Snowflake Summit 2026 | Denise Persson, Snowflake & Kevin Longo, Commercial Fanatics

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More from Snowflake Summit 2026

Denise Persson

CMO

Snowflake

Kevin Longo

VP

Commercial Fanatics

play_circle_outline Real-Time 360° Fan Personalization: Unifying Siloed Data with AI to Transform Engagement

play_circle_outline Sports ecosystem: commerce, merchandise, trading, betting, events data integration

play_circle_outline Dynamic fan need states and real-time marketing activation

play_circle_outline AI use cases: scouting, player development, rehab, custom content

play_circle_outline Powering LA28: Snowflake–Fanatics Data Collaboration and Privacy Governance for Scalable AI Personalization

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Transcript

Denise Persson, Snowflake & Kevin Longo, Commercial Fanatics

Denise Persson

CMO Snowflake

Kevin Longo

VP Commercial Fanatics

In this interview from Snowflake Summit 2026, Denise Persson, chief marketing officer of Snowflake, joins Kevin Longo, vice president of commercial at Fanatics, to talk with theCUBE's Dave Vellante and Rebecca Knight about how data and AI are transforming sports fandom from a one-to-many approach to personalized, real-time fan engagement. With Snowflake named the official data collaboration provider of LA28 and Fanatics joining as a major sponsor, both guests bring a front-row view of the data challenges ahead. Persson underscores that siloed fan touchpoints ... Read more

explore Keep Exploring

How can sports teams leverage data and AI to understand fans and deliver personalized, unified experiences across channels? add

How is the company adapting its fan engagement, commerce, and advertising strategies to account for individualized fan journeys and new technologies like AI? add

How do you keep customer profiles dynamic (rather than static) so they reflect changing interests and recency—using data and AI for personalization? add

Where is AI being adopted and having the greatest impact—both within your organization and across industries like sports? add

How should organizations balance personalization with trust/privacy as technology rapidly advances in the lead-up to major sports events like the LA28 Olympics? add

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Denise Persson, Snowflake & Kevin Longo, Commercial Fanatics

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Rebecca Knight

>> Good afternoon everyone and welcome back to theCube's live coverage of the Snowflake Summit here at the Moscone Center in San Francisco. I'm your host, Rebecca Knight alongside Day Vellante, co-host and co-CEO of theCube. I've been looking forward to this next segment all week. We have Denise Persson. She is the CMO of Snowflake. Welcome back to the show, Denise.

Denise Persson

>> It's great to be back.

Rebecca Knight

>> And welcome back to Kevin Longo, VP commercial at Fanatics.

Kevin Longo

>> Excited to be back. It's been a year since I was on the show. I've missed you guys.

Rebecca Knight

>> Oh, well, we've missed you too. And this time you brought a prop because this is very exciting. Snowflake is the official data collaboration provider of LA28 and Fanatics is also on board as a major sponsor. Both your companies are really driving the future of global sports fandom. As you think about this next era, I'd love both of your thoughts on how data is fundamentally changing, what fans expect from live sporting events. So let's start with you, Denise.

Denise Persson

>> I mean, fans are customers of these sports teams and they're expecting personalized experiences like consumer does for other brands. So they're fans, they're buying merch, they're buying tickets. They are the most important asset of a sports team. So with data, you are able to develop those personalized experiences for your fans and also making your fans feel truly special as well. How about you?

Kevin Longo

>> Yeah, I think it's exciting for me, I get to see it through two perspectives. One, as somebody who works in sports and the other is just being a huge fan myself. I don't think sports fans are waking up saying, "I want more AI in sports." But they do have increasing expectations around personalization, immediacy, relevancy. And a lot of that's coming through AI. If you think through sports, traditionally, it's always been a one to many vehicle. It's a singular broadcast, a singular sponsor sent to a bunch of fans, but fans are not all the same. I think we've always known that, but now with AI and our partnership with Snowflake, we can understand that in real time and sort of act on it. So we've spent the last year really working with marketers of how you evolve the way you think about sports marketing from, "I want to reach a bunch of fans," to, "I want to connect with them."And we think that connection actually comes from a better understanding of the fans, the nuances, the layers of fandom, and that's really what we're working towards.

