Neil Patel

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Gil Elbaz cofounded Applied Semantics which he sold to Google for over $100 Million. Applied Semantics was the creator of Adsense which Google turned into a $15 billion business representing 23% of its total revenue. Elbaz most recently founded Factual which provides accurate and comprehensive data on places and people worldwide. The company has raised over $100 million from investors like Andreessen Horowitz, Index Ventures, Felicis, Founder Collective, or Data Collective.

In this episode you will learn:

  • How to be effective during tough times
  • Dealing with economic downturns
  • Raising capital to fuel growth
  • Negotiating M&A with tech giants


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About Gil Elbaz:

Gil Elbaz is the founder of Factual, a new information-sharing startup.

He is also the co-founder of Applied Semantics (ASI), a new language that helped create Google Adsense.

ASI helped to define and build new addressable markets with its AdSense platform and other contextual advertising products. The company formed important partnerships with key players in both internet and content spaces such as Overture (now Yahoo), Verisign, and USA Today, effectively paving the way for markets which are today measured in the billions in annual revenue.

Google acquired ASI in 2003, and first-round investors reaped more than 100x return on their investment. Elbaz was appointed Engineering Director for Google Santa Monica where he focused on building up the local office, and continued to work on AdSense and other products. AdSense helped establish Google’s place as a leader in the field of online advertising and in 2005, Elbaz was presented with the prestigious Founders’ Award. Since leaving in 2007, true to his entrepreneurial bent, Elbaz has founded a new company whose technology will soon be revealed.

In 1991, he earned his bachelor’s degree from California Institute of Technology with a double major in Engineering & Applied Science and Economics, and in 2008, Elbaz was very honored to be named Young Alumni Trustee to the Caltech Board of Trustees.

Active in a number of non-profit areas, Elbaz sits on the board of trustees for the X Prize Foundation. He and his wife Elyssa manage the Elbaz Family Foundation, which supports environmental and educational causes, and are involved in Los Angeles Social Ventures Partners. Committed to the open information arena, Elbaz supports organizations such as public.resource.org, and is president and founder of the CommonCrawl Foundation, dedicated to helping democratize access to web information.

Connect with Gil Elbaz:

 

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FULL TRANSCRIPTION OF THE INTERVIEW:

Alejandro: Alrighty. Hello, everyone, and welcome to the DealMakers show. I think that today, we are going to learn quite a bit because we have someone that has been around the block many, many, many times. So, I guess without further ado, I want to welcome serial entrepreneur, Gil Elbaz. How’s it going, Gil? Welcome aboard here.

Gil Elbaz: Thank you. Thank you, very much. I’m looking forward to chatting.

Alejandro: Let’s do a little bit of walkthrough memory lane. You basically have the engineering background, and your education is from Caltech. Is that right?

Gil Elbaz: That’s right. Caltech Bachelors of Engineering and Applied Science.

Alejandro: Then right away, you go into IBM. So, tell us, what made you go into IBM in 1991?

Gil Elbaz: Well, let’s see. In 1991, frankly, the economy in Los Angeles was quite poor. In tech, it was dominated by the defense industry. Companies were laying off. All my friends were going to Silicon Valley. That’s where the jobs seemed to be. So, I jumped on that train not really knowing very much about the world of industry, but I got an offer at IBM in South San Jose. It was going to give me an opportunity to do database development work. I was very interested in that, so that started my journey up north.

Alejandro: Got it. And I saw that you did a couple of stents before going at it on your own. You were an engineer. Then you became a database engineer at MicroUnity, and then Silicon Graphics. Can you walk us through these three different roles that you did before you started Applied Semantics? One thing that I found is that you were for one year in each one of those companies. So, why was this the case and what did you learn from these three companies?

Gil Elbaz: I think I was at IBM two years. I seemed to be spending most of my time working on mainframes. We learned in the 90s that mainframes were not going to be the future of computing. UNIX was becoming very important. Sun Microsystems was a very fast-growing computer company. Then PCs were also becoming a relevant technology not just for the consumer for the frontend, but for server side as well for back-end computing. Moving to Sybase in 1993, I believe it was, gave me an opportunity to develop UNIX and PC skills, and also work on at the time what was a really hot relational database. So, I jumped at the opportunity, and that took me farther north in the Bay Area to Emeryville.

