Name: The science behind successful pricing strategies
Uploaded: 2025-09-04T15:15:27.013Z
Duration: 44 min 40 s
Description: The science behind successful pricing strategies

Transcript for "The science behind successful pricing strategies": Hi, everyone, and welcome. My name is Helen, and I'm a product marketing manager at Stripe. Thank you so much for joining us today. I know we're all here to talk about pricing. So before we start, I'd actually love to get a sense of who's in the group and how you're pricing today. There should be a poll that just popped up on your screen, so let us know what pricing model you're currently using in your business. And while we do that, let me just do a quick introduction. For those who might be unfamiliar with Stripe, our mission is to grow the GDP of the Internet. So Stripe provides the financial infrastructure for the Internet. Last year, 1.3% of the global GDP actually flowed through our platform, and we're also helping companies scale the subscriber base globally with integrated billing and payments, tax compliance, and support over a 100 payment methods. Today, we power millions of businesses from industry leaders like Atlassian and NVIDIA to leading AI companies like OpenAI, propensity, Livable, and ElevenLabs, and so many more. Actually, 78% of the Forbes top 50 AI companies are already building on Stripe today. So why am I here today? As a product marketer, I work with users day in and day out on their billing needs, which often turn into these broader conversations about how should we price our products, especially in this era where AI is really changing the pricing landscape a lot. So if we take a look at the poll results just now, if we can pull that up on the screen. Yeah. That seems to be the case here today too. There's a lot of different ways of pricing present in the audience. So today, I actually brought along my colleague, Julius, to share his perspective on pricing alongside me. So, Julius, why don't you introduce yourself? Hi, everyone. I'm Julius. I lead product for Stripe in the, Germany, Austria, Switzerland region, and Central And Eastern Europe. First of all, super excited about all the different messages in the chat. Seems like you are really we really have a global audience, which is great because Stripe is truly a global company and a global product. I joined Stripe about a year ago, and before I joined Stripe, I ran my own SaaS company. And so the two business that I ran was a crypto portfolio management and tax accounting software, specifically, for the NFT space. Rest in peace if anybody remembers that back in, 2122. That was a pretty hot topic back in the day, and my tool helped subscribers figure out how their trades were going, if they were doing well, not doing well on given given crypto trades. And it's primarily a b to c product. So my users were, consumers, but what kind of business characteristics because they were signing up to a I I did. I had various different pricing models, which we can talk about in a second. But the main pricing model was a flat subscription fee, like a a a monthly €10 a month or a €100 a year fee. And learned a ton about pricing, to be honest. I I had to experiment a lot because, the software offered both this, like, portfolio and trading profit insights, but also tax reporting, and I kind of, like, switch back and forth on how to price each of these different products differently. And funny enough, I was also a Stripe user before. So I was a user of Stripe's subscription management suite, Stripe Billing. And I'm I'm very proud to say that I built the entire back end integration myself pre pre LLMs. So a lot of stack overflow and googling. Pretty amazing. Awesome. Well, it's so great to have you join us today. I think it's gonna be really great to get your perspective from the product side and also, you know, as a business owner, and having gone through some of those pricing decisions firsthand. We actually have a pretty packed agenda ahead of us today. So on my end, we'll actually share some data that, from new first party research that we did here at Stripe. We actually surveyed over 2,000 global businesses across industries. And what we did is zooming in on specifically the high and hyper growth companies, both of which have a very impressive revenue growth rates year over year, and we wanna see how they're approaching pricing differently. And throughout, really wanna pick your brain, Julius, on, you know, a pricing framework that can help folks here think about testing and iterating their own pricing strategy in their own context. And, of course, we'll end up with, q and a to address any questions. So please do submit them throughout in the q and a session that you see on your screen. So if we go to the next slide, just to set the context, I think it's very clear that pricing is extremely top of mind right now because when we did our survey, 65% of global business leaders said that they aren't actually sure if their pricing model today will support their needs in the future. And even a bigger percentage actually consider this ability to adapt pricing quickly to be a very key competitive advantage in the next one to two years. So, Julius, why do you think that is and why is it so top of mind right now? I generally think that we're seeing a pretty rapid and evolving landscape when it comes to software and software businesses. So we and pricing kinda just reflects that underlying shift. So, I mean, we all know with the rise of AI that the way that you have to price for AI services is pretty drastically different than how you have to price for a traditional