A Product Market Fit Show | Startup Podcast for Founders
Every founder has 1 goal: find product-market fit. We interview the world's most successful startup founders on the 0 to 1 part of their journeys. We've had the founders of Reddit, Rappi, Cohere, Glean, Huntress, ID.me and many more.
We go deep with entrepreneurs & VCs to provide detailed examples you can steal. Our goal is to understand product-market fit better than anyone on the planet.
Rated one of the world's top Startup Podcasts.
A Product Market Fit Show | Startup Podcast for Founders
YC founder raises $3.5M, keeps team to 3 people—then grows 10x to $2M ARR in 1 year. | Benjamin Encz, Founder of Ashby
Last month, Ashby raised a $30M Series C. Ashby is used by customers like Notion, Ramp and Sequoia. Benji built Ashby as an end-to-end Applicant Tracking System (ATS) that would replace several point solutions. He had to build heads down for 18 months and couldn't launch a simple MVP.
Surprisingly, even though he raised $3.5M at seed, he didn't grow his team. He built the product with just 3 people. "We could spend time recruiting or we could spend time building"-- he decided to build.
When they launched, they grew to $200K in ARR within a year and then 10x'd a year after that. Here's the story of how they found product-market fit.
Why you should listen
- Why keeping your team small helps you go faster.
- How to displace point solutions with an end-to-end platform
- How to validate pain points.
- How to move up market from startups to enterprise companies.
Keywords
Ashby, all-in-one platform, recruiting, reporting, pain points, product market fit, Series A
Timestamps:
(00:00:00) Intro
(00:01:29) No Website, No Problem
(00:03:08) A Viral Loop
(00:04:40) Origin Story of Ashby
(00:05:39) The Biggest Pain Point
(00:07:50) De-Risking
(00:09:26) A Sticky Product and Market Evolution
(00:10:50) A Hundred Conversations
(00:13:09) The Main Feedback and Key Learnings
(00:16:16) The Pitch
(00:17:20) Bundling and Unbundling
(00:20:50) Building a Great Engineering Organization
(00:22:26) Letter of Intent Stage
(00:24:45) Validation and Feeling Ready
(00:28:18) A Little Bit of Luck
(00:31:51) Finding True PMF
(00:32:44) One Piece of Advice
Pablo Srugo (00:00.078)
So you had raised three and a half million and you kept the team to three people?
Benjamin Encz (0:02)
Yeah. Yeah.
Pablo Srugo (0:03)
Oh wow.
Benjamin Encz (0:04)
The main piece of feedback we got in the end was like, I don't know that you can actually build all of this, but if you can, that would be absolutely amazing. So at that point, we're like, okay, now we know we're down to like, it's just the execution problem, but we've kind of de -risked it.
Pablo Srugo (0:16)
What are your thoughts on that? Like, when does this one stop shop for X model actually work? And when does it sound good in theory, but then you go in and you try and rip and replace it and it just falls flat.
Benjamin Encz (0:26)
I don't think an MVP makes a ton of sense if you are replacing an existing system one to one. So 2020 was the first paying customer. By the end of the year, we had hit like hundreds of thousands. And then the year after that, we went into the multiple millions. So it was like a pretty fast, like more than 10x growth.
Pablo Srugo (0:45)
Welcome to the product market fit show brought to you by Mistral, a seed stage firm based in Canada. I'm Pablo. I'm a founder turned VC. My goal is to help early stage founders like you find product market fit.
Benji, welcome to the show.
Benjamin Encz (1:02)
Thanks for having me.
Pablo Srugo (1:04)
You know, I normally we start at the beginning, but like one thing that kind of shocked me is you said you didn't have a website until you raised your series B, which I'm looking now is like kind of three, four years into your journey. You know, you're doing a couple million in revenue, raising tens of millions of dollars and no website. What tell me that story?
Benjamin Encz (1:21)
:Yeah, there, there's a lot that kind of preceded that, but they'll probably work our way backwards throughout the conversation. When I say no website, you know, we had a wall of logos. that we added to. So it was like, it was like Ashby, but there was no description of the product. It was basically just Ashby and then customers and then a request access box. The way we got there to Ashby today is like this all -in -one platform, which has like four, depending on how you look at it, four to five different products built into it. And it took us quite a while to get there. Early on, we stumbled into opportunity to take like one of the key modules, which was like better reporting for recruiting data. And I actually offered that as a standalone product. It was not really the plan that we had.going into it, but it was like a thing we learned that worked pretty quickly on top of existing systems. And so we ended up with these two products. One was this all -in -one thing, but it was not fully built yet. So we really only wanted to give it to like early stage startups. We went into like a pretty crowded existing kind of applicant tracking system space. And so we wanted to launch a full -fledged product if possible. And so, and then we had this other set of customers that were using an existing incumbent system, but we're using our reporting on top of it. So all this was a little bit messy. behind the scenes, but the nice thing because we had no website is like we didn't have to tell a public story about the company. It was basically we had a bunch of really stage companies using us and they thought we were just this ATS for startups. And then we had a bunch of like enterprise customers using us for just reporting and they thought we were just this reporting product. And so it's like, from a product marketing perspective, it was great because you could tell different kinds of stories to different segments of the market. So that's kind of.