Dave Vellante

>> And you always approach this as a data problem, right? I mean, you still have... I've been hearing for years, real time signals and behavioral data personalization, but now you're taking it to a new level. How do you see that being uplifted as a result of data and AI?

Denise Persson

>> And today, my sports team, they're meeting their fans through so many different channels. They're all siloed disconnected experiences. They're fans, right? They're expecting that more unified experience. And that is a data problem. All the data is sitting in silos. So the key thing is to unify that data so you can really provide that 360 experience in real time.

Dave Vellante

>> We were talking to SiriusXM. We were using the concept of a power law. And amazing thing about Sirius is they have all the whole power law covered. They've got the big Howard Stern and then all the long tail, they got that covered too. You guys are similar, right? I mean, you've got women's sports taking off in a big way. How are you able to sort of cover such wide amounts of ground?

Kevin Longo

>> Yeah, it's really... I mean, it's both covering it and then doing something about it because it's become really complex. The way we used to think about fans, we'd put them in these buckets and it was neat and tidy. And now we have to think about individuals on a journey and all of their journeys are different. Again, going back to TV, it was this one to many approach and then digital came along and all of a sudden we understand some team affinity, some demo, some behavioral. But what we've built now, to your point, goes way beyond that. So our ecosystem, we're seeing people across commerce, merchandise, obviously, trading, betting and gaming, cards, events, all these things. And it gives us incredible level of depth of just understanding. And so when we think about unleashing that, to your point, there's sort of like two perspectives I have to take. There's the company and there's me as sort of the leader of the advertising team. As a company, when you come buy a Topps card, we have to know, "Are you a lifelong better," or, Do you love collecting? You die for?" Or, "This is your first pack you've ever purchased?" And the kinds of things that we would surface to you to be relevant after that are totally different. On the ad side, I think it's just as interesting if not more, though I am biased. I'll state that bias upfront, but we start to think about previous limitations before sort of AI and everything you guys are unleashing at this show, were... We were constrained by bandwidth or technical capabilities and now we're constrained by our own imagination like, "How far can we push this?: And so we're pushing ourselves to keep exploring these boundaries. I think one interesting example of that is... You think about the Knicks run to the playoffs right now and that city-

Rebecca Knight

>> We're Celtics fans, but so... Okay. It's okay.

Kevin Longo

>> I'm sorry for this example.

Dave Vellante

>> No, it's all good.

Kevin Longo

>> And everybody's buying into it. You see those videos of them in the bar rejoicing at every bucket. You see them parading in the streets and what you're observing is the diehard fan who is going to be there anyways, but the casual fan has been ignited. And how do we create sort of dynamic understanding of audiences that would account for that in real time? So if I'm looking for a Knicks fan, it's just not the die hard who's always there. It's that person who's experiencing this alongside them right now.

Rebecca Knight

>> Because they want different things from the experience.

Kevin Longo

>> So it pushes us to your point, just how do we keep making everything more dynamic in real time?

Dave Vellante

>> And you have to maintain the trust of the core fans, right? And then you're bringing in new fans and you want to have that trusted relationship with them as well. Is that also a data opportunity?

Denise Persson

>> I mean, trust is absolutely essential for all brands and it's so important to be upfront as well with how you're using your fan's data or your customers in your data. If you have to read through five pages on how your data is going to be used, you're not willing to give your data, right? So fans, they want to make sure that if I give you my data, I'm going to get something of value back to me. So those brands that are successful, all those who are very, very sure today here, if you give us your information, this is how it will be used and for nothing else. If you do that, then you're willing to share more. And again, of course, if you share more with the brands, you're going to get the better experience in the back. So it really needs to be value coming from both sides.

Dave Vellante

>> And transparency.

Denise Persson

>> Yeah, transparency. Yes.

