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

Transcript

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.