Snowflake Data Cloud Summit 2024 | Denise Persson | Snowflake & Ravi Kandikonda | Zillow

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Denise Persson

CMO

Snowflake

Ravi Kandikonda

SVP, Marketing

Zillow

Four insights you might have missed from theCUBE’s coverage of Snowflake’s Data Cloud Summit

The Snowflake Data Cloud Summit in San Francisco last week offered an in-depth look at how artificial intelligence, data and open source are continuing to reshape the enterprise world.As Snowflake Inc. moves from its Data Cloud into the AI Data Cloud, the company is seeking to write its next chapter under the leadership of new CEO Sridhar Ramaswamy, supporting an AI-driven environment where customers are demanding data simplicity and value for the business

Zillow’s AI revolution: How Snowflake’s Data Cloud is transforming real estate

Snowflake Inc. built its AI Data Cloud as a single platform to bring data and workloads together.The ability to integrate internal and external data sources is proving to be attractive for a number of businesses, including Zillow Inc., the online real estate marketplace.Zillow’s Ravi Kandikonda and Snowflake’s Denise Persson talk with theCUBE about the AI evolution.“It’s not only about using your own data,” said Denise Persson (pictured, right), chief marketing officer of Snowflake. “You want to be able to use data from data providers such as Zillow. You might want to combine that with weather data … to build an application

play_circle_outline Discussion about Zillow and its impact on the real estate market

play_circle_outline Use cases of Snowflake for data aggregation, security, and privacy

play_circle_outline The challenge of identifying customer behavior and personalizing offers in real time

play_circle_outline The role of AI in marketing and its impact on customer expectations

Info

Denise Persson | Snowflake & Ravi Kandikonda | Zillow

Denise Persson

CMO Snowflake

Ravi Kandikonda

SVP, Marketing Zillow

search

Rebecca Knight

>> Good afternoon everyone, and welcome back to TheCUBE's live coverage of the Snowflake Data Cloud Summit here in San Francisco. I'm your host, Rebecca Knight, sitting alongside my co-host and co-analyst, Dave Vellante. Dave, I don't know about you, but I spend a lot of time on Zillow, maybe a little too much time.

>> Okay, so a long time ago, Rich Barton's brother-in-law's sister, really good friend of mine, I walked into a house, dropping off her kid for a baseball practice. She said, "Check this out, zillow.com." And I was like, "Wow, this is going to change the world."

Rebecca Knight

>> They say that real estate is porn for middle-aged people, so I'm not going to add that, but our next guests are... I'd like to introduce our next guests. We have Denise Persson. She is the CMO of Snowflake. Welcome, Denise. And Ravi Kandikonda, he is the SVP of marketing at Zillow. Welcome, Ravi.

Ravi Kandikonda

>> Thank you. Thank you for having me.

Rebecca Knight

>> So I'm actually going to start with you, Ravi. And tell us a little bit about how Zillow uses Snowflake for marketing.

Ravi Kandikonda

>> Yeah. So we are Snowflake platform users for a while now, and there are three main use cases that we use it for. Number one is data aggregation. So obviously if you can think about the 212 monthly unique users that come onto our site on mobile web, on desktop, on app, they do create and generate a significant amount of data, and aggregating all of that and putting it in a secure place is of paramount importance to us. So aggregation, then obviously the security and privacy aspects of it. But more importantly also, how do we actually explain to our internal stakeholders the value of this data and how we are actually using all of this. So those are the three use cases that we use Snowflake on our Zillow platforms.

>> Yes. Your data is so good. I presume you have a hand in that I can nail the market when I look at the Zillow data. And so I'm curious. Zillow started way before Snowflake, so that must have been sort of a big transformation internally. But from your standpoint, Denise, you've done a couple of things since last year. It's the AI data cloud now. Nice touch. And so how do you think about customers like Zillow from the standpoint of assisting with their marketing? What do you guys bring to the table? What's that conversation like?