Alejandro: Got it. What a time where you needed a moving company to transport your computer rather than how easy it is to carry your computer around today. No?

Gil Elbaz: That’s right. Those days. Yes.

Alejandro: Those days. So, the last stop was Silicon Graphics before you became an entrepreneur, and you did that for a year as well there in Mountain View from ’96 to ’97. How did you get the entrepreneurial bug? What happened, because here you have this path from being an engineer, having the comfortable paycheck coming every month. So, why did you decide to complicate your life?

Gil Elbaz: Well, even after Sybase and before Silicon Graphics, I did have a year and a half at this really interesting startup called MicroUnity that very few people, even in Silicon Valley, know about. They had this widely ambitious plan to revolutionize computing. They were going to displace Intel. They were going to displace Microsoft with a radically new computing architecture. It gave me a little taste into ambition at a really broad scale. The CEO was revered as a visionary. So, they bit off a little bit more than I can chew, which by the way is one really important lesson as an entrepreneur is ambition, yes, but take achievable stepping stones on the way to the grand vision. The one incredible learning there. But my affinity for entrepreneurship I think goes way before even that experience back to my childhood where I was just really interested in economics. It was kind of a game. Baseball cards is an example of something that got me started. Buying and selling and trading and predicting which players are going to improve with an increase in value. It was fun.

Alejandro: Really cool. So, I guess that was kind of like your first exposure to the hypergrowth startup mode, and building, and scaling. Walk us through the incubation process of the idea behind Applied Semantics.

Gil Elbaz: My interest in creating a company like Applied Semantics started in my childhood with a deep fascination and love of data. I was the kid that was constantly bugging my parents to take me to the library so I could just spend time in the reference section. We didn’t have our own encyclopedia at home. If I wanted to comb through an encyclopedia, I’d have to get a ride to a library. I also loved the reference section of bookstores. Probably another important moment is getting to experience streaming data on cable TV. With cable TV, all of the sudden you had channels that were streaming financial news and weather data. I didn’t realize at the time that my fascination with charting and storing data would lead to an interest in computers, but that’s how it worked out. When I finally got a computer, I realized this is a much better tool than pen and paper to store, and chart, and graph, and make predictions. To me, that data felt like power. It felt like I had control of my universe; maybe the universe.

Alejandro: That makes sense. What was the process of really saying, “Hey, we’re going to take a look at this company,” and what was the founding team that brought it to life?

Gil Elbaz: Yes. Getting closer to that founding story at Applied Semantics, toward the end of ’93 or maybe it was early ’94, the Mosaic browser had just come out on, and I had this exposure to the web. Mosaic browser was the first web browser before Netscape Navigator. It’s a whole 25 years ago. I saw just a little inkling of how the world might be very, very different where people around the world could connect and collaborate, could understand and share information. I had a sense that the world was going to be remade based on this kind of sharing and connectivity. I got extremely excited about that, so after I saw that, I became a fan and a student of understanding as much as I could about this new space. I was following all of the companies that were growing in the space. For example, I followed very closely as search engines were being developed, like AltaVista, Yahoo was a link at a time organizing the entire web. I spent a lot of time with a college friend of mine, Adam Weissman, pondering how might we better organize the information in the world. That’s what ultimately led to starting a company.

Alejandro: Between you and Adam, what did each one of you bring to the table from a skill set perspective?

Gil Elbaz: That’s a good question. He was at a game company working on the AI behind games where the machine is representing players. There was a lot of AI, a lot of technology in gaming. I, on the other hand, always had this deep fascination with data. We believed that by bringing our interests, and skills, and AI, and data that we would be able to take over the world a stepping stone at a time. Also, my brother joined as a founding team member. He was an engineer by training, but a salesman at heart. So, obviously, that was an incredibly important skill set. Also, two other founding team members: my cousin, R. A. Barkin who was working at Network Solutions, and a friend Brad Stein who was in accounting. So, we brought together this crew of five that had this diverse skill set.