SaaS just because the underlying cost models are pretty different. So with SaaS, you're typically if you're thinking about about classic business terms, you're typically only constrained by fixed costs that kinda scale they don't scale they scale so linearly. Whereas with, AI, you're you have a lot more variance and costs. And so you can't you don't have zero, like, the classic zero margin distribution software model, but you have pretty high variable cost in every, like, additional user that you onboard. And so your pricing kinda needs to reflect that. And what we're seeing in the market is that a lot of businesses are experimenting with all kinds of different models. And we're seeing this evolution from sort of flat rate and proceed pricing to, freemium. That's something that I did in my company, for example, reverse trials, all kinds of add ons. And then now to usage based pricing, credit based pricing, hybrid, outcome based, like Sundar just mentioned on the channel here. All kinds of, like, all kinds of different new pricing models. And we're seeing that what's fascinating is that these AI companies and, if you go to the next slide, you can see that, AI companies are growing at a crazy pace and you're I mean, you're seeing it in the headlines all the time. Like, cursor hit, I don't know, a 100,000,000 in ARR within eleven months from founding. You see this sort of growth trajectory from single digit million ARR to double digit. Like, that is just drastically accelerating. And with that and the sort of rapid adoption of new, like, yeah, new value generating software businesses, you're also seeing explosion in pricing complexity. And another interesting stat or another interesting fact here is that if you compare it to sort of the SaaS how SaaS companies were scaling back over the last decade or so, AI businesses are scaling vastly faster. And what we're observing on Stripe, and this is also a function of of companies like Stripe and and and in general, the ambitions of these companies, they're grow they usually go global first. So they sell in all kind of geographies, not just, let's say, a German company in Germany or Europe or a US company in The United States. No. They sell, globally. So I I think those are some really, really interesting trends. Yeah. And I think this pace of growth definitely, you know, poses those challenges that you talked about, but also kind of, like, amplifies it because you have to adapt so quickly. Right? And so when we talk to, you know, this group of businesses within our survey, we kind of see the same things and trends, like, surface out. Like, these challenges that spans from having margin risk due to the cost that you talked about, you know, this new way that AI delivers value that is, like, very context dependent. And underlying all of that, they need to change around their pricing infrastructure to implement these more complex usage space or hybrid pricing models in order to counter these challenges. We see compute cost being cited as a top concern, and we see that defining value is really hard for them. So with all of this context, I really wanna bring our conversation back to our core question today, which is, you know, what is the best way to price an AI product, and what makes a pricing strategy successful? Right? And because we're talking about, like, science, I'm gonna start us off with a data point. So one thing that we noticed when we looked at high and hybrid growth companies and what they're doing differently is that the rate of pricing experimentation were very significantly correlated with growth. We see that these fastest growing companies were more likely to report having changed their pricing three or more times within the last two years, which is much higher than their lower growth counterparts. And so from all of this, what I parsed out is that there's not one single pricing model or method that won. But what we see is that across the board, these companies really focus on flexibility. They're showing an eagerness to combine pricing models, to experiment more with pricing, and to really see their value of their product as something that continually evolves, which is why they changed their pricing alongside with that. So, Julius, I wanna get your initial reaction to this data point. Yeah. It's a great, I mean, it's a great data point. All good companies change their pricing frequently. You also know this as a consumer. Pricing changes are obviously hard to do, and I think there are sort of two things there's two things going on. There's one and by the way, if you guys want to pop in stuff into the chat, I love the interactions. This is supposed to be, fun, so, be interactive. So there I think there's two things going on. With AI, you're seeing massive and unprecedented growth, and it requires experimenting. Like, these are things that people haven't really figured out if you're if you have variable costs all of a sudden and your marginal cost of distribution is not zero, but it can actually be quite high. You need to figure out how to price. Like, SaaS pricing is not gonna cut it because if you do flat fee pricing, you you're kinda screwing yourself as a business, unless you really severely restrict usage, for example, which is definitely something you can do. So I think that makes sense. And then the second part, which I find which I found myself reflecting on is the availability of tools to make pricing easier has also been exploding. There's a lot of subscription management tools out there and including, obviously, Stripe, the best one. But it like, these tools make it pretty easy to change and