Impact Pricing Podcast

Dan Balcauski is the founder of Product Tranquility, where he helps B2B SaaS companies improve pricing, packaging, and monetization strategy. 

In this episode, Dan breaks down the uncomfortable reality behind today’s AI gold rush: buyers are tired of “AI-powered” hype, SaaS companies are struggling to monetize features nobody uses, and pricing teams are rewriting their strategies in real time.

If your company is trying to monetize AI without becoming another forgettable AI feature, this episode will change how you think about pricing, adoption, and customer value.

Podcast: Play in new window | Download

Why you have to check out today’s podcast:

• Learn why AI features alone don’t drive purchases — and how to position AI around customer outcomes people actually value.
• Discover the biggest AI pricing mistake SaaS companies are making — charging for features before customers build adoption habits.
• See how smart SaaS companies roll out AI strategically — using adoption-first pricing, early access models, and workflow-driven product design.

“Prove value with your new AI features before you throw a paywall in front of it.”

— Dan Balcauski

Topics Covered:

02:10 – “Freemium Is a Terrible Idea for Most SaaS Companies”. Why most freemium models fail before companies fully understand the real costs behind them.

06:48 – Why AI Can’t Automatically Set Your SaaS Prices. Dan explains where AI can help pricing teams and where human judgment still matters most.

09:53 – The Dangerous Truth About AI Pricing Advice. Most LLMs learned pricing strategy from bad SEO content and outdated thinking.

13:35 – The Adoption vs. Monetization Framework. The simple 2×2 model every SaaS company should use before pricing AI features.

17:34 – Margin Percentage vs. Margin Dollars. A smarter way for CFOs and SaaS leaders to think about AI profitability.

18:32 – “Buyers Don’t Care That Your Product Uses AI”. Why customers care more about outcomes and workflows than your AI technology.

24:31 – Why SaaS Companies Keep Changing AI Pricing. Most AI pricing models don’t survive their first 18 months.

26:07 – The “Early Access” AI Pricing Strategy. How smart SaaS companies introduce AI features without hurting adoption.

29:24 – “Earn the Right to Monetize”. Why proving customer value should happen before putting up a paywall.

Key Takeaways:

“We need to prove our value first before we can monetize it.” – Dan Balcauski

Resources Mentioned:

• Steven Forth — Mentioned as a trusted source of pricing expertise and strategic thinking.
• Anthropic Claude Code — Dan’s primary AI workspace for research synthesis and pricing analysis.
• Readwise — Tool Dan uses to ground AI outputs using trusted expert highlights and notes.
• Salesforce — Referenced as an example of rapidly evolving AI pricing strategies.
• Pragmatic Institute — Mentioned during the discussion on product adoption and feature prioritization.

Connect with Dan Balcauski:

• Website: https://www.producttranquility.com/
• LinkedIn: https://www.linkedin.com/in/balcauski/
• X: https://x.com/dan_balcauski
• Podcast: https://podcasts.apple.com/us/podcast/saas-scaling-secrets/id1682338188

Connect with Mark Stiving:

• LinkedIn: https://www.linkedin.com/in/stiving/
• Email: [email protected]

Full Interview Transcript:

(Note: This transcript was created with an AI transcription service. Please forgive any transcription or grammatical errors. We probably sounded better in real life.

Dan Balcauski

Earn the right to monetize. Go out there, prove value with your new AI features before you throw a paywall in front of it. 

[Intro]

Advertisement

Today’s podcast is sponsored by Jennings Executive Search. I had a great conversation with John Jennings about the skills needed in different pricing roles. He and I think a lot alike. If you’re looking for a new pricing role, or if you’re trying to hire just the right pricing person, I strongly suggest you reach out to Jennings Executive Search. They specialize in placing pricing people. Say that three times fast.

Mark Stiving

Welcome to Impact Pricing, the podcast where we discuss pricing, value, and how buyers decide. 

I’m Mark Stiving, and I help companies get paid for the value their buyers can’t see. Our guest today is Mr. Dan Balcauski or Kalbowski, depending on if you listen to his mom. 

