WEBVTT - Target Earnings, AI in Focus 0:00:00.600 --> 0:00:07.280 Bloomberg Audio Studios, podcasts, radio news. 0:00:10.600 --> 0:00:14.400 This is Bloomberg Intelligence with Alex Steinel and Paul Sweeny. 0:00:14.520 --> 0:00:17.720 The real app performance has been in US corporate high yield. 0:00:17.880 --> 0:00:20.240 Are the companies lean enough? Have they trimmed all the fats? 0:00:20.320 --> 0:00:24.119 The semiconductor business is a really cyclical business. 0:00:23.600 --> 0:00:27.200 Breaking market headlines and corporate news from across the globe. 0:00:27.240 --> 0:00:29.880 Do investors like the M and A that we've seen? 0:00:30.080 --> 0:00:33.159 These are two big time blue chip companies. 0:00:33.320 --> 0:00:36.920 The window between the peak and cut changing super fast. 0:00:37.080 --> 0:00:41.720 Bloomberg Intelligence with Alex Steinel and Paul'sweeny on Bloomberg Radio. 0:00:42.560 --> 0:00:45.200 On Today's Bloomberg Intelligence Show, we dig inside the big 0:00:45.240 --> 0:00:47.560 business stories impacting Wall Street and the global markets. 0:00:47.720 --> 0:00:49.760 Each and every week, are going to provide in depth 0:00:49.760 --> 0:00:51.840 research and data on some of the two thousand companies 0:00:51.880 --> 0:00:54.520 and one hundred and thirty industries our analysts cover worldwide. 0:00:54.520 --> 0:00:56.920 Today, we'll look at why Apple says it's iPhone sales 0:00:56.920 --> 0:00:57.800 in China are falling. 0:00:57.960 --> 0:00:59.800 Plus we're going to dive into the world of art 0:01:00.320 --> 0:01:03.600 intelligence and how it's going to impact job organizations going forward. 0:01:03.680 --> 0:01:06.280 But first we'll begin in the retail sector. Earlier in 0:01:06.319 --> 0:01:10.039 the week, Target reported fourth quarter profit that beat analyst expectations. 0:01:10.040 --> 0:01:12.280 So this comes as the company reduced its stockpile of 0:01:12.319 --> 0:01:15.160 merchandise by about twelve percent during the quarter. So Target 0:01:15.200 --> 0:01:17.840 also confirmed it's going to launch a paid membership program, 0:01:17.959 --> 0:01:20.240 going up against rivals like Amazon and Walmart. 0:01:20.280 --> 0:01:22.360 For more, co host Bailey Lipschutz and I were joined 0:01:22.360 --> 0:01:26.160 by Jennifer bartashis Bloomberg's senior retail analysts. Were first asked 0:01:26.240 --> 0:01:28.400 Jennifer why investors are excited about Target. 0:01:28.640 --> 0:01:31.759 They've really revealed their plan for growth over the next 0:01:31.959 --> 0:01:35.399 several years and that is resonating well with investors, and 0:01:35.480 --> 0:01:39.040 it's all about recapturing top plane growth, traffic, market share, 0:01:39.400 --> 0:01:41.200 and they're a little bit more upbeat on where they 0:01:41.280 --> 0:01:42.479 see the consumer right now. 0:01:43.000 --> 0:01:45.399 And when we look at inventory being an issue that 0:01:45.480 --> 0:01:47.920 was such a big problem for Target during the pandemic, 0:01:48.040 --> 0:01:49.880 it does seem like that's being worked through. Kind of 0:01:49.880 --> 0:01:53.840 what's your expectation with how Target is handling their inventory 0:01:54.480 --> 0:01:56.480 ahead of schedule or not a head schedule. 0:01:56.640 --> 0:01:59.840 Yeah, they've done a major pivot with inventory, and obviously 0:01:59.840 --> 0:02:03.000 they had huge issues a couple of years ago with markdowns, 0:02:03.080 --> 0:02:05.720 and they've really been able to write size inventory that's 0:02:05.720 --> 0:02:09.080 shown up where inventory right now is actually lower than 0:02:09.120 --> 0:02:11.560 it was last year, and yet in stocks are better 0:02:11.600 --> 0:02:14.640 than they've been. That focus on those retail fundamentals of 0:02:14.680 --> 0:02:16.800 making sure that you have things in the stores and 0:02:16.880 --> 0:02:20.360 in stock has really been playing through and driving some 0:02:20.480 --> 0:02:22.800 of the results that they've seen, and a lot of 0:02:22.800 --> 0:02:25.320 that stems from inventory. And so right now they're very 0:02:25.320 --> 0:02:28.680 well positioned going into twenty twenty four and that should 0:02:28.880 --> 0:02:30.880 hopefully be a tailwind for them for the rest of 0:02:30.880 --> 0:02:31.639 this fiscal year. 0:02:31.919 --> 0:02:34.160 An Affinity Card, can you explain what's going on there? 