Pablo Srugo (2:52)
That's smart. So like as you're, as you're figuring out your positioning, cause what normally happens is as you figure out that positioning, you just constantly re -update your website, which means like all the copy, the tagline, like, and what you guys said, just kind of throw up your hands. Like I told you, we figured it out. Like we'll just leave it at the logos and that'll be that.
Benjamin Encz (3:08)
That's basically what happened. And we were lucky. All of this is like really kind of coincidence of kinds of market we're in. So we had these early stage companies using us for all of the recruiting, which also means that job boards and these job boards are branded. And so there was like, a little bit of a viral loop. And, you know, one of our first customers was Deal, the remote payroll company that grew from like 20 to like 3000 people or so over the last few years with us. They were raising a lot of rounds, they were pacing a lot of jobs. Other startups started seeing these job boards. They're like, hey, I didn't like Greenhouse, I didn't like Lever. What is this new thing that all these startups are using? So there's like a viral growth loop on the early stage side. And then for the later stage companies, Upbound was working really well because our messaging there was, hey, do you have problems around recruiting data?
we've got the solution and it was a big pain point, especially in 21, 22, when people are hiring like crazy. And so we kind of had the up and early motion for larger companies than the really viral growth loop for early stage. And that allowed us to kind of remain in the stealth mode way longer than some other companies. But that was like, if we could afford it, that's something we wanted to do to be able to launch and kind of just splash and be like, hey, you haven't heard about us before, but here's like this fully built product that's ready for like mid -market enterprise customers.
like today, rather than this like startup product that you can come back and look at again, like five years.
Pablo Srugo (4:24)
That's so helpful. Let's jump back to the beginning now. So you, I guess, I mean, you were a director of engineering at PlanGrid and I think PlanGrid was going through that, that Autodesk acquisition around 2018, which is right around when you start Ashby. So maybe think it's back to that time. It's just like the origin story of, of Ashby.
Benjamin Encz (4:40)
So my background is all in software engineering and then the most recent company I joined before starting Ashby was Plangrid. They were in a construction tech space. I joined as an iOS engineer, just an individual contributor. Rather quickly noticed that that team needed to grow and so stepped into an engineering manager role at Plangrid. At the time, the company was about a hundred people and I stayed there for like four or 500 shortly before the acquisition. And then as soon as I became an engineer manager, I basically spent all of my time hiring engineers. So that became like my full -time job. You know, it's like... 80, 90 % of my time was spent on hiring, working super close to a recruiting team. And that was my first exposure to kind of the existing products in the space. So I used Lava Ray, I used Greenhouse, I used a bunch of others and had quite a few pain points specifically around reporting and metrics and also around scheduling and coordination of interviews. And overall just felt like there's a potential opportunity here.
Pablo Srugo (5:31)
What were some of the problems? Cause that like the subtleties is really the key. A lot of things, you know, don't work as well as you. but what were some of the specific things that were just bothering you?
Benjamin Encz (5:39)
Good question.
Basically, we spent hundreds of hours on recruiting engineers across the engineering team kind of every month. It was like huge, huge time sync and huge effort. And when you do something that in almost any other field, you want data to support whether or not what you're doing is working or not. And that was just incredibly hard. You know, we're trying to figure out like, is this interview actually predictive? Is the source of candidates actually good? Like, are we wasting time at this stage? All of that required us to export data into like spreadsheets and do some manual stuff. It often took weeks. So that was like a big... piece, like I remember one particular point in time where we just had this hunch like, Hey, we're interviewing a lot of people from triple byte, which was like the sourcing platform back then. And it seems like we're not getting a lot of hires out of that. And so we looked at the data and we had like a 10 % offer acceptance rate for that particular channel. And it turned out it was because the value prop to the candidate was like, Hey, skip the ons, you know, skip directly to the onsite interview of like 10 companies at once. So they were having like offers from like Gusto and other competitive growth stage companies. And so, but it took us like three months to learn that. And we were just like interviewing. you know, tens of candidates.
Pablo Srugo (6:42)
Candidates who were actually good. It seemed like it was a good channel, but you just weren't actually landing them. So what's the point? That's kind of the...
