Loading summary
Transcript36 lines
- [00:01]
A
If you can really build a champion in the company, then it's probable that you can close the deal. But if you can't, and it's kind of like, you know, the black channel that exists for a week and gets three messages, they'd be thinking twice.
- [00:18]
B
Welcome back to another episode of Builders. As always, this show is brought to you by Frontlines IO, Silicon Valley's leading B2B podcast production studio. If you're bringing technology to market and want to learn from your peers, we have a library of more than 1200 interviews with Venture backed founders and marketing marketers. Where they talk, all things go to market. Of course, if you want to launch your own podcast, we offer podcasts as a service to more than 80 tech startups. The idea there is very simple. You show up and host and we do everything else. Now with all that said, let's jump into today's episode. Today our guest is David Yaffa, co founder of Estuary. David, thanks for joining the show.
- [00:56]
A
Hey Brad, thanks for having me.
- [00:57]
B
Of course. Looking forward to this conversation. So I know you sold a company to Liveramp, spent a bunch of time there. What was your big learning from your time at Liveramp?
- [01:05]
A
That was the first time I was a CEO when I sold the company. But I've been part of three acquisitions and the first was Ripe Media, got bought by Yahoo. The second one was Invite Media, got bought by Google. And then the third was the one that I was the CEO that was Arbor, it got bought by Liveramp, which is a public company in the marketing space. And you know, I think each one tells you a different lesson, right? Like there are all such different acquirers and different companies that end up, you know, taking ownership over you, that it's kind of an interesting way that they all proceed with them. So I think what I learned the most was just that, you know, know what they want of, you know, what they are going to be trying to do with the company afterwards and what the expectations are and stuff and their motivations and all of that because it really does affect the outcome. When we were bought by Google, I ended up leading product for a product that they were basically rebuilding and building on the Google stack to replace our previous product. And that was a really fun outcome. But one of the nice things about it was that Google's so big that we were so relatively small that no one really cared about us until we were like a billion in revenue. So everyone just ignored us. And that was a pretty nice thing to have like all of the Google backing but like no real interference. It did change if it got a little bit bigger. So it makes a big difference. And but Live Rep's a lot different in that they bought us and they paid a big chunk of their total market value price and that meant that we were going to have a big contribution after the actual sale. So it led to just a lot more work, I would say after the sale versus the Google side. So I think, you know, it really just depends. Both were, you know, unique experiences that were nothing like each other.
- [02:46]
B
And what about that comparison between Yahoo and Google? I was talking with a friend the other day, I don't know if you read this book is like kind of a popular book I think maybe like 12 years ago called Marissa Meyer and the Fight to Save Yahoo. And it was, you know, at the time she was like very actively trying to do it and it was, you know, so optimistic that she was going to do it and she was amazing and like all this stuff and like in the end like yeah, didn't work out I think as she had planned. What was that like, you know, being inside of Yahoo and then how different is or how are they different? I should say Yahoo and Google, of course they're different.
- [03:15]
A
But like how, I'll be honest, once we got bought by Yahoo, it was, it was like, you know, pretty fresh out of school at that point. So I wasn't a big hog in that wheel and it didn't behoove me to stick around very long. It was a pretty stifling environment. So I ended up leaving pretty quickly. But so you know, what it was was the company got bought. The original company, Right Media had this great culture and great environment and super fun to work in and changed overnight, right. Like it just became way less of a, you know, the classic tech company type of feeling and vibe. And we were kind of being told what we needed to do by someone who didn't bother to learn what our business did. And that ended up not working so well. So I mean that was in this time where Right Media and I think I forget the name of the company but they were all bought by the big Internet giants. Right? DoubleClick was bought by Google. Right Media was bought by Yahoo. And then Microsoft bought and wrote off a company for like $6 billion in the same space. And so it was kind of a competition to see who could do it first and best. And I feel like Google got the best deal there of all those three companies. It showed with their strategy too, right? Like they, they bought this DoubleClick bid manager and let them run the show and it just totally came through and how successful that side of their business ended up being.
- [04:34]
B
And for you, as you were preparing to leave Liveramp, I'm sure if you're like most founders, you have, you know, in some form, a long list of ideas, a long list of opportunities, probably some domains, I feel like all founders I know end up just buying a bunch of random domains for you. How did you settle on the problem that you decided to go out and solve? And then, of course, what is that problem you're solving today?
