Stigg is a powerful, flexible monetization platform that lets engineering teams deploy complex pricing and packaging changes instantly—replacing brittle billing systems with a scalable, unified API-driven infrastructure. With Stigg, SaaS companies gain full control over entitlements, usage metering, and subscription management, accelerating time-to-market and saving hundreds of development days.
In this episode, we speak with Dor Sasson, CEO and Co-Founder of Stigg, on the evolving landscape of pricing strategies in the SaaS industry. We explore how traditional static pricing models are becoming obsolete in the face of AI-driven, usage-based models. Sasson shares insights from his experience at New Relic, where he faced challenges in monetizing AI products, leading to the creation of Stigg. Stigg aims to provide a scalable monetization platform that allows software businesses to implement flexible pricing strategies without the complexities of legacy systems. The conversation covers the importance of aligning pricing with value, the shift towards hybrid pricing models, and the organizational challenges enterprises face in modernizing their pricing infrastructure. Sasson emphasizes the need for a collaborative approach within organizations to effectively implement new monetization strategies.
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Show Notes
Takeaways
- SaaS companies are often stuck in outdated pricing models.
- Stigg aims to transform how software businesses monetize their products.
- The shift to usage-based pricing is becoming essential for AI companies.
- Monetization should focus on value rather than just billing.
- Organizational structure can hinder pricing strategy implementation.
- Packaging changes are often more impactful than price changes.
- A strong foundation and team alignment are crucial for successful monetization.
- The credit economy is emerging as a new model for pricing.
- Flexibility in pricing strategies is key for enterprise success.
- Effective communication is vital when implementing pricing changes.
Chapters
00:00 – The Evolution of SaaS Pricing Strategies
03:58 – Stigg’s Origin and the Monetization Challenge
09:42 – Understanding Monetization Operating Systems
14:58 – Trends in Pricing Models for AI and SaaS
19:51 – Overcoming Roadblocks in Pricing Infrastructure
24:56 – Implementation of Usage-Based Pricing Strategies
29:47 – Advice for Rethinking Monetization Strategies
34:45 – Future Directions and Innovations in Pricing
Transcript
Beau Hamilton (00:02.93)
Hello everyone and welcome to the SourceForge Podcast. Thank you for joining us today. I am your host, Beau Hamilton, senior editor and multimedia producer here at SourceForge, the world’s most visited software comparison site where B2B software buyers compare and find business software solutions. Now when it comes to pricing strategy, most SaaS companies you could say are sort of stuck in the past. They’re locked into these hard coded plans that make every tweak a mini engineering project, so to speak. But in today’s AI world with usage based models, and enterprise level flexibility demands, static pricing just doesn’t quite cut it anymore.
So on today’s episode of the SourceForge Podcast, we’re joined by Dor Sasson, Co-Founder and CEO of Stigg, a company that is sort of transforming how software businesses price, package, and monetize their products. They call themselves the first scalable monetization platform for the modern billing stack. And Dor brings a pretty unique lens from his time over at New Relic, where he helped lead the charge on monetizing AI in a public company setting, a challenge that I would say sort of planted the seed for Stigg’s creation. I’ve got a lot of questions for him about his background. I also plan to ask more broadly about how Stigg is enabling front-end and back-end teams to roll out pricing changes without a lot of the headaches associated with that.We’re going to talk about what flexibility looks like in air-gapped enterprises and what the future of outcome-based pricing might hold.
A lot to cover. Let’s get right into it. Dor, welcome to the podcast. Glad you could join us.
Dor Sasson (01:33.006)
Thank you Beau, thank you for having me.
Beau Hamilton (01:35.472)
Now, can we start with Stigg’s origin story? What problem were you trying to solve when you founded the company and what sort of inspired you to approach the monetization kind of conundrum specifically?
Dor Sasson (01:51.342)
So it’s a really good question, Beau. Thank you for conceding the stage. I think the main thing for Anton and I when we first taking together first steps of building the company, we were part of the new relic team. We were building, especially focused on AI offering, AI product line within the Neuralic larger portfolio. And we were almost, could say, so to speak, almost the first product group that had to face the reality of what it means to deploy machine learning models in production and what would be the most efficient, effective way to go out and monetize them.