Benjamin Encz (6:47)
But there's like one example of many. And so, you know, in general, I think if you are investing a lot of time into any process in a company, that's really important. You want to have data to answer like how to iterate on that, right? And we didn't have access to that. So that was probably the biggest pain point. And then taking maybe one more step back, I think like many founders, I did like founder type stuff like super early on, you know, I sold like... recorded cassette tapes in school, copied from CDs and stuff like that. So I think I always wanted to start a company and I had this running list of ideas. The more I worked in existing businesses, the I think the more skeptical I became and less naive. The kind of things I used to be excited about were like in retrospect really dumb ideas. I still have to spreadsheet. And so I remember at this time I was like, man, this is a really visceral pain point, but I'm not sure if it's one of these things I'm excited about, but it's actually not really a market I should be going after.
felt this really acutely, but I kind of watched that space for about two years. You know, Labrador and Greenhouse were four year old companies already going head to head. It wasn't like any company had like, no company had space, had like a breakout massive success yet. There were a lot of question marks around it. So I think we'll get into this more, but one of the next steps was really kind of trying to de -risk that. And it took me almost like two years to build really strong conviction around this idea.
Pablo Srugo (7:56)
Was this while you're still at the plant grid or like, did you leave to do that de -risking?
Benjamin Encz (7:59)
Yeah, some of it was while still there. So I think again, the arc from like, you know, first feeling this pain to actually committing to it was probably two years of that, like a year and a half was very much like in the background. It was just like a thing. I was just taking notes on the side whenever I was running into issues. I'm like, man, I should just keep these notes in case I want to drop the dive into it. But I was really focused on my work at Plangrid. And then I think it was like summer, spring, summer of 2018, where I was like, okay, I'm slowly thinking about what's next. And one of the possible things next is like actually starting a company and just like a space when we look at more closely. And then
Pablo Srugo (8:37)
in that thinking, maybe just a question, because one of the pieces is like when you have a product that decently mature has like a pretty wide, let's say feature set and there's like one area that you feel like it lacks, which in this case seems like reporting and data. The obvious question a lot of times is like, a, are they going to do it? And to the extent that they're not going to do it, like, why not? Like you must not be the only person that feels that pain. Did you dive into that or over time gain any insights as to why they weren't fixing it themselves?
Benjamin Encz (9:05)
Yeah, it was, we did quite a lot of work there. So I agree because I think again, over time you get more skeptical about is this actually a real issue or not. So we started with like 10, 15 conversations or so before we committed to this, but in total we talked about a hundred some TA teams and reporting literally came up like 90 out of a hundred. And it was like the reason people were switching between applicant tracking systems.
You know, the other interesting thing to me was like, this is a pretty sticky product. It takes quite a while to implement. There are a lot of stakeholders that need to be trained, et cetera. But in these like hundred interviews, again, almost pretty much everyone had switched in the last three years. So it was like this kind of interesting category where yes, there's an existing product, but everyone is switching. And in 90 % of the cases they're switching because they want better reporting and data. There's still a question like why haven't they fixed that? I think part of it was timing of how does market evolve? Like the prior generation of competitors we have were built around 2012, 2013. And back then, recruiting teams weren't working with data nearly as much as they were in 2018. So a big part of it was like, there was actually a shift happening of how recruiting teams were doing work. Recruiting operations was becoming a thing. We had this advantage of like coming into space when that was happening. So we built a product foundation from scratch. And then the other thing is we actually did try to find people close to the company. We actually found ex - Greenhouse and Lever employees and investors. And we kind of worked our way around like, hey, why didn't they do this thing? And we learned quite a few things.
This is a live company, so I wouldn't share too much publicly, but we kind of learned a little bit about like how the engineering setup worked, how the teams were structured, how they had made technical decisions in the past that led us to believe that there's actually like, it's just hard for them to change course, even though it's a really important area of the product.
Pablo Srugo (10:39)
How did you make that happen? Because that seems really smart, right? Is to ultimately go after ex -employees or people who are actually close to the company and get, you know, that's really the source of truth. Like what's the upside for them to share any of that with you?
Benjamin Encz (10:50)
Yeah, I think we got a little bit lucky in the space that recruiting folks love to talk to people and make connections. And so it was actually really easy to get these hundred conversations. I think I'm not 100 % sure. I'm pretty sure that it was people there that introduced us to the company. And I think maybe also some potential investors eventually. Once we started talking about fundraising, they're like, Hey, I know someone who was at Lever early on, that kind of thing. But we got lucky with recruiters. They, you know, we had one interview and we just asked them like, Hey, are there a couple other people we should be talking to? And they gave us a list of like three or four relevant folks that we could kind of.
go from there. So certainly not the case in a lot of other spaces.
Pablo Srugo (11:24)
But specifically, that's how you got to the ex employees of like the potential competitors.
Benjamin Encz (11:27)
I think also some but mostly through other recruiters and recruiting teams. But I believe the first two introductions to people kind of that had worked at the companies came also for recruiters because they kind of just knew people. It's like, Hey, I know this person, I used to work with them closely when we were a customer, that kind of thing. Pablo Srugo (11:42)
And how did you structure those conversations? Because you know, talking to 100 is and those are the sort of numbers by the for what it's worth that I've seen. on the successful startup side, like it's not like 10 or 20, it's really, you know, it tends to be 50, a hundred, 200. But how do you structure those conversations to really get the most out of them? So you're not like leading questions like these sorts of things to pull out data that is actually quality, quality data.
