

Yeah, uh, I'd say per seat, per user, still pretty hot. Um, it, it's funny, like we said, we probably said a few years ago that like you're, you're messing up your pricing with per user. And I, I think, and this is more anecdotal, I don't necessarily have data to back this up, I think it's, it's a little bit back in vogue, uh, going back to the concept of like leading with simplicity, uh, and that folks can wrap their head around it. And oftentimes like a lot of the tools that we see today, especially selling PLG where it is like an individual user experience, per user makes some sense. But other stuff that we see is, you know, things like usage levels, right? It might be number of gigs, it might be number of videos. I forget how Riverside prices, we chatted with them a couple of years ago, but yeah, it might be bandwidth spent. It might be something like number of projects. Uh, it might be number of collaborators, um, and, uh, it might be number of web— there's a lot of options you can choose from. Really what it comes down to is we talk about 3 things that make a good value metric. One is that, as you might guess by its name, it aligns with customer value. Uh, two is that it scales with the customer, uh, meaning you don't want to be charging, you know, Disney the same as you do the mom-and-pop shop down the street. And 3 is that it's easy to understand. And we say that both in terms of like the underlying concepts, like per user, very easy to understand, but also in terms of the volume. So you could charge by number of gigs, which a technical buyer can conceive of, but the volume becomes pretty untenable if you're pumping out thousands of gigs, right? So those are the 3 tenets that we say, say produce a valuable or a good value metric.

Love it. What's the difference between pricing and packaging?

Uh-oh, that's pretty existential. Um, I know it, it might be, it might be semantic. Um, I'm happy, I'm happy to debate or not debate you on this. We use pricing, like for a long time we use monetization that encapsulated everything from like who you're selling to, to how you're packaging, how you're structuring, to what you're pricing it at. We now use monetization and pricing pretty interchangeably. But in terms of if we were to pit pricing versus packaging against each other, I'd say pricing is either the overarching strategy or it's the price level, basically the number that ends up on your pricing page. And packaging is how you're distributing your features across your packages.

Makes sense. Is that fair? It's very fair.

You agree?

Yeah, I do agree. Okay. But I mean, you guys would run different exercises for determining what price should be or what a price model should be and then how a product should be packaged. Is that fair?

Yeah, some, somewhat. Uh, it kind of depends on like the outcomes we're working towards. So if we're trying to build, um, if we're trying to build a model that, that interplays packages and pricing, like we may do that one fell swoop because people won't buy this suite of packages without the price being right. If we're trying to build more iteratively because, uh, we're optimizing for precision and we need to get every element right, then Yeah, we might do those separately.

You mentioned tech stack earlier. Maybe kind of what did you mean by that?

Yeah, so, and you're probably intimately familiar with this, but especially as your business grows and you start just like tacking on arbitrary tools to the stack, you find that those things impacted by pricing grow more and more far-reaching over time. So you may have everything from like subscription management or billing platform. Shout out to Paddle Merchant of Record, best in the biz. To, to invoicing solution, to accounts receivable, to your CPQ, to your actual codebase in your own business, to schematic, all of those having to interplay to to accurately pump out the right price package, et cetera, for the buyer and ultimately run a sound business because we're here to deliver value, but also capture value for that. If we can't do that through a tech stack, then we're probably shot.

So when you guys go into a business and you're doing a project or doing a study, is it fair to say you're having to try to go pull and reconcile data from a lot of different business systems as well as maybe application code?

Yes. It's interesting. There's some reticence to engage us, rightfully so, until folks have sort of their data ducks in a row. But I'd say 70% of the businesses we work with have very limited insight into something what we perceive as simple, like ARPU by segment, for instance, right? It's just like, it's tough to pin down for a lot of people. So for those out there that are in that boat, like You're not alone. Doesn't mean it's good, but, but yeah, we'll have to pull from a bunch of different systems. You then have to reconcile because you might have some competing feedback from different systems and it's oftentimes tough. And part of the reason we work with folks is we don't know what the baseline is. And in turn, it's tough to say like what good or bad looks like. Yeah.