Denise Persson

>> Yeah, of course, again, Zillow, the value of their data is incredible, and there's so many other organization who wants to be able to use some of that data. And as Ravi said, it starts with just aggregating all that data, getting that data into one place. And also then with the Snowflake marketplace, they can monetize and share that data with others who will use it. It could be companies in retail who want to understand movement in the market from a housing standpoint. And of course Zillow, that data is just gold that they have.

>> Yeah. And so could you talk to monetization? I'm really interested in... We've had several conversations, and we've got some more coming today specifically within the marketplace.

Ravi Kandikonda

>> Yeah. Sure. So going back to Denise's point, if you think about the use cases of sharing the data across internal stakeholders, but then also the external and getting to know the customers really well, because we do know customers when they are on our site, their preferences. What are they looking for? What is it that actually gets them to make the decision from dreaming to eventually deciding. You know what, I'm going to potentially make a move and get there. That transition involves understanding those nuances when the customer is about to make that shift. And once we identify that, there are external aspects that we actually need to understand well of because we know more about them on what they do on our platforms. We also need to equally know what they do outside of our platforms. And that's where the sharing and combination of assets to really get clear on the customer preferences and what they're actually going to be interested in, and then delivering on that promise, when they're on our platform or when they're actually outside on the platform, being consistent. And that is the great use case that we go through.

>> Denise, how has new AI changed the game from a marketing standpoint? We've all done machine learning for years, but the AI heard around the world changed things.

Denise Persson

>> Yeah. That's what we talk about this week, where there are big differences between consumer expectation when it comes to AI and enterprise expectation, right? Snowflake is not about booking your next travel or creating poems, right? We're really about AI for the enterprise. And what companies will be looking for is really bringing AI to their data. They want to be able to use their own curated data to build AI applications. We saw a few examples on stage here today. We brought up someone from the audience who've used Snowflake 10 times before, and she was able to create a Copilot using Snowflake. So for us, it's about making it extremely easy to use so we can enable everyone in the organization with the power of AU. It was also a lot of the imagination in terms of what you want to do. Doesn't sit on the technical side, right? They sit out on the business side, right? They get the ideas about what they want to do, and we want to enable them to build these AI applications on top of their own data.

Rebecca Knight

>> Exactly, because the customer expectations are then the employees who are... They're used to writing their birthday poems and booking their vacation using AI. And so when they come to work and they say, "Wait, why can't we do this? This should be easy, right?" So it's building in those expectations too.

Denise Persson

>> Yeah, it comes back to, remember back in the days, bring your own device, right? It's the same thing, that they have the expectations from outside work. Now they expect the same thing inside work. But also in the enterprise, it has to be governed and it has to be secure. Those are, of course, two critical components, and that's what we help our customers with. But again, it's not only about then using your own data. You want to be able to use data from data providers such as Zillow, for instance. You might want to combine that with weather data, for instance, to build an application. So that's also one of the core value propositions of the Snowflake AI data cloud, is... Again, it's not just about your own data, but also being able to use external data sources as well.

Ravi Kandikonda

>> But I'll actually add more to that point. So if you think about our evolution as a brand, as a company, we used to be a search platform. You could go on zillow.com and you can search. We're now more than search. We want our customers to know that they can actually come onto the site and actually find a loan, be able to find an agent and transact. Now if you think about that internal transition of an employee who could just do the digital platform work to actually also enable our frontline, it involves quite a lot of systems, operations, connecting all of that and making sure the data flows seamlessly across these different platforms. All of that with AI, I think is going to get easier, and hopefully more effective, especially when we are sending messages to customers on when they're on our site and our employees saying the same thing when they meet them in person. That's actually a pretty cool thing, and that transition is possible through some of these technologies.

>> How does it work in a marketing workflow and marketing campaign? What role does the data play, and Snowflake in terms of going from concept to actual program?