Benjamin Encz (12:04)
Good question. We treated it as a little bit like a product, I think intuitively. So when we started, it was much more open -ended because we were learning about the space, right? We had our own experience, but it was much more like, Hey, tell us how you do stuff, you know, maybe screen share as you work for a workflow, tell us about your pain points. very broadly, once we started having some patterns, what we could do is reuse that in future conversations. We actually use that to build credibility. So we talked to someone and be like, hey, we've been talking to a bunch of people and they said, this is an issue. Are you seeing the same thing? It's like, yes, you get me. And they kind of opened up, similarizing like sales, we started using kind of tidbits from prior conversations and new ones. Again, early on was super broad for us to learn the space. Once we had a pretty good sense about pain points, we started switching towards painting a picture of a possible solutions. So we kind of usually split the call and kind of half and be like, Hey, we're gonna spend some time just getting to know you what pain that's gonna have all of that. Then we're gonna spend some time showing you what we're building.
Pablo Srugo (13:01)
All the pain points specifically, like, was it literally just like, what are your biggest pain points like super high level or did you specifically say like, is reporting a pain point?
Benjamin Encz (13:09)
We generally once we had this like two part call, we would start very high level because you want to see where people take you without without leading and again, just like what is actually top of mind for them. And then the second half, We had basically like, here's what we're building. And we had basically built like a landing page, but actually we didn't have the website, but once you put in your email, you would get this kind of, we'd send you this landing page and there was a high level outline of what the product would look like. And so we'd almost do like a sales call without showing the product because the product wasn't built. But basically, okay, we've got the discovery done now, like, here's what we're building. What do you think about these different areas of the product? And so we kind of refine the mocks of the product based on what we learned from these conversations. What we got to towards the end was like a very strong signal that people were really excited about the product if it were actually existing. Like the main piece of feedback we got in the end was like, I don't know that you can actually build all of this, but if you can, that would be absolutely amazing. And so at that point we're like, okay, now we know we're down to like, it's just the execution problem, but we've kind of de -risked it. And so that was kind of the journey, kind of like continuously showing higher fidelity, kind of mock -ups of what the product would actually look like.
Pablo Srugo (14:12)
Do you remember some other key learnings from that process besides effectively validating your pain point and realizing that you're not the only one that really cares about reporting. Do you remember other things that really helped you figure out what that initial kind of product should be?
Benjamin Encz (14:28)
Yeah, I think one big step function. So early on, we talked to a lot of actual day -to -day recruiters because these were the people who had the most kind of tactical product feedback. We got into IC kind of industry research phase without, we had like a very, very early prototype, but no live product. One thing they pushed us to do, I think generally our approach didn't really fit into the YC model as traditional. You know, we didn't ship quickly and get weekly feedback from users and all of that. But one thing that pushed us, which was super helpful is actually talking to decision makers and getting crisper on the like, okay, you've validated that users have these issues and that users would be excited about a different product, but like, can you actually sell this thing? And so that was a pretty pivotal moment where we started switching, talking to heads of talent, heads of people, and then getting them to like really walk us through like, okay.You've seen this, like, what would it actually take to make this switch, you know, rip out all the tools you have today, to walk us through like, when would you do this and when would you not do this and give us kind of an honest answer? I think that was a, we learned a lot from that, which was very different than kind of the end user feedback.
Pablo Srugo (15:26)
What did you learn? Like, was there willingness to rip and replace?
Benjamin Encz (15:29)
I think, yeah, there was definitely, you know, again, I think if you just go from first principles, right, I think one of the key things for me was like, people were already switching. So there's no question in my mind that if people are already switching from solution A to B to C, whatever. There is a possibility for us to be one of these solutions. So that was a good news. So we had that validated already. What we focused on in these conversations was like, what are the key things they get you to switch? And so obviously the reporting and data thing came up a lot. And then also what are your biggest concerns around switching? And that was mostly like data transfer and like training enablements. So we could start weaving that into the story as well. But I think, yeah, just going from first principles, we looked a lot at the existing market and that didn't require talking to users. It's just like 20 products, people are switching between them.
even though it's a high switching cost, so clearly there is enough pain that people are willing to move around.
Pablo Srugo (16:16)
And was your pitch switching their ATS for your ATS or was it switching multiple different products for your product?
