SaaS Interviews with CEOs, Startups, Founders
1013 Guess How This Data Tool Will Break $100m In 2018
03 May 2018
Chapter 1: What is the main topic discussed in this episode?
This is the Top Entrepreneurs Podcast, where founders share how they started their companies and got filthy rich or crash and burn. Each episode features revenue numbers, customer counts, and other insider information that creates business news headlines.
We went from a couple of hundred thousand dollars to 2.7 million.
I had no money when I started the company. It was $160 million, which is the size of many IPOs. We're a bit strapped. We have like 22,000 customers. With over 5 million downloads in a very short amount of time, major outlets like Inc. are calling us the fastest growing business show on iTunes. I'm your host, Nathan Latka, and here's today's episode. Hello, everybody.
My guest today is Frank Bien, and with over 20 years experience growing and leading technology companies, he's built his career on nurturing strong corporate culture and highly efficient teams.
Before Looker, he was SVP of strategy for storage vendor Versto, which was acquired by VMware, and VP of strategic alliances at big data pioneer Greenplum, leading their acquisition by EMC, which is obviously now called Pivotal. He led product marketing and strategy at early scale out data warehousing company Sensage, and was VP of solution sales at OpenText.
Earlier in his career, he had executive roles at Dell and the Federal Reserve. Frank, are you ready to take us to the top? Let's go. All right. So tell us about Looker. Obviously, there's people understand, I think, from the bio, it's a data play. But what do you do and how do you make money?
Yeah, you know, I mean, a lot of people are talking about data. I think what Looker is trying to do is finally deliver on this promise of creating data cultures. And, you know, I mean, that sounds, you know, big and and wild and everything, but really it's about getting every person in an organization to use data to make better decisions.
It's what everybody's been talking about for 20 years and no one's really been super successful doing. Why? Because it's a hard technical problem. Data comes from lots of different places that are very messy. You have to clean it up. You have to present it to people in the right ways. You have to make sure that it's not siloed.
There were really big technical problems that had to be solved over the last 20 years. that even make it reasonable to put data into the hands of the average user.
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Chapter 2: What is Looker and how does it generate revenue?
And, you know, I think what we're seeing is we're seeing that kind of trajectory. We're a real SaaS kind of a company on that trajectory in this data space.
Yep. Now, I mean, we can do a little bit of back-of-napkin math. You just mentioned kind of minimum contract values in the 30K annually range. And if you have 1,200 customers, it's fair to say you guys are well past the $36 million ARR mark at this point, correct?
Yeah, absolutely.
But below 100 still? Yeah, that's a good range. Okay, good. That's vague enough where it doesn't hurt you competitively, but still gives you enough credit to say, listen to this guy. He knows what the hell he's doing.
Yeah, I mean, we're about 400 people now. We have eight offices worldwide, and we're really capital efficient. Where's headquarters? In Santa Cruz, California.
Oh, I'm envious. I'm envious. You're not being affected by the wildfires, are you?
No, no, we had the, you know, the Sonoma stuff was up this way and there were a couple of fires down here, but no, not too much.
Okay, so we kind of understand team, we understand what you're doing. Tell me more about the economics of this space because it is competitive. I mean, there's a lot of people vying for kind of this data space. How are you acquiring customers?
Yeah, you know, it's interesting. I think a lot of people have been talking about how you get data into the hands of users. But if you really think about all the technologies, they really grew up around the limitations of the database. So you had lots of things to take load off of the database. ETL, data prep, visualization.
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Chapter 3: What challenges does Looker face in the data space?
You had all these little pieces. And what was ready and what was needed in the world of data was one platform that swept all that stuff together and did it in a different way. And that's what we do. I mean, architecturally, we're very different. We run on the big, fast cloud databases and the Hadoop stuff and all those kind of things that people talk about.
But really, we provide this full platform that allows people to do everything.
But literally, I mean, literally, how are you acquiring folks? Do you use some of your team? There's an outbound sales strategy there as a product marketing. What do you attribute acquisition to?
Oh, sure. Yeah. I mean, so, you know, we we believe really in focus. So we originally focus on a lot of e-commerce kinds of companies, really saturated that market, moved out from there and sort of the bigger, you know, the bigger, you know, Fortune 2000 kinds of things. We're about 80 percent inside sales. So it's an inside sales SaaS motion.
And then, you know, we're doing more and more enterprise sales as well.
And what do you like to keep as you're scaling? Obviously, you've raised capital. So you have created an ATM that works. You know how to put money in, get money out. What are you trying to keep your kind of money velocity at? When do you want to get your CAC back? How quickly? You're back? Yeah, can you hear me? No, my question is about payback period.
How quickly do you like to get your money back?
Yeah. I mean, so, you know, we look at, you know, sort of those SAS models. We would look a little bit like a Marketo looked originally or something like that. But if it's more than 18 months, you know, we start to worry.
Got it. So is it fair to say you're kind of between 12 and 18 now? Yeah. Yeah, that would be fair. And how do you decide when to get more aggressive there or more conservative?
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Chapter 4: What is the company's growth trajectory and customer base?
Absolutely, absolutely, yeah. So just, can you actually say that equation real quick in case folks want to calculate that themselves?
Man, I don't know, I couldn't even tell you that equation off the top of my head.
I'd go talk to Joe.
You guys can look it up. I'll put it in the show notes. It's a sales efficiency ratio. It is a good metric.
You know, Bessemer writes a lot of stuff, like buying Dieter and those guys. They write a lot on this stuff, and those are great articles to read.
Yeah. A lot of companies that I talk to that I have that are doing kind of more than $50 million in ARR, they start talking. They change their terminology. They stop thinking about lifetime value and CAC. And the numbers they give me is they say, Nathanā When we spend a dollar on CAC, we expect it to drive $0.90 in new ARR, right?
Exactly.
Can you share where you're at in terms of that ratio?
I mean, so we don't go through the specific numbers, but it's really healthy. We're very cash efficient. There's a lot of companies in sort of this ā data space that have blown up and spent a lot of money and things like that. And we knew we did not want to go that way. So it's very efficient.
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Chapter 5: How does Looker acquire and retain customers?
So the kids are out of the they're out of the home at this point. Empty nester.
uh they're just now applying to college so we're really exciting very exciting and how old are you frank uh 49 all right last question take us back 20 i had to think about that that's because i see the wine behind you that's because you're already you're already on wine this morning all right yeah just kidding last question take us back 29 years what do you wish your 20 year old self knew you know what like um pick your battles
You know, man, I was fighting everything. You know, I just was always picking everything, being the guy charging around. I think, you know, one thing I learned and one thing I tell people often is, you know, pick your battles.
There you guys have it from Frank. Pick your battles. Joined the earliest kind of startup team in 2011 behind Looker. Great co-founding team. They've now scaled to helping over 1,200 enterprise customers, paying on average at a minimum 1%. $2,500 a month. Actually, much more than that because that just puts them at about $36 million in ARR.
But Frank feels good potentially next year about breaking that beautiful $100 million ARR mark, growing around over 50% year-over-year, which is impressive at these large numbers. $180 million raise. Economics really healthy. Negative 25% net negative churn, which is great. Team of 400 folks based out there in Santa Cruz, California and other remote locations.
Again, helping you make more sense of your data. Frank, thanks for taking us to the top.
All right, great. See you, Nathan.
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