Alejandro: That’s great, and I’m sure having brothers and cousins involved, that also involved having business conversations at Thanksgiving dinners.

Gil Elbaz: Yes, absolutely.

Alejandro: That’s great. So, we’re talking about the late ’90s. What were some of the challenges that you guys were experiencing during the early days of the business?

Gil Elbaz: In the early days of the business, we had this big idea that a lot of the reason that there were knowledge gaps was because of the lack of precision in language. You can have a single word that means many things. You could have Jaguar, the animal, or it’s a car, or there are other products called Jaguar. Oftentimes, a keyword match wouldn’t get you exactly what you’re looking for. Maybe you search on a keyword, you search on travel, but the document that you’re looking for doesn’t actually use that word travel, it uses other words that refer. Maybe it’s flying. Maybe it’s destination. Maybe it’s hotel or airlines. We wanted to solve text-based searching and turn it into a meaning-based search. What was our challenge? Frankly, it was Google. They were dominating in search, and we were trying to get a piece of the market share in search, and we were starting to lose. We felt proud of what we had built, but the results weren’t coming in. So, we were going to have to pivot.

Alejandro: Got it. So then, what ended up being the business model? How were you guys making money?

Gil Elbaz: We realized that meaning-based search—we had built a lot this AI. At the time, we referred to it as our Natural Language Understanding Technology that could parse and read the text and assign meaning to it in a very human way. We knew that it had implications to search and could help search, be more precise, and more comprehensive at the same time, but we weren’t winning at the search game. We realized that it also had other use cases. One of those was in advertising. Applied Semantics became a pioneer in contextual advertising. We built a product called AdSense that would choose the most relevant advertising to align within a web page, within a body of content. We saw these really miraculous clickthrough’s because even though it flew in the face of how traditional advertising was done, it turned out that—today, it doesn’t seem so profound, but at the time, it was somewhat against the prior view on things. But it wouldn’t surprise one to believe that people click on these ads if they are right in line with what you are reading.

Alejandro: You were mentioning AdSense. That’s unbelievably impressive. I can’t even imagine how many lives you’ve touched with that. So, I wanted to ask you here. Obviously, you guys are growing. The team is growing. How did you capitalize the business? What was the structure there?

Gil Elbaz: It was tough. First of all, it was not easy because in Los Angeles, in 1999 and 2000, there weren’t very many angels if any, and if there were any, I didn’t know any of them. It was not a network like today where you have incubators and accelerators, and you can find advisors that have a long history in introducing you to angels. It was a very immature environment in that regard. There were few venture capitalists. At the Series A level, they often wanted more of a track record. So, it was tough, and we had to—I was going to say beg, borrow, and steal, but we definitely didn’t steal, but there was a little bit of begging and borrowing. I had an offer from one relative to invest $300,000, but he wanted me to sign this document that said that if the company didn’t succeed, I would work for him for the next 10 years at his company. Obviously, those were kind of owner’s terms.

Alejandro: Did you sign that?

Gil Elbaz: I ended up not. I was thinking about it because when you want money to fund a company, sometimes you do things that you maybe shouldn’t do. I did invest all my savings from Silicon Valley over six or seven years. So, that ended up being the capital we used for the first nine months. Then we managed to find investors. My brother was a technical salesperson. He was out and about, and he made some connections that proved very valuable in getting some of the seed capital.

Alejandro: So, how much capital did you guys raise for the life of the business?

Gil Elbaz: We raised under a million for the seed. Then we ended up doing a Series A in the summer of 2000, which turned out in retrospect to be very lucky that we got it done because months later, the NASDAQ Stock Market crashed. You entered this long winter for a couple of years where VCs were very paused in terms of investing in new companies. So, we ended up getting a Series A done: 5.2 million dollars we raised from a couple early stage Series A investors. That turned out to be enough. We had to be very frugal and careful with that money. Otherwise, we wouldn’t have lasted the long winter. We ran the business knowing that there probably wasn’t going to be another round, so we ran it to become profitable.