And I’m not sure it would become a surprise or not, but initially the core idea within the organization was to actually give away some of these features for free. Now the problem was, at the time Neuralic was monetizing based on seats. And the key problem was, well, if you give those new product lines, new models, new features for free, then you’re essentially burning dollars on deploying machine learning models in production, but you’re not monetizing them in inappropriate way to how much it costs to actually run them in production. So that was the first key hint that there is something there that is not exactly right with respect to how we go to market and what we’ve built. And so it was quite timely because at the time it was like the happy zero interest rates days. And Neuralic decided we had major change management, major shift in focus. And we’ve decided to basically double down on usage-based pricing, product-like growth, developer love, a lot of the themes that were very, very strong and powerful in 2020, 2021. But the infrastructure required to support that shift was in there. We were using legacy billing systems. We were using homegrown broken spreadsheets to manage our entitlements. We were using our own data metering pipelines in order to run meter-based billing.
And a lot of these complexities were not really solved. And that was the key moment that Anton and I felt like this should be software. And engineers everywhere, especially at the enterprise, should have the right obstructions and the right primitives and the right APIs to be able to do that safely and effectively without having to invent the wheel. So that’s like a very high-level story of how we got started.
Beau Hamilton (04:26.406)
Yeah, that’s really interesting. It’s interesting to hear your niche you carved out there and tackling this problem, which I haven’t spent a lot of time thinking too much about. I hear a lot about the end results, use cases of AI, but you don’t hear about lot of the behind the scenes pricing strategy around it, at least from the end user perspective. Because you want to strike that balance between you don’t want to give out these features for free.
But you also don’t want to charge too much where you of scare off consumers and you still want to remain competitive, Yeah, go for it.
Dor Sasson (05:02.734)
So, yeah, so good. Yeah, I was about to share that ultimately, look, I think there is a lot of opinions right now and debate within the AI builders and the AI space and the market as a general with respect to how things will ultimately evolve. I think some believe or work under the hypothesis that long-term infrastructure costs will go down, like they did with the cloud. So imagine, think today, everybody pay billions of dollars to Nvidia and, you know, similar companies to basically, you know, have enough GPUs, CPUs to be able to, you know, support the, you know, the scale and the spectrum of models running into production.
And a lot of that cost ultimately bubble up into the consumer because you need to keep some margins. You need to somehow start to become profitable. And you see some of these trials recently with CASA, with Claude, with OpenAI, trying different things, a different way to start getting out from this burn all your money type of strategy into a more effective monetization strategy. So one thesis is like costs will go down and then you’ll be able to monetize it the way you monetize any other software and we can talk about that.
But another thesis is that cost will always remain a significant component of using AI. And then how do you maintain the right margins and keep businesses small and large, effective and profitable in a world where there is always a cost that you need to be mindful of?
Beau Hamilton (06:49.138)
Right. Yeah. And I think that’s, it’s, it’s wishful thinking in a sense to think about the prices maybe coming down, but it’s, um, you kind of have to be realistic, right. And assume that that’s probably that’s not necessarily the case. And, you know, you gotta kind of have, um, effective pricing strategies in the, the present to set you up for long-term success. Right. One, one thing I’ve noticed, um, you, you, kind of refer to this monetizing, uh, monetization operating system you guys have developed and created, right.
Can you of unpack this for us and explain what it means in practical terms for maybe enterprise SaaS teams who are managing all these different complex pricing models?
Dor Sasson (07:28.46)
Yes.
So historically, monetization is something that has been coined and was very common within B2C and B2C apps, B2C builders in general, also like online indie developers, gaming studios. So monetization is a very common way of thinking in those worlds where you need to find effective, creative ways to monetize your application, your game, anything that you basically sell online.
But historically with SaaS and B2B in particular, the way of thinking about revenue is not necessarily with the monetization mindset, if you will. it is more rooted in the idea that, well, billing, right? Like we have to invoice, we have to collect payments, we need to be able to do that effectively. We need to have operations that will help us scale more and more deals as they come.