adapt your pricing because you don't need to, like, you don't need to go in and do massive code changes and, like, like, you don't need a dedicated engineer to change your pricing. You even as a even even me as a, script monkey PM, even I can do that. You know? And I I think that's been really helpful for people to be able to adapt their pricing models on on the fly. And I can I can give you a specific example for my business? So I used to have a flat free flat fee subscription, €10 a month that covered the, like, trading reports, which are, like, a bunch of nice charts, a dashboard. And then there would be, like, a downloadable tax report, kind of like when you if you've ever used, what's the name in what's the one in The US, Helen, that you always use for tax reporting? Like, doing my own taxes? Yeah. There's these tools where you, like, you put in all your stuff and at the end of the year, you pay tax like that. Yeah. Turbo tax. Exactly. Exactly. Like TurboTax. So it would have, like, this annual report like TurboTax at the end of the year, and it was included in the subscription. And then I realized that a lot of people that want that report, they don't actually wanna have a subscription to a tool. They wanna have the feel like, people don't like the feeling of being charged on a monthly basis for something that they only use once, and so I split out the pricing. So I made the I made the report. I I priced it separately, so you pay, like, €60 for the report or €7 for the report. And then you would get an option for an upsell into subscription that would then be cheaper. Or if you're on a subscription, the report will be included or it would be cheaper. And so, like, these are just these small realizations where you just gotta try to anchor pricing onto the value that you're creating for users. Yeah. That definitely makes a lot of sense. And, you know, as a consumer of those sort of products, that definitely resonated. Right? Like, I think in general, there is some sort of, like, a subscription fatigue in some way. I think that's causing a lot of business to kind of change around their models too. So you talked about how you've changed your pricing in your own business. You also work as a PM at Stripe. So tell me a little bit more about, like, how you have approached pricing. Are there any frameworks that you use and found helpful? Yeah. Actually, I I kind of alluded to that already. It all comes down to the value that you're creating for your user. And so you can define a value metric value metric. Like, what is it what is it that you are, like, what value are you creating for the user? And so you can you can make this pretty granular if you want to. You can make it high level. So going back to the tax report example, you can either price the entire tax report, and that is value that you generated for the user, or you can even go more granular. Let's say the person had 1,000 trades, then the tax report will be a €100. If they had a hundred fifth a 500 trades, then it'll be a €150 and so on. And so you're tying it more to the value that you're generating. And in the case of the tax report, the time saved by not having to manually check all your transactions, if that makes sense. Yeah. I think that makes a lot of sense. And I think it's something that, generally, customers seem to want as well. In our survey, a majority of our business says that their customers are increasingly pushing for outcome based pricing, which is a very good way of having a very tangible value alignment to how you're pricing. But when we look at the actual execution, only 32% are actually defining their usage this way. What's interesting is if we zoom in on those fastest growing companies, they're much more likely to have already adapted to aligning their definition of usage with outcomes. And I think it just shows how once again, like, part of their growth is probably related to how they're able to adapt their pricing with how customers perceive value. I'm gonna drop in a little example here. One of our users, Intercom, is a really great example of doing this well because when they launched the AI agent, Fin, they used to have a seat based pricing model, and they realized that that didn't work anymore because the better their AI agent, Fin, performed, the fewer seats that a customer would actually need. So there's, like, a misalignment there in terms of pricing. So what they did instead is they added a pricing element to charge based on support ticket resolutions. So not the number of interactions, just successful results. So their customers are paying when they actually receive value, and then Intercom's revenue grow only when their customers succeed. So then the pricing becomes a thing that aligns everyone towards the same objective, and it's I think it's a really great example of how a company can use pricing as this tool and reshape along the way to align more closely with the value that they deliver to customer as their product evolves. So, Julius, with that, I do have another question for you. I think the intercom example is great because the value was like, you know, the type of outcomes that the product offer is so clear. But what happens when there's a disconnect between what you can measure and how customers perceive value? Because, you know, sometimes the technical units don't match up with how me as a customer would understand the value that I'm receiving. Yeah. It's a pretty that's a pretty tricky challenge to find out, and it's not, as you said, it's not often clearly defined. Like, not every company has a tax report thing where you can, like, clearly tie the value