Alejandro: That’s interesting. Obviously, the 5 million A round that you did back them probably would have been 10 to 15 or even more today. It is really incredible how things have, I would say, evolved on the financing cycles. But one thing that I wanted to ask you here is, being part of that history where the market was really turning around on all the people that were in tech and especially doing hypergrowth companies. You were talking about being a little bit frugal with the capital that you guys had raised. So, what did you learn from being in such a long winter, an environment that if we were to go with another, say, market correction, you would absolutely keep very closely in mind?

Gil Elbaz: I think you’re right in referring to the idea that as a company, you have to accept the fact that there might be a period of time that springs on you where funding freezes. So, you always have to have that Plan B in mind. What happens if you can’t raise any more capital? On one hand, there’s an incredible pressure to grow the top line, to spend aggressively, to build new products and hire new salespeople to grow revenue lines. On the other hand, it may be the case that the money that you have in the bank is the last money you’re going to see. I think the lesson is you have to constantly have your Plan B and continue updating it and making sure that the Plan B might not be a healthy, happy one, but without one, you might not make it to the next chapter.

Alejandro: Yeah.

Gil Elbaz: For us, we did have to do a layoff. It was one of the worst weeks that I had experienced at the time laying off seven people out of let’s say it was probably about 45. It felt devastating to me. We did have to cut corners in order to make it ultimately to 2003 when things started turning around.

Alejandro: Talking about that a little bit, Gil, because people always talk about how beautiful everything is. I’m glad that you’re touching on this. As a leader, who did you have to be in that moment of doing the layoffs in order to be effective?

Gil Elbaz: Who did I have to be as a leader?

Alejandro: Who were you being because obviously, it’s terrible as an experience to have to go through as a founder and a leader of the business, but also the show needs to go on. So, how did you really execute so that you were able to minimize as well the impact on the culture, but them be able to continue pushing forward? How did you handle that?

Gil Elbaz: Yeah, that’s a good question. Later, I stumbled on this lecture, this Last Lecture of Randy Pausch that I think was incredibly touching and meaningful to me about how—it teaches stories of grit and how any successful company is going to have to encounter and deal with really painful and difficult obstacles. If you don’t run across those obstacles, then there’s almost something wrong with your journey. If you don’t encounter those obstacles, you’re probably not pushing hard enough, or you’re working on something that isn’t going to distinguish yourself from the field. I feel that one of the key experiences is just simply dealing with difficulty and pain and taking a few deep breaths and waking up in the morning and trying to disconnect a little bit of the emotion for a moment. I always like to write to myself. Writing down options and writing down as much as I could about pros and cons and trying to get comfortable with the fact that even though a particular choice feels and seems painful, it’s the right one for the company and for the highest percentage of people as possible. Then just moving forward, taking a step at a time. That’s what execution is about is just moving forward. I mean, as far as the people that were negatively affected, I think they understood. I let my emotions show, and they understood that I wasn’t happy, but it was the best thing that I could do for the company. I think if you’re just transparent like that, that things can still work.

Alejandro: 100%. I fully agree there with you, Gil. For you, how was the transition because here you are, a trained engineer, going full speed ahead as a business leader. So, how was the transition from the engineering side to the business side for you?

Gil Elbaz: It was tough. I don’t think I was prepared for a leadership role at Applied Semantics. If you’ve read or paged through Ben Horowitz’s book called The Hard Thing About Hard Things, he describes how really none of these founding CEOs are prepared for being a CEO. There’s not really a tool or a class to prepare. You’re just thrown into it, and every experience is a little different. So, I don’t think I was prepared, but one experience at a time, you build up a book of experiences, and you build some wisdom. Again, it was difficult. Here’s an example: somehow, I got all the way through high school and college never having made a presentation in front of a group of people. I’m not really quite sure why or how I got through education like that, but I remember the first times having to present to clients, not having any training or experience. On at least one occasion, I had a panic attack and forgot where I was and just stopped speaking. But through every experience, you learn a new technique. Whether it’s a breathing technique or you gain more confidence, you see another day, and you’re a little bit better. Over time, what you get addicted to is improvement. So, little by little you go from having no skill in something to if you’re really committed to it, you can gain quite a bit of skill in almost any endeavor that you set for.

