Omer (00:09.760)
Welcome to another episode of the SaaS Podcast.
I'm your host Omer Khan and this is a show where I interview proven founders and industry experts who share their stories, strategies and insights to help you build, launch and grow your SaaS business.
In this episode, I talked to Hung Dang, the founder and CEO of Y42, a fully managed DataOps cloud that helps companies design production ready data pipelines on top of their BigQuery or Snowflake data warehouse.
After having spent many years working in data analytics, Hung became frustrated with all the various tools needed to build out a proper data infrastructure.
So in 2020, he decided to build an end to end data platform that would replace those tools.
But Hung didn't go and interview customers to validate his idea.
He immediately started working on the product and spent a full year building it.
When he finally launched and put his product in front of customers, he realized it was still missing about 30% of the features they actually needed.
And about 20% of the features he spent the last year building weren't even that important to customers.
However, a year later, his business was still able to hit the first million in arrival.
We unpack why he was able to do that without doing all the customer validation that we always talk about.
And we talk about the lessons he learned from that experience.
We also discuss how as a tech guy, he learned to do founder led sales and why he believes it's an essential skill for every founder.
To date, Y42 has raised $34 million in funding.
The company has several hundred customers and a team of 150 people based in Berlin, Germany.
So I hope you enjoy it.
Hong, welcome to the show.
Hung Dang (01:51.280)
Hey Omer, thank you for having me here.
Omer (01:53.840)
My pleasure.
Do you have a quote, something that inspires or motivates you that you can share with us?
Hung Dang (01:58.800)
I do and I kind of make it up.
So usually I'm not the kind of guy that makes up some random quotes and, you know, walks around with it, but in this case, I really like it, you know, and it's called face the harsh truth or the harsh truth will face you.
And this is something we talk a lot about within our team, especially the leadership team, that we don't lie to ourselves.
We try to identify the core truth behind every decision.
If we see we took the wrong course of action.
Yeah, we don't lie to ourselves and correct it.
And you know, this is something that I keep reminding, reminding myself and we keep reminding us as a team on a daily basis.
Omer (02:41.960)
Great.
Love it.
So tell us about Y42.
What does the product do?
Who's it for?
And what's the main problem that you're helping to solve?
Hung Dang (02:49.400)
So we are a data infrastructure company and as the name already implies, why 42 and 42 is the answer to the ultimate question of life, the universe and everything according to the Hitchhiker's Guide to the Galaxy.
And what we're trying to do is we're once again connecting to my quote from before.
We're trying to understand the world, we're trying to understand what's the core truth, knowing that we might never find that core truth, but still we're on a journey to pursue it.
And this is best done in my point of view, through recognizing patterns of the real world in data.
And this is why we want to provide everyone the power to work with data efficiently and understand the world from different angles, changing their own perception and reality about the world.
And we're doing that by providing companies a software to help them get started really quickly building out data pipelines.
We started out with a no code, low code approach.
So we enable every company to build ad hoc data pipelines.
Pipelines get started really quickly.
And as a matter of fact, today is the day we're launching the next evolution of our product which we call the modern DataOps cloud.
And with the new product, yeah, Y42 now enables companies with the ambition to go beyond simple ad hoc reporting to build production ready pipelines with a quick turnaround time without having heavy investments in a data engineering team.
And so it's the mission control center on top of our customers data warehouse such as BigQuery or Snowflake.
And so we help the companies to produce reliable data effectively that can be consumed in consistent way by a downstream user or an application such as AI and ML use cases.
And so our customers are usually companies that are in the process of setting up this reliable data infrastructure which is their backbone for key decision making for C level downstream operation application.
And they usually tend to be in the earlier stages where there are around 100 people in the team, but also big corporations that would like to digitally transform parts of the organization such as the product team, the sales team or the marketing team.
Omer (05:23.300)
Great.
So give us a sense of the size of the business.
What are you in terms of revenue?
What's the size of the team?
How many customers do you have?
Hung Dang (05:30.620)
So we are quite young company.
We started early 2020.
So we built out our product for the first year we went online early 2021, like after a year and then we finished 2021 with 1 million ARR.
So this is something that allowed us to raise a very big round of money.
To be fair at the time it was a good time to raise money, but we are out to play a very big game, the data infrastructure game.
And we didn't expect to hit 1 million AR that fast with the kind of platform infrastructure plates.
