#327 Building a Sales and Marketing Capability for Data Applications with Denise Persson, CMO at Snowflake, and Chris Degnan, former CRO at Snowflake

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It'S so incredibly important to have that unified platform for your company that is governed, secure, connected. It's going to be really hard for companies who don't have their data in order to do anything with AI. You cannot have an AI strategy without the data strategy. Still, some companies are behind on getting their data AI ready. That needs to be priority number one now for every organization.

Historically it was you had this data and send it to the application, oh, I need to put it in Salesforce or I need to put it in Workday or whatever it is. I think the inverse will happen over time. And it is happening is where you're bringing the application of the data. And I think that's what Snowflake is really focused on, is allowing the application to sit on top of the data and having that all that data accessible by any application is incredibly powerful.

Welcome to Data Framed. This is Richie. For your business to make money, you need an effective sales department and an effective marketing department. Naturally, using data to drive decision making and using AI for automation and process innovation is key to your success. I want details on how data and AI are best used in marketing and sales and how you go about building great teams. Who do you hire and what data and AI skills do marketing and salespeople need? Today's guests are a double act from the AI data cloud company Snowflake. Denise Person is Chief Marketing Officer and Chris Degan, at least until recently, was Chief Revenue Officer. They spent nine years working together, taking Snowflake from startup to data behemoth. Denise and Chris have just written a book about their endeavors called Make It Snow. There's a lot of insight around building out sales and marketing capabilities for a data company and I want all the juicy details. How to build out sales and marketing teams is of course useful if you work in sales or marketing, but also as a data person. I keep being told that domain knowledge is incredibly important, so now's the chance to learn. So let's find out about data and AI for sales and marketing. Hi Denise and Chris, welcome to the show.

Great to be here with you, Richie.

Hey, Richie, thanks for having us.

Let's kick off. Get right to the heart of it. So how do you get to a billion dollars? ARR.

What's.

What's the secret?

I think we get super lucky. It's a lot of, you know, people, I think, had a lot of perception that it would. It was a lot easier than it was. I think there was a lot of rolling up our sleeves and doing some really hard things, especially early on. When I joined, there was zero customers. And when Denise joined, we were just at $3 million in revenue. So a lot of things have to go right. And get a little lucky and take advantage of that luck.

Yeah. At the heart of our growth. Right. Is, of course, an incredible product. Our founder had a big vision for Snowflake. It took me three years to develop the platform. So it's really the product. And, of course, a relentless customer focus. That has been kind of the consistent theme at Snowflake has really. It's always been about customer obsession here and always doing the right thing for the customer.

Okay. I love the idea of customer obsession.

Yeah.

It's maybe something we get into a bit more depth later, but I think one of the recurring themes throughout your book is all about trying to have some kind of alignment between the sales team and the marketing team. So I'd love to know how that happens. Maybe. Denise, do you want to go first this time?

Yeah. I mean, the unfortunate thing is that in most companies. Right. There is often a lot of tension between the sales and the marketing function, but not just, you know, among those functions. Right. There could be tension, you know, across the entire company. Right. And if you want to build, you know, $100 million, $1 billion business and beyond, you all have to align around one mission for the company. And you really need to have a culture of alignment. Competing with each other internally or having tension internally, it kind of distracts everyone from what the focus should really be. The focus needs to be on your mission. Your focus needs to be on the customer. And again, that tension that often exists. Right. It's. Takes a lot of energy from people.

Absolutely. Yeah. Certainly you don't really want each other to fight. Chris, do you have a take on this as well from the sales side? How did alignment work?

Yeah, I think, you know, when Denise came in, in previous lives or previous. Prior to Snowflake, Denise arriving at Snowflake, there was friction between sales and marketing because we. We really struggled with getting leads and getting meetings. That's really all I cared about was getting qualified meetings for the team. And so I would argue over the definition of what an MQL was. And then Denise came in and recognized that friction and said, listen Chris, like, you are my customer. You're the number one most important thing in the company because if we hit our revenue targets, all things are good. And so she took that approach and that was really the approach that we went through at Snowflake. And so that was really important and her treating me as a customer and caring about the quality of meetings that the sales team was having. Not even the definition of an mql. So I think that was the beginning of like you had me at hello type thing of like, you know, okay, great, let's talk about qualified meetings.

And also, Snowflake is an infrastructure company, right. Our deals are sold through a sales organization. We have. There is a PG component of Snowflake as well. But again, that's not where the largest deals are coming from. Right. So it's really sales is the distribution channel for Snowflake. You know, primarily. We also have a very big in a partner ecosystem as well. But marketing's role were you in, you know, an infrastructure play like, like Snowflake is really about how do we make our sales organization in a more efficient. Then you need to really kind of integrate yourself, right. With the sales motion and not try to kind of for sales to do something different. Right. I mean, it's really again, having that exact same priority, you know, sharing the same, you know, objectives and making sure that marketing isn't measured on metrics that doesn't make sense for the company. In many companies, Snowflake marketing has been measured around this MQL metric. Right. MQL is a metric that is easy for marketing to deliver on. Right. And we sort of determine what that qualified marketing lead is. A lot of marketing departments just goes out to third party content syndicators and essentially buys a thousands or a thousand or ten thousand MQL a month. Right. I mean, that is not what marketing is all about. You want to create your own content, right? So you kind of, you, you build up the house. It's like renting a home versus, you know, buying a home. So you really want to deliver incredible educational content that kind of draws your audience in. Right. And then it's about, you know, the pipeline metric. Right? That is the most important metric. That is kind of where marketing sales really intersect, not on the number of MQLs you're bringing in.