that you're generating to a price. So what what we're seeing, especially in growing companies as they're adding more features, like, you have your core product, you have some AI add on, maybe you have enterprise support, maybe you have, like, a bunch of usage based components. Like, it becomes really, really complex and almost like a math problem, not only for you, but also for your users. And so users start losing control and they start using, they start losing predictability. Like, it becomes pretty hard to predict how much you're gonna be spending on this given tool. Also, obviously, internally for yourself, like, your billing and finance teams are gonna go nuts if you're gonna have, like, I don't know, 30 different subscription tiers and, like, add ons, yada yada. And so what we've seen in the market is credits, kinda like an abstraction layer. So you the the simplest example is, let's say, a company has, like, three three products, AI to text, text to AI, and then a speech agent or something like this, and they charge $10 a month and you get a hundred minutes. And you can distribute those hundred minutes freely across these three products. And so instead of having to buy each of these products by themselves, you can just, you can just use them however you want until the credits are used up. And it kinda aligns the incentives well because you still as a as a company, you still get the benefit of predictable recurring revenue, but also, you're there is an immediate upsell opportunity if the upper if the credits are being used or or if they're used up. So companies can buy new credits or they can go into a higher tier. And if they don't use up the credits, either they carry over or they they're not being used. And so you're not gonna suffer the cost basis of that because every credit used and this goes back to some of the comments in the chat. Like, every credit used is costly for you. And it actually, you can so there's a bunch of different companies that you can look up that do this. Eleven Labs, one of our one of our customers in Runway, they both do this. So if you go to Eleven Labs, there's a they have various types of subscriptions where you basically just purchase credits, and you can use those credits across their product suite. Yeah. I think that's a pretty pretty neat one. Yeah. I agree. I think their pricing is definitely very interesting. And we're gonna circle back to, a little bit of a closer look of how ElevenLabs grew towards the end. But back to, you know, these steps that we're going through in terms of pricing. So then I assume from here, we're bringing all these components in terms of, like, how we want to charge and how to actually package and put it together into a pricing model. So, we have the stats here in a survey. We actually see that, like, hybrid models are really gaining traction, and they're kind of taking over traditional subscription models. 36% of businesses reported using hybrid pricing. But more significantly of those who aren't using it yet, 61% says that they're planning to do so within the next year. And it's not shown on this slide, but this is actually even more prominent in the AI space because when we segmented out AI industry businesses in our survey, 56% so over half of them already offer hybrid pricing today. Julius, why do you think that's the case? Well, we kinda talked about hybrid pricing already a little bit with the with the credit and the subscriptions, and it just makes sense because it makes it clear like, going to a pure usage based model is kinda hard. Like, are you going to build an agent on a given like, OpenAI actually, funny enough, has this challenge. Right? If you build an agent on OpenAI and you don't really know what it's going to cost and you're just subscribing to credits and you it's the classic, first time people have had this the AWS and the surprise, cloud infrastructure bills. Like, usage based billing can be pretty hard for people to comprehend. And so if you put natural caps on it, and Panos, this actually goes to your point on like, isn't it harder to understand for small companies? It's harder to understand for small companies if you have pure usage based billing. But if you help them put caps on it, like, hey, $20 a month, you get this and that many credits, and you make it super abundantly clear, especially in the dashboard view on how these credits are being spent across different, like, product categories or product usages, then I think it's a lot more it's it's probably one of the best pricing models we have for this date and time because it just creates transparency. It creates security on the, for the companies offering these pricing models. And, yeah, you from the company side, you also, like, usage based models or, like, you don't wanna do, like, flat you don't wanna do flat fee models because those can really screw you up if you have certain users. And you always see this. You kinda have the the on on many of these, like, AI model companies. And I'd love to hear examples in the chat, actually, if you if you have concrete examples here. But what you're seeing is that you have whale users. Right? The users that'll go in, they abuse your free trial, or they'll sign up for some flat fee, and then they do a crazy amount of requests or and that can really eat into your margins. And so you gotta be super hyper careful with this. And I I think these hybrid pricing models kinda strike the right balance. I'm sure we'll find more innovation or more different. Like, we'll see how that develops. So maybe the prices for inference or, like, AI AI usage will go down over time. And