Kevin Longo

>> I would just say trust for us is also just everything. You hear us talking about relentlessly in service of the fan. If we violate that trust, there's no amount of personalization that can sort of bring that back. And so we keep exploring like, "How can data drive relevance but not make it feel like surveillance?" It's been really fun thinking through this as we've signed a number of big partnerships. So we started with AT&T, American Express. I think our sponsorship strategy is driven by alphabetical order, so we're kind of chipping through, but the way it manifests itself in each is totally different. So with AT&T, connectivity powers everything, that's their mantra. And as we think today, we're in San Francisco, we could figure out who all the displaced Steelers fans are in San Francisco, create a watch party, bring a legend like Jerome Bettis or Kordell Stewart to come hang out. I think we had to have the insight of who those people were to make a really special experience, but nobody's going to leave that saying, "That was creepy." They'll say, "That was cool. That was community." And that's sort of the responsibility that we have of... We understand a lot, but how we use it is just as important.

Rebecca Knight

>> Well, what's really interesting to me is that you started out by saying... And also, I'm a huge fan myself. So this is personal to you. So when you are the human in the loop who is helping the AI figure out how to splice and dice this data and connect with fans, how much are you using your human judgment as well as getting ideas from the AI about what you can do differently to connect?

Kevin Longo

>> It's something we're wrestling with in real time every day, especially as we just think about AI augmentation to all of our workflows. It's constantly like, "Where is the human checkpoint in this? Where are we reasoning?" And for as far as AI has come and even just the last four months, it's been unbelievable growth. There's still... We have to keep the human checkpoints in just as far as how we're thinking about and really the responsibility that comes with it. So we have not fully shifted over to pure play automation as we have humans, but we can still do infinitely more than we could have done even four months ago.

Dave Vellante

>> Well, and it's not static. This is the thing. I mean, we are huge Celtics fans. I used to be a bigger Celtics fan back in the '80s. I'm old school. I'm kind of a casual golfer, but I went to the Masters this year. I'm now hooked. You put something in front of me, Masters, I'm in merch, I'm in, I'm ready to get out the credit card, always looking for offers. So you've got to be dynamic in that sense. Again, comes back to the data, I presume, but I wonder if you could talk about that a little bit, how you handle that.

Kevin Longo

>> Just the data that we would get from different events?

Dave Vellante

>> Yeah, just keeping things fresh and not a static profile of Dave Vellante, but something that recognizes that his or Rebecca's attitudes change over time and their affinity changes over time.

Rebecca Knight

>> I'm a Spurs fan now.

Kevin Longo

>> And you'll stay that way. Maybe next year's going to be great.

Dave Vellante

>> Well, right, based on... We're down the funnel.

Kevin Longo

>> And I think that's a huge opportunity that comes with AI. So again, as we used to look at these things, we would take signals from your last year, two years, depends on how strong the signal is. Buying a Celtics jersey, pretty strong signal. Looking at it, browsing, maybe put it in your cart, less strong signal. But what we can do now is really become more dynamic in like, "Okay, you just went to the Masters," you're really hyped on that. I've been to the Masters, it's maybe the most special event in sports. So we have to understand that. That has to become a layer in our understanding of you. And then we can use recency to say, "Hey, Masters is the key right now," but he hasn't forgotten about those Celtics and how do we think about him sort of cohesively at that point?

Rebecca Knight

>> Great.

Dave Vellante

>> The ecosystem, I wonder if you could talk about that a little bit. I mean, I know it's a passion of yours, Denise, and you've been sort of watching this grow and grow and cultivating it. Where are you at? Where do you want to go with it?

Denise Persson

>> Well, I mean, the ecosystem is growing every year here. We have about 230 partners here exhibiting and I mean, it takes a village, right? I mean, all of us don't solve every challenge for our customers by ourselves, right? Monday we laid out the vision for the agentic enterprise, right? It takes... You need a context layer, you need a data layer. There are a lot of different technologies that fits within that layer. You have the LLMs, you have all the systems of records, right? It's how we all work together seamlessly to provide a great experience for our customers, provide value for our customers. I think the most partner focus from the companies are the ones that are succeeding today as well. We need to make it easy for our customers to bring all these technologies together.

Dave Vellante

>> We were asking you last year about how you're using AI in your internal marketing. I would imagine that's advanced from where we were a year ago.

Denise Persson

>> Every day.

Dave Vellante

>> I wonder if you could sort of give us the update there.