It's a very different go to market motion than a point to point tool where you can onboard customers rather quickly.
But in this case data infrastructure, it, it's like deep tech.
It takes you just a couple of years to really build out a product that you can sell.
So we were super surprised by that as well.
And then we raised that amount.
It gave us the confidence to then really build out the new product.
And we have the ambition to become the core data infrastructure layer for many companies out there.
And so no code, low code wasn't enough anymore.
We knew that a more comprehensive software was needed to tackle the complexity that working with data entails.
So we were heads down building out the product again over the last year and so we didn't focus much on revenue.
Nevertheless, we're still talking about a growth between 2 and 3x this year.
But the new product should allow us to consistently grow 3x year over year, at least for the next couple of years.
And so this is the bet that we are making right now.
Omer (07:26.890)
And you've raised I think $34 million to date, is that right?
Hung Dang (07:32.010)
Yeah, that's correct.
Omer (07:33.610)
What's the size of the team and how many customers do you have?
Hung Dang (07:36.650)
So we are around 150 people now in the company and customers, it's in the lower hundreds of customers that we currently have.
Omer (07:48.230)
So let's start with where you came up with the idea for this business.
What were you doing at the time and how did you have your aha moment about building this business?
Hung Dang (07:59.270)
I studied business analytics.
You know, I come from a very mathematical and statistical household.
So my stepfather, he's a professor in sociology and he teaches statistics.
My mom made her PhD in Statistics and so I grew up with this natural edge of okay, if I don't understand anything, I can go to my parents, they will explain it to me in math, statistics, whatever that is.
So I have this natural advantage in school and uni and I got a lot of approval for that.
So you tend to be gravitating towards that and you like, okay, I'm good at that.
But obviously my parents were good at that and they helped me to become good at it also.
So I was always in the field of data.
I started actually two analytics ventures with the last one in 2016, and that one then was focusing on the live event industry.
So we were analyzing all the major festivals like Ed Sheeran or Justin Bieber, like concerts festivals, like arenas, like the O2 arena in London.
So we had like roughly one third of all events in Europe at the time using our software to capture and analyze data.
In 2020, the company was bought by a German Fortune 100 company.
So in that time I've worked with many data teams in an industry that I would say event organizers are not the most sophisticated ones, but they still have a lot of data.
Because at an Ed Sheeran concert you have 100,000 people there producing millions or billions of data points.
So we needed to build a solution that is super scalable, but at the same time quite easy to use.
It's almost like an oxymoron.
So I've been operating in that industry for quite a while.
And then with the rise of data warehouses such as Snowflake and Bigquery, so the compute and storage cost became just so low or like 10x low or 3x.
It's a kind of 3 to 10x jump in terms of performance and cost savings to work with data.
Back in the days when the iPhone4 came out and the apps marketplace, the iOS marketplace, everybody starts to build apps on top of that.
And it's the same in the data industry when the data warehouses became a thing.
So now there are so many of these point to point solutions out there.
And in order to build out a proper data infrastructure, you need like five different tools and more like one for data integration, one for data transformation, one for data orchestration, one for observability, one for visualization, one, you name it, right?
Like the whole shebang stack in there.
And I was working in this industry and I was very frustrated with that.
And that's why I decided to build out a tool which we call now the modern DataOps cloud that takes the best of breed open source software.
From each of these discipline, we alter the underlying code and write our own code in order to natively integrate all of these tools together and then offer a solution that is very accessible in the first place for technical users, but then also very accessible for non technical users with a no code, low code layer on top of of the technical layer that produces code at the end of the day.
And this is where I was coming from, from the event analytics world where things has to be no code, low code.
But in order to build our production ready data infrastructure, you need to Include software and product management, like software engineering and product management best practices.
I mean, it's a lot of industry knowledge that I've had for my previous venture.
It's not just like, oh, I have this fantastic idea, I talk to five people and off we go with the journey.
It could work like that.
I just think that's very difficult just because you don't have enough experience in the one industry in order to go deep enough to really understand, oh, okay, maybe stuff like that.
It already exists because there's a competitor doing that.
I just don't know about that or, oh, nobody needs that.
And you don't have enough time to run that cycle of iteration when you're on your own with very limited set of resources to figure it out.
But still, I always did that.
Don't get me wrong, when I first started into the data world, I had a bit of an edge, like understanding data, understanding the tooling space.