so maybe that's not gonna become a concern. Maybe it's gonna become zero margin again, TBD, or zero cost. Sorry. But we'll see. Yeah. Yeah. Yeah. There I I think this what's really fun about being in this space is I was changing so fast. So we're all kind of figuring it out as we go. You know, what's really interesting is one thing that I hear from users is that they know what they know that they want to do a hybrid pricing model, but they don't actually know how to construct this. So I'm gonna use this chance to share this framework that I like to call gaps. And it's really based on four key dimensions that looks at both your customer related and your business related priorities, to decide how you should build out these different levers within your hybrid model. So looking at growth, asking the questions around how easy is it for your customers to grow with your products as they increase their usage? Is there a path built in for your business to capture the additional revenue, from that incremental value that you're providing to your customer? The second thing is about adoption. So this is all around the barrier of entry, especially with AI tools being a little bit more novel and fairly new. Some customers might not be open to paying a lot upfront. So what does that path look like for them to start testing your product, especially in cases where they might not want to have a very big upfront commitment? The third thing, Julius, has talked about this a lot, which is the that revenue predictability piece. Does your model allow for you to forecast your own revenue? And similarly, for your customers too, they probably want to have some predictability on how much they'll be spending on your tool. So providing a means for both you and your customers to do that. And the last part is safeguards, and this is all about risk management. I think throughout the session so far, we've talked about the risk in terms of variable cost and running an AI business. So how are you protecting yourself against risk, whether that's usage spikes, a few bad actors, even, like, a fraudulent transaction that, like, runs up your usage, and then you're ending up with footing the bill. So it's really about balancing each of these considerations depending on your business priorities to find the right model. I think Julius has already gave some examples on, you know, if you want more predictability, find something that gives you a recurring revenue. But if you're really focused on, you know, the acquisition and adoption, skewing more towards that usage base, like, pay as you go path might be a good way to go. And there's so much mixing and matching that you can do of, like, having some flat fee component with usage included, using credit bundles. And I think, like, to echo what we talked about in the beginning, there's not necessarily one perfect model, but you can definitely build something and evolve over time for, like, that model that is perfect for you at that instance. Any reactions, Julius? Yeah. I I first wanna react to what Carl said here around, fair usage. I think you just got a cap usage, honestly. It's kinda when you sometimes when you're a renter and you go into, like, Airbnb. Right? Airbnb's typically have uncapped utilities, but you could technically bring your Bitcoin mining rig and just drain all the electricity in the neighborhood. And it's hard to protect against that. But as a business, you do wanna protect against that. And so putting putting, like, tangible safeguards in place, like, either you stop usage after a certain degree or there's, like, a number of tokens or credits. You see this often in API pricing as well, actually. So the gaps, framework that you talked about, I I really like that. I think it's a really nice way to as a as a as a product manager, you typically get pulled into a lot of different, directions. Right? The sales team, they just want the simplest price to sell something. Finance and billing, they they want it to be easy on the back end and make it predictable. Engineering wants to have something robust, and your risk compliance wants to have safeguards in place. And by the way, safeguards in the world of SaaS were not really a thing because you could just, you could usually just YOLO it and then scale up. You just gotta look at your cloud bill and make sure that that doesn't explode, but that typically, like, unless you configured something wrong was not really a problem. Totally different with the AI in the AI world now. So with this framework, you can, like it's a nice way to think about the trade offs and, like, forces you to be a little bit more intentional about your pricing strategy and and look at it from a couple different angles. Right? Customer acquisition, growth, predictability, and risk. So just nice to get everyone on the same page and and make a decision that that involves every stakeholder. And I think product has a very special role to play here because product is typically closest to the user and their needs along with sales. And, like, on the products that you really need to tie all of that together and I think the most important thing there is and I'm I'm not gonna get tired of saying this. This is a Stripe webinar after all, but I I also truly believe it. You gotta have the right tools to do pricing. Because if you don't, you're setting yourself up for failure. If you if you just do your pricing in the back end in code, like, good luck with changing that because over time, that'll become an absolute monster and an impossible to maintain. You need to have flexibility. You need to be able to translate your pricing into your