And so a lot of the way that historically SaaS companies adopted solutions for monetization was driven by toil, like the idea that, well, you you need to somehow build and invoice a customer and not necessarily from the root principle of how do we effectively continuously monetize in a way that is focused on value, on lots of growth, and repeatedly create success for both the vendor and the customer. So by design, a lot of the billing solutions out there, especially for the enterprise, are focusing on basically solving obstacles related to infrastructure, plumbing, data, integration, compliance, governance, and et cetera.
But there are not enough solutions out there that are focused on flexibility, change management, creating more dollars, aligning the value to the customer, and basically helping you as a business to scale, not just in terms of operation, but in terms of effective way to see ROI from the software that you’re selling. And so with monetization OS, the key principle here is, how can we help product and engineering teams out there not only solve the bare bones basics of being able to help the customer see an invoice or create the right invoice or generate it on time, but move from that idea into how can we help create better monetization strategies? What is the type of visibility that we can help create in order to drive more value for the business? If the business wishes to run experimentation, iteration at scale, or use pricing as a leverage for growth, how can we enable that?
And so a lot of how we build Stigg, a lot of how we think about Stigg, is driven by the idea that Stigg is essentially an operating system where builders first and foremost, before finance, before operation, before anyone else, builders are able to opt in and basically use the app to drive change, to be agent of change and use pricing and use signals coming from Stigg as a vehicle to experiment, expand and create more value for their users and their customers.
Beau Hamilton (10:46.544)
Yeah. I mean, you’re tackling an important problem, right? Cause there’s so many, so much of a dialogue around AI companies and services can attorney a profit. because you have these others, this do sort of technology just, rolling out so quickly, even almost before sort of consumers even realize kind of the use cases of it. So as a result, you have to figure, you have to kind of convince them what, how they can use it, right. And then create a business model around it.
And yeah, there’s just a lot of, conversation around how profitable these companies will be and, and like the timelines of when they’ll start turning profits. And it seems like here with 2025, I mean, you hear like open AI is not going to turn a profit for at least maybe a few more years. And that’s just one example. So like, yeah, it’s interesting just to hear about kind of layering this layering in this pricing strategy effectively and kind of finding the right balance here.
Now, I know many SaaS companies, they’re shifting from subscriptions to usage or outcome-based pricing, especially with AI features in play. What trends are you seeing and how should companies rethink monetization in this new era?
Dor Sasson (12:04.706)
So truth is a matter since the moment we started the company, it was never about this pricing model over the other. Anton and I are strongly strong believers that there is no one pricing strategy fits all type of idea. And there is no one pricing strategy that triumphs others in that sense.
Pricing should be focused on value. It starts with positioning. It starts with really good segmentation of your market and your customers. It starts with fundamental research and deep understanding of value creation for your customers. And that drives typically the best monetization strategies.
I think a lot of what we’re seeing today with respect to seed-based and the shift to more hybrid type of models, by hybrid I mean a mix of subscription and usage, a lot of that is actually driven not just by consumer preferences, but also related to some macro dynamics related to the investing atmosphere, ARR multipliers, how ARR is being perceived, and especially in the era of AI where
We’ve talked about it earlier. The cost of doing business is so high. So how you maintain gross margins. So a lot of what you see with respect to hybrid models and usage components in pricing strategies is driven by that. And we see a lot of companies basically trying to move towards that direction. With respect to Stigg, so essentially one of the main pulls we are seeing from our customers today is the need for flexibility and the need to be able to change their existing product portfolio, their existing catalog, how they monetize existing software and introduce more concepts and more layers that weren’t there before without having to go through like a very risky, very long-term, you know, digital transformation project, really complex cross-organizational effort.
So the idea of Stigg is how can you help companies of large scale to be able to do a more layered concept of monetization, more usage, more hybrid concepts without having to go through a very, very difficult and risky change in tooling, architecture, and processes, and what have you. To your question, I think the shift from seed-based model to algorithm models, I think there’s a lot of opinions on how exactly or where exactly it’s going to land. But I actually see a lot of applications right now, even in the AI space, monetizing based on seats. Even some of the large models like OpenAI, Carousel, and others are still using seats as part of their monetization strategy. And also some applications in the space as well. So I think seat space is not really going away.