That's interesting. So I guess if I've understood this Correctly, when you've got these sort of big pieces of software where you're selling very large deals, all that goes through a sales organization. So it's your accountants, executives who are selling. So it's a very different from selling stuff on a website or in a shop. So there, I guess the sales side of things leads stuff. Whereas marketing. Would you say marketing is more of a support function then as opposed to the other way around if you're selling to individuals?

I don't want to calling it a support function. I think what has been unique also at Snowflake is that we are first and foremost a customer driven organization. And if you look at many tech companies in Silicon Valley, they would say, oh, we are a product driven company, we're an engineering led company, we're a sales led company. Snowflake has always been a customer led business and every department essentially is equally important. Right. So I think we're all here in support of the customer. That's kind of the culture that we live, you know, by here. But again, from a, from a go to market standpoint, again we are all here to make sure that in our sales organization can sell as efficiently as it possibly can. From a marketing standpoint, essentially I would say that we have two objectives. One is of course around the positioning in the market. I mean we are leading that, we're leading the perception of Snowflake and driving kind of the education right. In the masses. So when the sales team of course at some point come in, the customer is already kind of educated, they know how Snowflake is positioned. Many, many people in the organization knows about Snowflake and would support the decision. Right. So it's not that we're just a support function per se, but again our goal is to make the selling motion as efficient as possible. And Chris can share a little bit about the metrics. Right. We've had over the years as well.

I double down on that. Richie is like, I definitely would not consider marketing as a support function. I think, you know, and building an enterprise, a company that's selling to large enterprises, I think you're, it's a machine, like you have to have a great product. So it's, it's on the, on the product team to develop a product that customers want to buy, number one. Number two is it's on the sales team to get and tell as many people as they can to get out there and tell them, tell the story about why the product is so great, why it's differentiated, et cetera, et cetera. And marketing helps get the, the brand awareness out there helps get the sales team in front of those customers to tell the story. And so really what Denise focused on and I think what she developed at Snowflake was a world class account based marketing system. And I think one of the things that like every sales leader, every salesperson that we brought in after Denise and her team developed this ABM program, they were like, I can't believe what an amazing marketing team we have. It was whether it was taking case studies and putting those case studies in front of prospects, whether it was a field marketing event that we would have and we would generate a bunch of interest in future prospects of having a customer get on stage, tell them why they love Snowflake so much. Those things were invaluable. And that was really the kind of the. My sales team loved Denise's marketing team because they were just, they were like, how can we help and how can we drive revenue? And that was like the number one focus.

When we say that, oh, you know, sales is our customer, I'm sure some would be. Well, that doesn't sound like a partnership. It's more just a mentality, right? On, on the marketing side and being sales, it's really, really, really hard, right? You have a number to deliver on, you know, every quarter. It's not an easy job. But if you feel that the entire organization is behind you and it's not just marketing, right? I mean the. It's the product organization, it's the finance organization, it's legal, right? Legal is also very, very important business partner to sales and also up to the CEO, right? Our CEO is out on sales calls helping the sales organization, you know, close deals. It's more like a mentality that we're all here to support the customer. And of course it's a sales team who leads the process.

Denise, you mentioned the idea that some companies describe themselves as being product led. And so certainly on a lot of the data framed audience are people who are building things either with data or with AI as we have a lot of product people. And one of the big challenges, okay, I've got a product which is technically amazing and then have no idea how to sell it. So I'm curious as to like how you go about finding that the market for your product or finding product market fit, maybe. Chris, do you want to stop this? How do you approach this?

At Snowflake, we had an investor in Mike Spizer from Sutter Hill who, who firmly believed in hiring a salesperson prior to the engineering team, believing that they actually needed A salesperson. So Mike's kind of pitch to me was, come and help define the product direction at Snowflake and go talk to a bunch of customers. So I joined Snowflake like no external people had ever touched the product. And my initial pitch was not like, try the product because I couldn't give it to anyone. It was like, hey, do you have 15 minutes for me to tell you about this company that has no website, that is in stealth mode, where we've built this brand new architecture and for a database and here's what we've done. And so that was my, the initial, like, hey, do you believe in this architecture? Do you think it will solve pain points that you have? That was my initial conversations. And then as I found people that were interested, then I started in the product, matured a little bit. I was like, okay, well, hey, Mr. Or Mrs. First or Second Alpha Customer, will you try the product? And then we started getting people to try it. And during that process, we, we, we broke the product a lot. So like, you know, before I ever got a purchased order or signed agreement for anyone to give us any money, the earliest customers were beating up the product. And, and what, what ultimately the, the founders and, and Mike Spicer were looking for was we want to build a product that people cannot live without. And so that was really my goal is like, get people to try it. And then they got addicted to it. And then we could start figuring out pricing and then we could figure out how to build out scale at the go to market. But it was at first like, hey, shaping the direction because early on I had, you know, delusions of grandeur of like, hey, I would go out to like a large enterprise that was stuck in the 1990s who would say, hey, when will Snowflake deploy in our cloud, in our private cloud? And the founders would say, never. Okay, so there was two options there. It was either continue to badger the founders, which I knew I would lose, and I would get fired, or go find the right customers that only were in the cloud because those were the ones I didn't want to sell. The religion of the cloud. I wanted to sell why I had a better product than anyone else in the market for cloud data warehousing. That was the initial intent and that really helped honed in the messaging that helped us even as Denise came in and she helped define, you know, product marketing and all the what markets did we specifically want to go after. It was really our earliest customers that led us to this direction. And that's. And that was the beauty of me joining as early as I did, I.