pricing choices into software, into code, make that as easy as possible with no code ideally, and then also into payments at the end of the day. Right? Because people have to pay for these different solutions. And, if you wanna do recurring subscriptions, etcetera, like, not every payment works equally for this. So little bit of a side tangent, but it's important that when you're thinking about, hey. I do wanna do a lot of experimentation on pricing, and the experimentation on pricing is key. Set yourself up for success now and, like, don't, yeah, don't build hobble together crazy custom solutions. Just get something out of the box. Like, doesn't have to be Stripe. It should be Stripe. It doesn't have to be Stripe. It should you should get a tool. But that is so true because we do get a lot of users coming to us. You know, they started their business and they want to go to market. They built kind of their homegrown billing solution. And it worked fine for a while, but then with the speed that things grow, you have to do these iterations. And they just become, like, such a big thing to manage. And, you know, engineering resources are scarce. There's not enough time for anyone in the day. And so having to pull some of that talent and resources over to manage your billing and payments infrastructure instead of working on your core product is just not the best way to use time. Right? No. It's actually horrible. And, like, it's like, it's and it's not just about billing. It's about, like, how do you recognize your revenue? How do you, like, calculate tax as you expand into different markets? And it's it's like you need to have a different point of solution every time. Like, it's expensive. It takes forever to do these integrations. So that flexibility is so key and such a common pain point that users come to us trying to solve. To bring that us back to our conversation, there's been a lot of chatter in the chat about, like, safeguards, building our guardrails, you know, risk management. It was like a consistent topic throughout this whole talk. So, Julius, tell us about guardrails. Like, what are some strategies, levers that we can do to mitigate some of this? Yeah. I mean, I I touched upon it a little bit already. I actually think the, someone mentioned utilities. I think utilities are such a perfect example because utilities have to manage this all the time. And the way it works in Germany and in The US too, if I remember correctly, is you just pay, I don't know, like, $50 a month. And then at the end of the day at the end of the year, your utility provider sends you a bill. Oh, you overspent by, like, I don't know, $50 to $600 a year. So you you actually spend a thousand dollars on electricity, so pay me an additional 400. So I actually think that works well in utility. And the reason why it works well in utility is because users are not gonna turn off utility or just kinda, like, evaporate into thin air. They're usually gonna pay those $400. But in SaaS or in software, a lot of users might just, like, write off into the sunset once you sent them the $400 and never pay it. So you gotta think about a way how you can stop them from overusing. And a fair fair usage policy I don't know how you would define that, Tony, but if if it's just like, oh, please don't spend more than x. Otherwise, we'll be angry. I don't think that works. I think you need to draw hard lines in the sand. That that's my take on this. And drawing a hard line in the sand honestly, there's a lot of variation. Like, if you're doing credits, for example, are you gonna when credits roll, when credits deplete, like API calls is a great one. When your API could call credits deplete, is there, like, an auto top up? Do you need to do a manual top up? Do the credits expire? Do they roll over to the next month? Do you like, what happens if you upgrade a subscription? Yada yada yada. There's, like, all kinds of ways that you can think about this, but I would always put pretty hard limits in place. And I think I just think credits are a very elegant way of doing that. Anyway, just a just a couple of thoughts. At the end of the day, it's really about and I think that I I hope this comes across in this in this webinar. There's a lot of options in this space. Right? And, ultimately, you have to iterate on your pricing strategy. Pricing is not set and forget and that's it. Like, you're not gonna get it right the first time. You're absolutely not going to get it right. It's going to be bad for you. It's gonna be bad for your customers. But over time, you will get it right, and you'll get it right by experimenting. When I've been working in product for about fifteen years, and if you have product people on your team that don't see pricing as core part of the responsibility, I would seriously consider whether they have the right whether they're the right fit for the job. Because thinking about pricing and thinking about how what what is pricing at the end of the day. Right? Pricing is how you tie how you put a number on the value that you create for you. And on product, that's your whole freaking job is to create value for the user. And ultimately, being able to put a number on this is a core part of your job and that requires constant experimentation. And you'll see this in the wild. The most successful companies in the world are the ones that are constantly iterating with their pricing to find out what works best. And, yeah, it's not, as I said, not not set and forget, but, like, just try out and see what see what sticks. Yeah. Totally. If there's one thing to take away is that that flexibility is key. As