How to Steal Customers From Giants 600x Bigger than Your Startup | Pigment, Eléonore Crespo

1. 0:00 – 0:45

   Intro

   1. ECEléonore Crespo0:00

      We compete against legacy player, SAP, Oracle, that are very dusty, but that have been here for a long time. Some of them have been built before I was even born. And so since day one, we actually decided to climb Mount Everest and to build a, a product and a platform that was enterprise ready. We live in a world where decision-makers are looking after the best decision-makers out there. You need to have fast-forward-looking companies telling, "We love Pigment, we love that platform, and we will tell the entire world that this is true," and people will follow. So it was not easy, but today it has an amazing compound effect. So sometimes, you know, taking the hard route can bring you to an easier route over time, and sometimes, you know, you start easy and then it gets hard, so you have to pick your battle.

2. 0:45 – 1:17

   What is Pigment?

   1. ECEléonore Crespo0:45

      I'm Eléonore Crespo, co-founder and co-CEO of Pigment. Pigment is an AI performance management platform. We bring data within one platform. So you bring your finance data, your supply chain data, your HR data, your sales data, and the goal is really to make the best possible decision on that data. We've raised over $400 million since the beginning of the adventure. This year we are growing. We are still on a 2X trajectory in terms of ARR. We were on the same trajectory last year. [instrumental music]

3. 1:17 – 4:38

   Even the Most Innovative Companies Got It Wrong

   1. ECEléonore Crespo1:21

      When you are in Europe, you for sure are going to live in a small country. France is small. Entrepreneurship in France at that moment was clearly not as big as what it is today in the world. But still you could see, and you, you started to have the first few unicorns that were really inspiring. And actually, my co-founder was a, a very, very big inspiration for me because he had built one of the first French unicorns that was very famous at the time I did my studies. And I did actually at that time a minor in entrepreneurship because I knew that this career of potentially building a company at some point would definitely have to be part of my journey. I wanted to have a big impact on the world, and I just needed to find the right moment. So Google was my very first job, and I actually worked for the CFO of Google EMEA and the CFO of Alphabet. I was really exposed to everything planning at Google, strategic planning, strategic decision-making. But I was pretty naive. I saw that whenever they had to make a strategic decision, they would have the best possible tools internally to do that. You know, Google is one of the most innovative company out there, so you would imagine they are very well-equipped. And I was very, very surprised actually that everything they were doing there was made on Google Spreadsheet pretty much. So they would, you know, really trying to understand their business, do their revenue forecast, understand their margin, understand their budget. Most of it was done on Google Spreadsheet. But Google Spreadsheet has never been built for that scale, has never been built for that amount of data. When you have to combine data from multiple business, dozens of countries, it just doesn't scale that way. So that was very surprising to me. I thought this problem probably has to be cracked because if Google doesn't do it right, I'm pretty sure thousands of companies out there are do it wrong, too. After that, I joined Index Ventures, and I was very lucky to be with some of the best founders in the world. You could think about the founder of Figma, the founder of Datadog, the founder of Revolut in Europe. I was working with the most fast-forward companies out there that were equipped with the best technology because these founders are the early adopter of the technology. And yet that's the topic they were struggling for. They were preparing for an IPO. They were post-IPO. They were trying to understand their finance data. They were trying to understand how to improve their margin, how to optimize their quota, their sales territory, their revenue, but they were not equipped. They were not equipped at all to do that. Even with AI, a lot of companies will keep using Excel for quite a while. Now, I do think that Excel has its own limit. Excel was created to be a very flexible platform that would help you build quick models. But what's happening obviously at a company of a certain scale is that you need to bring together the right data, the right people with the right governance, the right security, and the right modeling to really help them take these decisions. So imagine Coca-Cola. Coca-Cola is a company where you have literally hundreds of business units, hundreds of countries, thousands of products, and all of a sudden you have to understand what's happening in your business. You have to understand your supply chain. You have to understand your revenue. You under- understand your margin by product, by business unit, by contract. Can you do that in Excel? Does that scale? No. When you have to look at billions of rows, billions of cell, that is not the technology that you want to use. And we realized that this problem was real, and it was really everywhere, and it was a massive market to go after, and that's what we decided to

4. 4:38 – 6:13

   The Hard Path is The Fast Path

   1. ECEléonore Crespo4:38

      create Pigment. [instrumental music] We come in the market, we're in front of companies in the likes of SAP, Oracle that are very dusty, but that have been here for a long time. Some of them have been built before I was even born. As a VC, I had seen many, many times founders that were starting in a category, but where what they were building was not a must-have, it was a nice-to-have. We really wanted to create a platform that would become a must-have. We live in a world where decision-makers are looking after the best decision-makers out there. Today, a lot of people are looking at, uh, the CEO of Anthropic. It's one of our customers. The CEO of OpenAI, the CEO of these companies to think about, you know, the future of their own companies. Because especially in our category, as you can imagine, we serve CFOs. We serve large finance team. When you serve this type of customers or when you serve strategic decision-maker, you need to build trust as early as possible. People need to trust you, right? If you want people to trust you, you need to have fast-forward-looking companies telling, "We love Pigment, we love that platform, and we will tell the entire world that this is true," and people will follow. We wanted to create that network effect. So since day one... We actually decided to climb Mount Everest and to build a, a product and a platform that was enterprise ready. But getting the f- very first customers was very hard. Very, very hard because, you know, we were based in Paris at the time. We didn't have a very big US presence, and we needed to go after these very large tech companies here in the Valley that had never heard of us, where we had zero brand