Here are three things you wanna know about Dan before we start.

He is the founder of Product Tranquility.They work on SaaS pricing strategies. He’s deeply focused on AI and SaaS pricing, which is what we’re gonna talk about a lot today. 

And he’s worked with numerous SaaS companies, helping them rethink monetization, positioning, and value capture. 

Welcome, Dan.

Dan Balcauski

Oh, good to be here again, Mark, and definitely gonna send this to my mom.

Mark Stiving

Okay. I know I asked you this before, but let’s just get a reminder. How did you get into pricing? 

Dan Balcauski

Yeah. Well, like any good career, a mix of luck, experience, and some interest, and also with a blend of market demand and need. 

I started on the technical side, been in software technology my entire couple decade career. I went to business school. I actually came across some notes from my business school days where I came across an economic value estimation in some of my old slide decks from class. But I took a couple pricing classes when I was in business school. 

Everything from, hey, you’re the brand manager for Minute Maid orange juice, and you’re looking at scanner receipts from all of the local Chicago Cub Foods stores trying to figure out how, you know, promotions, placement, and competitor, you know, discounts and promotions affected, customer, you know, purchase decisions  to, you know, more kind of abstract, you know, mostly more abstract, I guess, in the relative sense, you know, economic value estimation stuff.

During my MBA internship, I worked for a successful Silicon Valley startup, and the project during my internship, one of the questions on the CEO’s desk was, you know, should they pursue a freemium model? 

So I looked at that for them and realized that except in very rare circumstances for most companies, freemium is a terrible idea, and you shouldn’t do it. So we get happy to rant on that if that’s interesting. We may have touched on that previously.

And then, as I moved into product leadership roles, I wasn’t explicitly responsible for pricing at the companies I worked for. Product marketing was, which I think is the right place for it to live inside the business. But product management, product marketing, they’re a Batman, Robin team. 

You could make your decision about who is who in that relationship, but I believe they’re often paired at the hip. And the product marketers will get asked to review or revise pricing, and they’re like, “Hey, I know stuff about m-messaging and positioning. I don’t know anything about this pricing. You got an MBA, could you help me with this?” 

And so, I got a lot of scar tissue from those experiences, trying to apply my Minute Maid orange juice theories to B2B software and it didn’t necessarily apply. And went off on my own about six years ago and decided that, hey, I’m hearing from a lot of companies, they really struggle with this pricing and packaging thing, so focused on that for the last six years.

Mark Stiving

Nice. Nice. Great story. 

I wanna add some nuance to something you said just for kicks, right? So you said product marketing should own pricing. So here’s the nuance I usually give. The people who should own pricing understand the value of the product to the customer. And so, in SaaS, that’s almost always product marketing.

Once you move to hardware-type products, it’s usually product management, as opposed to product marketing, ’cause they’re much more involved in what the next version of the product is gonna look like. 

Dan Balcauski

I generally agree with that. I would say, you know, for the marketers, we love our acronyms, right? We’ve got the three Cs of pricing. We also have the four Ps of marketing, product, price, promotion, and place. And usually in a software company, product management has responsibility for just one of those, because it’s all-consuming.

And so, that is really the reason that I generally see product marketing own it. It’s not that the product managers don’t understand value. In fact, if product managers don’t understand value, you probably should maybe look to train them up or get new product managers who do. But rather it’s so all-consuming that they’re just…it falls off their plate, the ability to do it rigorously.

So I think either of those could be a good home. I just generally recommend that it doesn’t live in finance. They tend to be too attached to their spreadsheets. And  good stakeholders, really important stakeholders to have, both in the strategic lens as, as well the operational lens. But I also recommend keeping it out of sales ’cause you don’t want Dracula in charge of the blood bank.

Mark Stiving

Yeah. So, so the sales one is fascinating. By the way, I wasn’t planning on talking about this, but the sales one’s fascinating because they’re probably the closest to the customer and understand value better than anybody, but you’re absolutely right. They’ve got these incentives that say, “Hey, I wanna go win the deal, so let’s lower price.”