promised, we're gonna close this by looking at ElevenLabs case study, because they're just such a great example of how fast a business can actually grow in the AI era. They searched a 3,000,000,000 valuation within two and a half years. And within all of this, right, like, this ability to stay agile and move fast was such a big part of it. They've actually evolved from a flat rate subscription to integrating usage based billing. So like Julius Danek has mentioned before, they now have a pricing model that charges per month of credit grants that can be spent on their various services. So if you're interested, definitely go look at their pricing plans because it's actually a very great example of using credits to kind of, like, abstract away the complexity and map their pricing to value. And throughout this period of rapid growth, they've also added many services. They've added enterprise level offerings. And what has allowed them to move so fast was this underlying flexible billing infrastructure, that Stripe actually provides across billing and payments and their different revenue needs. So for example, they were able to set up and maintain their subscription billing with just one engineer on the team. And then as they expand, they were able to do that by just doing simple adjustments to their setup. And this is actually really huge because that means the rest of their engineers can just focus their time and energy on core product development, which ultimately is what drives growth and is delivering value to their customers. So before I pass on to q and a, and I'll start looking at some of these questions, Julius, any takeaways, like, last bits of thoughts to share the audience here? Yeah. I just loved I just loved the last comment here about multiyear contract. So I I I used to work in the hedge fund industry before, and we sold data to hedge funds. And a lot of the agreements were kind of all you can eat contracts, and it's a lot harder it's a lot harder to have pricing flexibility when you're on multiyear contracts. Yes. But I think if you're again, if you're a product and you're multi year contracts and enterprises are typically you're not gonna have, like, 10,000 unless you're you're SAP. Right? You you will typically have a couple and those will drive a large portion of your revenue. And if you on the product that your product gets sold in there and you're not sure about, like, certain features and how they will monetize. I have a couple examples right now actually that I'm working on. Talk to the sales folks and make sure that some of the contract links or contract terms align with what you wanna see. Right? Like you gotta you gotta be close to these processes, especially if it's like outlier contracts where you can like, where you can make sure that you have the room for experimentation. Sometimes it's very valuable to have long term contracts, right? Like three, four, five years. Sometimes if your product is a little less mature, you might wanna have shorter time periods. It really depends. And also, like, obviously, there's a whole component of, like, business objectives and cash flow, yada yada yada, but that's just my take from the from the product side. Yeah. Overall overall, to sum it up, you gotta anchor your price and value, not costs. I think that's pretty that's pretty obvious. Like, think about what value your product creates and then price it accordingly. Right now, with AI models, use a strong use strong guardrails, with hybrid models. I think the the Eleven Labs example is pretty nice. When you think charge metrics are also a very nice example, especially from from Intercom, like, right, the number of successful customer interactions, I think is that's a very easy and and and beautiful one. And then I think my key point from this, and I hope you all took this away, is, iterate on pricing just like you do a product. Right? It's like when you experimentation is key. You're never gonna grid it. Right? Just like your product. Your product is never gonna be perfect unless you have a government granted monopoly, which, I I guess few people in this chat do. So Alright. So on that note, I'm gonna start throwing you some pressures, Julius. So the first one that we have here from Gishma, if we're thinking of bundling products that are currently sold with different pricing models, how should we approach pricing? What's the right balance between simplicity for the customer and sustainability? Look at the ElevenLabs website. I actually think they do it quite nicely. So they have this, like, they have this model where they have, I think, five different subscription tiers, and each subscription tier scales and usage credits. But not only usage credits, and I think that's key. It's actually quite a very nice example. They also scale it with the things that you can use. So on the, I don't know, amateur plan, you're going to pay $5 a month, and you can only use one specific feature, and you get a 100 credits. On the next tier, the $10 plan, you get, let's say I don't know what do I say, a 100 credits. Let's say you get double the credits, 200 credits, but you unlock, like, I don't know, five new features on the platform. And so this is actually a nice staggered way not to just do the the the credit based pricing, but also bundle in different features, into different into different categories. If you think about how SaaS works predominantly today, it's usually, like, the three three pricing tiers. Right? Like bronze, silver, gold, and then the gold the silver one is always highlighted, and that's the one that most people choose, with, like, a bunch