I think what’s going away is the idea that only seats is the way to sell, we’ll see more layered ideas in terms of pricing, more complex packaging. Typically, we’ll see a mixture of subscription together with usage, and the usage components will become a little bit more layered. And so that level of flexibility is something that is driving companies to look after solutions like SIG and be able to do more without having to reinvent what they’ve built for the last 12, 15 years.
Beau Hamilton (15:33.552)
Now you mentioned the cost of doing business and kind of gross margins you have to consider when implementing a pricing strategy. And you touched on this, but what are some of the biggest roadblocks you’re seeing enterprises face when just trying to modernize their pricing infrastructure? Like if you could, I don’t know, summarize it into kind of a handful of the roadblocks that you get feedback on.
Dor Sasson (15:58.648)
First and foremost, it’s organizational structure. The org chart is the number one thing that withholding and slowing down enterprises when it comes to their infrastructure. Typically, at this phase of the company, the responsibility for this infrastructure is splitted in sometimes not in a completely clean way between the CIO office, CFO office, and the CTO office.
And so that drives a lot of tension and misaligned expectations and requirements with respect to the ability to execute well on the strategy. The second piece of it is a sense of urgency. Basically, at the enterprise, think through one of the largest SaaS companies that you know that is publicly traded. They are basically right now turning into default AI.
And how can they default to AI if they sold subscription for the last 15 years or 20 years? So how can they move to that quickly without reinventing their entire architecture, something that enterprise scale would take almost two years. So sense of urgency is definitely driving complexity because you need to be fast, but you can’t take shortcuts or short circuit some of the complexities. The third thing is basically the conflicting needs of PLG self-service motion, revenue motion coming from like self-service versus revenue channel coming from SLG sales. Order to cash, quote to cash complexities have complete different complexities than PLG self-service.
So how do you coexist those in a single infrastructure is a very, very difficult challenge to solve and building an architecture that scale effectively to solve both is not very trivial, not as you would one would think. And I think ultimately, you know, the typical legacy homegrown debt, how do you graduate from it? How do you start migrating out of it? What are the key elements that you solve first versus others? So all of these things are really, really common in the enterprise.
Beau Hamilton (18:19.59)
Now, when you’re working with a company to implement a usage-based pricing strategy, what does the implementation typically look like for front-end and back-end teams? Is there a pretty steep learning curve or is it fairly plug and play?
Dor Sasson (18:35.832)
So Stigg is very similar in its adoption to, I mean, we haven’t talked earlier about what is Stigg exactly, but like Stigg is very in its deployment and how the product works is very similar to adjacent solutions such as feature flagging, like think LD or think, you know, static or maybe, you in the authorization authentication space think of C. So the deployment and the implementation is quite similar, with some obvious distinctions that Stigg solves for monetization, it solves for business type of problems versus officer in the security identity space or launched directly in the product space. And so we have SDKs front and back end, we have our sidecar, there’s different ways to deploy Stigg, integration at the code side is fairly straightforward.
Obviously, like any other solution, is some work that needs to be done in terms of completing the deployment. There are solutions to support the deployment at scale, like caching solution, ways to fetch data from the cloud, CDN, at the edge. There’s a lot of things that we do that are quite extensive and advanced to support the scale of the enterprise. But ultimately, it’s quite a straightforward learning curve.
Beau Hamilton (20:05.714)
Yeah, that’s good to hear. I mean, I was just, you know, I don’t want to be overly, you know, simplistic and, you know, I guess that answer, because you guys, like you said, you, have, every company has a different way of doing things. There’s not like a one size fits all necessarily pricing strategy, so to speak. So, you know, it kind of just depends, but, you know, it’s still, it’s, it’s good to hear that it’s, it’s pretty, I guess it not too, there’s not too much of a learning curve, right. Associated with it. What is the implementation timeline look like?