Dan Balcauski

Yeah. Incentives drive behavior, and the incentives are not aligned. And I also, you know, just going back to product marketing, you know, they’re usually at a strategic intersection of the business, right? So their incentives are the long-term value and growth of the product line. Not a quarterly quota target.

I firmly believe that pricing and packaging is a function of positioning, and usually product marketing is the keeper of positioning, right? Again, like pricing, it’s not something that, you know, they could just go into a room and change the company’s positioning ’cause it’s truly cross-functional. But you know, you want those two probably living close to the same brain. 

Mark Stiving

All right. We were gonna talk about AI today, so let’s talk about AI for a little bit. And before I do, I wanna split AI into two huge, huge topics. 

One is using AI to do pricing, and the other is pricing products that include AI. I am guessing that most of your work is in the pricing products that include AI. And so, before we get there, let me ask the other side. How do you see companies using AI today to help them with pricing? 

Dan Balcauski

Yeah. I could speak from my own experience. I’m a heavy AI user, and that is, you know, I’m in the last few months, like a good chunk of at least my Twitter feed have moved to Claude Code. So, every day I start and work out of either Claude Code or my email pretty much is my two work surfaces. 

So, a couple misconceptions. 

I do not really believe that in SaaS you’re going to be able to let the AI, you know, set your prices. There are industries where you can do that. I mean, I’m sure you and your listeners are really well-acquainted with, you know, the pricing companies like Zilliant or PROS or Pricefx, right? 

And those are even very, very before the pre-gen AI companies. But that’s because you’re able to build very robust machine learning models around large amounts of transactional data to figure out, you know, price elasticity and all those other components.

But for my work, when I’m using something like Claude Code, you know, that could be everything from, “Hey, help me take this interview with a customer where we discussed value and pricing, and create a synthesis document that helps outline, extract the value of that conversation,” right? And then that becomes a basis for further work down the line. 

And so just in terms of lowering research cost as a general dimension there, I think there’s a bunch of leverage that folks can get from that perspective. ‘Cause always the question is like, “Well, you know, research takes time and it’s expensive.” And those things can be true, for sure. But I think things like AI, it begins to make a lot of those things that were just so time-consuming much more accessible.

You start to lose that excuse of like, “We don’t have time to talk to our customers and really understand the value and understand, you know, how they feel about our pricing and our packages.” Because now you’re able to, you know, everything from creating, you know, “Hey, here’s our research questions. Help me turn this into an interview guide.

Help me post-process that. I did 20 customer interviews. Help me bring this together. What’s the overall story that I’m hearing across all of these conversations?” I think that’s where AI can be a real thought partner in helping you do pricing. 

Mark Stiving

Yeah. I think that brings us back to the, we had a brief conversation before we hit record, and, and it brings us back to the issue that says, “Hey, I love AI for helping me do research and helping me come up with hypotheses, but I just, I never trust it. I never trust it.” 

Dan Balcauski

Yeah. Well, and a good part of that too is that, you’ve gotta remember, I remember when I first really, really got in the deep end on pricing, I was talking, you know, before we hit record about my love of Steven Forth. I respect him as a really good thought leader in the world of pricing and highly recommend everyone read his new Substack.

But I don’t know about you, but I used to come across all of these articles, if you just typed into Google, “SaaS pricing strategy,” you would get these ultimate guide to SaaS pricing 101 that were really in-depth articles, but you read it through and you’re like, “The person who put this together had no idea what they were talking about.”

And so you gotta remember that to a certain extent, this is what these LLMs are trained on. So what does that mean is that you have to start with what is the grounding under which you’re going to, you know the philosophers would call this epistemics.

Like, well, what do we know to be true? You don’t know what’s baked into the weights of those models because they were trained on a bunch of garbage on the internet. Maybe they read some of Steven Forth’s stuff along the way, but it probably was swamped out with, you know, a bunch of other nonsense that people wrote for SEO for, from someone who wasn’t, you know, as wise as Steven is.

