 Hey, welcome back everybody. Jeff Frick here with theCUBE. If you can't tell over my shoulder, we are at Oracle Park. It's a glorious day. The marine layer is burning off and it is really spectacular. We're happy to be here. Haven't been here since, I think 2014. It's an interesting event called Sports Tech Tokyo World Demo Day. About 25 technology companies in the sports area are giving demos all day today. It's a huge program and we're excited to have our next guest coming from the analytics side. She says in AXOE, global data strategy and analytics for AXS. Welcome. Thank you. Absolutely, so global data strategy. Everything's all about data. Correct. So if somebody's really happy to have you on board, what are you working on? What's top of mind? Sure, so it's going to sound cheesy, but data is the power of the world. It's going to empower people making better decisions. So that's kind of my role is at AXS. So AXS is a ticketing platform for live entertainment events. We operate in the US, Europe, as well as in Japan. And if you think about it, when a consumer comes to your website, that's the first touch point that you have. Whether they buy the ticket or don't, whether they buy or sell and transfer the ticket or they attend the event, all those are various touch points that we are collecting so that we can inform our clients to make better decisions with data. Whether it's pricing decisions or marketing decisions or scanning an event which gates will be more busier than others. So that's kind of what my team works on. Excellent. So let's jump into a little bit on the dynamic pricing because we've seen dynamic pricing and you said you were in the airline industry. We've seen it in the hotel industry. My father-in-law talks about when he was doing dynamic pricing as a young kid, just make it a call when somebody came through the door at 11 o'clock, what's my marginal cost to put somebody in that room? Or not. But it's really slow to get beyond kind of the travel industry for other people to kind of get on board the dynamic pricing. We saw the giants here, actually a couple of years ago we came by and they were starting to do dynamic pricing, a Friday night Dodger game compared to a Tuesday-day Milwaukee game, very, very different. So what are some of the factors going in? What is some of the resistance that had to be overcome for people to actually accept it? It's okay to charge more for a Friday night Dodger game than a Tuesday afternoon Milwaukee game. Yep. So my background, starting the airlines, which is where dynamic pricing revenue management started specifically at American Airlines. And if you think about it, there are a lot of similarities between airlines and live entertainment. It's a fixed cost. You have to, flight has to go or the game has to be played no matter how many people are there. So you really have a limited time to really maximize your revenue and you kind of have a product that the demand level is different by day, whether it's a Tuesday game or a Friday game. It's really something you have to study the sort of the behavior from the consumers when they buy their tickets, what are the factors they put into play to make that decision. And in that, Mixed San Francisco Giants was one of the first teams that actually incorporated dynamic pricing about 10 years ago, that slowly. The challenges with it is we are not as the consumer, not as trained to know that the price may change. Hotels, airlines been doing it for years and years. And for them also it didn't start from like doing all the flights in day one. So it really needs to be a phase approach. It needs to be a lot of education for the public and to think about the right way to think about it is, you wanna incentivize people to buy early and you wanna make sure they are the ones that are getting the best price and not necessarily the people that are buying last minutes. If you're buying last minute, you must accept that it may be the availability that you're not looking for or the price not looking for. But I will say though that plans change, people decide to not attend the game. There is always that potential for finding other seats for that similar game, but really if you have your plans, it's better to buy early and that's kind of what the industries needs to be trained on more and more. Did, was there more opportunity in getting additional value out of that high demand game or was the bigger opportunity in getting kind of lowering the prices on the less desirable games and getting kind of marginal revenue on that side? Where was the easy money made on dynamic pricing? I mean the immediate impact is from the high value seats for the high value games because that's really is your premium product at that point. But in the meantime, there's always a low number of seats that you have in your premium area and if you found the right price and if you started early and really the goal is to sell all the seats and to fill all the seats. Also just selling the seats is not, doesn't get you far enough. You wanna make sure people actually come to the game and they're the people that are gonna attend the game. So if you kind of, the lower level has many more seats so it really has to be both ways. It can't be in one area, you do dynamic pricing and you don't do it, it's just all about training the public and the consumers. Now the other interesting you said in your kind of intro was keeping track of what are the busiest turn styles and where are people coming in and the flow within the game. What are some of the analytics that you do there and how are teams using that information to provide a better fan experience? Yeah, so we have a scan data