Ravi Kandikonda

>> Yeah. So again, I'll start from the top, 212 million unique users on a monthly basis. Well, this year, we are projecting about 4 million homes being transacted. So you think about the drop off, 200 million monthly unique users to 4 million transactions in a year. So think about the data challenge there. How do you parse out customers who are dreaming? And then how do you identify customers who are actually ready to take the leap and start the process of transaction? And if you think about that as finding a needle in the stack problem and all the activities, the first aspect of the whole Snowflake and our CDP platform, Simon Data, is to, number one, pay close attention to customer behavior and identify those signals. And this is where some of the AI and machine learning tools become important. How do they pick up on those subtle changes in customer behavior that indicate, oh, that someone is moving from being in a dreaming state to a transaction state? And the moment you pick on that signal, the entire process flow, to your point, has to catch up and go, if I'm talking to them on paid channels, our own channels, or when our frontline is intersecting or humans are intersecting with the customer, it needs to be consistent. And that to me is the platform is the common thread that essentially keeps the entirety of the equation in balance.

Rebecca Knight

>> That is fascinating, and I'm also thinking about the background of what's happening right now in the housing market too. So there's the signals of the individual, but the individuals paying attention to interest rates and inventory and all of these things too. So Denise, how are you working with other marketers to collaborate and figure out what exactly needs to be done here with the technology?

Denise Persson

>> The starting point for most marketing department is to get to that customer 360 that we just talked about, right? That's the ultimate dream you're looking for. We marketers are used to having so many different data silos. During the past 10 years, there's been all these new digital channels, right? We're using new digital channels every day, and that creates a data silo in itself. So we don't get the complete overview of the customers in a journey. So you need to be able to aggregate that data, like we talked about, into one place. And when you have that, you'll be able to really see that entire journey. Like Rob talked about, they know when someone is starting to look for a new home, right? They can see from where they start looking for a new home until they're actually buying a new home. They can see that entire journey. In the past, when you didn't have all your data in one place, you couldn't see that. You couldn't stitch all the different channels together. It's actually one of the reasons why I came to Snowflake in the first place. I used to be in that world where I had to knock on the door of IT, "Please, please, can I have this data set?" And maybe I had to go to the finance department asking for another data set, and then I had to try to stitch it together on the marketing side. I got the data at the end, but it was too late. In this world we're in now as well, it's real time, right? You want to be able to get real time data and do that personalization for the customer in real time. That's the expectation that consumer has as well. The expectation, consumer expects you to know more about them and personalize offers for them.

Ravi Kandikonda

>> That's a great point. Sorry, I have one point I want to make.

>> Yeah, please.

Ravi Kandikonda

>> Going back to the interest rates and then the personalization aspect, if you think about a customer who's first time home buyer coming into this market where inventories at historical low levels and trying to understand what information they get from what place, we as a company, as a brand, need to deliver on the promise of helping them versus a customer who probably is more comfortable and confident about the process, then it's a whole different work stream. So internally, our teams need to be able to share that intel and coordinate what actions we take. And that's the real benefit that all of this brings.

>> And your point about, Denise, having the data in one place is critical, but also you've got to harmonize the data in a way so that it means the same thing. You've got geolocation data, you've got pricing data, you've got history, you've got tax data, and you're presenting in a way that's coherent. Where's that magic come from? Is that a combination of Snowflake and Zillow? Is that IP that you guys had to do yourselves?

Ravi Kandikonda

>> It's a combination of both. Because if you think about the first party and then the second party intel that we have, geotargeting is one, but also the customer actions that they take on our site. So I might be living in Seattle, but I might be interested in a home somewhere in Philly. So if I'm clicking on and looking at that, I need to be able to parse out that information and give you a different set of curated content that actually works with you, right? So that's part one. And then being able to measure and attribute, a specific action, that outcome that comes out of that, the whole process is another whole equation. And marketers, now more than ever, have to prove the incremental value of the investment that goes into this and the real investment mix that you're optimizing at all the point in time. So to me, it's a combination of Zillow data. We have a CDP, Simon Data, that sits on top of the Snowflake instance and how all of the data sharing happens both internally and externally.

>> I'm just going through all the actions when I buy a property of them thinking, what signals should I give?