And so, even things like, you know, I use a platform called Readwise. So as I’m reading your book, like Selling Value, for example, I go through on my Kindle, and I highlight that. Readwise sucks all those data points in, and now actually just a couple weeks ago, Readwise launched a MCP that allows me to, within Claude Code, query Readwise and be like, “Hey, I wanna know what Mark thought about how to sell value in this circumstance.”

Use my Readwise to go actually pull in what Mark thought, not what you just think about what you were trained on on the internet. And so, having that grounding of what you’re having the LLM base the answers on I think is really important. 

Mark Stiving

I think that’s brilliant. I build custom GPTs for my clients, and what I do is I upload all of my content so that they can query and know what I think about something, or at least what I’ve written about something, right? Maybe I’ve changed my mind since I wrote it. Who knows? 

Dan Balcauski

Yeah, I know. I change my mind all the time, right? I look back at stuff I wrote like three years ago, I’m like, “Why did I think that?”

Mark Stiving

Yeah. Yeah. Okay, so let’s flip the coin over and let’s talk about the hard part and that is, how do we help companies who are adding AI to their products?

So, it feels like there’s two really different issues. One is an AI native company, and the other is an existing SaaS company that says, “Oh my gosh, AI is about to flip my world upside down.” 

Dan Balcauski

Yeah. Well, it’s flipping a lot of worlds upside down, especially if you’re looking at the basket of software equities in the public markets. Their valuations are getting compressed on a daily basis every time Anthropic or OpenAI releases some press announcement. You see an entire sector of the software world get hammered that day. 

So, I think, it might sound basic, but I think one thing I run into constantly with pricing work with clients is having a very clear, explicit goal, because oftentimes maybe you’re talking to the CEO and you’re like, “Hey, we’re gonna do this project.” You’re trying to release this new AI feature. You know, much like you talk about in, in selling value, you value discovery. 

What is this gonna do? You know, are we trying to, you know, increase customer retention? 

Are you trying to increase net revenue retention? Are you trying to increase top-line AR- accelerate top-line ARR? Is this a competitive threat? You’re just trying to add a me too, so because your competitor added something and we need something there so we don’t, you know, lose that race. And all of those things could be true, and none of them are necessarily the right answer. 

But what I find is that usually internally, as you start these projects, we’ll do deep dives with each of the executives one-on-one. And the problem is each of them might have different goals, and it’s very difficult to come out with any outcome on the other side if everyone’s not aligned on the goals. 

So I think simply where I would start is with your AI feature, you know, any consultant if you can’t make a two by two, they take away your consulting license. So if you think about two axes adoption versus monetization, you know, low to high on both of those axes, where are you trying to go? Are you trying to maximize monetization out of the gate? 

Are you trying to maximize adoption? Are you trying to take a more of a middle path? And having that conversation explicitly with the executive team can really help illustrate or illuminate what is going to be the right path for them because there’s a lot of different patterns that I’m seeing out in the market for how companies are doing this.

And again, outside of knowing what their internal strategy is, it’s really hard to judge if it is right or wrong. It’s like it may be perfectly right for them, but given what else they’re trying to do. And so, I really recommend, look, a big argument going on right now is CFOs are having a panic attack because maybe their traditional SaaS margins were eighty, ninety percent LLM-enabled applications, much less than that. 

I don’t know if they’ve settled out yet, but I’ve heard more in the range of fifty, sixty percent. And so if the CFO is like, “Man, we’ve got to charge for these things ’cause I’ve got to protect margin,” that might be at odds with, you know, the CEO trying to accelerate top-line revenue or the CPO trying to make sure that customers don’t churn because the competitor just added a product.

So is cost containment the primary mover? Is it customer retention? Is it top-line growth? 

And then as well, you know, what we see is that companies, when they are trying to maybe put that paywall up front to protect margin, are putting a barrier in front of their adoption in a way that may be not explicitly named if you’re not thinking through this carefully.

So what do I mean? I know, I think you used to work with the Pragmatic folks. Is that correct? So I love their stuff. A lot of good thinking around, you know, how to do product management and product marketing and pricing. And any feature you release, right, everyone always thinks, “Oh man, this thing is really gonna be a game changer,” right?