0:02:34.480 --> 0:02:37.760 They're kind of reimagining their loyalty program. So the baseline 0:02:37.800 --> 0:02:40.520 was Target Circle, which was free to join, and they 0:02:40.520 --> 0:02:43.600 have one hundred million users that have joined it, and 0:02:43.720 --> 0:02:46.320 that's where you can go in and save different offers 0:02:46.360 --> 0:02:49.000 and you get an extra ten percent off your paper 0:02:49.040 --> 0:02:51.639 towels you know that week and that brand. What they're 0:02:51.680 --> 0:02:53.520 doing is they're making it so you don't have to 0:02:53.600 --> 0:02:56.200 search and save. You get the things automatically when you 0:02:56.320 --> 0:02:59.000 check out, and if you're a Red Card holder, for 0:02:59.000 --> 0:03:03.079 forty nine dollars, you can get unlimited free delivery, same 0:03:03.160 --> 0:03:06.320 day free delivery to your house and they're calling this 0:03:06.840 --> 0:03:09.920 Target three sixty. You can also subscribe to just that 0:03:09.960 --> 0:03:12.480 if you're not a Red Card holder. Also an introductory 0:03:12.480 --> 0:03:14.480 price of forty nine, but it will go up over time, 0:03:14.639 --> 0:03:17.400 although they didn't say to what. So it's a move 0:03:17.400 --> 0:03:19.320 where they're trying to get, you know, a little bit 0:03:19.400 --> 0:03:22.600 deeper into consumers' lives, you know, doing more home delivery. 0:03:22.880 --> 0:03:25.760 There's some additional perks in there where you can access 0:03:26.200 --> 0:03:28.320 all of what Ship does, which is their same day 0:03:28.320 --> 0:03:30.840 delivery service, and that includes being able to shop at 0:03:30.840 --> 0:03:34.079 other retailers. So that's kind of the differentiator here with 0:03:34.120 --> 0:03:36.720 regards to the membership program that once you have it, 0:03:36.760 --> 0:03:39.120 you could also have your Target run include something from 0:03:39.120 --> 0:03:44.440 Costco for example. But it's early days and we'll see 0:03:44.440 --> 0:03:47.640 how much appetite consumers have for yet another membership that 0:03:47.680 --> 0:03:48.400 they have to pay for. 0:03:49.040 --> 0:03:51.600 Well, what are your expectations on that? Because I feel 0:03:51.600 --> 0:03:54.800 like everyone pays for Amazon Prime and Walmart Plus I 0:03:54.840 --> 0:03:56.880 know has had a strong roll out and has partnerships 0:03:56.920 --> 0:03:59.520 with different credit cards. Like, what can Target really do 0:03:59.600 --> 0:04:02.560 to get people to pay another annual fee when it 0:04:02.640 --> 0:04:05.320 seems like, at least looking at the streaming platforms they're 0:04:05.360 --> 0:04:07.280 struggling to maintain users. 0:04:07.680 --> 0:04:09.760 It's a great question, and I think that's one of 0:04:09.800 --> 0:04:11.960 the big questions that we're going to need to see 0:04:11.960 --> 0:04:15.560 as they really talk about what differentiates this program, because 0:04:15.760 --> 0:04:17.680 you know, forty nine dollars is cheap, but it is 0:04:17.680 --> 0:04:20.080 an introductory price, and there are a lot of people 0:04:20.120 --> 0:04:23.080 out there that do delivery, and so you know, when 0:04:23.120 --> 0:04:24.960 I look at it, I think in order for it 0:04:25.000 --> 0:04:26.800 to be a successful program, they're going to have to 0:04:26.960 --> 0:04:30.839 really do something extraordinary that appeals to people to prompt 0:04:30.839 --> 0:04:34.599 them to pay extra And historically, you know, Target's formula 0:04:34.640 --> 0:04:37.280 for success has never been mimicking others. It's been about 0:04:37.400 --> 0:04:39.680 kind of forging their own path. And I think this 0:04:39.760 --> 0:04:41.680 is an example where it's going to be very very 0:04:41.680 --> 0:04:44.240 important for them to do that. But it's not clear 0:04:44.320 --> 0:04:46.440 yet how that's going to be realized. 