Yeah. I talked to an FP&A analyst yesterday actually, where he was lamenting the number of systems he's trying to reconcile every month for month-end close. From the ERP to the CPQ to the CRM to the billing system to the product. Oh yeah.

That plus my not having high IQ is why I'm not an FP&A guy.

Yeah. So you've consulted with— I'm going to just throw it out there— like hundreds of companies over the last half decade.

Thousands. Yeah, no.

Thousands.

I think I agree. Or about 500.

Sure. Okay.

So I'll take dozens.

Yeah, yeah, yeah. So mistakes, what are the most common mistakes that you're seeing early stage companies make around pricing and packaging? And then what about growth stage and enterprise? And are those mistakes different at different stages?

Uh, yeah, I like that question. We actually, we use something, um, we call the maturity matrix to actually scope out our own projects. Um, a little bit of inside baseball here, but, um, as, as companies grow more mature with respect to pricing needs, there's a few, say, vectors that change. Um, one is the number of pricing blind spots, right? Those tend to go down over time because you sort of collect more data, you have better understanding of the market, you often have, uh, capabilities in-house that solve for these things. Another is revenue or risk associated with a pricing change, right? So like, as time goes on, like, if you're just starting up, there's only so much risk you have in, in changing price versus if you are an enterprise behemoth. Um, or let's say you're, you're a Peloton that has room to, to hike price by $200. That could have pretty instrumental impact to your bottom line. Uh, other things are internal inertia and complexity, which you probably see this like once you hit growth stage. You, uh, have a bunch of internal inertia that it can sometimes be prohibitive to instrumenting a meaningful change. And you haven't quite hit that threshold of like enterprise specialization where you have individual people owning different things, right? You have like a lot of overlap and in turn a lot of butting heads, et cetera. And then complexity, I mentioned like complexity goes up over time and in turn it's tougher to like rip out and unroot. So those are like the axes that we think about when we think about like changing problems in pricing as company maturity grows. Um, I'll pause there. Any questions? And otherwise I can dig into to kind of—

okay, makes sense.

Cool. Uh, in terms of the, I'd say like the, the most common mistakes in, in early stage companies, there's, there's probably, they're probably making like too many mistakes that aren't pricing to worry about mistakes that they, that are pricing. And that's maybe the most common mistake is just like you're not focused there because you have 30 fires burning that could put the company out of business tomorrow to sweat, you know, if you're charging $9 versus $9.99. Um, and then I, I'd also say that like it's probably undervaluing what you're, what you're producing in the market. Um, so, uh, people at that stage, especially because it's often founder-led and it's their baby, they're probably pumping just a ton of value into the product. And not reflecting that value in an evolved pricing strategy. So they are both leaving a bunch of money on the table by not capturing additional value revenue. And also they're conditioning their buyers to expect more for less. And it's all either based in lack of time and focus because again, they're putting out other fires or fear of turning people off to their baby that they've worked to build good value into because they're charging too much or mixing things up, et cetera. So that's early stage. Um, any thoughts there?

Makes total sense. I agree. You know, on the earliest— I mean, I'm an early stage company myself. I've created an early stage. There's always this like fear of charging too much too early. Um, and my sense is that many founders carry that fear with them. Yeah. Um, and so they'd end up kind of giving away too much for free, and it's like really sort of a muscle to build. I've interviewed a few founders who are like trying to charge too much upfront, but that's also a problem, right? Because early stage, you need a lot of oxygen in the product and you need to win your first customers and get your case studies. So there's a balance there.

Totally. And it's some of what you're optimizing for. Most folks in early stage, they probably want to get reps in the product. They probably want adoption. They probably want folks building out a network effect that are telling their friends how cool Schematic is. Versus charging this absolute premium. And then those folks that are early on, they helped you work through some of the bugs. That's okay. You can throw them a bone and keep them at legacy pricing into perpetuity. But that opens up a communication channel, not just for the product and improving there, but also for pricing outgoing. So if you have someone that you've come to as sort of a design partner, you can use that to pick brain around, hey, I'm thinking about shaking up my value metric. They'll tell you that's stupid. Okay, I'm going to go validate with some data. And then once you hit scale, then you get it right.