Alejandro: Absolutely. Gil lets shift gears a little bit here and let’s talk about the M&A. So, how was that process for you guys? Obviously, the company ended up being acquired by Google, but make us be insiders for a minute here on that M&A process.

Gil Elbaz: The M&A process with Google and Applied Semantics you’re asking about?

Alejandro: Yeah. Did you guys make a decision to go ahead and do an M&A process and so forth, or was it Google coming to you guys, or how did it happen?

Gil Elbaz: In building companies, my goal has always been optionality, so not having an absolute goal around an exit. At Applied Semantics in 2003, we did not have a goal to be acquired. Our goals were to build good technology, and to serve our customers, and to grow. We did not begin any sort of M&A process. What happened in 2003 was we were seeing a lot of growth in our AdSense. We were working closely with Overture on this product, co-marketing with them at AdSense and selling into publishers, tying it to their large ad network. Overture, as you probably recall, ended up becoming Yahoo’s advertising network when they got acquired, also in 2003. Google also was getting very, very interested in this area, and we were having discussions with Google. At the time, what we were hearing was that Google and Overture (Overture became Yahoo), these two powerful companies were both telling us that they were going to invest heavily in contextual advertising, and they told us, “You’d better sell or else we’re going to be competing with you shortly.” We decided that it was the right opportunity to strategically align with one of these two companies, and Google made us an offer that we couldn’t refuse. A very good offer. I was also a little bit less experienced, so I think I was a little bit terrified, frankly, that competing against what would become Yahoo and also Google at the same time would be too much of a challenge to surmount. In retrospect, I think it wasn’t the game ending moment. We could have managed. We saw other companies after us grow even larger in the space, but I certainly don’t regret anything. I think Google made us the right offer and employees and investors felt like this was the right exit. It enabled us to have this fantastic experience with Google to grow the AdSense business. I was there for four years. Today, it’s something like a 15 or 20-billion-dollar-a-year revenue wedge for Google.

Alejandro: That’s amazing. How big were you guys prior to the transaction closing?

Gil Elbaz: We were 45 people. We were profitable. I don’t recall the exact revenues, but we were profitable, and we were growing very quickly.

Alejandro: Got it. What were the terms of the transaction, Gil?

Gil Elbaz: It was a cash-in-stock deal. So, we were able to pay back our investors and pay back a return, and there was upside with the stock. So, that was a positive outcome.

Alejandro: I believe I read that it was reportedly somewhere around 100+ million. A little bit over 100 million. In Google, you worked for four years. How was this shift for you where you go from building your own baby and not reporting to—maybe like your investors and the board, but here, you’re working for someone else. So, how was this for you?

Gil Elbaz: It was an incredible opportunity to be at Google. As an engineering director to run the Santa Monica office. Then it got renamed Google Venus. Now, it’s Google Los Angeles. This opportunity to be an engineering leader was fantastic. Getting to learn from engineering leaders and an organization that had this true data and engineering DNA, who had the experience to build up a culture to incredible scale. It was a fantastic experience, so I really enjoyed that and learned a lot over three and a half years.

Alejandro: How big was Google at the time where you guys did this deal?

Gil Elbaz: Google was 1,000 people at the time.

Alejandro: Wow.

Gil Elbaz: Probably 300 or 400 in engineering, I would guess.

Alejandro: Wow. Compared to probably the hundreds of thousands of employees that they have today.

Gil Elbaz: That’s right. Yeah. That was 2003. I stayed there until 2007, and I think they grew the employment base around approximately 10X in that time, and then as you mentioned, they’ve grown approximately another 10X on top of that since I left in 2007.