- [04:51]
A
Yeah, so this particular company came out of my last company. So we're doing S right now. And we are what we call a right time data company. And so what we mean by that is we build a data infrastructure solution that offers both streaming and batch capabilities. So it's basically, it delivers data how you need it for whatever application you're doing, whether it's AI analytics or operational data. And that's squarely came out of our last company and solving a problem that we actually had. So we were in Martech in the last company, and in that space we wanted to be able to deliver data to customers in real time because the value of data degrades over time. And so if we could deliver it really quickly, it would lead to a much higher value solution. So we built this. We didn't want to use Kafka. That's like the thing that's out there for the most part. And so we ended up doing something kind of strange and building our own streaming system. It happened to also work with batch data too. So that was a unique thing. We wanted to do that because we wanted to have a single system that worked for our own analytics and powered our own product. And afterwards we kind of took a step back and said, does anyone else want this? And it turns out that they did. So that's what got us there.
- [06:01]
B
And when you asked that question of does anyone else want this? Is that answer still the same today? Like, has that ICP stuck from those early ideas that you had, or has the ICP evolved?
- [06:10]
A
It's changed a little bit, only in that I think it's a broader list of use cases that want it. When we first asked that question, a lot of people were like, well, I'm not sure that real time data is as necessary to us, but nowadays with AI, it's. I think more and more people, more and more companies are realizing that they do have need for it, and less technical practitioners are too. Right. Like, there used to be this huge divide where software engineers would Want, they operate Kafka and most companies operate like this today still. So software engineers on that side, they can actually do real time stuff. And then data engineers, analytics people, they wanted more batch solutions because they're simpler. And you know, it really was the dividing line of how complex is this thing? AI breaks down the barriers. It means that everyone wants the capability to potentially run an agent or, you know, do something that's in process, in customer experience, and that's led to like a broader group of people that are potential consumers than what we had in the in general.
- [07:09]
B
And if you think about the early gtm, what did the early go to market motion look like?
- [07:13]
A
We were really, really just going after what we thought the easiest thing was possibly to sell. And for us, that was the analytics use case. So the analytics use case, you know, get data from a fourth to a warehouse. Really, really straightforward, kind of undervalues our product. It doesn't make the most out of it, it's totally batch. But there was an easy go to market there. Everyone was going after the modern data stack and we could kind of go after people who wanted that. And so that has changed quite a bit since in the last couple years. But you know, I think what's nice about an early go to market is just to figure out something that you can do repeatedly, go after a specific set of customers that you can go after and build that early revenue so that you can build it up as the foundation of your business. And that's what we tried to do, even though it wasn't like where we wanted to be long term.
- [08:01]
B
This show is brought to you by Frontlines Media, a podcast production studio that helps B2B founders launch, manage and grow their own podcast. Now, if you're a founder, you may be thinking, I don't have time to host a podcast. I've got a company to build. Well, that's exactly what we built our service to do. You show up and host and we handle literally everything else. To set up a call to discuss launching your own podcast, visit Frontlines I.O. podcast. Now back to today's episode and what has that evolved into today? And maybe take us through any of the inflection points or the major iterations that happened.
- [08:32]
A
So we do a few different types of things. Like we still have that original sale, which is pretty straightforward. Then there's a lot of use case based selling. So we'll, we'll publish some use cases that we assume that people are trying to accomplish online, talk about them a bit, and that ends up getting people to Come to us, we were mostly PLG and we still do a decent sized PLG motion. But the big thing that's changed recently is that our product's much more useful for enterprise. So we can actually go and direct sell into an enterprise and we look for a bunch of different signals that you know that they probably are changing technologies and kind of go after that as well as what we used to do. And then even going into other types of sales which are more industry specific. Like, you know, we know that logistics care is about real time and we know that this type of customer has always been a pretty good one for us. So that's a pretty good target. We'll just, you know, pick the top 20 companies in that space and go after them. So now it's a lot more broad. It's like much less of a single focus and more industry agnostic and broad.
- [09:37]
B
And what is that line item that customers are buying today and is that an established line item? Like are they already in market looking and then you have to just go and capture that demand or is this more of a category creation play where you have to go out and create the demand in the first place and then capture it?
- [09:51]
A
We'll usually start on something that they're already buying today or that they know that they need. Right. So it's easy for us to start with. You're doing analytics, let's sell you basically data pipelines for analytics. Most companies have a marketing budget or a data engineering budget for that, but usually we will expand to something that doesn't exist. So the reality is like if we get in with the marketing team, they don't care about streaming data, they don't care about low literacy. But a lot of the times they will evangelize us in house when they hear about a use case that does care about that. And that's where it starts to change and get to be a much bigger, a more interesting sale to us. So our NRR is very strong. It's you know, like 150. And that's because it's a huge Levin extent opportunity.