Dor Sasson (20:37.646)
So the one thing you want to always think about this area and infrastructure solution as a whole is if you’re building for engineers, you have to have certain DX expectations met. Otherwise, you’re going to be ruled out at the start, at the gate.
If your docs are not in place, your API is not well documented. You don’t have the right preferences. SDKs don’t run well in testing environments. You don’t have support for different environments. don’t do support for infrastructure as code. Your reporting is not in place. So if those things are not well baked into the infrastructure as first-class citizens, nothing else matters because you will get ruled out right at the start.
So all of these things are like, primary null stars for us as we build Stigg. With respect to the implementation, so one way we like to think about Stigg is almost like a unbundled or like a modular way to approach this space. Like every component that we’ve built within Stigg can work as a standalone or they can work together. And it’s almost like, think about it, like almost like AWS, right? Like you join, you start using AWS, you don’t necessarily in day zero use all the different services, Postgre, Lambda, know, the Edge, like you don’t necessarily start using DynamoDB, like you don’t start using everything all at once, right? You start consuming all the services you need and they play very nicely together. think about Stigg in that sense. Like if you assume that enterprise environment is by design complex and you’re inheriting a lot of different software that you might not necessarily be able to change, you don’t need, you can’t force yourself as like a box that you just plug in and it needs to work. You have to build Stigg in a very, very nice and modular way.
So engineers can, in a very graceful way, opt into the right components they need and use them in a way that’s surface the most value. And they can graduate and introduce more and more as they go, right?
Beau Hamilton (22:55.762)
That’s a good way to put it. Yeah. Now, maybe you can touch on briefly the sort of technical support may be required to make that transition, you know, for companies shifting from hard-coded pricing to Stigg’s infrastructure, what kind of technical support is required to make that transition as smooth as possible?
Dor Sasson (23:13.622)
So it very much depends on the level of complexity or the depthness that has been built before they were opting in to bring in Stigg. With some teams, we’ve seen as few as a matter of weeks going live. For instance, recently we did a huge integration with one of our largest customers, and the first production use case was launched in four weeks.
And they’re huge. Their infrastructure is huge. This company used to be publicly traded. They’re huge. And they did the first drop in four weeks. On the flip side, we also have seen teams require or need more time. Sometimes like a matter of like a couple of months or so. But maybe it’s because they inherited more complexity, maybe talent. There was some turnover. So there’s some knowledge gaps.
And it’s there where we would deploy somebody with technical background that would hand hold the team and help them kind of guide through. Interestingly, we guide through most of their side of the code more so than ours. it’s quite interesting, but ultimately, typically see those type of dynamics at the enterprise.
Beau Hamilton (24:33.616)
Now I know one of your customers, Webflow, recently shared a story about how they reevaluated their pricing situation and decided to work with you guys over at Stigg. And this could be the company maybe you alluded to, I’m not sure, earlier. But can you walk us through that sort of pricing transformation of theirs and what role Stigg played in that process?
Dor Sasson (24:53.858)
So, it wasn’t the example actually from before. Webflow wasn’t public yet, though I’ll surely cross my fingers for them at some point. So Webflow use case was quite different. So basically we do see a segment of companies that come to stake wherein they are basically looking to expand their scratching surface with respect to what they sell. And basically they have anticipated they’re going to grow massively on all fronts. SLG, PLG, K-offense pricing, selling more complex ideas with respect to cross-sell and upsell, more complex, all in all, pricing and offering with how they go to market.
And they basically realized that pricing and packaging is going to be a strategic lever they’re going to use to continue to iterate and grow the business versus just pure infrastructure work, they decided strategically that in order for them to make it a strategic growth level, they need the right infrastructure in place. And so they did their own vetting, they did their own diligence, they decided ultimately to go with buy versus build. And then they chose staying in that effort. We’ve been with them for almost three years now.
And we are very, very proud of the overall relationship with Webflow. And I think they are very, very forward thinkers as a team and as a company with respect to how they see this infrastructure. obviously the first phase was like graduating from their legacy systems, graduating from their legacy infrastructure, their entitlement systems, their metering systems, et cetera. But today they run iteration, they introduce add-ons.