But I still went into it and tried my best and have to be as quick as I can to iterate and learn.
So the first failure, I wouldn't say that it's so bad to.
I wouldn't say that it's too bad if you don't have experience, but just expect to fail.
And then when you fail, you can always try it again.
Omer (12:55.440)
You had this industry knowledge, you had the personal pain yourself, and that was where the core of this idea came from.
When you started building the first version of the product, did you go out and still talk to other people to get feedback, to do more validation, or did you feel like, look, I understand this problem deeply enough, I've experienced enough pains here.
I feel confident about going and starting
Hung Dang (13:30.430)
to build something was classic overconfidence, you know, like in many other areas of humanity.
So I think I should have talked to more people.
But nevertheless, of course, not talking makes me more focused on building out the product on a very first principle.
But I think I could have avoided a couple of mistakes along the way if I talked to more people along the way, and I make it a point to whenever we develop a product now, to always have certain gateways to, hey, even if it's not done now, stop here and start talking to people right now, even three or four people, that's more than enough for you to validate the idea and you don't need to talk to more.
So, yeah, I think I underestimated that a bit.
So I was rather the silent builder, believing that I understand the problem deep enough just to figure it out, that I should have talked to More people along the way.
Omer (14:32.790)
Tell me about one mistake that you made because you didn't talk to people.
Hung Dang (14:39.110)
I don't think there are any mistakes.
In terms of product building in particular, I don't think there are mistakes.
Right.
It's just rather you can say it's a prioritization mistake.
So something that was only in terms of priority on number five, I thought it's number three or number two, so it has to be done anyways.
But we could have gotten through it a bit smoother by prioritizing certain stuff, like in a certain sequence, which then again, at the end of the day, that's the whole game, like putting the right prioritization behind the action that you do.
So if I say, oh, it's just a prioritization thing, then no, it was a mistake.
Wrong prioritization.
Omer (15:27.090)
How long did it take you to build the first version of the product and get it in front of potential customers?
Hung Dang (15:32.290)
One year.
Omer (15:33.410)
Okay.
And so in that one year you weren't talking to any customers.
In that one year you were just, as they say, in the basement, building the product.
Hung Dang (15:43.470)
Yes, exactly.
Omer (15:45.070)
And were you doing this full time?
Had you kind of moved on from the previous business?
Hung Dang (15:50.190)
I was doing it full time.
Omer (15:51.710)
And was it just still just you?
Hung Dang (15:53.710)
No, I hired quite some engineers starting out, but again, I had some success with my previous company.
And so this is a game that not everybody can afford to play right off the bat.
So yes, I had a team behind me on day one.
Omer (16:14.130)
Right.
So you were kind of basically self funding this business in the early days on the back of the previous business and the acquisition.
And so you've kind of put it out there for a year, you go and then eventually get it in front of potential customers.
And what was the reaction?
Hung Dang (16:31.570)
That there is roughly 30% of the things that we still need and there are like 20% of things that are nice to have but are not super needed.
And so we had to spend like two more months building out the 30% that was lacking to really get that initial traction.
And then the 20% that wasn't needed wasn't providing that much value like we thought it would.
Omer (17:00.600)
And then how did you go and get your first 10 customers?
Was it you kind of just basically, you know, doing outbound sales?
Were you, you know, kind of talking to people that you already knew that had that problem?
Hung Dang (17:16.540)
Yeah, we were lucky that I had a couple of business angels in the company and they were all friends.
Also, like throughout my last company, I've met some, some people that are quite Successful and we became friends.
And so it was rather a situation where my friends would recommend me to their friends, like, hey, do you need a data tool?
You know, I have a great friend here.
He just started his company and the product just is just out, like, do you want to give it a go?
But it's still a hard sell because like, we're talking about data infrastructure, right?
Like, and that's so fundamental to many business to get that right, than just trusting a random company that is like one year old with like, I don't know, 10 employees.
So it's a, it's a trust game in the first place so that we were able to close our customer, like clients.
It's like friends from our friends, basically.
Omer (18:09.660)
Okay, great.
So I want to talk a little bit more about this because first of all, I think we should make it clear that you're not a sales guy, you're a tech guy, right?
Going out and doing sales, or at least that's what you were doing.
And I think when you get these referrals, these warm intros from people that you know, like angels and so on, that's great.