Rebecca Knight

>> I know. Right. Exactly. Exactly. Well-

Denise Persson

>> Yeah. Remember as well, this is about all your information is, of course, entirely anonymous, is kept safe, your identity, all those sort of things, right? So it's... Yeah.

>> Yeah, claim this property.

Denise Persson

>> Your information stays with

>> You got to know your customer.

Denise Persson

>> Yeah. Yeah. Yes.

Rebecca Knight

>> But Ravi brought up a really interesting point about what marketers now have to prove to the rest of their colleagues and their stakeholders. Last night on the main stage, you asked the CDOs you had, how their job has really changed over the last 10 years. I'm interested to hear your perspective about how the role of the CMO has changed.

Denise Persson

>> I must say I've been doing this for 30 years, and this is the best time ever to be in marketing, because today, we can show the impact of our marketing efforts. I remember 30 years ago when I had leads coming in through the fax, or I had to go to the post office and pick up the coupons coming in, and then enter them into an Excel spreadsheet and put that on a floppy disk and go over to the sales department, and then I knew nothing. But today, when you can track everything, you can see the direct impact of your marketing investments on the end result, it's absolutely incredible. Things are moving fast. It's a little bit hard to keep up. You need to really build the data culture on your marketing team. You need to really be on top of things that are happening. That's maybe the hard part because things are moving faster than ever, but it's never been a better time to be in marketing. And also not only for the marketer, but also for the consumer as well. Because on the consumer side, you've been overwhelmed by marketing information that is completely irrelevant, right? Also as a consumer, now, well, you're going to get offers that are really relevant to you, right? It's going to be much, much better place to be and time for the consumer as well.

>> It's true. You're not annoyed when you get an offer that is appealing and resonates with you at all. You think, oh wow, great. I going to go-

Ravi Kandikonda

>> ...

>> down this rabbit hole.

Denise Persson

>> Exactly. Yeah. Yes.

>> And so to your point about the pace, and it is a little confusing sometimes, but you're making bets and you're betting on data. That's very clear, both of you.

Denise Persson

>> Yeah.

Ravi Kandikonda

>> Marketing, to Denise's point, it's the best time to be a marketer, and marketing... The definition of marketing has evolved. I think of it as equal parts creative, equal parts technology, equal parts data, and equal parts execution and operations. And that is an amazing training ground for all the things that we can do for customer and internal stakeholders.

>> Well, you've both built a great product, so thank you.

Rebecca Knight

>> Indeed. Ravi and Denise, thank you both so much for coming on The CUBE.

>> Thank you for having me.

Denise Persson

>> Thank you.

Rebecca Knight

>> I'm Rebecca Knight for Dave Vellante. Stay tuned for more of TheCUBE's live coverage of the Snowflake Data Cloud Summit. You're watching TheCUBE, the leader in enterprise tech news and analysis.

Denise Persson | Snowflake & Ravi Kandikonda | Zillow

search

Rebecca Knight

>> Good afternoon everyone, and welcome back to TheCUBE's live coverage of the Snowflake Data Cloud Summit here in San Francisco. I'm your host, Rebecca Knight, sitting alongside my co-host and co-analyst, Dave Vellante. Dave, I don't know about you, but I spend a lot of time on Zillow, maybe a little too much time.

>> Okay, so a long time ago, Rich Barton's brother-in-law's sister, really good friend of mine, I walked into a house, dropping off her kid for a baseball practice. She said, "Check this out, zillow.com." And I was like, "Wow, this is going to change the world."

Rebecca Knight

>> They say that real estate is porn for middle-aged people, so I'm not going to add that, but our next guests are... I'd like to introduce our next guests. We have Denise Persson. She is the CMO of Snowflake. Welcome, Denise. And Ravi Kandikonda, he is the SVP of marketing at Zillow. Welcome, Ravi.

Ravi Kandikonda

>> Thank you. Thank you for having me.

Rebecca Knight

>> So I'm actually going to start with you, Ravi. And tell us a little bit about how Zillow uses Snowflake for marketing.