But the dustbin of history, and your, probably your product, is full of eighty percent of the features that you released that had all these hopes and dreams are things that, like, nobody barely touches. They touch the other twenty percent all the time. So we have that for every product, and now if we put a monetization gate in front of that, we really run the risk of putting a barrier on that adoption which allows the product team to get that user feedback.

What are customers, like, here’s what we said we do, but that’s a hypothesis. Once you get that as customers, did we actually deliver that value? If not, where are we missing the mark so we can improve the product over time? 

And I think we’ve seen a lot of companies go out the gate maybe two years ago with, “Hey, we’re gonna monetize this,” and margin protection, and a lot of companies have now started to back that off significantly, where we’re seeing like, Hey, like actually this really put a barrier on adoption. We need to prove our value first before we can monetize it.

I have another friend, he calls it earning the right to monetize. 

Mark Stiving

Yeah. I’m gonna jump back. That was a long rant there, Dan. 

Dan Balcauski

Sorry.

Mark Stiving

No worries. I wanna jump back to, first off, the gold in what I heard you say was the two by two adoption and monetization.

I think everybody who’s thinking about putting out a new feature, a new AI feature in particular, they should be thinking about that. I mean, that was such an insight, so thanks for sharing that. 

The second thought that I had is when we start thinking about CFOs protecting margin, what I find fascinating is the difference between margin percentage and margin dollars.And so, if CFOs are trying to protect margin percentage, it is really, really hard ’cause you may as well stop using AI, right? ‘Cause you’re not gonna succeed at that. 

But if we can get them to switch to thinking margin dollars, now it matters, right? Now I can pick up fifty points of margin on an AI feature and still make money while I’m making good margin on the rest of the SaaS product as well.

Dan Balcauski

Yeah, I agree. I have the same frame.

Mark Stiving

Okay. Let’s slightly switch gears. 

How is it that buyers are looking at AI today? So if I’m gonna release a new AI feature, I see that companies are out saying, “Hey, we’ve got this new AI feature.” And my personal opinion is they don’t care, right? Buyers don’t care.

What are you running into? How are you helping clients with this? 

Dan Balcauski

Yeah, I generally agree, right? You don’t go to market and talk about, “Hey, our SaaS product runs on an Oracle database,” right? Nobody gives a shit. 

So, you know, people don’t care. AI is an enabling technology. I think we saw this most explicitly with the crypto Web3 craze we went through four or five years ago, where everyone was like, “Oh, it’s this product, but it’s built on a crypto backend or blockchain.”

And everyone’s like, “I don’t…so what does it do for me? I don’t get it.” And then, you know, we run the risk of AI washing our customers. 

How are buyers interacting with it? I think it’s really dependent, you know, I always think in customer segments and segmentation. And I would put myself probably in the early adopter category, which you’re gonna have, you know, maybe five to ten percent of your market or users within your particular count who are in that frame.

Usually probably heavily dominated by folks in the engineering team, but might be also, you know, marketing folks or finance folks, and they just wanna play with the new toys. 

And so I think, you know, that’s one thing that companies have really struggled with. You know, I think- This was endemic, especially two years ago when everyone added, you know, that m-magic wand chatbot to their product, and everyone’s looking at a blank text box being like, “What do I do?”

Because a graphical user interface speaks to you about what the functions are available, but if I just give you an open text box, you’re like, “Do I ask for a recipe for crème brûlée? What am I supposed to do with this thing?” So I think there’s– this goes back to my point about what does that adoption curve look like and how do you bring customers along?

So, you know, we’re seeing companies, you know, kind of realize that that’s not enough, that they need to figure out different touch points in their product such that adding AI capabilities is a no-brainer. I’ll give you a simple example from my CRM. 

You know, every CRM has different fields that they, you know, support, right?

It’s like maybe how did you get in touch with this person? You know, where, what, where did the lead come from? You know, how maybe there’s a propensity score to buy, right? All sorts of different things. And so usually those would be manually entered. Well, now you put like, “Hey, have AI generate this based upon all the rest of the information you have in this account record.”