And I think that that gets you in the door and that makes people more likely to give you time and have that conversation and listen to your pitch and learn about your product.
But as you just said, it's one thing to give you time to listen.
It's another thing to say I'm going to move my whole infrastructure or whatever else I'm doing and rely on this product that, as you said, it's just a startup.
You guys have just been doing this for the last year.
That's a big leap of faith that people need to make.
So can you tell me maybe just what were some of the objections or challenges you were getting in trying to get these people and closing the deal?
And then beyond just using the kind of the endorsement that you got from the angels and so on, how did you get these people to the finish line to commit?
Because it is a big commitment to make.
It's not like, try this CRM product, right?
It's like, that's a very easy, low risk kind of thing to do.
Switching your infrastructure is kind of a, a much bigger decision to make.
Hung Dang (19:46.250)
I think when I say infrastructure, it's a bit extreme also.
It was like we started out with a no code, low code data ingestion and transformation tool.
So definitely much higher risk than a simple CRM that you can kick out at any given time because you invest in that infrastructure.
Nevertheless.
But it's not like, hey, we're the core backbone and every of your business process relies on this to work, otherwise it will fail.
This is not the case.
It is now with the new product, but Obviously we have 34 million in our bag and much more time, so it's not as hard of a sell as you just put it there.
That's the first one.
But the second one is it's future sell.
So you sell a vision also.
You sell a vision where the product will be and how that like the before and the after state.
And if you say I'm not a CS guy, that's also not fair because there was a path in my life where I did CS for one to two years, but I ended up being a techie nevertheless.
So, yes, I'm more of a techie than I'm a sales guy.
But I think as a founder, it's your job to be able to communicate very well, communicate your vision very well, to be able to break it down and talk about it in just a couple of sentences, you know, what you do.
And that's already a great sales skills to have.
And so, yeah, I think I'm a naturally gifted salesperson to set also not to set the wrong stage in here.
And somehow I got lucky that my parents were so statistical and technical that I've also gotten the other part within me.
So, yeah, it's a combination.
Hey, good sales skills, future selling.
And then of course, you know, when you do future sell, like you're going to really see what they need and don't need and then you build that along the way.
So you sell first and then you go back and build immediately.
And then there was a lot of, lots of trust elements in there borrowed from angels and you know, like friends of friends, basically.
Omer (21:55.010)
What were you selling when you said in your background you were, you had sales experience, what were you selling back then?
Hung Dang (21:59.650)
I was collecting donations for the Red Cross, like door to door sales.
So basically I just went from door to door, you know, asking for people.
Like I'm selling basically a good feeling at the time.
So yeah, it's a sleazy.
Not sleazy, but like it's a kind of, you know, you're selling like vacuum cleaners at the door.
But I'm just selling like a good feeling.
Hey, do you want to donate for the Red Cross?
And I, you know, I want to do, yeah, something good for society, humanity.
And that's what I did for quite a first years of my life working as a student job.
Omer (22:35.990)
So is it still hard to Sell a good feeling door to door.
Do people still slam the door in your face from time to time?
Hung Dang (22:41.830)
Oh, they slam the door all the time.
Like I go like to roughly 200 doors every day and I like half of them, they won't even talk to me.
They just slam the door on my face.
Like not talking.
And then you know, 25% are just being nice but still closing the door.
But.
And then there's like, you know, around 25, they would listen to the.
You keep like there's a funnel basically.
Like then half of them would then listen to my first three sentences.
Like half of them then continues to listen to the fifth sentence and so on and so forth.
And so it's a funnel.
So at the end of the day you're getting like 20, 30 people to donate at the end of the funnel.
Omer (23:20.850)
I spoke to somebody who had done door to door sales and they were saying that it just makes you so much more resilient once you have that experience making a cold call or sending an email.
It doesn't seem as hard when you have the door slammed in your face 100%.
Hung Dang (23:35.240)
This is a great skill to have as a founder.
Also to be like, to take rejection extremely well and to be able to process that emotionally and then just continue with high level of motivation as well.
Omer (23:47.400)
Let's just go back to the piece in terms of the first 10 customers and what you were selling them.
So you clarified that hey, this wasn't like, you know, you need to kind of replace whatever infrastructure you're using.
This was kind of like giving them a way to start using it for some kind of use case alongside what they were already doing.
Can you give me kind of an example of the types of things those early customers were using Y42 for?