Benjamin Encz (16:22)
It was actually multiple different products. It was the way the market had evolved was there was a traditional ATS market, but then there were more and more point solutions being added in part because the prior generation ATS, again, they started like 2012, 2013, there was like this big wave and then
Recruiting teams really changed the way they worked in like 2017, 18, 19, and these tools didn't really keep up. And so there were more and more add -ons, like add -ons for reporting, add -ons for scheduling, add -ons for like sourcing past candidates. And so our point of view was if you're going to build something from scratch in 2018, in hindsight, what you want to do is like bring a lot of these key things together into a single product. And so that's kind of, as we started iterating on like, what would this look like? That is part of the pitch and that landed super well. Where people were like, man. I really need all these things today because my ATS doesn't do them. But if I could have all of that in a single product and have really good reporting across all of these things at once, that would be just amazing. Again, I don't think you can build it, but it would be awesome if you could.
Pablo Srugo (17:21)
You know, there's that like popular quote that like everything is bundling and unbundling and bundling and unbundling. And, and from my end, like the way that it, that it comes up is like you, you often hear pitches that are like end to end software, you know, one stop shop for X. And I guess I'm just like, curious for your thoughts on you kind of did that, right? You did an end to end sort of solution. They got a bunch of different point solutions, just put mine instead. It worked. What are your thoughts on that? Like when does this one stop shop for X model actually work? And when does it sound good in theory, but then you go in and you try and rip and replace it and it just falls flat.
Benjamin Encz (17:56)
Yeah, it's a good question. I mean, the circumstances for every company are quite unique. So I always have a hard time giving general advice to anyone. It's like, You know, if I take a step back, even like replacing a system of record is usually something that's not easy to do. In this particular case, the opportunity for us was there because there were multiple really big pain points in the market that have been there for many years. Like people were talking about reporting for like two, three, four years and none of the vendors were making improvements. That's again, like one unique thing about our market. The other unique thing was in recruiting at a time, it's still today, a lot of the point solutions were kind of smaller vendors because the markets aren't massive. It felt easier for us to bundle these products at the same quality with not a massive engineering team. Like, you know, if there's like some company working on a solution that's like three or four engineers and part of what they need to build is like, they have to build notifications, they have to build permissions, they have to build all the basic SaaS things and they have to build your product. Replicating that within your platform, if you can reuse all the underlying pieces is easier if the offering is pretty small. Like, and so I think on a recruiting side, that felt possible. It felt like... hard but not impossible to build a bundle of best -of -class products, which is like our particular strategy. Like we didn't say we're all in one, but you're going to lose half your functionality. We said like you're all in one and you get an on -par replacement. Like you're not losing anything across all the different things we're replacing. That was our unique strategy. I think it only worked in this market. I think if you try to do it on sales, it's way harder because there are really big companies of like hundreds of engineers in each of the point solutions in sales. Whereas in recruiting, that's not the case. And then again, I think, you know, when you talk about all in one, we're end to end. It really depends on your approach. I think there's companies out there like Rippling, they go much, much, much broader, but not as deep. And that's their strategy. And it makes a lot of sense for us. The strategy was going a little bit broader, but very deep in the things that we do cover. And so there's a lot of nuance to all of that. In our case, again, from first principles, if you can give people one product that works as good or better than four products, and they're not losing a single piece of functionality, then it's pretty clear that people will be happy to use that. And so that's kind of how we work backwards into this. We said, we're just going to build full parity across all these things. You just have to have a space where that's actually possible.
Pablo Srugo (20:02)
Well, I think that, I mean, that's kind of the hard part here, right? Because when you go to end to end, you've got to spend so much time building a product that for, you know, let's say 70 % of it is really just feature parity with everything else. And then 30 % is your add -on. And I think that's where like, you know, you talked about YC pushing you and every company. And I've heard this actually recently from three different founders that YC is really on this launch something, you know, every week and those founders were like, you know, it just didn't fit for them. But maybe in a side, like, I guess the point is how do you set up your MVP so that you still get something out as fast as possible, but you're good enough that somebody will, will rip and replace it. It's a tough balance, right?
Benjamin Encz (20:43)
Yeah, it's tough. But yeah, we basically didn't, I don't think an MVP makes a ton of sense if you are replacing an existing system one to one. I think for us, the MVP was like our
mock -ups and basically like our design, the design and research work we did upfront was like, that was the MVP. You know, it's like, here's all the things we're going to build. Here's exactly how it's going to work. But then it was really just, and this was like something my company and I felt like we were uniquely suited for was like, we don't love market risks. Like we don't want to build something in social consumer where like maybe pivoting around for years to find, find a holy grail. Like we're really good at building a great engineering organization. We want to figure something out that turns out to just be like a pure, pure execution problem. So. We sequenced it such that the MVP was really the research and like figuring out what to build. And then from there was just building, building, building. The problem we did run into was it took us longer than we thought. And so there was like a little bit of question of like-
Pablo Srugo (21:35)
How long did it take?