0:04:46.680 --> 0:04:50.120 And how does Target play into a recession. Are they 0:04:50.200 --> 0:04:52.240 one of the companies that can weather the storm because 0:04:52.240 --> 0:04:54.120 of their loyalty or how does that play out just 0:04:54.160 --> 0:04:56.640 given their typical demographics. 0:04:56.200 --> 0:04:59.440 If there is a recession. With their typical demographics, Target's 0:04:59.440 --> 0:05:03.920 customer base is extremely loyal, but Target's product mix does 0:05:03.960 --> 0:05:07.200 skew to more discretionary items, and so whenever there's a 0:05:07.240 --> 0:05:10.200 pullback and spending, it tends to have an outsized impact 0:05:10.240 --> 0:05:13.880 on Target versus other big box retailers. Now, Target has 0:05:13.920 --> 0:05:17.480 been really focused in the last eighteen months, especially on value. 0:05:17.640 --> 0:05:20.240 They've launched some new private label brands that are meant 0:05:20.279 --> 0:05:22.880 to be the cheapest option in every category in the store. 0:05:23.320 --> 0:05:26.160 So they're trying to respond to that. So they have 0:05:26.279 --> 0:05:28.880 the breadth of category and they have the loyalty of 0:05:28.920 --> 0:05:31.960 consumers that they can weather a recession, but it will 0:05:32.000 --> 0:05:34.280 make it harder for them to get back to that 0:05:34.440 --> 0:05:37.200 top line growth and that expansion of margin that they're 0:05:37.200 --> 0:05:39.120 talking about if we find ourselves in the midst of 0:05:39.160 --> 0:05:39.760 a recession. 0:05:40.160 --> 0:05:43.520 Hey, Jen, how do I differentiate how much shopper between 0:05:44.120 --> 0:05:45.160 Target and Walmart? 0:05:45.680 --> 0:05:48.520 It's all about perception, right When you think about Walmart, 0:05:48.600 --> 0:05:51.960 it is usually about lowest price. Walmart is a EDLP. 0:05:52.640 --> 0:05:55.720 Every day you get the lowest possible price. They've got 0:05:55.760 --> 0:05:58.839 a very big assortment and they have some perks with 0:05:58.880 --> 0:06:02.000 regards to their Walmart Plus program. When people think of Target, 0:06:02.040 --> 0:06:05.160 they think a little bit more of discovery, They think 0:06:05.200 --> 0:06:08.640 a little bit more about inspiration than functionality, and that's 0:06:08.680 --> 0:06:11.400 where you really see the divergence between those two retailers. 0:06:11.760 --> 0:06:13.400 I will say, when I go to Target, I always 0:06:13.480 --> 0:06:15.080 end up buying more than I want, where if I 0:06:15.120 --> 0:06:17.640 go to Walmart, I'm kind of in and out. Jen 0:06:17.800 --> 0:06:20.159 question off of that comparison, I always talk up the 0:06:20.160 --> 0:06:22.960 fact that Walmart owned Sam's Club. When you look at 0:06:22.960 --> 0:06:26.640 the company makeup, how much does that differentiate Walmart versus 0:06:26.680 --> 0:06:28.719 some of the other peers, just given as you mentioned 0:06:29.000 --> 0:06:32.960 Target potentially partnering with Costco if you're using their membership card. 0:06:33.480 --> 0:06:36.919 Yeah, so obviously there's a great benefit to Walmart of 0:06:36.960 --> 0:06:40.479 having both it's US Walmart stores as well as the 0:06:40.480 --> 0:06:44.000 Sam's Club stores, because they really can capture spending by 0:06:44.080 --> 0:06:47.560 different groups of people and for different shopping reasons. Now, 0:06:47.560 --> 0:06:49.720 when I talked about shipped, it's not so much that 0:06:49.760 --> 0:06:52.680 you get the benefits of a Costco membership, for example, 0:06:52.720 --> 0:06:55.200 with Target. It's just more that you can have your 0:06:55.440 --> 0:06:59.160 delivery person pick up purchases from other retailers, which is 0:06:59.200 --> 0:07:02.200 something that isn't in vetted in a Walmart program, for example. 