of features. But I think in hybrid based models, you can do the same. I also do think there's an interesting nugget in there in terms of, you know, thinking about simplicity, you know, depending on what their business priorities are. Maybe having a more simple plan is the way to go. When we talk to intercom, they actually talked about their thought process behind this very simple outcome based model, and they're kind of taking on the risk of, you know, some resolution, some resolve tickets are gonna take more interactions, and it's gonna cost more from their end. But at this point, they're focused on that customer acquisition. They want to get people on board and really get comfortable with this model, and they're really aligned with the value delivered. So they opted for more simplicity in the model versus, you know, tearing it out in more, like, various complex ways. I think we can do maybe, like, one or two more questions. So, the next question yeah. Sorry. Go ahead. Oh, no. No. Sorry. Go ahead. Okay. So the next question is from Helen. When a customer's usage drops, is that a sign of an issue, and how should we be tracking to distinguish between healthy, low usage customers and those at risk of churning? I think it's a function of time. Right? As you said, there's, like, a pattern. If they're healthy low usage customers, then they should be bottoming out at that. And if you actually, I think it's most instructive if you see a whole bunch of these, if it's not just, like, one single customer that all of a sudden does this. But if you if you consistently see that, it might also tell you that maybe your pricing is not perfectly aligned for these users. Maybe you could maybe you need a maybe you need a lower pricing tier, especially if they churn. Yeah. I think it's like a that's a that's a bit of a hard question to answer, but it's just something that you gotta monitor and you gotta you gotta build a pattern of these users. Right? You gotta you gotta see over time, like, how would how does their behavior change? Do they keep on being in this, like, low usage pattern or do they actually churn? And if they actually churn, why do they churn? Right? I do think, Lisa and and the important thing that you're saying here is you're already tracking the usage. Right? That's the that's pretty advanced. Like, a lot of companies don't even get to that point. Right? So if you're tracking that and you're already aware of it, you won half the battle. Yeah. And I think that that, like, having that data on hand is so important. We actually have some of our users that meters across multiple dimensions, but they don't actually charge on all of those dimensions. It's more of like a a data collection method of you would say to see what usage patterns emerge. And sometimes they find interesting things within, oh, users are actually finding incremental value based on these specific attributes, and that kind of opens up a path for them to make more informed decisions on their pricing. Also love this question about forecasting for pricing. I usually do it myself, because at the end of the day, it's my product. And as a product owner, like, I I usually get incentivized on the success of my product, not like sales, obviously, where you get a commission, but typically, your incentives are tied up to the growth of a product or a margin. And so you better do you better know how to do forecasts, because finance and data science teams often don't have time to do your to do that work for you. So you better have a little bit of skill there yourself. It's not the perfect answer, of course. And, obviously, there should be a tool for that. But Yeah. Let's do one quick last one. Claire asked what are the key measurements tools to track usage? Let me see. Oh, jeez. There's so many out there. Google I use Google Analytics. I use Crazy Egg to see see John's screen. You can actually just do, like, the very bare minimum. It's just, like, your monetization because that's probably what you're gonna be tracking initially. It's just, let's say, how many people are actually purchasing stuff and what are they purchasing, and then you can just get more sophisticated, with installing trackers on your web page and, like, I don't know, Optimizely ample there's, like, there's so many tools out there that do this, but I actually think if you're starting if you're a small business, you don't have to worry about that too much. You just you might just wanna worry about, like, if you're doing freemium subscriptions, like, conversions, you wanna look at trial conversions, that's an important one. That one you should definitely track. And then, yeah, just help help folks are purchasing. Yeah. I think Just just to plug, since this is a Stripe webinar, we do have a usage based billing product of Stripe that allows you to track usage based and meter how your users are using your product and bill accordingly from it. So, like, that can surface a lot of insights, and there's, like, analytics that comes with it to help you really gauge those patterns as well. I think that's all the time that we have for today. Thank you, Julius, and thank you everyone here for joining us. We really love having these conversations, so do connect with us on LinkedIn. We'll put our LinkedIn profile in the resources. So come say hi, and then we can continue from there. We'll be sending out the recording, following this. And then if you have any questions or would like to learn more about how Stripe can help support, your payments, monetization needs, reach out to us to talk to our team. Thank you so much again, and have a great day. See you.