That’s not a chatbot like, “Hey, just I’m gonna…” But that’s directly implicated in a user flow. But I think we have a lot of work to do on the design and product side to make that value apparent for folks. I also think that there’s some interesting things going on as it pertains to rollout.

So, you know, as we see companies go to market, what is it that they’re doing with monetization as they release to market to in o- in order to really understand what usage is going to be so that they can understand, you know, how big is that cost risk, but then also encourage adoption? And so seeing companies do things like giving additional usage to net new customers, right?

Such that, hey, like we have these limits for, for long-running contracts, but as a new customer, you know, you have extended limits for the first six months to, to really drive that adoption. 

And really thinking about that intentionally as you go to market with a product versus saying, “Well, if you wanna use this at all, it has to be paywalled.”

Because the other thing is you’re trying to create that habit loop, that habit pattern where, you know, if I give you, you know, sort of the just taste of it, like, oh, you could do this action three times and then you hit a paywall. Well, I don’t know. 

Maybe the first, maybe one of those three times didn’t actually work. But if I did it three times, like it didn’t really become part of my daily life, so when I hit it, I was like, “Okay, I guess I’m just not gonna use that thing.” So we really need to think intentionally about those. 

Mark Stiving

Yeah. So, what you’re talking about reminds me a lot of an argument I have with Steven Forth a lot, right? And we talk about credits and credit-based pricing, and does it make sense? 

And so, the big argument for credits is that buyers don’t really know what they wanna do, what they can do. There’s too many options, there’s too many things. And so, we sell credits as a way to say, “Go experiment,” right?

You can go try a whole bunch of different things and figure out what plays or what, what doesn’t play. So part of the issue that I’m having with AI or I’m watching companies have with AI is because they don’t understand their buyers very well, they throw things against the wall and say, “Hey, go tell me what works. Go tell me what sticks.” And they’re just trying things as opposed to understanding truly what buyers care about. 

The CRM example you gave I thought was phenomenal. I don’t use a CRM because I hate filling out forms, right? So if I had a CRM that just took my calls and filled out forms for me, I might even use it.

Dan Balcauski

We may agree more than disagree ’cause I also dislike credit models. 

I will separate, right, there… I think there’s a big distinction as folks are going to market between what you might term like a co-pilot conversational AI versus maybe what we’re seeing more with things like Claude Code and there are others, where they’re more agentic such that they’re going off and, and doing activities for you.

And I think yes, the credits have maybe gotten a lot more ahead of their skis. In the agentic world, I mean, companies are facing real trade-offs, though. 

Those agents can do a lot of things, and they could also do a lot of things really quickly if you spin multiple of them up. And so, I think everyone’s learning in real time.

Like, I would say probably the predominant takeaway if, if anyone, you know, is listening and, and just like, “Okay, we said a lot,” I think the dominant mindset I’d like to impart to people is agility. 

Almost across every company I’ve looked at who’s rolled out these features, 100% of them have revised their pricing and packaging within 18 months of their initial launch.

So I think there’s a real fear, again, going back to this like, “Hey, we don’t want costs to get out of control. You know, we wanna make sure, you know, we put proper monetization gates in place,” everything I said before about that stymying adoption. .

But knowing up front that you’re not gonna have it perfect, but then this is going to be an ongoing learning process, and that you should be prepared for that when launching these capabilities into market.

Mark Stiving

I think that’s brilliant. I mean, Salesforce is changing their pricing strategy every year now, or something like that?

Dan Balcauski

In 18 months they’ve changed it  three times. They’ve changed it three times in 18 months.

Mark Stiving

So, of course we’re gonna just…right? And it’s only fair ’cause this is so new and so different, we’re all learning and trying to figure this out.

Dan Balcauski

And there’s a structured way to go about that. 

So, usually, you know, if you’ve been in software development for a while you may be used to alpha, beta, you know, GA, general availability. What we’re seeing companies do is, come out of beta, it’s like, “Hey, we’re, we’re still building the product and all the kinks aren’t worked out.” Instead of jumping to GA inserting another phase called early access. 