Love that you're trying to sell a cloud data warehouse and the customer saying, well, can we have it on premise?

It happened a lot, trust me.

And also that concept of ideal customer profile, it will change, of course, right? And in the early days, right, of course, we had wanted to sell to the large enterprises immediately, right. But they don't trust, you know, a company with no customer, right. They can't experiment the way those early customers at Snowflake did. So we were, in the early days, we were big in the ad tech space, in the gaming space, and these were customers that really pushed the product to the limit, right. And helped, of course, develop Snowflake to what it is today. They were the early pioneers and everyone else was looking at them, they were envying them, right? Because the big companies couldn't do what they did yet, right. But when they saw that, okay, it's really working for them, right, Then they started believing Snowflake as well. So I think being a startup is really about finding the early believers, right? It's even when you hire people, our founders had to get inspired people to believe, to move from very big companies to come and join this company, right? And then it's the same thing with customers, right? How do you find those really early believers who are willing to bet on this? And then, right, you, when you start crossing the custom, right. It's about those people who believe in the believers, the anxious people, right. Who are not willing, who cannot take the risk. Right. Early on. So of course, the ideal customer profile really evolves, you know, over the years.

We hired this amazing CEO, Bob Muglia, early on, like nine months into my tenure of being at Snowflake, and Bob invented our pricing model. I, I was, I took a crack at it and failed miserably. And what really, Bob's genius was around, around the product was, okay, we ultimately want to sell to large enterprises. And early on, you know, our board members were like, this isn't a great business. Because all I was selling to was, as Denise said, was ad tech and online gaming. And they're like, this is not sustainable. If we, if that is the market we're going after, we're not. This isn't a real company. And so Bob did, he came from an enterprise background. He said, okay, well, what does the large enterprise need to, To. To, you know, to use this product? And so he then came up with that list. And every week in our company, All Hands meeting, he. He had a list of all the enterprise features that any, any large enterprise would need. And then he design it to an engineer and in the, in the all hands meeting, he'd point to every engineer who, who, who is responsible for that feature and say, how is it coming? And every week. And the engineers hated it. Selfishly, as the salesperson, I loved it because my accountability wasn't the number. And I never knew like if engineers were going to, you know, develop the product or not. And for them to be held accountable in a public forum, they didn't like that. But it, it actually got us to what we declared GA in, in June of 2015 to become a generally available product because of the stuff that Bob took into, because I think it's important how to figure out how to sell the product. What are the differentiators? That was what our earliest customers showed us. And in fact that was helpful. As I brought on salespeople, I actually understood to a deep level on what the pain points were that we were solving for these customers, these earliest customers. And I would then say like, these are the things you have to look for. Mr. And Mrs. Sales rep that we've hired that has not never sold Snowflake before. And that was incredibly valuable because then it gave us like I could actually tell them these, this is an A account, a B account or C account. And that's where Denise and I partnered up and said, let's go after the accounts and let's give each sales rep a hundred accounts each and then let's go get them a bunch of meetings in those a hundred accounts. And that's where we kind of started to really focus our time and energy. Because if a sales, sales rep has thousands of accounts, they're just going to like be super reactive. But if, if there's, here are the accounts, here's why they're a. Denise, help us get into these accounts and like, let's get meetings, qualified meetings in those accounts. That's what we centered our kind of focus on and partnership in, on driving, you know, ultimately, you know, world class revenue growth.

So on the marketing side, before even the sellers had started, right? Since it was so clear which accounts were the accounts, I mean, we went in, did all the contact discovery, all the mapping of those accounts in terms of who are all the different decision makers and influencers that we need to engage within this account. So we went in, it was usually about maybe a hundred different roles right within the company. And then it was about, okay, how do we drive engagement with 20 or 30 of those? So when the seller joined, right, they got okay here are your 100 accounts. But these 10 accounts you should focus on because there's already really strong engagement here. They already want to, they already want to hear from Snowflake, essentially.

This is fascinating and I have to say the idea of making product people like stand up in a meeting and say this is where I want to on that feature. I'm sure that I just kind of like really terrified all and saw them. But both you mentioned that you focused early on on ad tech and online gaming. So why did you decide that? I'm curious as to how you go about trying to figure out these are this industry is going to be our best customers. Like, how do you choose this?