and we actually have it real time. So we are able to provide the teams. We have Kinesis Streams not to go too technical to kind of empower them to do their game operations in a certain way. So example would be you could have studied the past games and understand where people came from typically for a Friday game versus a Tuesday game, your crowd will look different, right? The Friday game may be more the families or Saturday, Sunday, but Tuesday may be more corporate world, right? So understanding their patterns, but also then having that data accessible to you to real time. So that way you're able to see how many people are coming in from this one gate to other. You can mandate the gates differently that way. And the real time data is not something that comes just easily. There's a lot of infrastructure built for it. But we've done it at access and we've been able to provide to the team so they can manage their getting in better. So real time is interesting because there's always conversation about real time and I would say, you know, how do you define real time? In my mind, it's in time to do something about it. So, you know, using real time, I mean, are there things that they can do in real time to either lighten the load at an overdone gate or what are some of the real time impacts that people are using this data to do? Yeah, so exactly the example you provided, like, you know, making sure there are more people at this one gate as opposed to others, but also like knowing who's coming into the arena. So access as ID ticketing, ID based ticketing platform so we actually know who's coming in. It's a rotating barcode, so if you just copy paste the ticket and text to your friend, that doesn't work, that eliminates fraud as well. But because we know who's coming in, you can actually empower your sales reps as a team to make sure you're, you know, if they're coming into a suite or a premium area, so on and so actually just scanned in so you kind of can come up with ideas for sales reps as well as some of the marketing activations. Like, it could be that you have people that typically come in late, you want to incentivize them, you could actually come up with promotions on merchant food and beverage to incentivize them early, right? Or at the same time, you can actually, there are some platforms that do marketing activation. You may have had a lot of hot dogs left that you couldn't sell. Towards the late quarter, you could send a message to everyone, say, okay, you know, hot dogs are 20% off. So you need real time for the data for that because you again need to know how many people scan in. You may want to know how many people scanned out. So for some conferences and other type of events, you want to make sure there's a, you know, fire marshal rules, you want to make sure. So all that real time data is helpful for that. If you just looked at the purchaser data, we're not going to get that specifically there. That's really interesting. So I was going to say, what are some of the next things that we can expect to see dynamic pricing applied to? And you just went through them, which are really situational specific opportunities to clear inventory, to do whatever. Exactly, it's not just the ticket purchase could be applied to other things as well. Right, right. How cool. So what other kind of data sets are you looking at to help teams that maybe we're not thinking about? Sure, just when people buy their tickets, what marketing may have they done so that we can understand the web traffic and, you know, did they buy the ticket when you send out that email or did they actually buy it three days later? So that's one area. As well as sort of the inventory that you have available for that game, you know, does it sell faster for that Friday game versus the Tuesday game? Also we are a comprehensive marketplace where we have both primary and secondary in the same map to give the convenience back to the consumer. So you kind of have a chance to see all the inventory available in front of you. So understanding how tickets transact in the secondary marketplace is helpful for the teams to really price their product better. Because, you know, sometimes we have, I've worked for a team, so I have that background where you may have just 20 price points and you've done it for 20 years, but it's been certainly changing then. But now that you have all these different data points on the secondary also, you kind of may be like, okay, I need 40 price points really because there's that much differentiation in demand. Wow, really sophisticated analysis and the real time data flow and everything. Really interesting conversation that goes so far beyond just dynamic pricing. If you use these more sophisticated methods to get more value, provide better experience for the fans. And actually in Japan, they do more about dynamic pricing. So they utilize our platform to actually able to price every seat differently if they wanted to. We've just went out with on sales for B-League teams and that's kind of how they apply that. So it's been used elsewhere, maybe in the US in sports. It's definitely catching up and it's much, much big difference from the 10 years ago. But I think Japan has already been kind of doing that. Excellent. Well, Suzanne, thanks for taking a few minutes and sharing that story. There's a lot going on behind the scenes that we may not be conscious of, but hopefully we're getting the benefit of it. Yeah, thank you. All right. She says that I'm Jeff. Yes, we're live. They're banging on something down there. I'm not sure what. But keep watching. We'll be here at Oracle Park in San Francisco. Thanks for watching. See you next time.