0:07:02.600 --> 0:07:06.120 But that Target membership fee is going to be competing 0:07:06.160 --> 0:07:09.039 with your Costco membership fee. It'll be you know, competing 0:07:09.040 --> 0:07:11.880 with a bjays membership fee along with all of your 0:07:11.880 --> 0:07:14.920 streaming services and everything else out there. So you know, 0:07:14.960 --> 0:07:17.960 Walmart definitely benefits from the scale of having both the 0:07:17.960 --> 0:07:20.720 course stores and Sam's Club, but it is a little 0:07:20.720 --> 0:07:22.680 bit of a different business model than what we're talking 0:07:22.720 --> 0:07:23.480 about with Target. 0:07:23.560 --> 0:07:23.680 Oh. 0:07:23.720 --> 0:07:26.800 Thanks to Jen Bartashis Bloomberg Intelligence senior retail analysts. 0:07:26.800 --> 0:07:28.200 All right, we turned out a big tech So this 0:07:28.240 --> 0:07:31.280 week we learned that Apple iPhone sales in China fell 0:07:31.320 --> 0:07:33.560 by a surprising twenty four percent. Now this was over 0:07:33.600 --> 0:07:35.840 the first six weeks of twenty twenty four. Those figures 0:07:35.840 --> 0:07:37.840 came from the Counterpoint Research firm. 0:07:38.040 --> 0:07:39.880 For more on this, co host Bailey Lipshaltz and I, 0:07:40.000 --> 0:07:43.800 we're joined by anaag Rana, Bloomberg Intelligence Senior technology analyst. 0:07:43.960 --> 0:07:46.600 We first asked Anurag what's causing this to decline in 0:07:46.640 --> 0:07:48.200 the early part of twenty twenty four. 0:07:48.440 --> 0:07:50.360 This is the same story that's been going on for 0:07:50.400 --> 0:07:53.320 the last six to nine months, ever since Wallwei released 0:07:53.320 --> 0:07:56.920 their higher end phone last year. So Apple's been losing 0:07:56.960 --> 0:07:59.720 market share there that has been you know, you could 0:07:59.760 --> 0:08:03.200 say opened or coupled with consumer weakness in China. And 0:08:03.240 --> 0:08:06.080 it's all that's you know, driving these problems right now. 0:08:06.440 --> 0:08:10.560 When I look at the PGEL function on the terminal, 0:08:11.000 --> 0:08:14.120 iPhone accounts for more than half of Apple's revenue China 0:08:14.200 --> 0:08:17.120 call it a fifth of their sales anak. When you 0:08:17.160 --> 0:08:20.200 look at those numbers, what does this actually mean for 0:08:20.320 --> 0:08:23.640 Apple if they're going to see that competition eating into 0:08:23.680 --> 0:08:24.239 their sales. 0:08:24.480 --> 0:08:25.880 Yeah, I think it's going to be a tough time 0:08:25.920 --> 0:08:28.840 for Apple in China for that at least this year 0:08:29.080 --> 0:08:31.640 and maybe into next year before they can, let's say, 0:08:31.640 --> 0:08:34.560 make some inroads in India and other markets. Emerging markets 0:08:34.640 --> 0:08:37.079 is the real growth driver for Apple, there is no 0:08:37.440 --> 0:08:39.920 two ways about it. And and you know iPhone is 0:08:39.920 --> 0:08:42.680 the big growth driver. So if phones are not selling 0:08:42.760 --> 0:08:45.600 in China, that's a problem for Apple. It means numbers 0:08:45.640 --> 0:08:47.960 need to come down even more for Apple this year. 0:08:48.280 --> 0:08:51.680 You know, we saw about double digit sales drop in 0:08:51.800 --> 0:08:56.120 China last quarter. I looked up on MDL consensus is 0:08:56.160 --> 0:08:59.319 about seven percent drop in China for this quarter. I 0:08:59.400 --> 0:09:01.800 think that number needs to creep up to someone in 0:09:01.800 --> 0:09:05.280 the low double digit decline going forward. It's a painful 0:09:05.320 --> 0:09:09.400 situation for Apple, and frankly, there aren't at many rosy 0:09:09.480 --> 0:09:11.600 things looking forward, at least for twenty twenty four. 0:09:11.960 --> 0:09:16.760 So I guess the biggest concern for Apple obviously is competition, 0:09:16.800 --> 0:09:19.920 because they haven't really had that robust of a competitor 0:09:19.920 --> 0:09:23.120 and they're part of the market. Are there any responses 0:09:23.160 --> 0:09:25.960 Apple can make here from a competitive landscape other than 0:09:26.520 --> 0:09:27.880 lowering the price point? 