Denise Persson

>> I think this year has really been moving from... Of course, last year was a lot around experimenting. We're still experimenting it a lot, but this year we're seeing more transformative use cases are really having big impact on our business, both from again, operation efficiencies to really driving revenue as well. And I think the most amazing thing has been that the greatest innovation is really coming from the most unexpected places. This year, we've been very focused on really enabling everyone, a lot of training, education, peer-to-peer learning, of course, making sure everyone has access to the technology and it's really those people are the closest to the problems who really have come up with the greatest, most high impact in innovation for our company.

Rebecca Knight

>> Because they understand the work. They understand.

Denise Persson

>> Exactly. Exactly. Today, right? I don't understand any longer the work of every single individual in our market organization. My job is to really make sure that we enable everyone, that we create the right culture of curiosity that makes this innovation happen.

Dave Vellante

>> Rebecca and I were talking yesterday about how sort of initially it was sort of this top down initiative, you had CEOs like Jamie Dimon, thou shalt become AI savvy. And now we're seeing sort of like the original personal computer, but much more sophisticated where there's a bottoms up personal productivity and that seems to be what's happening in organizations. I think you just described that inside of Snowflake and I wonder if it's true, Kevin, inside your organization.

Kevin Longo

>> Same. I mean, we were early adopters. We've been pushing AI. I think even from my own perspective, it was like AI changes everything, everybody figure it out. And you had this sort of like passive resistance. I was like, "What? Are you firing me? What's going on?" It's like, "No, I want you to be a superhero." And I think where we sort of started to refactor our approach and where we are now is, "Okay, sit with each job type and start to deconstruct what they've been doing and spending their time." And how do you reconstruct that with AI at the center and then what do you unleash them to do with their now 90% of time that they're getting back? It's a journey we're on. I think it's slower than I might have expected, but it's probably a really strong reformulation for us and how we think about it that'll drive more long-term adoption, I think.

Dave Vellante

>> Where's the friction? What's slowing-

Kevin Longo

>> Human resistance, is that fair? I don't know if people... I think there's some concern if it replaces me and that's a valid concern and I get that. I think there's some things that like, "Oh, I enjoy that process even though I know that process is wrought and mundane." And so you find some attachments to things that maybe I didn't anticipate of like, "Oh no, I really appreciate that thing that takes me three hours." And so we're kind of like untangling some of those and then I think the light at the end of the tunnel is when they see what they can re-express their time as. So when they're like, "Okay, I really like that process. I don't have to do it anymore, but I get to spend my time on strategy now and I get to be really thoughtful about how I engage with partners." And then that's when you see like, "Okay, what else can I move to AI?"

Rebecca Knight

>> Right. And what are the things you hate doing and getting AI to take on more of that. That takes real leadership though to push those decisions downward as you said and have the people closest to the work are the ones that are being able to either outsource to AI or figure out what AI could help them do differently. But again, that takes real messaging from the top of, "I want this to happen." Do you have any best practices in terms of how you've gotten your teams to really take on that mindset?

Denise Persson

>> Yeah. I think you need to deliver a vision of an exciting opportunity, what this really means. So the vision we've been driving with the market organization is that we're going to become the most AI assisted B2B market organization in the world. Do you want to be part of this journey, really pioneering what B2B marketing is going to look like moving forward. And also I say that... My message has been, "If you have time savings, if you now have saved 30, 40% of your time, you know what? We're going to invest that time right back into you for you to learn even more, to experiment more." But if you would say like, "Well, you have savings of time and we're eliminating your role" That's not very exciting. We don't want to do that. So instead, we are really taking all that time saving into experimenting more. I think the hard thing for most people is that people have a day-to-day job, and at the same time, they're going to reinvent how they're doing things. So it's really about carving out that time. So for each function on the market organization, we have two to three individual and their job is really only to spend time on this. So essentially, what we call our AI accelerators. So they're finding those opportunities, developing kind of the new AI assisted workflows. They're also responsible for doing weekly enablement of the team as well, sharing best practices. But I think it's very much starting grassroots. Those AI accelerators, they're really within a team of 10 people. It's not a leader of a 100-person team, right? They're really, really close to the problem.

Dave Vellante

>> And I would imagine your experience is similar to ours where that time that you get freed up from doing the mundane. I think people talk about universal basic income and three-day work weeks. We've never been busier. We have so many ideas in our pipeline that are much more interesting than the mundane tasks that we're trying to get to. So I think in our industry, that's certainly the case. I don't know about outside the industry, but I would imagine that that is the case. Do you see that with your customers and your customer's customers?