Ravi Kandikonda

>> Yeah. So we are Snowflake platform users for a while now, and there are three main use cases that we use it for. Number one is data aggregation. So obviously if you can think about the 212 monthly unique users that come onto our site on mobile web, on desktop, on app, they do create and generate a significant amount of data, and aggregating all of that and putting it in a secure place is of paramount importance to us. So aggregation, then obviously the security and privacy aspects of it. But more importantly also, how do we actually explain to our internal stakeholders the value of this data and how we are actually using all of this. So those are the three use cases that we use Snowflake on our Zillow platforms.

>> Yes. Your data is so good. I presume you have a hand in that I can nail the market when I look at the Zillow data. And so I'm curious. Zillow started way before Snowflake, so that must have been sort of a big transformation internally. But from your standpoint, Denise, you've done a couple of things since last year. It's the AI data cloud now. Nice touch. And so how do you think about customers like Zillow from the standpoint of assisting with their marketing? What do you guys bring to the table? What's that conversation like?

Denise Persson

>> Yeah, of course, again, Zillow, the value of their data is incredible, and there's so many other organization who wants to be able to use some of that data. And as Ravi said, it starts with just aggregating all that data, getting that data into one place. And also then with the Snowflake marketplace, they can monetize and share that data with others who will use it. It could be companies in retail who want to understand movement in the market from a housing standpoint. And of course Zillow, that data is just gold that they have.

>> Yeah. And so could you talk to monetization? I'm really interested in... We've had several conversations, and we've got some more coming today specifically within the marketplace.

Ravi Kandikonda

>> Yeah. Sure. So going back to Denise's point, if you think about the use cases of sharing the data across internal stakeholders, but then also the external and getting to know the customers really well, because we do know customers when they are on our site, their preferences. What are they looking for? What is it that actually gets them to make the decision from dreaming to eventually deciding. You know what, I'm going to potentially make a move and get there. That transition involves understanding those nuances when the customer is about to make that shift. And once we identify that, there are external aspects that we actually need to understand well of because we know more about them on what they do on our platforms. We also need to equally know what they do outside of our platforms. And that's where the sharing and combination of assets to really get clear on the customer preferences and what they're actually going to be interested in, and then delivering on that promise, when they're on our platform or when they're actually outside on the platform, being consistent. And that is the great use case that we go through.

>> Denise, how has new AI changed the game from a marketing standpoint? We've all done machine learning for years, but the AI heard around the world changed things.

Denise Persson

>> Yeah. That's what we talk about this week, where there are big differences between consumer expectation when it comes to AI and enterprise expectation, right? Snowflake is not about booking your next travel or creating poems, right? We're really about AI for the enterprise. And what companies will be looking for is really bringing AI to their data. They want to be able to use their own curated data to build AI applications. We saw a few examples on stage here today. We brought up someone from the audience who've used Snowflake 10 times before, and she was able to create a Copilot using Snowflake. So for us, it's about making it extremely easy to use so we can enable everyone in the organization with the power of AU. It was also a lot of the imagination in terms of what you want to do. Doesn't sit on the technical side, right? They sit out on the business side, right? They get the ideas about what they want to do, and we want to enable them to build these AI applications on top of their own data.

Rebecca Knight

>> Exactly, because the customer expectations are then the employees who are... They're used to writing their birthday poems and booking their vacation using AI. And so when they come to work and they say, "Wait, why can't we do this? This should be easy, right?" So it's building in those expectations too.

Denise Persson

>> Yeah, it comes back to, remember back in the days, bring your own device, right? It's the same thing, that they have the expectations from outside work. Now they expect the same thing inside work. But also in the enterprise, it has to be governed and it has to be secure. Those are, of course, two critical components, and that's what we help our customers with. But again, it's not only about then using your own data. You want to be able to use data from data providers such as Zillow, for instance. You might want to combine that with weather data, for instance, to build an application. So that's also one of the core value propositions of the Snowflake AI data cloud, is... Again, it's not just about your own data, but also being able to use external data sources as well.