5. 6:13 – 8:39

   Why Enterprise Sales is Harder than Founders Think

   1. ECEléonore Crespo6:13

      awareness. One difficult moment a lot of founders get wrong is how difficult it is to sell to large companies. You think perhaps that your product is enterprise ready, you're ready to sell to enterprise. That's not the case at all. What we do is quite different from a lot of SaaS companies out there. We compete against legacy player that have been here for 15, 20, 30 years, and hence they have built a platform end-to-end that brings a variety of features and functionality. And in order to be really relevant in the world of enterprise performance management, business planning, and to bring and deliver value to our customers, we couldn't just ship one feature, or we couldn't just ship one product. We needed to deliver the entire platform because the first use case we were shipping at the time were already embarking dozens, hundreds of people on the platform to work on a variety of use cases. In order to do that and in order to bring that value, we needed to come with a superior platform from all angle. We needed to build this incredible, what we call the elastic Canva, which is an incredible computation engine that really helps you model any data on Pigment, and we need to build the most incredible UX for anybody to adopt the platform. And in order to do that, we sh- we would not be able to ship a product in a month. It took us some time. We started end of '19, and the product was truly ready in '21, and we actually carefully picked our investors on what help they could bring us. So could they actually open some doors for us? Could they really help us also find perhaps some US executives that could help us open doors for us? And that's really how we managed to create this first moat and this first advantage of being able to open as many doors as possible and to find our very first customers. Because again, these customers, I, I think if they didn't have VCs backing us and telling them to use our product, I'm not sure they would have been able to really go after that. And I have amazing stories. Figma is one. Brex is another one where they really were the first one to say, "Yes, we are going to go after the platform." I even remember the CFO of Carta at the time that was also one of our very f- first customer that immediately wanted to become an angel because he saw the potential, and that's really what made the beginning of the adventure. So it was not easy, but today it has an amazing compound effect. So sometimes, you know, taking the hard route can bring you to an easier route over time, and sometimes, you know, you start easy, and then it gets hard, so you have to pick

6. 8:39 – 10:37

   Your Team is the Deck

   1. ECEléonore Crespo8:39

      your battle. Before we launched our product, we had raised about 25 million. We didn't do, like, a proper fundraising. Some investor went to us and, and asked us if they could actually put a term sheet out there. But I think what they saw goes back to trust and credibility. If you want to raise pre-launch, you need to have a very, very strong story around what you've done, the team you've put together. It all goes back to the team. The team is the most tricke- critical piece where investors will spend a lot of time looking and digging. When you are not in the Gartner Magic Quadrant, for instance, for us, when you do not have thousands of reference already to share, people have never heard of you, they have never read about you in the Wall Street Journal yet, th- the only way to scale yourself is to hire people that are smarter, better than you, and that can help grow the company to the next phase. In the first one year and a half, two years of the company, we had brought together the highest caliber team of talent. We have one of the best engineering team on the planet, actually, that is building that product. We also hired people that were former finance analysts, former revenue operation analysts, so former personnel of ours. When you go, uh, to a customer and you say that, "Yes, perhaps your product was just born two months ago, but in your team you have people that are experts in the ecosystem that have been selling similar platform for the past 15 years," and that can then tell to your customer that this is the best platform out there, that's a very strong message. So that's one advice I would give, actually, is to try to find people from the ecosystem that have the right level of expertise and that would create that trust, and, uh, I think that's the only recipe for success. So that's the number one tip I would advise anybody is to think about the values of your company and write them and have them very clear to you day one, and keep them forever at your company and make them evolve if

7. 10:37 – 12:41

   The Two Hiring Stages that Reveal Everything

   1. ECEléonore Crespo10:37

      need be. Calibration is also a very good tip for anybo- what... one out there. What I mean by calibration is being able to go, um, in the market before you hire for a role and asking to meet the best CFO out there, asking to meet the best CROs, asking to m- meet the best salespeople to understand what best look like and how can that apply to your company. And for me, the, I think the most two critical, uh, stages of a hiring process are around the case study and the background check you are going to do on the person. The case study is really way, what is going to reveal to you if the person is a doer, if the person is ready to get their hands on, their hands dirty to solve a problem, and if the, the person is ready to listen. And the second moment is the background checks that you're doing on a person. Calling people that the person has not even referred to you, but trying to understand who that person is from that angle. And we really try to do that consistently, and this is really when you learn the most. And you have to dig, dig, dig. You never hesitate to ask question that hurt to the person even if you don't know them. That's okay. At worst, they don't answer. But you really want to understand, uh, as much as possible about the person. We really try not to shy away from showing to the, the person during the interview process the reality of the job, the difficulties of the job, what they were really going to do, and never trying to oversell or undersell the company, being very honest to ourself. Now, don't get me wrong. We made tons of hiring mistakes. We made tons of them. Every hiring mistake that we've made has caused mistakes everywhere else in the company. That's where you start having a, a lower bar at everything you do. But the most important always is to try to understand why you made this mistake and what you are looking for next not to make them again. That is the only thing that matters, whether it's day one or whether it's today. [outro music]

Episode duration: 12:42