They introduced new AI features using Stigg with credits. They do a lot of innovation in how they sell Webflow without having to code all of that, without having to write all of that, without having to maintain all of that.
Beau Hamilton (27:09.766)
Interesting. Yeah, I love hearing about sort of those those stories of clients you’ve worked with in the past because I mean, I know a lot of people listening are, you know, maybe prospective customers and they kind of like the tangible aspect of seeing companies and clients you’ve worked with, they can go kind of Google and figure out kind of the pricing strategy and see firsthand what their system looks like and how it’s set up with with sort of your partnership, right?
And along with that, I want to transition to talk maybe about some advice for some of these types of listeners, maybe the SaaS listeners out there who are evaluating their monetization strategy right now, listening right now. What kind of advice would you give them to give these type of listeners to thinking about beyond just price points? What should they be thinking about beyond just price points, is my question.
Dor Sasson (28:09.634)
So frankly, it’s very easy. It’s like a very common mistake to think about pricing and monetization strategies in terms of price points. But 99% of pricing changes are actually packaging changes, packaging strategies. This could be whether you’d get a good, better bass, platform. In Pago, it’s like metrics pricing. So it’s basically like the structure, the modeling and the packaging itself. I think the number one thing is every company that builds software, whether it’s AI or not, and I think now it’s like 99% of everybody are building AI, face the core challenge of how you basically sell it.
Every conversation is, typical conversation should never start with, well, should it be $20, $50, $100? It’s always about, well, first and foremost, who is our customer? Who are we selling to? What is our ICP? What is the positioning? What is the segmentation?
What are the different segments that we sell to? Do we sell to them in SLG? Do we sell to them in self-service? What are the dynamics that allow for each strategy and why? What are the obstacles that each strategy beholds? And then walk backwards from positioning and segmentation into packaging. then the last thing is actually pricing point. Because pricing point is the easiest thing to iterate on.
Because you hop on a sales call and I tell you, Stake is 10K. You’re like, whoa, 10K is a lot. So next call I’m going to say, hey, Beau, Stake is 5K. He’s like, oh, 5K is okay. So you start basically getting a good feel of willingness to pay. And SLG, you do it in research and you do it live on disco calls. With PLG, you do it with experimentation and iteration. So pricing points are actually the easiest thing to try and with the least amount of risk actually. The thing that is most complex and you see the recent example with Kelser, the recent change they’ve introduced in June, the most complex changes are actually not just price points, they are packaging changes. It’s how you start adjusting and calibrating value perception.
If you used to give something for unlimited access and then you suddenly cap it at some limit, now you have a consumer change that you need to somehow overcome. If you’re moving from selling pure flat subscription and get access to all the features to pay per usage, how do you breach that gap?
Most complex pricing changes are actually packaging changes and revenue models changes. the way to bridge them beyond software goes into great amount of research, marketing, great communication, great brand credit. If you’re doing something that might come with a backlash, how do you build communication rollout plan to make sure that it lands with the right hears, with the right narrative? Building the right narrative towards the pricing chain plan could change a lot. You know, also in terms of operational, right? Like if you roll out the pricing change of the scale of companies like Webflow, for instance, you can just announce it in a day and that’s it. need to, from an operational perspective, you need to manage that.
So not just in terms of customer comms, also internally, how do you grandfather existing pricing plans and customers, how do you now break existing commitments, how do you graduate and roll out to the new world, like a lot of these things you need proper software to solve that and a lot of that is seamlessly built and baked through stick.
Beau Hamilton (32:25.51)
Yeah, that makes a lot of sense. I initially thought maybe it’d be the opposite, right? You have the pricing conversation first, but I think you’re absolutely right. You have the lever. You use pricing as a lever as you’re developing these features, building out your platform, getting your ducks in a row, so to speak.