What does that mean from a pricing rollout perspective? So early access is a period, and I’m seeing periods from companies ranging anywhere from two to 18 months for early access before they go GA, where you announce your pricing fences or your metrics.

You put prices on them, but you make it very clear we’re not charging for this yet, and we’re not enforcing these barriers. And that does a couple of things. 

One, it allows you to learn what real usage looks like. Your beta customers are probably not representative proxies of your user base, right? So going back to what I was saying before, I think Kyle Poyar, who I also really love, I think he had something in an article recently. He said, like, 10% of your users will drive 90% of your cost, right? 

A lot of those early adopters are gonna spit up all, you know, they’re gonna be inside AI all day, every day, and maybe you got somebody in accounting who’s never used the thing or used it once and is like, “I don’t get it,” and walks away.

And so, the chance that you got that 10% as representative in your beta program is probably very low. But what this does is it allows you to get that adoption flywheel going, understand where the problems are. Are you really delivering the value you thought you were? 

But it’s important that you have the pricing there, because what I’ve noticed or, and it’s been apparent in the research, has been that is…It eases customer anxiety. Because if you say, “Hey, we’re releasing this thing and you can use it,” but you don’t announce what the gates are, that creates tension and anxiety on behalf of the person. 

They’re like, “Well, if I don’t know, I’m just not gonna use it.” 

So by doing that, you’re actually helping them adopt it more and saying, “Hey, we’ll have a thirty, sixty-day announcement period before we start enforcing it.”

You have a dashboard that shows your usage, so you understand where you are. And also maybe you run that in different tracks. So, you know, new customers versus existing customers have different, you know, policy of enforcement and timelines associated with those. And then it’s once you get to GA that it’s like, okay, we, we now know what this looks like.

And then alongside that, one good practice is making your initial gates that you explain in early access more conservative than you expect, because it’s very customer friendly to then when you get to GA be like, “Hey, you know, before we allowed you to ask, you know, twenty queries per user per month, we’re now gonna up that to a hundred.”

Everyone’s gonna be happy. No one’s gonna have any complaints. You go the other direction, we had a few bad examples, even in the past month of companies going the other direction and that causes a bunch of problems. So, having those in combination can really make for a much smoother rollout as you learn.

Mark Stiving

Yeah. That’s brilliant. 

Dan, we are gonna have to wrap this up. We’re running out of time already. 

But final question for you. What is one piece of pricing advice today you’d give our listeners that you think could have a big impact on their business? 

Dan Balcauski

I’m gonna steal this from my friend Ethan. Sorry, Ethan. 

Earn the right to monetize.

Mark Stiving

Okay, give us more. What does that mean? 

Dan Balcauski

Earn the right to monetize meaning, you know, summary of what we’ve talked about. Go out there, prove value with your new AI features before you throw a paywall in front of it. 

Mark Stiving

Nice. Demonstrate value before you charge for it. Absolutely. 

Dan, thanks so much for your time today. If anybody wants to contact you, how can they do that? 

Dan Balcauski

Folks could reach out to me at LinkedIn. Happy to connect with folks there. Just let me know you heard me on the podcast so I can separate it from the rest of the LinkedIn spam. 

Folks can also go to my website, producttranquility.com. Can’t say I write as often there as, as Steven does on his substack, but I try to, you know, be present there. 

I also have a podcast of my own called SaaS Scaling Secrets where I interview scale-up B2B SaaS CEOs. It’s not pricing specific, but sometimes we do touch on pricing, so folks can find that wherever podcasts are available.

Mark Stiving

Awesome. 

And to our listeners, thank you for your time. If you enjoyed this, would you please leave us a rating and a review? 

And finally, if you have any questions or comments about the podcast, or if you wanna get paid for the value your buyers can’t see, email me, [email protected]. 

Now, go make an impact.

Advertisement

Thanks again to Jennings Executive Search for sponsoring our podcast. If you’re looking to hire someone in pricing, I suggest you contact someone who knows pricing people. Contact Jennings Executive Search.

[Outro]