Hung Dang (24:11.960)
Mostly teams that are less technical.
They don't have like data engineers and that still needs to integrate with data and do their own transformation in order for their reporting to work.
And then we were also lucky at the time it was during COVID and E commerce was booming.
And E commerce tend not to have data engineers.
At least they don't have a lot of that knowledge in house.
So they need a no code, low code tool.
And so we had a good angle to get started.
So we found product market fit quite easily with this angle.
But then again, in the beginning we didn't find out that E commerce was the perfect fit.
Like the first 10 clients that we closed were a combination of B2C, DTC Marketplace, also B2B and so on.
And then it crystallized after the first 10 customers, hey we can serve E commerce very well.
So it was still a very shotgun approach like whatever customers we can get for that product we will try to get.
And so the use case for E commerce is very simple.
You sell on Amazon, you sell on Shopify, you use Stripe, you use Braintree, you have Facebook ads, Google Ads, TikTok, Pinterest.
You need to pull all of this data in your single source of truth like your data warehouse.
And this is what we help you with.
And then you need to merge and transform and clean and automate this pipeline and put tests and observability whether, whenever, an alerting when a pipeline breaks and so on.
And so we help with that with a no code, low code approach.
And by now it's a whole different sophisticated system that really you can access then by now you can access the data with APIs and you can use the CLI to automate that in the API.
So it was a small subset of what we do now, but it was just like very MVP good enough for one set of customers.
And I think it's like the level of sophistication also.
It's a level of sophistication we target like small startups, e commerce that have a lower need for high sophistication tool and our tool was just a good fit for that.
So yeah, for us it's like finding the sophistication level match with the sophistication that we can provide as the tool.
So yeah, you have to find product market fit and you have to find that market.
Omer (26:50.370)
So you see that there's a benefit with e commerce companies around when you've got those first 10 or so customers.
What did you change?
Did you start saying okay we're now going to focus on E commerce, we're going to refine our messaging, our sales pitch everything to talk to that type of customer.
Or was it still let's keep selling to whoever will be, you know, we'll sign up and then we'll see where this goes.
Hung Dang (27:15.870)
I think we're still a startup so it's important to say that you still need to run a lot of experiments.
Like we were not a scale up at the time and so we would invest.
We know that of course we have to still sell and like proof to our like we didn't raise at the time from institutional investors but like prove soon to potential investors that we can scale the business.
And so yes we were focused on focusing on numbers and we were closing them very effectively with E commerce.
But that was maybe 50 or 60% of our time.
Like we still ran a lot of experiments with like different messaging for different markets and maybe like new features that might enable B2B SaaS and like continually to learn and understand how the product has to evolve in order to to go to the next level.
Because just E commerce alone won't make us a billion dollar company and it's just a benchmark.
I'm not here to build a billion dollar company.
If it happens it's great.
And I definitely work towards building something of significance that provides a lot of value in 10 plus years to come.
So I'm playing the long term game.
But yeah, what I'm trying to say is that wouldn't be big enough of a market better proxy.
We wouldn't provide as much value as I want we could with the potential that we have.
And so we have to continue iterating to find that a bigger market and how can we serve people more.
Omer (28:47.540)
Okay and then so today what industries are you serving?
We talked about e commerce B2B SaaS.
Are there any other industries that are kind of a focus for you right now?
Hung Dang (28:59.500)
Yes.
So I mean E commerce still will never go away.
It's a great industry for us to operate in.
Retail also very adjacent to e Commerce B2B SaaS Industries where you have a lot of data in different sources and you need to analyze them for key decision making for downstream use cases like machine learning or AI.
Then any digital business out there is very relevant for us but we really have a wide net of.
Because data is so relevant to every type of industry.
So we are almost industry agnostic by now.
We have a tax agency, the biggest tax agency in New Zealand they're using us for and then we have the biggest car wash in Brazil with a lot of different stores using us and so on and so forth.
So a lot of different types of.
But yes, still predominantly e commerce, retail, B2B SaaS, mobile apps, those are the industries that predominantly continues to use a tool like Y42 and they're big industries and that's why we might have like an over distribution of these industries.
Omer (30:19.920)
So in those early days it was basically founder led sales.
You were going out and meeting customers and closing these deals.
At what point did you bring on somebody to help with the sales and marketing?
Hung Dang (30:33.360)
Unfortunately too late.
It took us really long to hire our VP of marketing and head of sales.