Dor Sasson (32:47.598)
So one of my mentors used to say, like, you want to think about pricing strategy almost as like a pyramid, where the very bottom of the pyramid is positioning first and foremost, like PMM 101. Like, who are we selling to exactly? Yeah, once you have that, like, very well figured out, like the ICP, the segmentation, then you hop into packaging. Like, how do we sell to them? And then lastly, the last piece of it is like dollar value. Like, that’s the last piece of it.
Beau Hamilton (33:14.48)
Interesting. Yeah, yeah, I like that analogy. Now, looking ahead at your product roadmap and kind of what’s next for you guys, do you have any upcoming features or integrations you’re particularly excited about that will just further enhance your platform’s capabilities?
Dor Sasson (33:33.302)
Yeah, so I’ve been writing about this a lot. So there’s a couple of major splashes that we’re planning to do end of this quarter. The first one is very much tied to some of the conversation you started early on with respect to AI and what is essentially critical for AI companies to be successful with respect to monetization. So I started to write a lot about credits and the credits economy. I think while people talk about the move to outcome-based pricing, I think there’s not enough conversation about the move to credit economy. And I think credits in general and how credits work is something that is on our minds and something we deeply care about. And I anticipate that we will increasingly see more and more software companies assume and introduce layers and concepts that you can tie to the idea of credits and currencies. And there’s a lot of good reasons behind it, not just AI, but also AI.
And good examples, I think companies like Clay, think companies like Miro, who is a customer. A lot of companies basically introducing credits as a vehicle to proxy set and challenges with respect to monetization. I think the second thing that we’re extremely excited about is we are moving from iteration and pricing changes as something that you do a handful of and in a small scale to a much larger, robust, first-class use cases related to pricing changes, pricing experimentation, different offerings, campaigns around offerings, because we see more and more, especially think through most of the AI iconic companies that you know today. A lot of them see most if not all of their revenue actually coming from self-service and coming from like individual consumers selling to the consumer.
And consumer behave differently than what we know in classical B2B SaaS. The numbers are like a volume play and volume play unlocks a lot of opportunity, relates to experimentation, iteration, geofencing, differential pricing, a lot more ways to basically optimize and try different things. So we’re very bullish as a company on the idea that AI introduces a wave of opportunity on how to optimize and iterate an experimental pricing.
Beau Hamilton (36:24.71)
Yeah, that’s very, that’s interesting to keep in mind. just the move to the credit economy is something I’m have to just kind of look into and tap into. Do you have a, do you have a sub stack or do you write kind of quarterly blog posts or about the topic or?
Dor Sasson (36:39.714)
So my amazing marketing team is already helping me see the light and understand that I need to write more. So I don’t have like a sub-stack yet, but I try to write regularly on LinkedIn. I am planning to actually write a bit more in the very coming future. Yeah, I think probably the best way is my personal LinkedIn profile is the best way to keep in touch.
Beau Hamilton (37:08.54)
Now, I got a couple more questions for you, of talking more about your sort of background and tap into your thought leadership experience. So I know you were a product guy before you kind of turned into the founder, co-founder of Stigg. So I’m curious, you know, obviously there’s a lot of, it’s 2025, we have a lot of, it’s a crazy world with a of macro conditions to navigate that make it difficult to run a business. How do you just like stay motivated to keep things positive, keep your team chugging along during tough times?
Dor Sasson (37:56.558)
I think, I don’t think I have some special formula to how it’s done and I think for me more than anything is just being your authentic self and you know treating and thinking of people as people and trying to remind to myself every morning, this is Antons and I approach since day one, that any given individual that decided to join Stigg basically in some sort of way made the bet on their career on us. And we basically loan their time from them, their career, their needs, their aspirations, their things they want to fulfill in their own life.
And we basically are privileged to get their time, their wishes and what they want to do. And they made their bets in their careers on us. And so there is only one way for us to redeem that bet, which is just show up for them and give them the right environment, the right settings, the right tools, the right opportunities to grow. And so as long as they get to grow with the company and they get to be their best version of themselves. There’s a good reason that they will have their own self motivation, their own self powerhouse that drives them forward. so autonomy is key and the ability to make an impact is key. And I know a lot of tech companies do that and say that. So I don’t think we’re unique in that sense. I think the second sincere question about tough times, I think.