0:09:28.120 --> 0:09:30.360 Yeah, Paul, I think there is a little more hype 0:09:30.360 --> 0:09:34.360 in that competition news than reality only because Huahwei didn't 0:09:34.440 --> 0:09:36.719 release a phone for many years, So that you can 0:09:36.760 --> 0:09:38.880 think about it. If you have an install base of 0:09:38.920 --> 0:09:41.400 WAWE phones. I mean, let's say you know that's X 0:09:41.480 --> 0:09:44.520 and that hasn't been updated for four or five six years, 0:09:44.520 --> 0:09:46.720 and you just certainly get a brand new phone. All 0:09:46.760 --> 0:09:48.760 of those people are going to go and refresh that, 0:09:49.080 --> 0:09:51.959 So I think you should take that as a bigger factor, 0:09:52.240 --> 0:09:55.600 plus the subsidies they are getting in China from the 0:09:55.600 --> 0:09:58.800 local providers. So I think Apple will do okay in 0:09:58.920 --> 0:10:01.480 China over the long term. But I think that's not 0:10:01.520 --> 0:10:03.120 going to be a twenty twenty fourth story. 0:10:03.280 --> 0:10:06.400 And you mentioned emerging markets as the next driver. What countries, 0:10:06.440 --> 0:10:08.800 what regions are going to be able to pay up 0:10:08.840 --> 0:10:11.520 for what I would say, is quite an expensive phone. 0:10:11.760 --> 0:10:13.960 Yeah, I think that's the most important question, and I 0:10:13.960 --> 0:10:16.120 think you know, just by the sheer size of it, 0:10:16.280 --> 0:10:19.480 India is the next one. But frankly speaking, right now, 0:10:19.559 --> 0:10:22.400 Apple doesn't even operate in you know, five percent of 0:10:22.440 --> 0:10:25.480 the entire market because of the price point of the phone. 0:10:25.600 --> 0:10:27.800 I think the strategy India is going to be a 0:10:27.840 --> 0:10:30.679 mix of the lower phone the se as well as 0:10:30.760 --> 0:10:33.440 the refurbished phone where the price point is even lower. 0:10:33.559 --> 0:10:36.040 But having said that, I think India is a developing country. 0:10:36.080 --> 0:10:38.559 The middle class is getting more richer, so I think 0:10:38.600 --> 0:10:40.520 that's going to be the next big growth catalyst. But 0:10:40.600 --> 0:10:42.760 this is it's not going to play out in twenty 0:10:42.800 --> 0:10:45.080 four to twenty five. That's more of a I would 0:10:45.080 --> 0:10:46.320 submit to long term story. 0:10:46.679 --> 0:10:49.520 We've talked about this before that Apple might introduce a 0:10:49.679 --> 0:10:52.880 lower price phone into India for just that reason. Is 0:10:52.880 --> 0:10:56.120 that something they're still considering or will they just wait 0:10:56.160 --> 0:10:58.160 for the market to kind of move up to where 0:10:58.160 --> 0:10:59.400 the Apple phone price point is. 0:10:59.800 --> 0:11:01.600 I think it's going to be the latter. I've done 0:11:01.640 --> 0:11:04.040 a lot of analysis of how much share they can 0:11:04.080 --> 0:11:06.720 gain if they drop the S price by fifty dollars 0:11:06.840 --> 0:11:09.400 hundred dollars, and you know, when I publish that stuff, 0:11:09.400 --> 0:11:11.440 I think they actually raise the price by fifty bucks. 0:11:11.480 --> 0:11:14.280 So they don't believe in dropping prices. They are more 0:11:14.320 --> 0:11:17.760 on a margin story. So think of Apple more on 0:11:17.760 --> 0:11:20.520 the long term basis right now, not on the short term. 0:11:20.920 --> 0:11:23.320 I don't think they're going to you know, I would 0:11:23.360 --> 0:11:27.640 say swap margins for market share. They've never done that 0:11:27.679 --> 0:11:30.040 in their history, whether it was on the mac side 0:11:30.400 --> 0:11:31.600 or on the phone side. 0:11:31.840 --> 0:11:34.920 And quickly anorak, I look at the news, there's no 0:11:35.040 --> 0:11:39.040 more Apple car. There's tepid reception to the vision pro 0:11:39.120 --> 0:11:41.960 What actually drives the stock, what drives sales in the 0:11:42.000 --> 0:11:43.400 next twelve to eighteen months. 