Alejandro: Wow. That’s amazing. So, what made you switch gears and say, “Hey, Google is fun. This is a rocket ship, but it’s time to go at it again.”

Gil Elbaz: Yes. As I mentioned, getting to see in action a culture of incredible engineering talent and culture of innovation and wanting to challenge whatever status quo is in the world and try to do things better. Oftentimes, using data, using automation and software, increasingly using machine learning and AI, it was amazing, but it also refined and continued to shape my world view that the data moat is an incredible advantage that Google has, and it’s because data is a fundamental building block for almost any important discovery or innovation. I became a little bit concerned that Google could become a monopoly of innovation. I felt like a world where many companies are bringing innovation forth, across the world, I felt like that ultimately is the world that I want to live in. So, I started to think about creating a neutral data company, a company that wants to democratize access to information to provide data to other companies so that they can work on innovation, on building innovative new products and services. I thought it was an important role to play. That’s what we ended up doing. I left in 2007 and began building Factual in 2008.

Alejandro: Got it. What was the early, I would say, founding team or members of the team?

Gil Elbaz: In the early days, I had two founding engineers joined me. One researcher, Ph.D., that had experience in natural language technologies and AI, Tim Chklovski, and an experienced engineering lead from IdeaLab named Mironov. So, the three of us began working on ambitious ideas that we were writing down on paper in 2007. Then we began building the company in earnest in 2008.

Alejandro: Got it. Really, really cool. Basically, what ended up being the business model for Factual?

Gil Elbaz: Much like Applied Semantics. Granted, there was only one data point, but my one data point at Applied Semantics, a lesson that I took from that is you can overoptimize a business by focusing too much on a specific solution. If you want to do something really disruptive and ambitious, focusing on a technology first, a technology that you think is going to be widely applicable, and then building something differentiated first. Then focusing on business model and use case second. That worked for me the first time. Again, at Applied Semantics, we had no idea that we were going to build a technology for ads at the time. We were just building a technology for organizing information. So similarly, at Factual we put down some founding notions of what we want to do. It was a little bit similar to Applied Semantics in that we wanted to build a foundation all technologies for aggregating, cleaning, and structuring data so that we could build databases as scale, and so we would have and control unique databases that were of higher quality and would be in demand. On founding in 2008, the App Store had just been launched. We were working on it even before the App Store had been launched, so this whole concept of this mobile ecosystem was brand new. But we had a feeling that location was going to be very important in this new mobile ecosystem. That was a good bet. We started working on location data very early, and that ended up being the premier focus of Factual, wanting to understand everything about every point on the globe and putting it into databases.

Alejandro: Got it. As you were mentioning, we’re talking about 2008. So, this is before all the hype of data being the new oil or the craziness around AI, and machine learning, and things like that. So, I guess, for you being early in all of this data momentum space, I would say what would say that were some of the challenges that you were experiencing?

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Gil Elbaz: Yeah, you’re right. It was before all the hype. Terms like big data and data scientists hadn’t even been coined yet. So, these weren’t words that people knew or understood or used. It was a few years before data became mainstream as an area that companies should invest in. Yes, they were investing in IT, information technology, but they were thinking about it in a very traditional, more pragmatic around how do we make sure everybody has email and can access our corporate apps. They weren’t thinking about it broadly in terms of how do we collect as much information about our customers in the world as possible so that we will be in the single best position to serve our own customers? I think because of that, the main challenge in terms of building a business model is that many companies weren’t that interested in investing, in licensing, and in getting access to our data. We were in a sense in a limbo period waiting for a customer to be born. Later, you’d have location-based services companies that would later become our customer like Uber and Snapchat. Facebook was around but hadn’t been focused on mobile. These companies would later become our customers, but we would have to wait for them to be invented and founded.

Alejandro: Got it. One thing that was just coming to mind is for something of this nature, obviously, to support growth, you need capital. Now, in your case, you had the financial muscle from the previous transaction that you had done with Applied Semantics during the acquisition to Google, so why did you decide—well, two questions here. At what point do you decide or you see that the business is going to require capital? And why did you decide to raise that capital from outsiders rather than doing something internal?