Benjamin Encz (21:36)
Uhh, depends on which milestone. So it took us, we quit our jobs, August, 2018 or something. We went for IC early 2019. In that phase, we were still only building like a really early prototype. And then in March, 2019, once we finished YC and wrapped up the seed round, that's when we started in earnest, like now building the actual product. It was using the same foundation, but. And then the first paying customer is like mid 2020. So it was like over.
Pablo Srugo (21:57)
Okay. So it was like two years from idea to first paying customer.
Benjamin Encz (22:00)
Yep. A year and some months from like just coding full -time every day to actually giving it the hand of a customer and letting them use it for the first time.
Pablo Srugo (22:10)
And you talked about de -risking like during that year, how far did you push customers to help you de -risk? Cause there's one thing somebody telling you, yeah, this is awesome. Yeah. If you build it, I'm going to buy it. It's another thing. Somebody signing a letter intent. somebody signing a purchase agreement and somebody actually giving you a check.
Benjamin Encz (22:26)
Again, YCE, again, super helpful in that they got us to do this letter of intent thing, which doesn't really hold any ground, but it does get someone in the company to sign something, which if the company is big enough, they need legal review. There needs to be some motivation. And so we actually got to this letter of intent stage and we signed some design partners. In the end, none of them were like, it took us way too, a lot of them actually became customers now, but at the time the people had left since then. But for this phase where we were building.
Pablo Srugo (22:51)
Did you charge them, like those design customers?
Benjamin Encz (22:53)
We didn't charge anything, yeah, at the time. For us, it was too far out. It was like, you know, it just will take, we thought it will take nine months, and then it took more like 18 months or so. But it was too early to charge. Maybe it could have, but it was not, it wasn't the thing we prioritized. The thing we cared about was getting their time and attention. And that was mostly what we needed. But basically what happened, so just if you go through the phases, we did this de -risking phase, where we did all this analysis, et cetera. And then we went to the kind of the build phase. In that build phase, we had a couple of design partners at any point in time who would just show areas of the product as you were building them. The product end -to -end was not usable, but I'd meet with them every couple of weeks and be like, here's what scheduling is going to look like, here's what reporting is going to look like. And we do actual live demos for very small segments of the product with demo data, et cetera. So it was helpful, but 90 % of the time we were just spending heads down engineering and just churning out code.
Pablo Srugo (23:44)
How are you eliciting just on those design reviews? there's this challenge, right? Where you obviously, you want to show customers what the product's looking like. You want to get their feedback, but they're also not necessarily product managers, right? So it's not like you want to take everything they say and just implement it. Like what were you looking for from them in those discussions that you had?
Benjamin Encz (24:03)
I mean, that's a general kind of product management question. I think the real goal for me always when talking to customers is just get a really, really deep understanding of them, their priorities, their problems, their industry. We're not looking for solutions, right? We're not being like, tell us how, what we should build or give us suggestions, but like, what are you trying to do and why are you trying to do that? And I think you can, if you have curiosity about a space, you can spend like an hour with someone you can go down and you're going to learn so much. And so I think I started building this map of like, you know, from these hundreds over time, hundreds and hundreds of conversations and just following different threads. But really just trying to build a mental model of like, who are the kind of people we're serving? What are the kinds of jobs they do? What are their motivations? What are their problems? Who do they collaborate with? All that kind of stuff. So that's what we really focused on.
The product demo is a little bit more validation of like, you told me all these things. Can you actually, here's how I think you can solve for that thing. Did we build the right thing to solve for the thing you're talking about? And so it's more validation of the solution rather than like
learning. The learning kind of happens before that.
Pablo Srugo (25:01)
Perfect. So, so you're building this, you're doing these design reviews. When, when did you feel like you had something that was ready to be sold?
Benjamin Encz (25:07)
Yeah, again, I think the, you know, I think our ideal solution would have been like raise, you know, $50 million out of the gate, higher 10,20 engineers built for like two to three years. That's kind of what Workday did when they started the company because they were all former people from PeopleSoft. And so if you want to build like a really complex SaaS platform, being able to invest a lot of friends is great. So we basically would have liked to wait as long as possible, but there were some constraints on like actually needing to show that this will work to be able to raise subsidy funding, et cetera. So we tried to go wait as long as possible, but at some point we reached a point where we said like, okay, now we probably have to, and it's... was like mid 2020 and we focused at that point on kind of pivoting it a little bit from like building all this like powerful underlying stuff that was like really big long -term investment to now we need to make it work end to end for like the smallest possible customer. And so we pivoted to that and then we got it to a point and then I started outbounding people. But at that point, the product was working end to end for early stage companies. There were still a lot of bells and whistles at the top missing for like bigger companies, but we were a good replacement for any of the other tools that may have used the space. And we had some differentiated value props around.
being able to bundle these multiple tools. And that actually ends up working super well, much better than I expected. Early on, we didn't really think early stage companies would be as relevant to us because we really focused on these sophisticated customers of like, you know, they need reporting, they've got recruiting ops, all that kind of stuff. We treated startups more as like, we need someone to actually use the product and find bugs and, you know, make sure this whole thing works. That's not just us. But we kind of got lucky with startups as well because this all in one offering really resonated. And so that took off relatively quickly.