As I said I had customers, I'd go to these like Fortune 500 companies and they'd say, when are you going to the private cloud? And so, you know, our founders are like, never. Okay, great, I'm not going to go sell to those right now. So, you know, it's either like, I accept defeat in those accounts for now. And I, like I said, I was not selling the religion. And the people that were selling the religion were Amazon or Microsoft and Google of the cloud. That was their job. My, my job was to say I have the best product in the space. And so I quickly then figured out that I was only going to sell to customers that were in Amazon because Snowflake only existed at the beginning only on one cloud and it was aws. And so I looked, I went on job boards and looked for people that were, you know, advertising for people that were on aws, using a particular product from or a couple different products from aws and then find the head of data, find the VP of engineering and then send them emails. And the what, what I realized is we didn't have like basic enterprise features, so we didn't have things like encryption. Like, hey, we didn't have SOC 2 type 2. These are things that large enterprises care about. Well, guess who doesn't care about that? Ad tech and online gaming. So it's a bunch of log file data. And so I quickly, you know, focus my time and attention on log file data that, that people didn't care about encryption. Now eventually we added the encryption that allowed us to go after, you know, regulated industries and like HIPAA compliance and all this other stuff. But in the earliest days it was just deduction of like, who I could sell to. And that was really it. Obviously the ICP of Snowflake ideal customer profile changed over time. As Denise said, it wasn't going to be ad tech and online gaming forever. But that was like what kept us alive as a company. And one of the beautiful things of that was that one of the ad tech companies that we sold to got bought by a huge perspective, like a Fortune 500 company. And that Fortune 500 company actually then decided to use Snowflake as the back end to their, their marketing cloud. And because they did that, all of a sudden then another, you know, massive Fortune 500 retailer heard that this marketing company was doing that and all of a sudden, boom. You know, we get that customer talking to that customer, talking to that customer, and then all of a sudden you start to see that flywheel of the Fortune 500 Go. And the earliest adopters of the cloud in 2016, 2017, you know, those were the ones that we focused on. If we were going to go to like a bank and convince them that they needed to move their on premise data warehouse into the cloud. And they had not even talked to Amazon. That was like a C account. That was not an account that we'd go after.

That's very interesting. I think, like, banks are some of the big adopters of AI. Like, so they're sort of cutting edge in this way, but like, maybe they were a lot more hesitant in terms of the infrastructure. Interesting. Okay, so talking about, like trying to find your best customers, I mean, you've got to get a lot of signal on, like, who's going to be good at buying, I guess from the marketing side of things. Denise, do you want to talk us through, like, what do you learn about, like, who are potential customers from your marketing efforts?

Well, I mean, we run everything on Snowflake, right? So we run everything, you know, on data here. And that has been also instrumental to our growth as well. It's one of the big reasons why I joined here. Data was always my challenge. I had to go in it, knock on the door, hey, can I get this data set? You get it sort of three weeks later, right? That was the case 10 years ago, still the case for many, many companies today. So in terms of that ideal profile, right, we built those models in Snowflake so we can identify more. It was always about then finding the twins, right, to the early, early successful customers and again start building out engagement within those. So it was an entirely data driven process in terms of how we identify the twins of our, of our ideal customers. And then we started sort of expanded, expanding from there. And often what happens right, in B2B infrastructure is that the sales team have had a set of accounts right, at the previous company. So let's say they were running 10 different accounts, they move to another company and they start selling into those same accounts. But that wasn't relevant to Snowflake in the early days. Right. They came in here, those customers again could have been those customers who says, oh, when are you moving in on prem? So you really had to kind of deliver to the sales team here. Here are in your patch. Here are again that 50 to 100 accounts you should focus on based on data, based on also intense data that we're sort of buying from third party as well. So we really had a formula for how we developed that ICP list for sales. And also usually right in sales you go out and just hire in all territories. There were territories that we just didn't hire in because there were not enough ideal customer profile prospects in those regions. Right. So also sales hiring was really determined on then the volume of ICPs in different territories. Also that that model was an entirely data driven model where again usually, and correct me if I'm wrong here, Chris, but usually as a sales leader goes out and hire maybe previous leaders in different territories and that's how you build. We really built it from an outside in standpoint, really from where are the ideal customer profiles and the volume of those. And that's how we built the sales team as well. Okay.

I mean I love that it's such a data driven approach to kind of building out like, well, I guess to making all your decisions to building things out. And actually just think about marketing. I mean there's a lot of different areas of marketing. Like actually I think one of the things your book is the idea that it's like five different departments kind of glued together. So maybe Denise, do you want to talk us through like the different reasons? So we've covered some of the terms already. Like we talked about account based marketing, field based marketing. Like what are all the different areas of marketing and where is sort of data most amenable to being used?

Again, data is absolutely used everywhere and especially today. Even more every function is running on data. And also there's some recent numbers here across our marketing team shows that 90% of all marketers are using AI on a day to day basis in their work today and they're saving hours on a daily basis using AI. Especially of course from a performance marketing standpoint, the growth marketing teams, it's very, very data driven. Right. We were data driven in the way we identified the right prospects to targets. We were data driven in the way we of course, you know, engaged with those. You know, you know, audiences. It's really data throughout the entire sales process as well.

Wonderful. Yeah. Chris, how about on the sales side, talk me through where you're using data.