Gil Elbaz: I think there’s a lot of value in raising money from venture capitalists, especially top-tier capitalists beyond the capital itself. We raised a very large Series A. It was 25 million back in 2010. So besides, obviously, the capital is important if you’re going to try to attract tough talent. But it also, in the case of Andreessen Horowitz and Index Ventures, they were able to offer guidance, a large network. Andreessen has teams. They were among the first that were revolutionizing the idea of having teams that were available to help with marketing, with recruiting, with business development. So, there’s a lot of support there. Also, to the employees, employees are happy to know that this isn’t just a founder’s game or love. It’s a business. In order to attract top employees, you have to show that you are very focused on building a real business that’s going to ultimately be a great growth opportunity for this top talent.

Alejandro: Yeah, just like you said, I think that the resources that these VCs bring or these investors bring are fantastic. But just like you were pointing to the signals that you sent to the market and the social proof is great. I was just taking a look at the cap table that you guys have. I mean, Index Ventures, Andreessen Horowitz, Felicis Ventures, Founder Collective, Data Collective, Upfront Ventures. It’s like the Who’s Who of startup investing. So, how did you meet these guys, Gil?

Gil Elbaz: I was definitely proud of the group of investors that I was able to assemble back then in 2010. I don’t know if there’s a pattern to drop on in terms of how I met these people, but I certainly got out there. I was investing. I loved angel investing, so I had the opportunity to pay it forward a little bit, but it was also a fantastic financial opportunity to invest in other founders. Maybe through some of those founders, I got to meet some of these investors. I enjoyed that process.

Alejandro: That’s definitely a good way, boards and stuff like that. How big is Factual now?

Gil Elbaz: Factual is about 200 employees. Our headquarters are still here in LA, but we’ve opened up offices and have a significant headcount in New York. We also have people in Chicago, London, Singapore, San Francisco. We’ve been growing around 50% over the last five to six years, so it’s turned into quite a sizable operation.

Alejandro: Why the different offices? Is it because of the skill sets that you’re looking for that perhaps you’re not able to find them in LA, or why?

Gil Elbaz: The remote offices are sales offices. That’s a pretty typical configuration. We’ve decided to centralize product development and engineering here in Los Angeles, so almost all of the product managers and engineers and data scientists are here in LA, but we need salespeople on the ground in these remote regions in order to grow our marketing and sales footprint there.

Alejandro: Got it. Where do you see, Gil, the data space heading?

Gil Elbaz: The data space. I think it is still very early innings in terms of companies investing in first-party data, in understanding as much as possible about their own customers, and about the rest of the world so that they can optimize their experiences, optimizing the user experiences. Companies want one-to-one relationships with their customers. They want to make sure that they’re not disintermediated. They want to strategize and have very personalized one-to-one messages delivered, and you can only do that through the power of big data. We see this as still a very much growing area, and specifically with location data, location data is a key element in terms of understanding your customers. Even if you’re an online store, understanding when somebody’s shopping. Are they doing this at home? Are they also buying your product in physical locations? What are their patterns? These things all figure; it’s much more than just sending a geofence coupon. Sometimes, when people think about location experiences, they think about a geofence coupon. When you’re near a Starbuck’s, they could give you an ad that says, “Walk into our store, and then we’ll give you this discount.” We see this so much more than that. We see it as fundamentally understanding the mindset of your customers.

Alejandro: Really cool. Going back to what you were saying before, you did your angel investing, but then you also created your own VC structure or vehicle to invest called TenOneTen Ventures. Can you tell us a little bit about TenOneTen Ventures?

