Sezin Aksoy, AXS | Sports Tech Tokyo World Demo Day 2019

Sezin Aksoy, AXS | Sports Tech Tokyo World Demo Day 2019


(upbeat music)>>Hey, welcome back everybody. Jeffrey Frick with The Cube. 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’s Sezin Aksoy, Global Data Strategy
and Analytics for AXS.>>Correct.
>>Welcome.>>Thank you.>>Absolutely.
>>Glad to be here.>>So Global Data Strategy. Everything’s all about data.>>Correct.>>So, somebody’s really
happy to have you on board. What are so… What do you, what are you
working on, what was top of line.>>Sure, so it’s going to sound cheesy but data is the power of the world.>>Yes.>>It’s going to empower
people making better decisions, so that’s kind of my role is at AXS. So AXS is the 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 touchpoint 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 touchpoints
that we are collecting. So that we can inform our clients to make better decisions with data.>>Right.>>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.>>Sizen: Hm mm.>>Because we saw, we’ve
seen dynamic pricing. And you said you were in the airline industry.
>>Correct.>>We’ve seen it in the hotel industry.>>Yup.>>My father in law talks about when he was doing dynamic pricing as a young kid.>>Sizen: Okay. Just making a call when
somebody came through the door, at eleven o’clock.
>>Sizen: Yeah. (laughs)>>Jeffrey: What’s my marginal cost…>>Okay, yep.>>Jeffrey: with somebody
in that room or not. There’s really slow to get beyond, kind of the entertain, oh
excuse me, the travel industry for other people…
>>Hm mm. Yep.>>To kind of get on
board the dynamic pricing.>>Yeah. We saw the Giants here…
>>Yep.>>Actually a couple of years ago. We came by, they were starting
to do dynamic pricing.>>Sizen: Hm mm.>>A Friday night Dodger game, compared to a Tuesday day…
>>Sizen: Yep.>>Milwaukee game, very, very different.>>Sizen: Hm mm.>>So, what are some of the
factors going in, what are some of the resistance,
>>Sizen: Yeah.>>that had to be overcome
for people to actually accept that it’s okay to charge more for a Friday night Dodger game, than a Tuesday afternoon Milwaukee game.>>Yep, so yeah, so my background
start with the airlines, which is where dynamic pricing,
revenue management started at, specifically the American Airlines. If you think about there
are a lot of similarities between airlines and live entertainments. Fixed costs, 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 Friday game. It 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 mix, San Francisco Giants was
one of the first teams that actually incorporated dynamic pricing about ten 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.>>Right.>>And for them, also it
didn’t start from like doing all the flights in day one. So it’s really needs to
be a phased 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 want incentivize people to buy early. And you want to make
sure they are the ones that getting the best price, and not necessarily the people
that are buying last minute.>>Right.>>If you’re buying last
minute, then you must accept that it maybe the available
today you’re not looking for or the price not you looking for. But I will say though that plans change, people decide to not attend the game. The reason is that, potential for finding other
seats for that similar game. But, really for 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.
>>Right.>>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,
>>Yeah.>>Jeffrey: On dynamic pricing? I mean the immediate impact
is from the high value seats for the high value games,
cause 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 find the right
price, and if you start earlier. And really the goal is
to sell all the seats, and to fill all the seats.
>>Right.>>Also, just selling the seats is not, doesn’t get you far enough. You want to make sure people
actually come to the game, and they’re the people that
are going to attend the game. Right?
>>Right.>>So, if you kind of, the
lower level has many more seats, so it’s really has to be both ways. It can’t be in one area,
either dynamic pricing and you don’t do it. It’s just all about training the public and consumers.
>>Right. Now, the other interesting you said in your kind of intro,
was keeping track of… What are the busiest turnstiles? And where people coming? And the flow within the game.
>>Sizen: Yep.>>What are some of the analytics that you do there,
>>Sizen: Yep.>>And how are teams using those…>>Sizen: Yep.>>that information to provide
a better fan experience?>>Yeah, so we have scanned data, and we actually have it real time. So, we are able to provide the teams. We have kineses 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 study the past games and understand where people came from. Typically for a Friday
game verse a Tuesday game, your crowd will look different, right. The Friday game, maybe
the more the families or Saturday or Sunday. But Tuesday may be more
corporate world, right. So understanding they’re
patterns, but also than 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 man 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.>>Right.>>But we’ve done it at
AXS, and we’ve been able to provide to the teams so they can manage their getting in better.
>>Right.>>So real time’s interesting
cause you know a lot of these conversations about
real time, and I would say, “How do you define real time?” And in my mind, it’s in time
to do something about it.>>Exactly.>>So, using real time,
I mean are there things they can do in real time
to either lighten the load at an overdone gate, or…>>Sizen: Yeah.>>What are some of the real time impacts that people are using this data to do?>>Yeah, so exactly the
example you provided. Like 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 AXS’s I-D ticketing, I-D
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 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 are, you
know, if they are coming to a suite or a premium area. So in so actually just
scanned in, so you kind of 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 merch and 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 hotdogs left that you couldn’t sell. Towards the late quarter,
you could send a message to everyone saying, “Okay, ya know, hot dogs
are 20 percent off.”>>Right, right.>>So that, you need real time
for it, for data for that. Cause you again need to know
how many people scanned in. You may want to know how
many people scanned out. So for some conferences
and other type events, you want to make sure there’s
a Fire Marshall rules, so you want to make sure. So all the real time
data is helpful for that if you just look at the purchaser data, you’re not going to get
that specifically there.>>That’s really interesting
cause 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.>>Yep.>>Opportunities to clear
inventory, to do whatever.>>Exactly, it’s not
just a ticket purchase. It could be applied to
other things as well.>>Right, Right.
>>Yeah.>>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 did they buy the ticket
when you send out that email. Or did they buy it three days later. So that’s one area. As well as sort of, the inventory that you have available for that game. Does it sell faster for that Friday game versus a Tuesday game? We also, we’re a comprehensive marketplace where we have both primary
and secondary in the same map. To give the convenience
back to the consumers, so you kind of have a chance to see all the inventory
available in front of you. So, a bit of understanding
how tickets transact in the secondary marketplace is helpful for the teams to really
price their product better. Cause sometimes we have… I work 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 second, you also
you kind of maybe is like, ‘Okay I need 40 price
points really because there’s that much differentiation demand.>>Wow, really sophisticated analysis…>>Yeah, it’s a passion area for me, so…>>And doing the real time, real time data flow and everything.>>Yeah, yeah. A really interesting,
interesting conversation.>>Yeah.>>To go so far beyond
just dynamic pricing.>>Exactly.>>It uses 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 Big League teams, and that’s how they apply that. So it’s been used elsewhere,
maybe in the U-S 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.>>Mm hm.>>Well Sizen, thanks
for taking a few minutes, and sharing those stories. There’s a lot going on behind the scenes that may not be conscious of, but hopefully we’re
getting the benefit of.>>Yeah, thank you.>>All right. Sizen, and I’m Jeff. Yes, we’re live. They’re banging on something down there. I’m not sure what, but keep watching. We’lls be here at Oracle
Park in San Francisco. Thanks for watching, and see ya next time. (upbeat music)

Leave a Reply

Your email address will not be published. Required fields are marked *