0:11:43.800 --> 0:11:46.640 Yeah, I think that's the most important question for Apple investors. 0:11:46.840 --> 0:11:48.520 And I think there's going to be an event in June, 0:11:48.520 --> 0:11:51.920 the World Wide Developers Conference, where they have pledged that 0:11:51.960 --> 0:11:54.040 they're going to show a lot of AI enhancements to 0:11:54.080 --> 0:11:56.920 the operating system. I think that really is the one 0:11:57.000 --> 0:12:00.720 wildcard that can completely change the sentiment of the company, 0:12:00.720 --> 0:12:03.520 both in terms of sales and the gloomy investor sentiment 0:12:04.000 --> 0:12:07.440 only because remember, Apple has a distribution network that stands, 0:12:07.520 --> 0:12:10.040 you know, next to nobody out there in terms of 0:12:10.200 --> 0:12:13.520 you know, affluent people using their phones. More than one 0:12:13.559 --> 0:12:16.720 billion devices connected just on the smartphone. I think that 0:12:16.840 --> 0:12:18.840 really is the big driver. One of the things I 0:12:18.920 --> 0:12:21.240 was thinking about was if you go back, you know, 0:12:21.600 --> 0:12:24.280 five years, seven years, there were apps such as trip 0:12:24.320 --> 0:12:27.080 Advisors an Yelp where people used to go for their 0:12:27.400 --> 0:12:31.600 you know, specialized functions for restaurant advices and tourism. But 0:12:31.640 --> 0:12:34.040 when you look at somebody like Google, a lot of 0:12:34.040 --> 0:12:36.920 that traffic has moved on to them because they control 0:12:36.960 --> 0:12:40.160 the distribution. I think Apple has the same ability, but 0:12:40.280 --> 0:12:43.680 they have to show up with some AI products otherwise 0:12:43.720 --> 0:12:44.280 that's not going to. 0:12:44.280 --> 0:12:47.160 Flow our Thanks to Ana rog Rana Bloomberg Intelligence Senior 0:12:47.200 --> 0:12:48.440 Technology Channels, I com. 0:12:48.320 --> 0:12:50.160 Going to bring a break down the role of AI 0:12:50.320 --> 0:12:51.680 in sports analytics. 0:12:51.760 --> 0:12:54.560 You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in 0:12:54.600 --> 0:12:56.760 depth research and data on two thousand companies and one 0:12:56.840 --> 0:12:59.640 hundred and thirty industries. You can access Bloomberg Intelligence v 0:12:59.679 --> 0:13:01.880 A BI. I go in the terminal, I'm Paul Swimming and. 0:13:01.920 --> 0:13:03.920 Am Alex Steel and this is Bloomberg. 0:13:08.240 --> 0:13:12.120 You're listening to the Bloomberg Intelligence podcast. Catch us live 0:13:12.200 --> 0:13:14.880 weekdays at ten am Eastern on fo car Play and 0:13:14.880 --> 0:13:17.959 Android Auto with the Bloomberg Business App. Listen on demand 0:13:17.960 --> 0:13:22.360 wherever you get your podcasts, or watch us live on YouTube. 0:13:22.840 --> 0:13:25.560 Earlier in the week, Bloomberg Intelligence broadcasted live from the 0:13:25.600 --> 0:13:28.679 campus of the New Jersey Institute of Technology. Paul was 0:13:28.720 --> 0:13:31.240 pumped and the main topic of conversation was AI. 0:13:31.520 --> 0:13:34.320 We took a look at zealous Analytics and Austin based 0:13:34.320 --> 0:13:38.080 sports analytics company that evaluates, predicts, and improves player and 0:13:38.120 --> 0:13:39.400 team performance in sports. 0:13:39.440 --> 0:13:42.360 So one of our guests was Evana Serk, senior product 0:13:42.440 --> 0:13:45.840 scientist at Zealis Analytics, and we asked Havana how Zealos 0:13:46.000 --> 0:13:47.200 uses AI in sports. 0:13:47.600 --> 0:13:51.000 This field that has expanded in last maybe ten years 0:13:51.040 --> 0:13:54.040 of a lot in other sports. Even before that, it 0:13:54.080 --> 0:13:56.560 was in baseball that was one of the first sports. 0:13:56.559 --> 0:13:58.920 If you've seen Moneyball, that's that's really yes. 0:13:58.880 --> 0:14:02.120 Yeah, okay, the moneyball Okay. And so it's basically like 0:14:02.160 --> 0:14:05.719 how to position, like what players to put where combinations? 