- [10:38]
B
What else have you done to be able to say that NRR is that high?
- [10:41]
A
Honestly, we don't even have like a CSN team. Yeah. So it's. We haven't really done much. We've built a product that I think is something that people realize is good and strong and capable for other use that they've never imagined when they first start and that just gets them using it more and more. There is one other thing that I think we've done. We've priced it in a way that doesn't try to extract maximum value immediately. Right. Like we're not just trying to like get a big check up front. We're trying to price it in a way that lets the customer grow with us and not worry too much about that. Right. So they can spend a lot more and still feel pretty good that they're getting a decent deal and that lets them, you know, over time grow with us and not worry about trying to replace us with something they've built in house, an engineering team or something along those lines.
- [11:29]
B
As you were thinking about that pricing strategy, was that something that was heavily debated or is that just like a no brainer? It was so obvious that was the pricing strategy to pursue.
- [11:38]
A
It wasn't heavily debated. Surprisingly it was. You know, at the time when we created it, it was basically me creating it. So there was no one to debate it with me. I debated it with myself. But my co founder is our CTO and he's much more technical for the most part. We have this really good working relationship where he focuses on the stuff that he's really good at and I focus on the stuff that I think I'm pretty good at and we trust each other enough to let us do our own thing. So he didn't debate it. He said, that sounds like a great idea.
- [12:10]
B
What has been debated from a go to market perspective?
- [12:12]
A
I mean everything is the answer, right? Like, are we doing the right thing for going PLG up front? Like, should we focus on that more? Should we focus on sales team? Like I think one of the biggest things that everyone's thinking about right now is like what's happening to search, right? How is that changing and how do you optimize it and how do you, you know, all of those types of things. Is it worth the investment? Should you be doing ads? Should you be focused on organic as. As you know, since that's such a great strategy in the past? And so those types of things are what we're debating every single day.
- [12:46]
B
Does any other ones come to mind of things that, like even if it wasn't debating with your co founder, but like with yourself, like what was the most like intense debate that you had with yourself later on?
- [12:56]
A
We lowered prices once and so, and we might even do that again, honestly. But we lowered prices so that it would encourage larger use cases and it did sacrifice a little bit of revenue when we did it. But I think it worked really well because it got people with bigger use cases to be able to use the platform more. And that led to, you know, long term it probably led to more revenue and short term it probably hurt us. And so we're thinking about doing the same thing again for some larger use cases as well, which hopefully there's probably some people who use the platform and they're like, wow, this is at scale, it's way too expensive and I want to just get in front of that and make sure it's just not ever that. This show is brought to you by the global talent company, a marketing leader's best friend. In these times of budget cuts and efficient growth. We help marketing leaders find, hire, vet and manage amazing marketing talent for 50 to 70% less than their US and European counterparts. To book a free consultation, visit globaltalent.co.
- [13:55]
B
how many different use cases are there within the platform or what's possible in the platform? And then how do you decide which ones to focus on and emphasize?
- [14:03]
A
Yeah, it's a platform and it's totally do whatever you can imagine with type of platform. It does three basic things. That's it. So it captures data from sources, it transforms the data and then it pushes it to destinations and it can do all that in either increments like batches or in real time. So millisecond latency from source to destination. The transformations are kind of cool in that you can do three types, right? And going on a fourth which I'm really excited about. So the three types are SQL, TypeScript and Python. So it's, you know, nowadays with AI you can have that made for you if you have no idea how to do any of that. And we have integrations that make it really possible for like someone that's non technical to be able to use your favorite LLM and just have that transformation made for you. So like an example of a really cool one that we're working on now and we're going to publish is we can extract data from HubSpot in real time. HubSpot has this buyer intent data. So it's people who've gone through your website or companies who've gone to your website rather. And so we can extract that in real time, look at it, compare it to a bunch of data sets, figure out information on the likely people who are reaching out to our site and then that are looking at our site and then potentially contact them and reach out to them on LinkedIn or email or something like that, all in real time and pipeline with a bunch of information around what someone's done. And so that is possible now based on us having LLM driven transformations as well. For me that's like really cool. But to go back to your actual question, you could imagine that you can use it for like just about anything. It's basically multipurpose for moving data in any business. From the simplest, moving it just from a source to a warehouse and doing analytics in Snowflake to the really complex stuff of like setting up full fledged data pipelines that are cleansing your data, Preparing it, using LLMs to clean stuff up and suggest what you want to actually do.
