So we, you know, you could almost argue, stubbornly focused on product managers to build that category and really focus on crafting a budget. So one day I came into the office and I went to the sales team and I said, 'Minimum price is now $1,500 a month.' And they were like, 'This is never going to work.' The reason we don't do seat-based pricing is to actually extract value. The seat-based price would be so high that it doesn't even make sense. So we crossed it off the list early on. We decided we're going to price on monthly active users. The idea being if you've got a bunch of users using your software, presumably it grows, that's good for you and it's good for us. So if we can help increase adoption of your software, then you should be able to monetize that, that should be driving your growth, and henceforth we want to take a cut. So you can basically connect Pendo to your agent. We're going to give you topics and themes on conversations. We're going to tell you which ones were successful and good. But you can click on a conversation and hit a button and watch the replay. Now there is no other AI product in the world that has the ability to go watch replays, but because it's an integrated platform, I can build these things in ways that are very unique.
Yeah, we have an existing customer base and it's not small, and we have customers who want certain features. They want capabilities, and I have to invest in our product to make them happy or I'm going to get churn or I'm going to run the risk of not expanding. It's going to absolutely impact our dollars. Well, I have to invest a pretty significant amount in AI and in this new economy.
Welcome. This is Second Act, a podcast where we document how SaaS leaders chart the exacting foundational shifts of scaling up. And I'm your host Chris Subramanian, co-founder and CEO at Charsb. This season we are diving into AI's all-out enterprise embrace and how that's accelerating second acts everywhere, reshaping software categories, business models, and teams to meet never-before-seen stakes. Now on to the episode. This week's guest Todd Olson co-founded Pendo in 2013 with a stubborn conviction. Product teams deserved their own system of record, their own budget line, and their own category. Investors pushed back hard. Why build for an unproven persona when Martech budgets were flush and waiting? Pendo built it anyway and has spent the next decade defining and leading the product analytics and adoption category. Today, the team faces a different challenge. In a market bifurcating between companies riding the AI wave and those still making their case, Todd is raising to write Pendo's consequential second act. In this conversation, we spoke about why early investors wanted Pendo to sell to marketers instead of PMs and how Todd and team created an entirely new budget line item. Why the incremental value of a click has declined in the ChatGPT era and how that is fundamentally changing product analytics. The big open questions for modern product teams. Todd's platform philosophy of innovating at the intersections. An early top-down pricing bet, raising minimum price from $99 to $1,500 per month that accelerated their growth. How they landed on charging for MAUs instead of seats. The innovator's dilemma of being a scale-up in the AI era, serving a massive base of existing customers while betting heavily on transformation, running one zone race, and so much more. Let's dive in.
I want to touch upon some of the lessons from the early days, right? And you noted that a common objection from potential investors was that you are building in a completely new space instead of Martech where the demand was strong or the budget is clearly known. You were building for a persona that was often misunderstood or not known for buying a lot of products. Right? And a lot has changed in the last decade. And so what is same and what's different about this moment compared to when Pendo was kicking off its category journey way back in 2013?
Yeah, look, I mean going back those days, that was kind of the heyday of Martech. You could argue that the market, the exact targets, I mean that was a dominant space and everyone sort of knows that the largest variable budget in an organization is marketing. So I feel like a lot of the venture capitalists and investors at the time were like, 'Why don't you do this? There's so much money there.' And we always saw an opportunity to sell to product managers. So we stubbornly focused on product managers to build that category and really focus on crafting a budget. And I think there's always a bit of a chicken and egg. At the time, I would argue, well, the reason there isn't a budget is that there aren't solutions to buy. If there's solutions to buy, you would go and justify budget for it. So it's a bit of a chicken and the egg thing. And you have to focus on how do we create a budget line item. So a big part of our early sales motion and even to some degree today is how do we help justify, help create a budget line item? And I will say that's hard work. And if you read Frank Slootman's book 'Amp It Up,' he says go disrupt existing markets. Don't try to create a new one. So he wouldn't do this. And he's arguably one of the best CEOs we've seen in the last few decades. But that is the journey we're on now. Now your question was how's it different today? Well, fast forward today. Product teams have budgets. There's not just Pendo. There's dozens of solutions that sell to product managers. There's conferences for product managers and there's plenty of sponsors that fill the room in the halls. So the world's a little bit different today than it was back then. And it's just a lot of hard work and a lot of investment in community to get here.
Right. I think the developer as a key stakeholder in the buying process and then the CPO's office actually buying has changed a lot, right? So how do you...
No, I think that's an interesting point too, because developer marketing is such a unique problem domain and we kind of sit just adjacent to it. So you think about developer tech, obviously the Atlassian suites are really dominant there, Datadog is really dominant there. I think selling to developers is its own sort of beast and I have actually a lot of experience prior to Pendo selling to developers, so quite experienced there. But I thought that product sits in between development and essentially business stakeholders, sales, marketing, etc., and has a strong degree of influence. So making sure that audience has a strong system of record, understands how to do their job, they aren't just operating on instinct and intuition. I feel like there was a huge opportunity and that's kind of what we see today. How do we empower this audience with data to be better at their jobs? Because there's such a force multiplier for a business. A great product manager versus a very average one, you're going to have a wildly different impact on businesses. So that's kind of how we think about it. And it's fun. I definitely enjoy it.