As Denise said, like you would say to me is like, no, no sales reps left behind. She would always look at, you know, where leads are coming from, making sure that we could then attribute them to a territory and if someone was starving from a, from a lead perspective, she would, you know, focus there. So I think number one is we'd look at, you know, from a territory perspective where were leads coming from. And those are obviously good metrics to look at as you start to hire. You know, I, I advise companies now that I'm not a, don't, don't work at stuff like anymore. I advise them with the startups and a lot of them, you know, are eager to go, you know, just geographically to different places. And what my comment is, take a look at where the leads are coming from geographically first. Who's raising their hand? If you're an early stage startup, who's, who's raising their hand saying I want to buy. And I think you have to think about that before you say I'm just going to randomly put people in Europe or randomly put people in the Midwest or wherever you want to really focus on that. So I think we focus there. And then on the metric side, you know, there are basic things that I, that have been consistent that Denise knows that I've, I've said from day one is, hey, every sales rep. And I would say this to, even at my, like as I was, you know, towards the end of my tenure of Snowflake in the last year, you know, I would get in front of new hire classes and a lot of these people would come into Snowflake thinking, oh, I'm going to ride this wave of this amazing company because it is a world class company, world class product. And I would say it's the, the misperception of Snowflake is that it's easy to sell because we are, it's a knife fight every single time you're going out and you're competing with some of the biggest companies in the world. You're competing with Amazon, Microsoft, Google and then there's some other very well funded startups like, like Databricks and others that are like you're, you're literally in every deal knife fighting. And so which is still true to this day is go on eight sales calls every single week. If you hold yourself to that metric then, and you have a great product and you tell that story and you understand how to, how to tell the story, then guess what, you'll put yourself in a position to win. But if you're waiting for, you know, marketing to send you a bunch of leads and you're waiting for something to happen, good to happen to you, it won't, I promise you. And so I would tell salespeople, there are people in this room that think it was easy, it's easy to sell Snowflake when it actually is not. But if you go out and tell the story eight times a week, you will hit your number. If you do not do that, you know, flip the coin and you may or may not make it. So I was, you know, kind of very brutally honest with, with people when they came on, and that is kind of what I tell everyone is hold yourself accountable to these metrics. And then like, if you have a good product and you're, and you know how to sell that product, the revenue will come. And that's, that's what I've learned through, through the years of building the team.

I mean, if we fast forward also to we are today from it from a data perspective, the challenge in marketing has always been there's always some market investments that goes to waste, right? Because you're, you're, you're targeting the wrong people. You know, it's not the right time, right? All about that marketing is of course about being the one who's the most relevant, is gonna, of course, you know, win, win the deal, essentially. But the ability today to do predictive forecasting or everything. So the way we can today predict what our pipeline is going to be in different territories is game changing. Often in the B2B world, you end up in a quarter where you realize, oh, okay, there are certain territories that they don't have enough pipeline this quarter in the pipeline, in the quarter, it's very little you can do in marketing, right? The work we do in marketing is setting us up for success in maybe six months from now. But to be able now, today with predictive forecasting of our pipeline, to see, okay, let's say California is not going to make it in six months from now if we continue doing what we're doing today and to fix that problem before you're in the problem, essentially, that has been a game changer. So for us to be able to reallocate resources to where they're going to have the most impact, right, that really makes every single dollar work for us in a whole different way. The way we run our digital spend for Instance we can in real time see which digital channels that are working or not, which messages that are working and just adapt all of that in real time. Where before and still for most companies they will know maybe months or weeks later what worked and didn't. And there's so much money that goes to waste. There's no better time to be in marketing today because of data.

Wonderful.

Yeah. I love the idea that you can in real time make decisions about how to resource. It seems like an incredibly important thing about just making sure that you have operations are running optimally. Okay, so Chris, you mentioned that selling stuff isn't easy since you've both built out departments. I'd love to hear more about like what kind of profile do you hire, what kind of like skills you look for and I guess does it change over time? Because I mean you both took the company from kind of scrappy startup to multibillion dollar company. So yeah, I guess. Who do you look for when you were hiring and did that change over time?

We actually early on found like people that were successful and not successful. At Snowflake we actually went to the next degree of metrics and actually made everyone do an assessment. And so I made all like the best and the worst performing people do assessments. And it was both on intellectual assessment and personality assessment. And it turns out like, okay, we were selling a technical product so you had to have some intelligence, right? Like you didn't have to be a rocket scientist. You know, that's not what I'm looking for. I'm not looking for someone from Stanford or Harvard to you know, jump into sales. But I want some sort of intelligence and so I'm looking for that. And then on the, on the personality traits, I'm looking ironically for early stage startups. I'm looking for people that are, are maybe pessimistic, distrusting of people, maybe even like, or very competitive. So competitive athletes, stuff like that. But, but just are you competitive? And you can get that in these personality assessments. A lot of times they were, they were kind of not like everyone has a perception that salespeople are like these hyper social people. In our earliest days, a lot of our earliest salespeople weren't like trying to be best friends with everyone. They were not like these people that were the lives of the party. They were people that like were very driven, didn't trust what buyers were telling them. They would have to validate it across the organization. And you're looking for that because you know, at our scale when we were small, I couldn't be in every deal. And so I needed the sales team to do their job on qualifying these deals, to do their job on not trusting that, you know, Johnny procurement person is going to actually buy when, when they say they are. Because procurement people are traditionally not. Don't do it that way. They don't buy on our calendar. So we have to, you know, do what, you know, we do in sales to make sure we do that. And so, yeah, there were some commonalities of people that, that I was looking for as we grew. And by the way, they, the people that I hired early on, they had to have experience opening up net new customers, net new prospects or turning prospects into customers in the last 24 months of their job. That was really important because if I was going to hire someone that that was, you know, selling to like two accounts in our earliest days, that would not have been, that wouldn't have worked for Soflake because I, I, you know, that we, we were not, we were doing like $46,000 transaction, $30,000 transactions. A whale hunter is not going to do well in that environment. Over time it changed dramatically because Snowflake has, you know, customers that are, you're signing over $100 million contracts today. And so like that, that now you might have like, you know, three reps on one account and they're selling use cases versus like acquiring a new bunch of new logos. They. There's an acquisition team at Snowflake that's separate, but, but really the profile of, of the human on the account changes wildly as you mature as a company. For sure.