Pablo Srugo (26:44)
How did you set that up? Like, was it just cold outbound or did you?
Benjamin Encz (26:47)
Yeah, it started cold outbound.And then we were in my CE, so it helps a little bit, but honestly, we got quite lucky at this stage again, because I called outbounded maybe 10 people. And then two or three of them were really successful startups. One of them was Deal. Again, Deal, back in the day, they were raising around every six months or so. So we got a ton of free PR. We just got really lucky there, I think, in terms of - So from 10 cold outbound, you got three customers.
Pablo Srugo (27:11)
Yeah. Yeah. That's crazy conversion.
Benjamin Encz (27:14)
Yeah. Yeah. Yeah. I think part of it was, you know, it is a product that people do need once at a certain stage. It's like, it's kind of like, I mean, 10 call that one.
Pablo Srugo (27:21)
You're lucky if you get three replies, like even that I would be happy with.
Benjamin Encz (27:22)
And again, some of them were AC companies, so you could tailor a little bit more. I think part of it was people were receptive, because they bad experience of a past product in this space? And they were like, you're building something new, awesome, I'll take a look.
Pablo Srugo (27:37)
What was the pricing like for a product like this and for startups?
Benjamin Encz (27:40)
It was quite cheap. And it still remains actually quite cheap for early stage companies. Again, the goal for us was just get someone to pay something.
Pablo Srugo (27:47)
What's like an ACV like for -
Benjamin Encz (27:48)
At the time, it was like, you know, a deal with over 20 people. It was like, I think it was maybe $200 a month back then or something. Okay. It's a little bit more now.
Pablo Srugo (27:56)
It's like $2 ,500 a year. Okay.
Benjamin Encz (27:58)
Yeah. And it was month -to -month. We didn't ask them for like an annual agreement or anything. So it was pretty low, pretty easy ask basically.
Pablo Srugo (28:05)
Where did you have to get to? Cause you said your goal was to get really more money in so you could really beef up the product. I see raise like a $10 million series A walk us through like what that process was like and maybe where the company had to get to for you to be able to do that.
Benjamin Encz (28:18)
Again, a little bit lucky in a little bit of market at the time. A lot of this stuff may be harder to replicate in other markets or now, but where we were at, the literal conversation we're having is like, you know, my co -founder and I were both fiscally pretty conservative. So we had raised this sizable seed round. We knew it would take us a while to build.
Pablo Srugo (28:36)
It’s like 3 and a half right?
Benjamin Encz (28:37)
So we're trying to keep our cash burn. Yeah. Kept our cash burn quite low. We already have three people on a team. It's like, we're just going to keep heads down building. We don't get that many people.
Pablo Srugo (28:44)
So you were three people. So you had raised three and a half million and you kept the team to three people.
Benjamin Encz (28:47)
Yeah. Yeah.
Pablo Srugo (28:48)
Oh wow. Okay. *laughing* That's what was the thinking there because you're really, you've got a pretty clear idea of what you want to build. You'd think with three and a half million, you'd get to, I don't know, 15 people, 10, 15 people.
Benjamin Encz (29:00)
Yeah. I mean, we basically just needed engineers and we had engineers on our network that were waiting to recruit. And there was like one that was immediately available. And then there were two or three others that were kind of passively working on, but it was like, we could spend time recruiting or we could spend time building. And we were just like, we're going to be really fast. And we underestimated how much it was to build, right? But still.
Pablo Srugo (29:17)
Was that the right decision? Because there are pros and cons to having smaller people is also helpful sometimes.
Benjamin Encz (29:23)
Yeah, I agree. It was really helpful. So I think it was good. I think we probably could have gone to five a few months later, basically, and not stayed at three, but I think it was good. at a time because we didn't want to paralyze too much because we're building this platform. So we actually, there was some sequencing to be done of like, we need to build this first and then this first, and there wasn't that much stuff you could do in parallel. But yeah, we're just three people. And then we got these first few paying customers. And then a few months later, at that point, we have probably like 20 paying customers or so. One of our existing investors was like, hey, what does, what did it take you to go faster? To be comfortable, like open up the faucet on spending because like you are, it seems like you're doing great, but you're going very conservatively near spend.And so an existing investor just offered to do a 10 million series A and I was like, okay, that would definitely allow me to spend a little bit more money.
Pablo Srugo (30:08)
That'll do it. And you were, you were small. You're doing what like 5k MRO sort of thing at a time.
Benjamin Encz (30:11)
I won't disclose the exact number, but we were like, yeah, 20 some customers. So, you know, not, not, definitely not the traditional, not the series A mouth done today.