0:14:05.720 --> 0:14:06.600 Is it that kind of stuff? 0:14:06.640 --> 0:14:10.720 Correct? Correct? So, so player evaluation in game decision strategy, 0:14:11.320 --> 0:14:12.800 that's sort of sort of things. Yeah. 0:14:12.840 --> 0:14:17.319 So again, played for your starter for nja's basketball. You 0:14:17.360 --> 0:14:20.960 also represented your native Croatia and youth basketball. So you're 0:14:21.080 --> 0:14:23.400 great at basketball, but you're also a math nerd to 0:14:23.480 --> 0:14:26.520 the nth degree. She got a BS and a pH 0:14:26.600 --> 0:14:31.960 degree and applied mathematics from njiit focusing on computational fluid dynamics. 0:14:32.000 --> 0:14:32.720 I don't know what that means. 0:14:32.720 --> 0:14:34.480 I don't know what that means. That's art, but okay, 0:14:34.840 --> 0:14:38.200 I don't know. So a great mathematician, great basketball player. 0:14:38.280 --> 0:14:40.200 Let's put it all together. What are some of the 0:14:40.320 --> 0:14:43.480 really good applications for some of that technology we've seen? 0:14:43.560 --> 0:14:45.600 You mentioned moneyball for you know that we've seen it 0:14:45.600 --> 0:14:48.320 in baseball. What other applications are out there that you think? 0:14:48.480 --> 0:14:50.520 It seems like we're in the very early innings of that. 0:14:50.880 --> 0:14:54.400 Early on, it started with just using basic data, so 0:14:54.600 --> 0:14:56.680 box scores, play by play, and then a lot of 0:14:56.720 --> 0:15:00.720 sports in recent years have a what's called player tracking data, 0:15:01.080 --> 0:15:03.600 meaning we have locations of the players on the court 0:15:03.720 --> 0:15:06.240 or on a pitch, on a field, whichever sport we're 0:15:06.280 --> 0:15:09.520 talking about, at a high resolution. So from that data 0:15:09.560 --> 0:15:11.840 we can extract not only things that are counted in 0:15:11.840 --> 0:15:14.040 a box score, but also other things that happened during 0:15:14.040 --> 0:15:17.440 the game that you wouldn't see counted in like a 0:15:17.720 --> 0:15:19.280 basic box score for example. 0:15:19.640 --> 0:15:22.360 What are some of the common questions that like coaches 0:15:22.480 --> 0:15:24.440 or owners come to you with the. 0:15:24.360 --> 0:15:26.960 Biggest question is how do we value players? How do 0:15:26.960 --> 0:15:29.280 we find which players teams should sign, how long of 0:15:29.320 --> 0:15:32.040 a contract, how much money should be on a contract. 0:15:32.280 --> 0:15:35.080 That's one side, So that's the player evaluation side, and 0:15:35.080 --> 0:15:38.240 then the other side is coaching and in game decision making. 0:15:38.600 --> 0:15:42.440 So which situations are producing the most value for the teams? 0:15:42.720 --> 0:15:46.080 Which situations are creating better opportunities to score? 0:15:47.000 --> 0:15:49.360 I know, like in baseball, major league baseball and in 0:15:49.400 --> 0:15:51.120 minor league baseball. Now it's coming into all the other 0:15:51.120 --> 0:15:55.760 parts of baseball. The analytics people, the data people versus 0:15:55.800 --> 0:15:58.120 maybe some of the more traditionalists. They kind of butt 0:15:58.160 --> 0:16:01.040 heads on occasion. So how much chanalytics do you use 0:16:01.120 --> 0:16:04.160 versus just my gut I think this player will do well. 0:16:04.880 --> 0:16:06.640 How do you kind of bridge that topic? 0:16:06.920 --> 0:16:09.440 Yeah? Yeah, So that's that's a big important thing, because 0:16:09.440 --> 0:16:13.400 you can just have data without the domain expertise. And 0:16:13.440 --> 0:16:16.200 I think that's something that we Adzealas have a really 0:16:16.200 --> 0:16:19.200 good strength, is that we have the experts in data 0:16:19.240 --> 0:16:22.000 and statistics in AI in machine learning. But we also 0:16:22.040 --> 0:16:24.680 have a lot of people who worked in sports teams 0:16:24.680 --> 0:16:27.800 and have that sort of experience and know which questions 0:16:27.880 --> 0:16:30.680 the teams want to answer, what's useful for them, and 0:16:30.760 --> 0:16:32.120 how can we help them best. 0:16:32.320 --> 0:16:34.920 So yeah, because when you were saying what AI could 0:16:34.920 --> 0:16:36.840 help you do, it feels like that's not what a 0:16:36.880 --> 0:16:38.640 coach is supposed to do. But you're saying that you 0:16:38.680 --> 0:16:41.960 need someone to interpret how to manage that and stuff. 