1 00:00:00,520 --> 00:00:05,120 Speaker 1: This is Bloomberg Business of Sports with Michael Bart, Scarlett Foo, 2 00:00:05,320 --> 00:00:10,280 Speaker 1: and Mike Lynch from Bloomberg Radio. This is the Bloomberg 3 00:00:10,320 --> 00:00:12,600 Speaker 1: Business of Sports show where we explore the big money 4 00:00:12,640 --> 00:00:15,000 Speaker 1: issues in the world of sports. I'm Michael Barn, I'm 5 00:00:15,040 --> 00:00:18,400 Speaker 1: Scarlett Foo, and I'm Mike Lynch. And today we are 6 00:00:18,480 --> 00:00:21,320 Speaker 1: talking big money. I mean big, big, big, big money. 7 00:00:21,360 --> 00:00:26,080 Speaker 1: With Super Bowl ads more expensive than ever, Let's break 8 00:00:26,079 --> 00:00:29,800 Speaker 1: down the big winners of the night with Hive Enterprise 9 00:00:30,240 --> 00:00:35,800 Speaker 1: AI president Dan Kalpin. Dan, Welcome to the podcast. First 10 00:00:35,840 --> 00:00:39,360 Speaker 1: of all, there were a lot of ads out there, 11 00:00:39,560 --> 00:00:42,440 Speaker 1: but it seems to me the one that really dominated 12 00:00:42,920 --> 00:00:45,400 Speaker 1: and caught my eye because I'm an old man. It 13 00:00:45,479 --> 00:00:49,400 Speaker 1: looked like an old palm game and I didn't get 14 00:00:49,440 --> 00:00:51,239 Speaker 1: it at first, but I guess it was like for 15 00:00:51,320 --> 00:00:55,440 Speaker 1: coin base or something. Yeah, I was thanking hi on, 16 00:00:55,600 --> 00:00:58,040 Speaker 1: thanks for having me, and yeah, that'll probably go down 17 00:00:58,040 --> 00:01:01,560 Speaker 1: in history. Is maybe the best director of ad ever 18 00:01:01,600 --> 00:01:04,520 Speaker 1: put on television. But I was definitely a fun one. 19 00:01:06,200 --> 00:01:08,400 Speaker 1: You're referring to the one with the QR code where 20 00:01:08,840 --> 00:01:11,040 Speaker 1: people kind of stared at it. It couldn't believe that 21 00:01:11,080 --> 00:01:13,959 Speaker 1: it was still on fifteen seconds later. And finally took 22 00:01:13,959 --> 00:01:16,160 Speaker 1: a picture of and decided they needed to do something 23 00:01:16,160 --> 00:01:19,399 Speaker 1: about it. What does that say about advertisers need to 24 00:01:19,440 --> 00:01:22,640 Speaker 1: rely on star power? Because when I was watching the ads, 25 00:01:22,640 --> 00:01:25,199 Speaker 1: which I enjoyed, I saw a lot of big names 26 00:01:25,200 --> 00:01:31,200 Speaker 1: Gwyneth Paltrow, Scarlett Johansson, Um Labron, James, the Jones Is, 27 00:01:31,240 --> 00:01:33,840 Speaker 1: the various jones Is, and I couldn't remember what company 28 00:01:33,880 --> 00:01:35,960 Speaker 1: they were advertising for. I just remember seeing them and 29 00:01:36,000 --> 00:01:37,720 Speaker 1: thought that it was really funny, but I couldn't tell 30 00:01:37,720 --> 00:01:41,319 Speaker 1: you which company made the pickup truck that Leslie Jones, 31 00:01:41,560 --> 00:01:46,920 Speaker 1: um Rashida Jones and Tommie Jones were driving for. Yeah, 32 00:01:46,920 --> 00:01:49,520 Speaker 1: it's a great point, Scarlett, and Yeah, I think different 33 00:01:49,560 --> 00:01:52,160 Speaker 1: brands have different approaches for both what they're trying to 34 00:01:52,200 --> 00:01:54,320 Speaker 1: achieve with their ads, but also who they're trying to 35 00:01:54,320 --> 00:01:56,760 Speaker 1: connect with. Um And I think so much of the 36 00:01:56,840 --> 00:01:59,760 Speaker 1: value of a commercial isn't anymore just the thirty or 37 00:01:59,800 --> 00:02:02,800 