Usually when I ask people about, like, what skills you look for when you're hiring, they're like, oh yeah, I just want someone with good communication skills.

I love that.

He's like, I want someone who's very competitive. Distrust other people. I love that. A refreshing answer. Okay, interesting. Denise, is it the same on the, on the marketing side? What kind of profiles were you looking for?

For the record, Richie, I still give Denise crap about this. She hired one of my best SDRs. She, you know, liked a lot of our salespeople coming into market.

Yeah, she's today. Yeah. This sdr, she actually runs field marketing for the Americas for Snowflake today. I mean, she's in a very, very senior position. And yeah, on the marketing side, I also were looking for people who also could build that relationship with sales as well. There were, there were some people on the team when I joined who just couldn't, couldn't do that to really, I mean, piss people off for Lack of better words here. So you had to be very, extremely collaborative, be again, humble and understand that I don't know everything, you know, you want to be motivated by constantly learning new things. A very curious, you know, mindset. Those are the type of people we're still looking for today. But in the early days, right, you, you're looking for those with a very entrepreneurial mindset as well. Because when you got in here, right, in the early days, again, you got your laptop, you got your 100 account list and yes, there were some training, right, but that's it. You had to go out and very much also figure out yourself. And it's what we're seeing today is that many of those who were with Snowflake in the early days, they're now running their own campus today. They have, they're, they're running startups today. They thrive in that kind of startup environment where you just go out and figure things out on a day to day basis. Right? At Snowflake today there's more, there's more process in place, right? There's a framework for how we do things and people have to kind of fit into that, right? Today you cannot come in and kind of break processes, break our framework. That's going to impact our scale, right? At some point you need that to scale, right? You need to fit into, to a system. The people in the early days are those who, again, they were out breaking the system essentially.

It always amazes me like how startups actually function. Like they're all held together with like string and glue and like there's no processes for anything. So yeah, I certainly say this is a very particular mentality for that.

And in the early days, especially in marketing, right, you need people who can wear many hats, right? They can do help out on the PR side. They can get test customer testimonials, right. They can, you know, also run an event, right? Very like they will go in and figure anything out essentially. And where we are today is that everyone now have landed in a place of specialization. So they're truly, those people are still here today, right? They landed in an area that they're truly passionate about, that they love again. Today you cannot have people running around wearing different hats, right? It would create sort of chaos in the environment we are today. But I think also it's great to see today that there's a great blend of those people who've been here early on. They have great dinner tribal knowledge, right? They bring the culture forward and then we're combining that with people who bring in more large enterprise experience, they know how to build systems, processes that can help the company scale further. So it's so important to have both today and the thing that everyone has in common. It's extreme collaboration, teamwork, respect, you know, for one another. Okay. Yeah.

I do think being able to collaborate with us is incredibly important because like the so few projects where you can do this on your own and be done, it's like you are going to have to collaborate with others. Okay. So I mean you both talked about the importance of data both in marketing and sales. So I'm curious as to what data skills you look for during hiring. Like maybe Denise, you want to go first. Like what data skills do you look for when you're hiring marketers?

We can actually teach people data skills today. And today it's easier, right? It's easier. Those skills are less complex than they used to be 10 years ago or before Snowflake. Snowflake made it easy, right. For organization to work with their data. In the early days we built our own center of data excellence within the department. So I had data scientists on the marketing team in the early days who were really close to the business problem. They completely understood what we're trying to do. Sales had his own team, everyone had its own team. Now actually that is a centralized team center of excellence for the company. When these teams were built, we ended up, they ended up being some duplications of work. Also there are special competencies. A unique area right today in terms of data science and AI. So that fine tunes today a centralized function that work then really closely with those that are very close to the problem that they're trying to solve. But again you need to. We're hiring people that are love data, right. That really lean into the data, want to make data driven decisions. So it was more the mentality of loving data, wanting to work with data rather than have any specific technology skill sets that, that we can easily teach people today.

Okay. I love that idea that yeah, you can teach people on the job because I'm thinking I have to use data, presumably if they're working at Snowflake. But yeah, they just need a little bit and they're willing to learn. Was that the same thing you found on the sales side?

On the sales side there's the sales operations and sales strategy Org and it's very similar to Denise had her marketing operations team, I had my sales operations team. So there's commonalities between each organization. They're looking at data different ways, but they're looking at the Data. And a lot of times they're looking at the shared data, figuring out how we can fix certain things. From a, from a sales leadership perspective, I think especially as you get, as the company gets big, like, like, like, you know, I, I had 3,500 people when I left working for me at Snowflake. And I think that organization, even my job was, was dramatically different. And I think it's, it's almost better to have someone who, who is very operational, very numbers driven because it's no longer like this intimate affair of like I know every single person. I, I'm going on all the sales calls, I know all the customers. It's a numbers game. And I think that's the difference in the job from like early days to where it goes. So I think leadership, sales leadership needs to have an operational mindset. Especially as the company gets big, you know, stuff like, you know, well over $4 billion in revenue. And because of that there's this massive scale and you need people to think in terms of numbers, not just like, you know, I would always think about like each deal and I'd be involved in every deal, very tactical. And then you kind of have to be strategic around what, what, what, what do you see in the data? And so having good operations teams. And I think Snowflake's done a wonderful job of, under Sridhar Ramaswamy's guidance of really having this centralized data function to look across the entire organization to make data, data centric decisions. And I think that I'll give Sridhar a ton of credit on, on helping the company in that, in that frame.