Luckily we very early on we hired our yeah VP of growth and he's like a mini co founder to me.
At the end of the day.
Right.
So Bacha is his name and he was handling marketing and sales.
And he's like a young but very hungry person that just like, hey, I want to get stuff done.
But him alone wasn't enough to scale the business.
Right.
Like, he lacks the experience.
It's not in a bad way.
Right.
It's just I'm lacking experience also in many areas as a CEO.
So we as a team lag experience for marketing, like for proper marketing and sales.
And now it took us a year to actually we just hired our SVP of Marketing Senior Vice President, Max.
He's worked for 20 years as a marketing executive with his last company being sold to Google in terms to Google Data Fusion.
So like always data infrastructure.
And it's a very hard hire.
And same with like, you know, our head of sales.
And we just, Jules just started as our newest president and he was the COO of Qualtrics before and there he was leading sales.
And so, you know, that position, it took us years, like over a year to fill them up.
I would say that having Bahai really helped because I couldn't do it myself.
Right.
Like I was the techy guy.
I was always building the product, doing engineering.
Omer (32:12.710)
So I want to talk about hiring the VP of growth, the VP of sales, and the VP of Marketing in a minute and why that took so long.
But let's talk about.
So you hire a VP of growth, you've got somebody now to beyond working your network to find people, how did you then start to grow and reach other customers?
Hung Dang (32:37.990)
So we're still in that phase of.
Of really figuring out what channels will really scale for us just because we're releasing a new product now as well.
So I cannot tell you the perfect answer yet.
What worked until this point is network continues to be very relevant for us.
So we get recommendations from other clients.
We continuously look into our own network of our investors and of the employees.
Then there's an outbound motion that we do.
We cold call people, we identify list of companies that are very relevant to us and then we're trying to reach them with an outbound motion, multiple channels, touch points, people.
Then there's also inbound marketing which is very relevant for us through people Google us.
People see us on pr.
So I think by now, since we are launching the new product Now, I think TechCrunch will release an article about us within the next half an hour to one hour as well.
So there we do get people coming in.
We get referrals, a network, then outbound followed by inbound and we paid also for advertising like Google Ads, et cetera.
But now it has gotten become very expensive recently and so we don't rely on this as a channel.
Omer (34:19.180)
You said people also were googling you and finding you.
What were people searching for?
Hung Dang (34:25.340)
So they're searching for data infrastructure, data ingestion, data transformation.
How can I work with data effectively without having a whole data engineering team?
These kind of keywords, like basically setting up a data infrastructure very effectively.
Omer (34:44.460)
So basically they're looking for solutions to problems and then through that they want to figure out how to do data ingestion better.
And through that they're finding some page on your site which either maybe it's an article or maybe it's a landing page talking about how I don't think
Hung Dang (35:04.190)
that's a relevant channel at all.
I think thought leadership is much more important than we share our thoughts on LinkedIn.
We participate in the community, in this case in the data community, because it's a very tight not community.
So I don't think the classic marketing playbook works for us.
It doesn't to that extent.
Like, oh, okay, yes, SEO is important, yes, search is important.
But thought leadership demand gen in general is just more important than bidding on keywords or optimizing for search.
Omer (35:49.960)
So, so that kind of organic search, it happens, but it's not exactly a major source of of leads and sales.
So when you talk about thought leadership on LinkedIn, how are you doing that?
Is that you personally spending time writing, publishing, engaging?
Is it coming through the Y42 kind of company profile and what you're sharing there?
It's a combination.
Like how are you building that thought leadership on LinkedIn?
Hung Dang (36:18.510)
So thought leadership can only happen based on one person.
That's our experience at least.
So people follow other people and not companies.
And when I do thought leadership, it's really about giving value first to the community.
Like sharing certain thought process that I have identified throughout my data journey.
Trying to be as unbiased as possible with your own offer, like clearly your thoughts are being driven by your offering and vice versa.
So I try to share content on LinkedIn that works quite well.
Go to these conferences and give talks, not just me, our engineers and so on.
We participate in the conversations that's happening.
I don't know, on Y Combinator, on Hacker News, we participate on conversations in LinkedIn we set up events.
For example, we have an event next week, a data meetup next week and sharing with the community.
Omer (37:27.110)
And when you said you focus on value first, is that basically it's really about number one, obviously understanding the people in the community, the problems that they have and spending most of your focus talking about either talking about those problems or solutions to them and not necessarily how Y42 solves the problems.