Speaker 1: six the seconds that you're in the program itself, but 38 00:02:02,880 --> 00:02:07,480 Speaker 1: all of the amplification before, after, on social media, etcetera. UM. 39 00:02:07,520 --> 00:02:09,720 Speaker 1: I think the other opportunity though, that you bring up 40 00:02:09,919 --> 00:02:12,360 Speaker 1: is um you know, if I were to say, what 41 00:02:12,560 --> 00:02:16,800 Speaker 1: is the headphone sponsor of the NFL or which company 42 00:02:16,880 --> 00:02:19,640 Speaker 1: produces the jerseys. Um, I've got all three of you 43 00:02:19,840 --> 00:02:23,000 Speaker 1: or the folksop and the audience would know that. UM. 44 00:02:23,040 --> 00:02:26,560 Speaker 1: And that's the the angle that we at Hive and 45 00:02:26,600 --> 00:02:30,320 Speaker 1: our partners at Elevated Sports Centers covered looking at yesterday's game, 46 00:02:30,440 --> 00:02:35,200 Speaker 1: which moved beyond the traditional as the fifteen and thirty 47 00:02:35,240 --> 00:02:37,680 Speaker 1: seconds and actually looked at the brands that works both 48 00:02:37,840 --> 00:02:41,200 Speaker 1: in the content. UM, and that's a massive amount of value. 49 00:02:41,360 --> 00:02:44,680 Speaker 1: So so we UH ended up estimating that there's north 50 00:02:44,680 --> 00:02:48,480 Speaker 1: of a hundred seventy million dollars of value generated inside 51 00:02:48,520 --> 00:02:51,120 Speaker 1: the game, UM from the brand that works those during 52 00:02:51,240 --> 00:02:55,959 Speaker 1: yesterday's telecast, excluding commercials. Hey damn, this is Mike Lynch 53 00:02:56,000 --> 00:02:58,840 Speaker 1: up in Boston. I'm fascinated at all this data that 54 00:02:58,919 --> 00:03:01,640 Speaker 1: you people of accumulate it over here. So are you 55 00:03:01,680 --> 00:03:05,240 Speaker 1: saying that maybe going forward that the best return might 56 00:03:05,280 --> 00:03:10,560 Speaker 1: not be that thirty or fifty second spot. I think 57 00:03:10,720 --> 00:03:14,680 Speaker 1: the interesting thing with you know, marketing is unlike the game, 58 00:03:14,720 --> 00:03:17,200 Speaker 1: where they're one winner on the field, there's lots of 59 00:03:17,240 --> 00:03:20,000 Speaker 1: brands that can claim victory. And depending on what you're 60 00:03:20,000 --> 00:03:22,920 Speaker 1: looking for, there's you have different ways to connect with 61 00:03:22,960 --> 00:03:25,959 Speaker 1: your audience and get value from the game. Um. But 62 00:03:26,040 --> 00:03:30,040 Speaker 1: you with with traditional commercials, those have been understood and 63 00:03:30,080 --> 00:03:33,240 Speaker 1: well measured for decades. UM. And the opportunity that we 64 00:03:33,320 --> 00:03:37,040 Speaker 1: see with sponsorship and branded content, UM is it represents 65 00:03:37,160 --> 00:03:40,800 Speaker 1: billions of dollars of investment. But historically there's never been 66 00:03:40,840 --> 00:03:44,760 Speaker 1: a consistent or scalable way to measure that most brands 67 00:03:44,760 --> 00:03:47,400 Speaker 1: have looked at kind of whistle to whistle measurement from 68 00:03:47,480 --> 00:03:49,120 Speaker 1: you have the time of game starts, the time of 69 00:03:49,200 --> 00:03:52,560 Speaker 1: game ends. Um but but but no one really has 70 00:03:52,600 --> 00:03:55,280 Speaker 1: put all those pieces together to to truly value how 71 00:03:55,360 --> 00:03:58,920 Speaker 1: much that exposure is worth. Um. You have both across brands, 72 00:03:58,960 --> 00:04:02,440 Speaker 1: but also