0:16:41.880 --> 0:16:44.280 Right, right, So you need like a bridge between the 0:16:44.360 --> 0:16:46.680 data and what's what's happening on the court. 0:16:46.720 --> 0:16:49.280 All right, If I'm an agent representing a player, now 0:16:49.400 --> 0:16:51.680 this is I got to learn this stuff because the 0:16:51.720 --> 0:16:52.760 team's gonna come at. 0:16:52.600 --> 0:16:54.880 Me and say, this is what the program tells me. 0:16:54.880 --> 0:16:58.160 That, Yeah, your client's worth blank because his or her 0:16:58.480 --> 0:17:01.360 OPS is this and blah blah blah blah blah, And 0:17:01.400 --> 0:17:02.720 you got to come back and say, no, I think 0:17:02.720 --> 0:17:04.000 he's better than that, and I think he's really more. 0:17:04.200 --> 0:17:06.560 So do you work with the agents and players themselves 0:17:06.600 --> 0:17:09.240 as well, because they better be smart on this stuff. 0:17:09.440 --> 0:17:11.879 Yeah, Yeah, that's it's a great area where where ZELS 0:17:11.960 --> 0:17:14.720 is growing as well in some of our sports. But 0:17:14.720 --> 0:17:16.840 but Yeah, an agent cannot learn all of this on 0:17:16.880 --> 0:17:21.199 their own, so having a company or a contractor who can. 0:17:21.280 --> 0:17:24.840 So do you guys work with agents and players directly. 0:17:24.760 --> 0:17:25.679 In certain sports? 0:17:25.720 --> 0:17:28.560 Yes, yeah, but not all across the board. So you also, 0:17:28.560 --> 0:17:31.000 as Paul was mentioned earlier, you got your BS and 0:17:31.040 --> 0:17:36.800 your PhD in applied mathematics and nj T. Because we're 0:17:36.840 --> 0:17:39.199 here and we're talking about NJIT kind of bridges the 0:17:39.200 --> 0:17:41.400 gap between learning stuff and then putting it out into 0:17:41.400 --> 0:17:44.400 the world. How did this help you evolve your career 0:17:44.560 --> 0:17:46.080 and leave you where you are today? 0:17:46.359 --> 0:17:46.560 Yeah? 0:17:46.640 --> 0:17:50.320 Even though I studied competitional fluidnamics, it's not exactly data science, 0:17:50.359 --> 0:17:51.359 but I've learned a lot of skills. 0:17:51.400 --> 0:17:54.080 There were transitions, by the way, so you can pretend 0:17:54.080 --> 0:17:54.399 it is. 0:17:55.440 --> 0:17:58.119 There's a little skills that transfer from from one field 0:17:58.119 --> 0:18:01.520 to the other, for example, coding, analyzing large data sets, 0:18:01.840 --> 0:18:06.520 creating visualizations, and communicating scientific results to regular audience. 0:18:06.720 --> 0:18:09.760 Are there some sports that are embracing AI or just 0:18:09.840 --> 0:18:11.959 technology analytics more than others? 0:18:12.359 --> 0:18:15.639 That's historically in baseball, particularly because they had more advanced 0:18:15.720 --> 0:18:19.520 data for the longest time, But other sports now also 0:18:19.640 --> 0:18:23.480 have the player tracking data and are starting to get 0:18:23.560 --> 0:18:24.399 more on that side. 0:18:24.560 --> 0:18:26.639 How did you wind up in this? Because if you 0:18:26.680 --> 0:18:29.520 played basketball, right, because you're originally from Croatia, right, So 0:18:29.520 --> 0:18:32.360 you played basketball and then you somehow wound up and 0:18:32.400 --> 0:18:34.320 deep into analytics. How did you do that? 0:18:34.560 --> 0:18:34.720 Well? 0:18:34.760 --> 0:18:37.080 I always loved math and I always loved basketball, and 0:18:37.160 --> 0:18:39.400 this was a perfect combination of the two. 0:18:39.720 --> 0:18:41.200 Where are we do you think in terms of the 0:18:41.240 --> 0:18:45.280