Or are you kind of trying to weave that into the conversations as well?
Hung Dang (37:55.680)
We try not to, but sometimes of course that comes up.
Right.
Because there's a certain hypothesis or angle to solve a certain problem.
And we just built Y42 exactly to solve this one problem.
And so sometimes I would bring it up in the conversations, but then other time is really, I think if you are facing with this problem in such a high intensity, it's like almost writing your PhD thesis, right?
Like you're going so deep into like one dimensional, so deep into one subject and like you can kind of push forward like you're at the very edge of human knowledge in that one discipline and field.
And so you have a lot of thoughts and you want to share that with the community and you want to drive awareness of where the whole like what's important in your point of view.
So it's a PhD thesis, but like in a more practical, worldly example.
Omer (38:57.060)
Great.
So let's go back to what you said about, you know, it took too long to hire your VP of sales and VP of marketing.
Was it just the search process and finding the right person or, or do you feel now looking back that you, you should have started that hiring process much earlier?
Hung Dang (39:20.080)
We started it at the right time.
It's just the process itself.
Like we tried it on our own for like two months.
Right.
And the problem is if you are a very early stage company, you don't have any like brand recognition, it's super hard for you to hire them.
And then that's when we realized we need to hire like an agency, like an executive search agency once we have more money raised as well.
And then that's going to take them three months to just identify all the people.
And then the next one to two or three months where we're sharpening the profile so we even know what we wanted.
Then another three months of talking to people, doing outreach.
And then usually people in Germany, they can only start within three months.
They're in high positions, they want to wrap things up nicely.
And in Germany you even have like three month notice period before you can leave.
In all extreme, we didn't hire our VP of marketing and CS from Germany, but that being said, it took us like 10 months plus depending on the role in total and certainly we could be more, I think if we were really executing well, we would probably be two months faster, but I don't think that it could be done faster than two months.
And we didn't want to hire just a random person.
Again, if you just hire somebody for the sake of hiring, then you can do that within two or three months.
Omer (41:01.930)
I mean, we look at the story here.
You started the business under three years ago.
You got to the first million arrangements faster than you had thought.
That help you to raise the funding to the 34 million that we talked about.
The team has grown to 150 odd people.
So it's still relatively early days, but you've got some, some solid traction there and you're kind of building on that.
And then the new product is coming out, you know, or announcement at least today as we speak, it's imminent.
What do you wish you had done differently?
What sort of look back over the last few years.
Hung Dang (41:42.550)
Talking more to customers is definitely one of the weaknesses and you have to strike a fine balance.
If you talk to customers all the time, you're hiding behind in action, but if you don't talk with them at all, then it's too arrogant for not taking it on.
But that's one part.
The other part is precise communication internally.
I underestimate how important it is to be very vocal about the vision and break it down in ways that everybody truly understands it and align people on the way.
I'm not saying like something I regret.
It's just like something that I recognize a bit too late that I should have done it earlier.
So it's just a learning for me.
I'm trying not to have many regrets because everything is just a learning.
Omer (42:36.730)
And then also I think as the organization grows, communicating as a leader in a team of 20, 30 people is very different to a team of 150, 200 people.
The dynamics are very different.
And you start to get to that point where you don't know everybody personally in the team.
And maybe you, you have managers of managers and the communication, there's just a whole different set of dynamics that you have to now deal with to communicate effectively.
And I think it's just, you know, part of the learning process.
The other thing I just want to quickly touch on before we wrap up and go into the lightning round is competitors.
So when you started this business,
Hung Dang (43:20.570)
were
Omer (43:20.930)
there other products in the market?
Did you have competitors out there?
And if so, what was the opportunity that you saw in terms of what they weren't delivering on?
Hung Dang (43:35.100)
We have, like I've said, the boom of the data Warehouse, we have a lot of competitors, but they are all in the super early days as well.
And so there was a one paradigm shift, Data warehouse.
There's one paradigm shift, Apple, the app store of Apple.
And so we wrote the paradigm shifting wave of the data warehouse, to be fair, later than we should have, like roughly three years later.
Exactly.
I think one step before they became really mainstream.
So three years after they came out.
And so there, there were a handful of competitors, there are a lot of competitors now.