- [15:56]
B
One of the themes that I see out there and from the founders I know is that this, the number of competitors is at almost like a comical scale for most people I know. You know, previously there'd be like a few players, but now there's just like a hundred or you know, 20. There's just a lot for you. How are you positioning yourself in the market?
- [16:14]
A
I think it's been weird for us. So since we're in the data infrastructure space that had this big huge peak in 2021 where a whole bunch of people or companies raised money. So we're actually on the downturn of competitors right now. We don't see as many as we did a few years ago. And that's good. All of our competitors ended up basically doing the same thing and we had a different capability set with being streaming as well. That led to us just pitching ourselves differently and doing something slightly different. And that led to us naturally being differentiated from the crowd. So I think that was good. It wasn't just like a me too business which leads to differentiation without even trying to basically.
- [16:58]
B
And was there any negative sentiment that you had to navigate in terms of buyers saying like, you know, we don't trust startups or we saw a bunch of startups come and go, like did you have to navigate through that at all?
- [17:09]
A
We've definitely had to do that. You know, there's this crossing the chasm thing where you know that there's certain companies and certain people that will never buy your product right away. And that is, it doesn't stop them from talking to you. Like they're still going to reach out to you and they're still going to have a conversation so that they can tell their boss that they've talked to five different companies and made the best possible decision, but you can almost tell the first time you have a conversation with you that they are kicking the tires and that's all they're doing. I wish it was easier to not waste time on those, those types of companies, but we've definitely done POCs where, you know, you just see that lack of engagement where, you know, they set it up, they never look at it, they never respond to you. They say, oh, we've chosen someone else. And you're like, can I ask you why? And they're like, well, you know, my boss wanted us to select the thing with a bigger name. And so, you know, sometimes there's not much you can do to convince them because they've basically started it with a preset notion of what they were going to do. Sometimes there is, and I think the key is navigating and figuring out, like, if you can really build a champion in the company, then it's probable that you can close the deal. But if you can't, and it's kind of like, you know, a black channel that exists for a week and gets three messages, you'd be thinking twice.
- [18:23]
B
I always like to think in bets. So for you, what are your big growth bets? If you think about not just, you know, this year, for the next few years, like, what are the areas that you're really betting on to achieve and sustain the growth that you're seeing?
- [18:34]
A
Yeah, I agree with that framing. So one of them is enterprise growth just going up market. We've been classically SMB and tlg, so even mid market, potentially. And so we've been successively doing stuff that allows us to appeal to the larger businesses. We can deploy our technology in a customer's cloud now, which is really nice from a security standpoint. And we're about to release the capability to basically parallelize any data flow. So we can parallelize it as much as you want, and that can scale to any scale, basically. So that's helpful. So enterprise is one. I think everyone has to have an AI bet, right? So I already talked about one of our AI bets. We have a second one too, which has been focusing on being able to create connectors with using AI, so allowing for users to bring their own connectors and make that really a nice experience so that we don't have to create every connector that's in the platform. And then a third AI bet which is using the system with AI. And so I think all of those together just. It appeals to a much broader audience than like a classically real time system has ever been able to. So those are the big ones for us. There's a lot of like smaller ones, but those are the big ones.
- [19:43]
B
The big ones are what we're after. David, we're going to wrap here. I'm seeing we're up on time before we do. For those who are listening in that just want to follow along with you in this journey. Where should we send them? Where should they go?
- [19:53]
A
Estroid.dev is our website. Would be happy to talk to you. My LinkedIn. You can look me up, you can reach out to me. I'm David Yaffe, CEO of Estree.
- [20:01]
B
Amazing, David. Thank you so much. Well, that's all for today's episode of Builders, brought to you by the Frontlines. If you want more amazing content like this, visit Frontlines IO where you'll find a library of more than 1500 interviews with founders, marketers and other GTM leaders, where we unpack the tactical lessons from their journey. And of course, as always, if you do want to launch your own podcast, we'd love to have a conversation with you. Visit Frontlines IO Podcasts as a service. Mention that you listen, mention you love the show. Then we'll give you a 10% discount. Thanks for listening. We'll catch you in the next episode.