Yeah, I love the idea that data just really helps you scale because you need to like run your operations more efficiently. And you said that. So Sridhar came on the show last year and yeah, it just seem very data driven guy. So.

Oh yeah, that's another thing. And he's great at it. I mean I've never seen anyone better. So he's great at it.

And building a company, it's about making a bunch of decisions every day. What are you going to do, what are you not going to do? And if you do make the wrong decision, it's going to set you back and you might even kind of fail as a company. Having data to make those decisions, that has been absolutely instrumental to our growth and making the right decision.

Absolutely.

Yeah.

I mean such a competitive advantage. Just make less stupid decisions than your competitors and that's going to be a really good way forward. Okay, so we talked a ton about data. Somehow we've Got like three quarters of an hour in, we're barely talking about AI. So I guess one of the big use cases of AI that a lot of people are pushing at moments around AI for automating things. And so you talk about scaling, like have you made use of AI for scaling stuff like.

Yeah, I mean, extensively. And we've used AI for many, many years at Snowflake and across the entire marketing in our process. What's unique today is today we have actually agents up and running now. So we have agents for running all our different campaigns. We have an agent for compete analysis, for instance. So instead of the sales a team having to be trained on every single competitor out there, they now have agents they can ask a question. I have a meeting tomorrow with this company. I believe I'm competing against this company. And these are the different use cases and problems we're going to talk about. And the agents give some, all the talking points back. I mean that's a complete game changer, right, in terms of time saving and equipping them with the right message at the right time. And then of course we use AI for everything for content creation. We, I mean we do a lot of, you know, customer interviews. I mean we've cut the time in terms of developing interview scripts and, and, and editing and all of that, you know, with AI. So it's truly used across every function in marketing today.

Wonderful. I mean I, I do love the idea of having an agent that just prepares all your talking points for you. So you go into a conversation, you're like, oh, I know what I should be talking about. I should probably try that on podcast sometime.

Truly. I mean we're truly at the point now where we are, we're talking to all data. I haven't looked at the dashboards in months now. We have actually a product coming out here in November in ga, Snowflake Intelligence. Right. It really lets you have a conversation with all your enterprise information, your structured data and all your non structured data. So for me, when I usually, you know, some, some queries are more complex, right, that I didn't do myself before. I would have to go to someone, hey, can you look in deeper into this? Right? You always want to dig deeper into a dashboard and get more and more answers in a back. Now I just go into Snowflake Intelligence and I can ask the question, I get all the answers, you know, back so I don't have to go and ask anyone for to go, go deeper into the data. I can go very deep and wide across all the information. At Snowflake.

Wow. I mean, that's a surprisingly radical shift like that. You don't need dashboards as much. I mean, I think pretty much every company like their analytics. It is dashboards. It's hundreds and hundreds of dashboards and that's how a lot of leaders get their information.

So you always work from that dashboard. You always want to. But I want to answer why, why did this happen? Why did we increase sales with 30% right in this region? What happened? Which, which, which products contributed to that? Which sales reps contributed to that? So to be able to ask that question and get the answers back. And again, if you get the answers back, you're going to be able to make the right decision, you know, quicker. And that's what else can I help you to meet, move at, at speed and focus on the right thing.

Okay. Yeah. That's the dream right there is just being able to ask a business question, get a sensible answer back. Just you can make the decision. Wonderful. Chris, do you have anything to add to that?

I think Denise hit it is, you know, Snowflakes, you know, always customer zero for all Snowflakes products. And you know, so, so Snowflake's rolled out Snowflake Intelligence and they call a product they internally call Raven, where it actually, each of the sales leaders can actually ask questions about, for example, what's happening in this customer. So historically, you might have to go to Salesforce, you might have to go to actually Snowflake. Cause Snowflake's a consumption model. Snowflake can actually look at how healthy the customer is. Well, what this Snowflake Intelligence tool does is goes out and says, here's what's happening across all the different sources of data. And then tells you like, hey, this customer's doing this, they're doing that. And then I foresee a day when you're interacting with a tool like Snowflake Intelligence where you're saying, hey, what has changed in my business in the last week, in the last day, in the last month and last quarter and actually giving me questions that I could go ask my sales leadership around what's happening. So I think, you know, I think it's just going to help people be more on top of the data versus like historically old school sales was, well, about your intuition. Like, hey, I intuitively think this is happening based on like what I'm, you know, reading the tea leaves. Well now you don't have to like, it's. That's still going to help people buy from people. But if you can be smarter about those decisions. And AI is helping you understand your data more effectively and you don't have to go to the data team every time to build a dashboard to hope that you're actually looking at the right data. I think that's the neat part is, as Denis said, interacting with your data more frequently and in your own way is something that's changing really in real time right now.