So I wouldn't recommend anybody to go in the data market unless you have a very solid understanding and angle and reason than just come in randomly and say, hey, I don't know much about data, but I can change it up.
It's too many competitors by now.
Omer (44:37.090)
Data, how hard could it be?
Yeah, I'll go and build something.
All right, so let's wrap up, let's get onto the lightning round.
I'm going to ask you seven quickfire questions.
You just try to answer them as quickly as you can.
Hung Dang (44:49.800)
Yes, sir.
Omer (44:50.600)
What's the best piece of business advice you've ever received?
Hung Dang (44:54.280)
Know your ICP and stay as relevant as possible to this icp like laser focus.
Omer (45:01.080)
What book would you recommend to our audience and why?
Hung Dang (45:04.600)
Thinking Fast and Slow by Danny Kay.
He talks a lot about human bias and it's a super valuable lesson that everybody should understand about the human nature because at the end of the day it's a human business.
If you want to build a big company like again taking back the old example of you want to build a billion plus dollar company, you need to change human perception in the first place.
And software or whatsoever is just serving human purpose.
At the end of the day, data architecture is a human sociological way of organizing things that human can work well together.
So whatever that is, it's all about human.
And Thinking Fast and Slow by Danny Kay really shows the human nature with its biases as well.
And within that bias there's a lot of opportunity and potential to build something great.
Omer (46:00.190)
What's one attribute or characteristic in your mind of a successful founder?
Hung Dang (46:05.070)
Resilience.
But resilience that results in self motivation.
So if you get rejected, yes, you can deal with it.
But not just deal with it, you have to make it as you feel to become self motivated and take action.
Omer (46:22.680)
What's your favorite personal productivity tool or habit?
Hung Dang (46:26.200)
Do the hardest task first in the morning.
Omer (46:28.440)
Eat your frog is not what they call it.
Isn't that what the book says, Brian Tracy?
Hung Dang (46:32.200)
Yeah, exactly.
Yes.
Omer (46:34.250)
What's a new or crazy business idea?
You'd love to pursue if you had the extra time.
Hung Dang (46:38.170)
So communication is something very difficult in my point of view because it's so multilayered and like we humans don't even have enough words to express what we really mean and it has to be repeated a couple of times until it sticks.
And what I find that I'm always having trouble with is messages that I developed like a couple of months ago to retrieve them.
And so I tend to forget them and, and so I want a version control system of my messaging, but preferably within the right context within our landing page.
So it's very accessible when I'm on the landing page.
Like, oh, what kind of wording did I use a couple of months ago?
And collaborate on this messaging with other people what they're thinking.
So build up a set of knowledge why we derive to a certain messaging through version control throughout different contexts such as csdex, website, whatsoever.
Omer (47:35.850)
What's an interesting or fun fact about you that most people don't know?
Hung Dang (47:39.370)
I make a lot of dad jokes.
I mean, actually, I think a lot of people actually do know that.
But yeah, I throw in quite some dad jokes.
Omer (47:48.570)
And finally, what's one of your most important passions outside of your work?
Hung Dang (47:52.170)
I used to do a lot of sports and games online, like playing World of Warcraft.
I don't have the time to do that.
I think I'm nerdy enough to say, hey, I would really enjoy doing that again.
But I found a new passion which is explore more about self, love about my inner self, and explore more about how I feel from the inside because that has a great effect on how I execute in the outside.
Omer (48:22.550)
Yeah, I love that.
I think there's this, there's this inner work, spiritual side.
I think that there's a lot of founders, I think, who are interested in that kind of topic.
It's almost.
Maybe we should have a special episode one day just talking about that and learning from people about that stuff.
Hong, thank you so much for joining me and sharing the story of Y42.
If people want to find out more, they can go to y42.com and if folks want to get in touch with you, what's the best way for them to do that?
Hung Dang (48:52.940)
You can reach me on LinkedIn, just add me and I'm adding back very regularly.
You can follow me when I share the data content.
So I'm Quite active on LinkedIn.
Omer (49:07.100)
Awesome.
Thank you so much.
I'll look out for the announcement on TechCrunch and I wish you and the team the best of success.
Hung Dang (49:16.510)
Oh, it just came out.
Literally.
Now I just check it.
Omer (49:19.070)
Perfect timing.
Thanks.
Congratulations.
And all the best.
Hung Dang (49:22.430)
Take care.
Bye.
Bye.