Ravi Kandikonda

>> But I'll actually add more to that point. So if you think about our evolution as a brand, as a company, we used to be a search platform. You could go on zillow.com and you can search. We're now more than search. We want our customers to know that they can actually come onto the site and actually find a loan, be able to find an agent and transact. Now if you think about that internal transition of an employee who could just do the digital platform work to actually also enable our frontline, it involves quite a lot of systems, operations, connecting all of that and making sure the data flows seamlessly across these different platforms. All of that with AI, I think is going to get easier, and hopefully more effective, especially when we are sending messages to customers on when they're on our site and our employees saying the same thing when they meet them in person. That's actually a pretty cool thing, and that transition is possible through some of these technologies.

>> How does it work in a marketing workflow and marketing campaign? What role does the data play, and Snowflake in terms of going from concept to actual program?

Ravi Kandikonda

>> Yeah. So again, I'll start from the top, 212 million unique users on a monthly basis. Well, this year, we are projecting about 4 million homes being transacted. So you think about the drop off, 200 million monthly unique users to 4 million transactions in a year. So think about the data challenge there. How do you parse out customers who are dreaming? And then how do you identify customers who are actually ready to take the leap and start the process of transaction? And if you think about that as finding a needle in the stack problem and all the activities, the first aspect of the whole Snowflake and our CDP platform, Simon Data, is to, number one, pay close attention to customer behavior and identify those signals. And this is where some of the AI and machine learning tools become important. How do they pick up on those subtle changes in customer behavior that indicate, oh, that someone is moving from being in a dreaming state to a transaction state? And the moment you pick on that signal, the entire process flow, to your point, has to catch up and go, if I'm talking to them on paid channels, our own channels, or when our frontline is intersecting or humans are intersecting with the customer, it needs to be consistent. And that to me is the platform is the common thread that essentially keeps the entirety of the equation in balance.

Rebecca Knight

>> That is fascinating, and I'm also thinking about the background of what's happening right now in the housing market too. So there's the signals of the individual, but the individuals paying attention to interest rates and inventory and all of these things too. So Denise, how are you working with other marketers to collaborate and figure out what exactly needs to be done here with the technology?

Denise Persson

>> The starting point for most marketing department is to get to that customer 360 that we just talked about, right? That's the ultimate dream you're looking for. We marketers are used to having so many different data silos. During the past 10 years, there's been all these new digital channels, right? We're using new digital channels every day, and that creates a data silo in itself. So we don't get the complete overview of the customers in a journey. So you need to be able to aggregate that data, like we talked about, into one place. And when you have that, you'll be able to really see that entire journey. Like Rob talked about, they know when someone is starting to look for a new home, right? They can see from where they start looking for a new home until they're actually buying a new home. They can see that entire journey. In the past, when you didn't have all your data in one place, you couldn't see that. You couldn't stitch all the different channels together. It's actually one of the reasons why I came to Snowflake in the first place. I used to be in that world where I had to knock on the door of IT, "Please, please, can I have this data set?" And maybe I had to go to the finance department asking for another data set, and then I had to try to stitch it together on the marketing side. I got the data at the end, but it was too late. In this world we're in now as well, it's real time, right? You want to be able to get real time data and do that personalization for the customer in real time. That's the expectation that consumer has as well. The expectation, consumer expects you to know more about them and personalize offers for them.

Ravi Kandikonda

>> That's a great point. Sorry, I have one point I want to make.

>> Yeah, please.

Ravi Kandikonda

>> Going back to the interest rates and then the personalization aspect, if you think about a customer who's first time home buyer coming into this market where inventories at historical low levels and trying to understand what information they get from what place, we as a company, as a brand, need to deliver on the promise of helping them versus a customer who probably is more comfortable and confident about the process, then it's a whole different work stream. So internally, our teams need to be able to share that intel and coordinate what actions we take. And that's the real benefit that all of this brings.