Pablo Srugo (30:18)
Sure. And so, and so from there, I guess, see you raised this $10 million, you know, from there for the next two years, is it just really like heads down or how do you balance like the outbound motion, adding new customers versus just building that product that you know you want to build.
Benjamin Encz (30:33)
Yeah. So it was interesting, and I think so 2020 was the first paying customer. And then by the end of the year, we had hit like hundreds of thousands of revenues. So the market back then was, you know, recruiting was like kind of exploding.
Pablo Srugo (30:48)
Exploding, yeah, it's true. 2020
Benjamin Encz (30:48)
we just got, we just got a lot of pull. And so my role switched pretty quickly where it was like before that was really engineering and product work together with other. early people to a lot of go -to -market stuff. We were getting a lot of inbound and I was doing all the demos and stuff. So we ended up, you know, adding it for Salesforce relatively quickly. And then the year after that, we went into the multiple millions. So it was like a pretty fast, like more than 10 X growth. And so it shifted pretty quickly from, we started, had to build out the other, other functions, but it was still.
Pablo Srugo (31:19)
Timeline to say back to you is like two years to like, you know, two and a half years to maybe a few hundred K in revenue, but then. couple million in revenue kind of a year later, like a 10X jump that once you've had things out, okay.
Benjamin Encz (31:30)
Yeah, that's roughly how it worked. And then yeah, from there, from there has just been kind of just like steady, but like adding everything over time. It was definitely this phase shift was series A, you know, we went out, we started hiring, we started building a bigger team.
Pablo Srugo (31:42)
Perfect. Well, let's stop it there. And let me just ask the two questions we always finish on. The first one is when did you feel like you had true product marketing fit?
Benjamin Encz (31:51)
Probably kind of around that series A.
In our case, fortunately, a couple of months after we had the first few paying customers, just because there was so much repeatability, you know, I would see dozens of customers sign up every month with like the same kind of positive feedback and the same profile. And just felt like there's, there's something scalable here.
Pablo Srugo (32:09)
And what was the retention like, you know, in the early days, especially for a product like this?
Benjamin Encz (32:12)
Really good was the ad was extremely high. The first time we saw any turn was kind of the venture capital downturn, you know, when companies were failing and going out of business. But yeah, it was, it was really high at the time. We had some very few customers go to competitive product, but they ran into gaps with integrations or some like, you know, part of it was still pretty raw. There were still some definitely, but it was very small. Like the retention numbers were really, really good.
Pablo Srugo (32:34)
And then the last question is if you could go back to 2018 with everything you've learned over the last six years with some advice for yourself, what might that be?
Benjamin Encz (32:44)
Good question. I mean, stuff will take longer. That's a big one, but you don't really want to know that. That's always the -
Pablo Srugo (32:50)
That's right. Yeah, being naive helps, right?
Benjamin Encz (32:52)
Exactly. You wouldn't start it if you knew. Maybe being a little bit less conservative, though I feel like we still remain conservative and I don't know if it's a bad thing. It's just a personality thing. I just feel more comfortable being conservative. We got lucky. Again, I think you build the kind of company that suits you personally, ideally. And I think for us, we went after an existing market and so there was a little bit less. There wasn't a line grab ever. It was like, we built this at a time we thought it makes sense rather than you're being like remote payroll being like one of these where you just have to go fast because like you want to be one of the two top companies in the space. So I don't know if I, yeah, stuff will take longer and maybe be a little bit less conservative. Overall, I think we got lucky, but also things kind of roughly penciled out the way we thought it would. I think in part because we did so much research upfront, I think we felt really confident after like six months about thinking about this problem and talking to hundreds of people.
Pablo Srugo (33:39)
Well, it seems like a classic case of going slow so you can go fast, right?
Benjamin Encz (33:44)
That's a good, that's a good summary.
Pablo Srugo (33:45)
Perfect. Well, Benji, thanks so much for spending time. This was great.
Benjamin Encz (33:49)
Awesome.Thanks for having me.
Pablo Srugo (33:51)
If you've listened to this episode and the show and you like it, I have a huge favor to ask for you. Well, it's actually a really small favor, but it has huge impact. But whichever app you're listening to this episode on, take it out, go to a product market fit show and leave a review. Please. It's going to help. It's not just going to help me to be clear.
It's going to help other founders discover the show because the algorithms, whether it's Spotify, whether it's Apple, whether it's any other podcast player, one of the big things they look at is frequency of reviews. It's quantity of reviews. And the reality is if all of you listening right now left reviews, we would have thousands of reviews. So please take literally a minute, even if you're just writing like great podcast or I love this podcast, whatever it is, just write a few words. Obviously, the longer, the better, the more detailed, the better, but write anything, leave five stars, and you will be helping me, but most importantly, many other founders just like you discover the show. Thank you.