Denise Persson

>> Yeah, I think it's super important to deliver a message around opportunity and not fear. And also, I mean, some leaders go out and talk about just, "Okay, we have spun up a thousand agents." You need to have the right kind of metrics and measurements around this as well. What are really kind of the business outcomes you're looking for? Are you saving money as a business outcome or are you generating money as a business outcome, but to measure success in terms of number of skills or agents, not the way to do it. And you really truly need to invest time in really giving the right technology for people to work in a way that's well. Just saying, "Oh, everyone is going to use ChatGPT or something like that." Okay, that's great, but it's giving you very kind of superficial impact, right? You need to go deeper than that. We're seeing a lot of companies looking at, "Okay, first of all, those operation efficiencies," but also looking at, "What is the hardest problem we can solve with AI?" It's not something they're going to solve in six months or year. It's going to be a journey, but really starting from that perspective as well is super important.

Dave Vellante

>> And you're not going to solve it with . So tokenmaxxing is maybe not the best idea. You're not going to solve it with that. I don't know how your organization is looking at that, but-

Kevin Longo

>> Yeah, I think the organization which we've spoken a bit about, but I would also just say sports at large. I think you're seeing resistance in some industries to AI, but I think sports is really embracing it and kind of exploding. And so you'll see it from the team perspective as they think about scouting, player development, even sort of rehab and performance. From a fan perspective, you see ESPN can now create a custom version of SportsCenter based on my interest, which is awesome, right? It's awesome. If you watch NFL on Amazon, they have the next gen stats, but for as much data as they have, they always say, "Go for it. I'm fourth down." My son runs around the house saying, "Amazon says go for it," even when we're not watching the NFL. But I even think about... So my experience and I'm a Cowboys fan, I talk about it a lot. In that game this year, it's going to happen when CeeDee Lamb sets the single game record with 337 receiving yards. I think about my own need state in that moment versus three hours prior and how AI is going to allow the sports industry to rally around what I might be feeling and needing in that moment. That's just so dynamically interesting, whereas it would have been a 24, 48 hour cycle in the past.

Rebecca Knight

>> Is that a term of your need state, a customer's need state?

Kevin Longo

>> Yeah. We think about a lot.

Rebecca Knight

>> That's really interesting. So when you think about major sports moments on the horizon like LA28 or others that we know are coming up, how are you conceptualizing balancing that personalization with trust at a time when technology will also have advanced so dramatically by the time LA28 is upon us?

Kevin Longo

>> Do you want to take that first? I feel like you've thought more about LA28 than I have.

Denise Persson

>> Yes, exactly. I mean, I can't even imagine what's going to be possible in two years from now. I mean, everything is moving at the break neck speed, even for Snowflake, we're in the midst of everything, right? It's really hard to predict. But I do think that privacy governance is going to be super important. And if you don't have governance and all those safety parameters in place, you're not going to be able to move fast either. We're seeing that's a challenge for all companies right now is that governance challenges are slowing them down. So you need to solve those things in order to move fast.

Dave Vellante

>> Yeah. In times like this, when it's hard to predict, I go back to Jeff Bezos, which don't worry about what's going to change so much, what's not going to change. And that's a fundamental principle right there.

Denise Persson

>> Technology is moving faster than cultures are evolving within organizations. So from a leadership standpoint, I think a lot of efforts are going to go into really evolving culture. Do we have the right culture? Are we adaptable enough as an organization to harness these opportunities coming our way? It's going to be a big, big test for leadership to go through these transformations.

Rebecca Knight

>> I have faith.

Denise Persson

>> Yeah, me too.Yes, me too.

Rebecca Knight

>> And we have next year for the Celtics.

Kevin Longo

>> That's right. Yes. There's always next year.

Rebecca Knight

>> There's always next year. Well, Denise and Kevin, thank you both so much. Really fun conversation. And I love the ball. I mean, it's just the best. I'm Rebecca Knight with Dave Vellante, stay tuned for more of theCube's live coverage at the Snowflake Summit. You're watching theCube, the leader in enterprise tech news and analysis.