Okay. Yeah. So that cross team communication tools, like someone in sales asking someone from the data team and maybe they're busy at the moment and it goes back and forth, I can certainly see how that slows things down. So, yeah, being able to cut that.

Out of the cycle and operating on the same data. Right. It's so incredibly important to have that unified platform for your company, you know, that is governed, you know, secure, you know, connected. It's going to be really hard for companies who don't have their data in order to do anything with AI. Right. I mean, do companies, companies do understand today that you cannot have an AI strategy without the data strategy? Still, some companies are behind on getting their data AI ready and that's going to. That needs to be priority number one now for every organization.

Yeah, I mean, data quality, it gets glossed over a lot. I think it's like, it's not the fun stuff. So, yeah, that can cause problems later on when you're like trying to build up with AI. I'm curious, what does kind of like, what's your ideal tech stack then for marketers or salespeople then? I know you're going to say Snowflake, but. So it's what, just a database and a load of agents or is there more to it?

I don't think we can predict exactly how things are going to look in a couple of years from now. What we're seeing in the marketing space is that everything needs to be connected from a data standpoint. So all these different applications you need in marketing, you need, of course, you need a data platform. You need to have the casting customer, 360, you know, Vue. You need applications for activating data, you need systems for doing identity management. Right. There's a lot that you need. The key thing is that all these applications needs to be connected from a data standpoint. That's what we're seeing now. A lot of these marketing applications are being built directly on the data. So they're being built, you know, on the Snowflake AI data cloud, you know, for instance, because you don't want to start fragmenting your data again. Right. If you start buying these point solutions again, right? You're creating more data fragment fragmentation and that is going to hinder you really from realizing the value of AI. So the importance is really that all these applications are connected from a data background standpoint.

Historically it was you had this data and send it to the application. That was like how everything has kind of been, oh, I need to put in Salesforce or I need to put it in Workday or whatever it is. I think the inverse will happen over time. And it is happening is where you're bringing the application to the data. And I think that's what you know, Snowflake is really focused on, is allowing, you know, the application to sit on top of the data and that, and having that kind of all that data accessible by any application is incredibly powerful because you can actually like in, you know, earliest days, you could look at a data set that I don't have access to. Like Denise could look at a data set from Marketo and I don't have access to the Marketo data. And I'm going to look at data from the Salesforce perspective. And that was the case. And now like, you know, it's like, hey, we want to look at the same data and you can ask different questions of it, but because we're, you know, Snowflake's doing a wonderful job of bringing the application to the data or AI to the data. Then all of a sudden you can ask the question seven different ways, but it's still looking at the same data. And that's really important.

Yeah, Data is truly the new infrastructure that applications need to be built on.

Yeah, it just seemed like the sort of historic idea that you want the data as close to the application as possible is just cause all these data silos, it just doesn't work anymore. So I do like the idea of just making sure that whatever application you're working with, you're going to have access to like data from different sources because most questions are going to involve data from multiple places. All right, super. So before we finish, I'd love to talk a bit about Snowflake Build. So you've got a whole week of developer events, so yeah, I'd love to hear what it's about and what you're most looking forward to at the event. So this is something datacamp's heavily involved with as well. So yeah, Denise, tell us about it.

Build is actually an entire season of build, you know, activation starting November 4th with our virtual build event. It's. That's also the mid year event where we're making all our media product announcements. So they're going to be a slew of new incredible products coming to market including, you know, partnership announcements, etc. A lot of customers talking as well. It's very much of a peer to peer learning event and then there's going to be in person build events all around the world. Many of them are in India but also in locations like London for instance, in, in early next year. And it's really our event series primarily for developers, but also practitioners, data practitioners as well.

Wonderful. Sounds exciting stuff just to wrap up. I always want more people to follow. So whose work are you most excited about at the moment? Is there anyone I should be looking.

Into in terms of companies? In terms of what?

Who do you read about people in companies who's doing exciting stuff, as Denise.

Said, is, you know, or as I said, it's. I'm on the outside looking in in terms of. I now advise early stage companies and so I'm super excited about what's happening in the next generation of AI companies. I'm advising a company called Factory AI and they're. And they're developing co generation tools and they have really a different way of doing it than the cursors of the world and cognitions of the world. So I'm excited about them. I'm helping a voice company that has a voice AI agent that, that's incredible company called Giga ML. They're super early and they've got these huge customers that they're replacing customer service agents with and there's a real return on investment. So stuff like that. I mean, look, I still love Snowflake. Snowflake has a wonderful story and it'll continue to be a wonderful company for years to come. But yeah, it's fun getting back in the stage and so that's where I'm spending a lot of my energy is with early stage startups.

That's cool. And yeah, certainly more ways of doing better code generation, improving software development, that's a really important thing. Denise, who are you looking at at the moment?

I mean I do think OpenAI is doing tons of exciting, you know, things. We look forward to using many of the products coming out of them. But again there are a range of different, you know, startups as well while, you know, we're looking at. So yeah, wonderful.

All right, yeah, OpenAI obviously been dominating the headlines for a few years with all their progress. So yeah, hoping the innovations keep coming out. All right, wonderful. Thank you Chris and thank you Janice for your time.

Thanks Richie.

Richie. Thanks for having us. Great talking to you, Sam.