Gil Elbaz: Sure. TenOneTen is an early stage seed fund. TenOneTen was founded by David Waxman and I. David Waxman has become a friend and colleague. He’s a serial entrepreneur himself. Spent time at MIT. So, also very technical and a great operator. We like to see ourselves as the technical operators. A little bit geeky. Understanding the deep power of technology and data to disrupt industries across the landscape. We started investing together maybe six years ago, but three years ago we set up a formal fund. We’ve had this great opportunity to build a brand as the fund that can invest in ambitious technical founders that have big, bold ideas. These tend to be in Los Angeles, although our mandate is broader than that. We can invest outside of LA. I do love to see companies with data moats company where people are building up unique proprietary data sets and using it to reinvent something. A company that comes to mind is Second Spectrum that has become the dominant company in basketball and sports data. They’re going to go beyond basketball, but they’ve become known as the basketball data company, and they’re working closely with partners. They got a big contract from the NBA. They’re looking to reinvent the entire consumer experience.

Alejandro: You’ve seen quite a bit of founders. You guys have been very active on the investing side. So, what kind of patterns have you seen on these founders that you saw them at a seed stage where they’re basically eating Ramen out of a garage or something like that. Then they’ve gone out to build meaningful stuff. What are some of those patterns for trades of these founders that have potential?

Gil Elbaz: Right. So, you’re asking what are the characteristics of a founder or founding team that to us makes for a great bet for an investment from TenOneTen?

Alejandro: Correct.

Gil Elbaz: I think it’s natural to look at many different dimensions. You’re right in pointing to that. A team is incredibly important. For us, we look at some indications of passion and grit. We want teams that are working to solve a big problem. We’re not just looking to build a company and flip it and sell it. We’re looking for people that deeply believe that they are put on earth to solve this problem. Sometimes, it takes a full ten years to materialize a value to the world that you’re bringing. That element of grit is important because sometimes, these stumbling blocks are really painful. We talked earlier about a long winter and having to do layouts. Some people, when the going gets tough, it’s just they have other opportunities in life. They can close up shop and get a very high-paying job somewhere else and have a wonderful life. I don’t necessarily hold that life choice against those people at all, but our job as investors is to predict which people are so wedded to the idea of success in terms of solving problems for customers that they’re just not going to give up no matter what, maybe until their heart stops beating. So, there are certainly cases where we’ve picked very well.

Alejandro: That’s really cool. So, I always ask this question to guests, Gil. If you could go back to the past, and obviously, you have an unbelievable amount of experience now, and if you could really go back to the past and give yourself just one piece of advice before launching a business, what would that be and why?

Gil Elbaz: Let’s see. If I could give myself one piece of advice before launching my first business.

Alejandro: Right. Let’s say if you were able to talk with your younger self, what would you tell yourself?

Gil Elbaz: Yeah. That’s a good question. Let me ponder it for a second. The first thing that comes to mind isn’t answering your question, but sometimes, I think I need my younger self to give me advice today and to remind me to go after big ideas. It’s so easy in life as one becomes older to become pragmatic and to do things you know are going to work. It’s hard to remember that risk-taking and doing a few crazy things, allowing for some moon shots is where the most exciting success comes from. I try as hard as I can to remember that, but I think it wouldn’t be bad for my younger self to occasionally shake that sense back into me. I think to answer your question, I’ve learned over the last couple of decades to not panic when difficult situations happen. I think it was somewhat prepared for that journey, but not entirely prepared. So, the first time around, the roller coaster of incredibly depressing, sad, scary things happening along the journey probably took at least weeks if not months off my life just because you can have panic attacks around, “Oh, my gosh. This new competitor has come out of nowhere, and is better funded, and has more Ph.D.’s.” I learned at Applied Semantics that there are many elements to success and some of the most important ones I think are less tangible than what’s on a resume. I think these attributes like passion and grit can’t be really measured. It’s really what’s inside of you. There’s every opportunity for you as a small company facing David and Goliath situations to prevail. You learn that over time, but it would have helped I think to hear that earlier.

Alejandro: Got it. Gil, what is the best way for folks that are listening to reach out and say hi?

Gil Elbaz: Well, you can follow me and send direct messages on Twitter. I’m Gil Elbaz on Twitter. I appreciate any interests.

Alejandro: Amazing. Well, Gil, thank you so much for being on the DealMakers show today.

Gil Elbaz: Thank you very much.

 

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Neil Patel

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