For whatever reason and this is not like a you know, you know a therapy session But like for whatever reason I feel like I feel more comfortable actually in very stressful Environments versus, you know standard regular day to day so for me, when things get hard, I see things more clearly and it actually helps me because it’s like you’re pushed to the wall and you have to focus on the most important things first. And so for me, when things become really, really difficult or hard for my team or for myself, I just try to be there for them more than anything. Be present. Be create the right attention, never go dark, create the right options and certainty even when it’s very uncertain and repeat basically.
Beau Hamilton (40:56.07)
Yeah, that’s a great answer. I, obviously there’s a lot of different avenues and ways you could approach that question. But, I think, yeah, with the sort of online world we’re in, I think it’s always a great reminder to be authentic to yourself. And, that’s just gonna, that’s just gonna set you up for, for like lasting happiness and your career, but also just everyday life. Right. and it sets you up for better relationships, and, and among other things.
So I think that’s great advice. And yeah, I know, I don’t want to turn this into a therapy session, but I appreciate the insights there. Now, one last sort of maybe introspective question where we can leave listeners with a takeaway. If you could give listeners maybe one message, maybe it’s an advice message, or maybe it’s like one big thing you wish you could tell potential customers about Stigg. What might that one big thing be?
Dor Sasson (41:57.42)
Yes, I think there’s a lot of noise in the market right now with respect to what you should or shouldn’t do in this realm of billing monetization infrastructure. And it’s becoming harder and harder to cut through the noise and separate signal from noise and understand exactly what is the right solution and how should we approach it. I think more than anything, the best companies we’ve worked and partnered with were the ones that they have established early on a really strong foundation of like a tiger team across the org. Let’s call it like monetization committee, if you will. That is including all the right leaders from all the different orgs.
And this, if that group not only exists, but actually have the right political power, the street cred, they work well together, they trust each other, and they start making decisions together, whether they choose Stigg or they build in-house or they move outcome-based or they go hybrid, as long as they are able to effectively communicate, meet on a regular cadence, sync on the right challenges, align expectations, and basically work towards the same goals or set of goals. These are typically the teams that we see operate and execute in the most effective way. And then a subset of that will be like, okay, now let’s talk about what’s the right solution in architecture for you.
And you can talk about whether it’s you need like consultancy from the outside or you need a vendor or you need some thought leadership or you need to talk to chat GPT. Like there’s a bunch of ways to start untangling and unraveling the complexity, but having that team in place, go the longest way because ultimately every monetization or billing solution becomes a cross-organizational effort at the enterprise and not having that alignment in place and those guardrails and set up will set you up for failure 100%.
Beau Hamilton (44:12.398)
Very well said. Yeah.Tthat’s lot, you give me a lot to think about after we sign off here. for those listening and are interested in learning more about Stigg, maybe want to get in touch with you, learn more about the credit economy and all your future Substack posts, where should they go? Where should you send them?
Dor Sasson (44:30.286)
So I think our company blog is a terrific way to start our Twitter account. My personal LinkedIn, of course, would love to connect. I always like to have meaningful conversations. Yeah, hit us up on Unstaged. We just had started like a very small, low key, low profile community talking with pricing, product, engineering, builders all across talking about the complexities of the enterprise.
Feel free to reach out, join us there, join the conversation. We’d love to see you there.
Beau Hamilton (45:02.866)
Perfect. All right. And then that’s Stigg.io, right? It’s a good starting place.
Dor Sasson (45:07.148)
Yes, Stigg.io.
Beau Hamilton (45:08.764)
Awesome. All right, thank you, Dor. It’s been a pleasure. And again, just thanks for all the insights and just educating me more about the world of pricing strategy. Appreciate it.
Dor Sasson (45:17.326)
Appreciate it Beau. Thank you for your time.
Beau Hamilton (45:19.462)
Thank you all for listening to the SourceForge Podcast. I’m your host, Beau Hamilton. Make sure to subscribe to stay up to date with all for upcoming B2B software related podcasts. I will talk to you in the next one.