>> And your point about, Denise, having the data in one place is critical, but also you've got to harmonize the data in a way so that it means the same thing. You've got geolocation data, you've got pricing data, you've got history, you've got tax data, and you're presenting in a way that's coherent. Where's that magic come from? Is that a combination of Snowflake and Zillow? Is that IP that you guys had to do yourselves?

Ravi Kandikonda

>> It's a combination of both. Because if you think about the first party and then the second party intel that we have, geotargeting is one, but also the customer actions that they take on our site. So I might be living in Seattle, but I might be interested in a home somewhere in Philly. So if I'm clicking on and looking at that, I need to be able to parse out that information and give you a different set of curated content that actually works with you, right? So that's part one. And then being able to measure and attribute, a specific action, that outcome that comes out of that, the whole process is another whole equation. And marketers, now more than ever, have to prove the incremental value of the investment that goes into this and the real investment mix that you're optimizing at all the point in time. So to me, it's a combination of Zillow data. We have a CDP, Simon Data, that sits on top of the Snowflake instance and how all of the data sharing happens both internally and externally.

>> I'm just going through all the actions when I buy a property of them thinking, what signals should I give?

Rebecca Knight

>> I know. Right. Exactly. Exactly. Well-

Denise Persson

>> Yeah. Remember as well, this is about all your information is, of course, entirely anonymous, is kept safe, your identity, all those sort of things, right? So it's... Yeah.

>> Yeah, claim this property.

Denise Persson

>> Your information stays with

>> You got to know your customer.

Denise Persson

>> Yeah. Yeah. Yes.

Rebecca Knight

>> But Ravi brought up a really interesting point about what marketers now have to prove to the rest of their colleagues and their stakeholders. Last night on the main stage, you asked the CDOs you had, how their job has really changed over the last 10 years. I'm interested to hear your perspective about how the role of the CMO has changed.

Denise Persson

>> I must say I've been doing this for 30 years, and this is the best time ever to be in marketing, because today, we can show the impact of our marketing efforts. I remember 30 years ago when I had leads coming in through the fax, or I had to go to the post office and pick up the coupons coming in, and then enter them into an Excel spreadsheet and put that on a floppy disk and go over to the sales department, and then I knew nothing. But today, when you can track everything, you can see the direct impact of your marketing investments on the end result, it's absolutely incredible. Things are moving fast. It's a little bit hard to keep up. You need to really build the data culture on your marketing team. You need to really be on top of things that are happening. That's maybe the hard part because things are moving faster than ever, but it's never been a better time to be in marketing. And also not only for the marketer, but also for the consumer as well. Because on the consumer side, you've been overwhelmed by marketing information that is completely irrelevant, right? Also as a consumer, now, well, you're going to get offers that are really relevant to you, right? It's going to be much, much better place to be and time for the consumer as well.

>> It's true. You're not annoyed when you get an offer that is appealing and resonates with you at all. You think, oh wow, great. I going to go-

Ravi Kandikonda

>> ...

>> down this rabbit hole.

Denise Persson

>> Exactly. Yeah. Yes.

>> And so to your point about the pace, and it is a little confusing sometimes, but you're making bets and you're betting on data. That's very clear, both of you.

Denise Persson

>> Yeah.

Ravi Kandikonda

>> Marketing, to Denise's point, it's the best time to be a marketer, and marketing... The definition of marketing has evolved. I think of it as equal parts creative, equal parts technology, equal parts data, and equal parts execution and operations. And that is an amazing training ground for all the things that we can do for customer and internal stakeholders.

>> Well, you've both built a great product, so thank you.

Rebecca Knight

>> Indeed. Ravi and Denise, thank you both so much for coming on The CUBE.

>> Thank you for having me.

Denise Persson

>> Thank you.

Rebecca Knight

>> I'm Rebecca Knight for Dave Vellante. Stay tuned for more of TheCUBE's live coverage of the Snowflake Data Cloud Summit. You're watching TheCUBE, the leader in enterprise tech news and analysis.