A Product Market Fit Show | Startup Podcast for Founders
00:03:09 · Rahul Shivkumar, Pablo Srugo
[00:03:09] S1: Yeah, our ACVs at that time were probably around like $60,000 or so. They've gone up substantially since then, but back then it was a pretty big deal. It was the first, I think, five months of the company, four months of the company I think is when it happened. Yeah. [00:03:23] S0: So, I mean, the simple way of thinking that is, I mean, you know, 50K deals, not massive enterprise, but it's still going to require, especially because you're probably underpricing. So it's probably going to still require like a decent amount of handholding in terms of onboarding and support and you were at the point where you had so much demand. It wasn't a matter of getting demand. Like you just couldn't meet the demand that was right there in front of you. [00:03:41] S1: Exactly. A lot of the workflows that we were solving then and that we still are solving today are on a forward deployed motion, right? So we have templates of what some of these agents look like, but a lot of our customers work with insurance companies in very unique ways and our agents are kind of built to be reasonably unique in handling any edge cases that a particular customer has. So this is early days where we did have a lot of templates. Some of these agents had to be built by scratch for each of these customers and deployments did take quite a bit of time. So four coming in in one week does take up a lot of bandwidth. Yeah.
00:04:18 · Pablo Srugo, Rahul Shivkumar
[00:04:18] S0: I mean, it's a classic, like it's literally the classic definition, right, of product market fit, which is when there's so much pull, the problem isn't getting growth. It's actually just servicing the growth and making it happen. We're going to talk about all that, by the way. Like we're going to talk about everybody's talking about forward deployed engineer, but we're going to talk about how you're doing it. And at the end, we'll talk about two pieces. One is the BDR motion and how you set up your BDRs. You never went all in on kind of the AI BDR, which was, I think, a bit of a hype cycle kind of came and went. Maybe we'll come back, by the way, once we have like Fable 6 or whatever it's going to be. But you decide not to go that way. You made it work. We're going to talk about like real numbers, conversions, quotas, all those sort of things. And then the AI sales tactics, like the tactics you're using today to close customers, to increase urgency and how you're doing like the forward deploy motion and onboarding, which at a high level everybody understands. But, you know, when you want to bring it to practice, the same playbook is not going to work for everybody. So take me back. That's the moment you said that was like five months, that product market fit moment, five months into your journey? [00:05:12] S1: Yeah, it was about five months into our journey. Yep. [00:05:14] S0: And when exactly did you start Assured? [00:05:16] S1: We started Assured in early 2024. So I think it was March of 2024.
00:05:16 · Rahul Shivkumar, Pablo Srugo
[00:05:16] S1: We started Assured in early 2024. So I think it was March of 2024. [00:05:20] S0: What were you doing before you started? Like, you know, maybe give me a little bit of your background, especially like right before you started Assured, what was going on in your life? [00:05:28] S1: My co-founder and I actually, we've known each other for years. We went to college together, but we did a business before Assured called Dawn Health. So Weaver, what I would describe as maybe the perfect Assured customer. So Weaver, a virtual sleep treatment center. So we were helping folks with insomnia, get off of sleeping pills and sleep better. And what our company looked like on the back end was really a telehealth clinic. So we hired providers full time. We had to get them kind of paneled by insurance companies. And about 99% of our revenue was either Medicare or commercial like insurance. So our business model was getting paid out by these insurance companies and making sure that you could hire providers on time, that their start dates were actually tied properly with being able to bill insurance was extremely important. So we had faced the problem firsthand and we exited that business. [00:06:20] S0: What kind of an exit was this by the way? Like a big, big success exit? Kind of like things didn't work out? So tuck in, somewhere in between?
00:06:20 · Pablo Srugo, Rahul Shivkumar
[00:06:20] S0: What kind of an exit was this by the way? Like a big, big success exit? Kind of like things didn't work out? So tuck in, somewhere in between? [00:06:26] S1: Somewhere in between. I think our investors were happy. I think we were happy. I think it was a very hard business to scale and we could probably spend an entire episode talking about should be venture scale and what sorts of business should not be venture scale. Right? And I think our previous business probably fell in the sole category of maybe not a venture scale like setup even, let alone like outcome, obviously. But we were insiders. We had seen the problem before and actually before we even incorporated the business, we had revenue. You know, we had like committed revenue where customers are like, hey, if you help us solve this problem, like we'll sign like an LOI, we'll sign a contract right now. So going into March of 2024, I think there were maybe two customers that had already committed to like using us when the product went live. Yeah.
00:06:26 · Rahul Shivkumar, Pablo Srugo
[00:06:26] S1: Somewhere in between. I think our investors were happy. I think we were happy. I think it was a very hard business to scale and we could probably spend an entire episode talking about should be venture scale and what sorts of business should not be venture scale. Right? And I think our previous business probably fell in the sole category of maybe not a venture scale like setup even, let alone like outcome, obviously. But we were insiders. We had seen the problem before and actually before we even incorporated the business, we had revenue. You know, we had like committed revenue where customers are like, hey, if you help us solve this problem, like we'll sign like an LOI, we'll sign a contract right now. So going into March of 2024, I think there were maybe two customers that had already committed to like using us when the product went live. Yeah. [00:07:11] S0: You started Assured with the same co-founder as the company before? Yeah. And so timeline's interesting here. Like you start the last company 2021 where like COVID remote work, you know, so telehealth, right? That's like probably the big thing. And as you're doing it, ChatGPT comes out kind of, I guess, in the tail end, right? So end of 22 and you kind of sold it in 23. Did that, by the way, I'm curious, like that drive at all, the exit, you obviously weren't running an AI native, company. Was that part of the math? How did that play into that and then what you decided to do later?
00:07:11 · Pablo Srugo, Rahul Shivkumar
[00:07:11] S0: You started Assured with the same co-founder as the company before? Yeah. And so timeline's interesting here. Like you start the last company 2021 where like COVID remote work, you know, so telehealth, right? That's like probably the big thing. And as you're doing it, ChatGPT comes out kind of, I guess, in the tail end, right? So end of 22 and you kind of sold it in 23. Did that, by the way, I'm curious, like that drive at all, the exit, you obviously weren't running an AI native, company. Was that part of the math? How did that play into that and then what you decided to do later? [00:07:39] S1: Yeah. I think a big part of the narrative of starting Dawn was this kind of shift from needing care in a clinic to being able to not just get like continuous care, but even diagnosis and things like that over telehealth, right? That was what happened in 2020 through 2021. What we started seeing in 2023 was actually people wanting to get back to in-person care. You know, they're like, hey, I've done this virtual thing. We want to actually see our provider in person. We want diagnosis in person. We want treatment in person. So I think there was a little bit of headwinds there. The classic public market example of that is Teladoc. If you look at their stock, the pop in 2020, 2021, and then the kind of fall in 23, I think was probably the best signal for what was happening in that market. AI wasn't a huge reason either way for us like exiting or continuing our business. I think it was very nascent in 2023. GPT3 had just come out.