Yeah. And the role of the product manager itself is changing in the world of AI, right? How do you position Pendo today in the mix of the AI bets that companies are making for the enterprise buyer? How do you position this today?
Yeah. Well, look, the entire software development process is changing. And I do think while we see a lot of these new tools sort of collapse roles, like if we had distinct product managers, designers, program managers, user researchers, do we need four different roles on our engineering and product teams anymore? I'm seeing changes there, disruption. And I really like Marty Cagan and the Silicon Valley Product Group. I saw him speak recently, so I'll quote some of him. They've spent a lot of time talking about this product operating model. And as they say, it's not something they invented, they're just talking about it. And I think when you're looking at a team of people building software, the question is what role owns whether this solution is viable and is it delivering value to the user? Who owns that? Now could a developer, could an engineer own that problem? Sure, they could.
We're just saying some role on the team needs to own that solution.
Right. And often that's a product-oriented thinker. But now if you're a product-oriented thinker and you have Claude Code, you can generate an application potentially.
Right, so I think there's an interesting blending of roles.
And look, I'm a developer myself by training. I helped write the first version of Pendo and I've been a head of product, so I clearly could do both roles if I wanted to. But I think the question is do you want distinct individuals to own these parts of the lifecycle or not? That to me is the fundamental question.
Sure. I think the way you're framing it towards the role play is very interesting because as a product that's actually thinking about the jobs to be done and all that. I think one of the clear distinctions is what outcomes. Shipping the product is one of the outcomes. If you think about it as one of the outcomes, the other outcome is also to track the usage of the product, then comes the monetization of this. So there are several layers to this and not every person actually wakes up thinking about all of the outcomes. There are certain people who are naturally inclined towards more the commercial role and then there are ones who actually lean inwards towards the problem that the product solves or the feature solves and then the ones who actually think about the adoption and then eventually into the commercial aspect. And there are those clear distinctions and generally you cannot change the nature of a person where they naturally get their energy from and what they gravitate towards. So there are always going to be those different flavors of different types of product managers and people who care about those different things that will come in.
Yeah. And look, a lot of the engineers that I know and meet, great engineers, they get so jazzed from solving really hard problems, hard technical problems, scale problems, concurrency problems. And they've been solving these problems for decades. These are the kinds of problems that engineers love solving. Now, a lot of the product problems are what's this customer willing to pay for this solution? And it means getting out of the building and talking to customers and evaluating alternatives. I think it's a very different set of skills and activities. Some people like that stuff and some people do not. And it's not a matter of whether someone can do something or can't do something. It's where do you get your energy from? What are you really good at? One way I like to think about it is many of us as humans have majors and minors in life. Things that we're really good at that we major in, then things that we can do we sort of minor in.
Yeah, and now in the age of AI, one of the most powerful things is that the things that we minor in we can leverage AI to get better at, fill in our gaps. And that's where it gets super powerful. But it's still going to be a minor and we still don't get tons of energy from it. So even with filling, for example design, I am not a designer and I can't design, but I can go into Lovable now and I tell it what I want to create and it'll create a design for me. I can go then validate it. That's pretty powerful. That's what AI brings to the table. It's a gap filler and also kind of helps us learn.
That's a very good way to actually think about all of this. And given all of this that's happening around our category, I would love to hear the way you think the second act of your category is actually emerging, right? Which is how do you see the product analytics and engagement space changing as a result of all of this happening?
Yeah. Well, look, first of all, it's still being written. So anything I say is evolving and changing regularly. But the first thing we started doing when we started thinking about how AI is going to affect our category and product analytics is okay, so when ChatGPT dropped, it fundamentally changed how users think about software. Whereas they're very accustomed to going in and pointing and clicking and scrolling, and we've had a traditional set of UI metaphors for a long time, since the era of mainframes. But now we can just tell the software what we want to do and it will interact with us or just do it for us. So that new paradigm is not only here but here to stay. So what does that mean for product analytics? It means that there's a new data set, a new way to engage with software that's a really important thing that we now need to capture and understand in concert with the rest of the overall experience. So what we started investing in almost immediately when we started seeing this change was the ability to capture analytics from these conversations. A conversation is qualitative data, a set of prompts back and forth, but we can grade it, we can score it, we can evaluate its success. We can also look at it in concert with a broader application. How do people get to it? When do they use a conversational UI versus a traditional UI? How do we optimize the experience? Maybe if you're going in to just buy something you've bought in the past, clicking a button is actually more efficient than writing a sentence. So what jobs to be done is a traditional UI more suited than a new conversational UI and vice versa. So the first area is that the incremental value of a click is probably less now than it was pre-ChatGPT.
So we've had to adjust our product strategy to now capture the data we were missing to make sure we have a complete view of what the user is doing.