Yeah. Yeah.

Um, and then growth and more like enterprise, I'd say, uh, growth in my experience there, and this kind of coincides with internal inertia. There tends to be, you're big enough, there's like a lot of noise in the room around pricing decisions, right? Like at that stage, whereas early stage is like the same person is managing pricing, is managing product, is selling the product. Right? Um, at growth, you, you have a VP of sales, a CFO, a CEO who might still be around as founder whose, whose baby's being called ugly. You also have, um, say, like, folks that are more operating in strategy, um, that have their own perspective and nose in the air. Um, and all those voices are, are loud in one room. And so what I, I'd see mistakes being made in growth is they probably don't have the right data to cut through that noise. Uh, I think Bezos said something like that, like the most junior person can upset the most senior person so long as they have data. They think that's probably true for growth stage. So get a lot of opinions in the room, but ultimately sort of cut through the noise with some sound data to point to the right direction.

Yeah, that resonates strongly for me. Is there, you know, if you were to kind of sort of a slight twist on the question, yeah, let's talk about mistakes. Are there common mistakes? Are there common misconceptions that companies have around operating pricing and packaging, or no common misconceptions?

I have a couple, but I'm keen to hear if you have something in mind.

I don't have anything in mind.

Just curious. I think one is that like people know what they're doing. And I don't mean that like, like I think folks like me thinks that the Jones down the street know what they're doing when it comes to pricing. And the reality is, I'd say like 95% of folks, and folks are definitely growing more sophisticated over time. You go back to your market inflection question. We've seen an overinvestment, like maybe shift away from pure go-to-market and selling product into focus there, of course, to run a sound business, but into pricing and how we pull this third lever of growth to grow our business. But I think like the expectation that folks sometimes have is that like, their competitor or some archetype in the, in the, in an adjacent space, uh, has done the research and knows what good the pricing looks like, uh, and it's probably more of the blind leading the blind.

That's a really good one. Was there a second, or is that— that's a really good one.

I had a second. You're right, I said a couple misconceptions.

You did.

Oh no, maybe that was a misconception.

That's a good one. We can, we can go there.

What did I have? Let me noodle on it for 20 seconds. I know we're about up on time, but, um, well, yeah, let me ask.

I know, I know you've got to jump, so closing question. If, if, if we've got some founders on the other end of the line here, if we've got some, you know, go-to-market executives, product executives on the other end of the line here, um, in the pursuit of constantly getting better at pricing and packaging, what are one or two or three things that you would suggest companies start to employ or deploy to continually get better at pricing and packaging as a practice?

That's a good question. I like that. I'd say first step is kind of infrastructural, both building out sort of like sound— I mean that with respect to like sound tech stack and ensuring that you're not bloating that so much such that you kind of have the tail wagging the dog and your tech is making your decisions for you versus value to the customer or your business strategy making the decision, uh, and then more infrastructural in terms of, of building a pricing committee, uh, so ensuring that you have consistency around who are, who are, who's driving input to decision-making and then who's ultimately making the decision, uh, and you have a, a nice rolling cadence for getting together on, say, like a quarterly basis to evaluate, uh, and that way it behaves because there's a bunch of fires you can react to every single day If you have a consistent function and you have a consistent meeting cadence where each time your head's down solving on pricing, you'll inevitably get better and instrument changes over time to better reflect the value of the business.

Yeah, really good. Pat, this has been so much fun. Where can people find you, learn more about you, and learn more about Price Intelligently?

Good question. Uh, you can check us out at paddle.com. Uh, not on Instagram, so you have to email me. Pat.dorn@paddle.com. Um, and I'd say, as you know, like, we're, uh, we're, we're pretty happy to chop it up on this stuff. We like to grow this space of pricing. It's important. So if you have questions, happy to be a sounding board. And if it parleys into something bigger than that, then great. So feel free to email me, and I'm happy to help.

Awesome. Thank you again. So much fun. Thanks, man.