across every second of every program of television 73 00:04:02,600 --> 00:04:06,240 Speaker 1: or other types of media. We're talking with Dan Klvin 74 00:04:06,400 --> 00:04:11,720 Speaker 1: with Hive Enterprise. The prices of a Super Bowl ad 75 00:04:11,800 --> 00:04:14,880 Speaker 1: on TV are just going up and up and up 76 00:04:15,280 --> 00:04:19,240 Speaker 1: and up, and it is not going to stop. The 77 00:04:19,400 --> 00:04:22,719 Speaker 1: NFL obviously is king and as long as they have 78 00:04:22,800 --> 00:04:25,839 Speaker 1: a product and a great product that they have delivered 79 00:04:25,880 --> 00:04:29,680 Speaker 1: so far this season that has just ended. Uh, the 80 00:04:29,800 --> 00:04:34,360 Speaker 1: ads are going to continue to climb. Yeah. I think 81 00:04:34,400 --> 00:04:38,240 Speaker 1: that's right. Um. You know, in general, brands want to 82 00:04:38,240 --> 00:04:42,800 Speaker 1: be associated with both where audiences are um and and 83 00:04:42,800 --> 00:04:45,240 Speaker 1: and where they find value with with the content. And 84 00:04:45,279 --> 00:04:48,120 Speaker 1: I think the NFL and live sports in general will 85 00:04:48,160 --> 00:04:50,760 Speaker 1: will always be a place that you know, brands find 86 00:04:50,839 --> 00:04:55,000 Speaker 1: heavily engaged audiences UM and value and associating in the 87 00:04:55,040 --> 00:04:56,400 Speaker 1: same way that if you were to go to an 88 00:04:56,440 --> 00:04:59,680 Speaker 1: electronics store and wanted to find a good set of headphones, 89 00:05:00,160 --> 00:05:02,719 Speaker 1: very likely if you've watched NFL games, those would be 90 00:05:02,720 --> 00:05:06,920 Speaker 1: in your consideration set because every Sunday and every Thursday 91 00:05:06,920 --> 00:05:10,719 Speaker 1: and Monday, UM, you're you're exposed to that brand um 92 00:05:10,760 --> 00:05:12,400 Speaker 1: you know within the game that you love and if 93 00:05:12,400 --> 00:05:14,320 Speaker 1: it's good enough for your coaches to hear, you know, 94 00:05:14,360 --> 00:05:16,479 Speaker 1: there's probably that presumption that it's good enough for you. 95 00:05:18,000 --> 00:05:20,960 Speaker 1: So now that you collect all this data UM from 96 00:05:21,279 --> 00:05:24,719 Speaker 1: companies that have brand exposure in the actual game rather 97 00:05:24,760 --> 00:05:28,560 Speaker 1: than during the commercial breaks, what is the takeaway for 98 00:05:29,520 --> 00:05:31,640 Speaker 1: some of the smaller companies who may not have the 99 00:05:31,680 --> 00:05:35,040 Speaker 1: budget to do their traditional advertising, but have an opportunity 100 00:05:35,160 --> 00:05:38,000 Speaker 1: to be part of the game itself, the content itself. 101 00:05:38,520 --> 00:05:41,640 Speaker 1: What is the takeaway for them in coming Super Bowls 102 00:05:41,760 --> 00:05:45,680 Speaker 1: or live sports events. Yeah, that's a great question. Scarlett, 103 00:05:45,720 --> 00:05:48,360 Speaker 1: and I think that, um, you are are our friends 104 00:05:48,360 --> 00:05:51,880 Speaker 1: that Elevate Sports Centers who we uh published the report 105 00:05:51,920 --> 00:05:54,960 Speaker 1: along with today work with your brands and right holders. 106 00:05:55,200 --> 00:05:58,840 Speaker 1: UM you're on this question every day. UM and yeah, 107 00:05:58,839 --> 00:06:00,920 Speaker 1: I think if you think of the the question which 108 00:06:00,960 --> 00:06:02,520 Speaker 1: is as simple as I want to be a part 109 00:06:02,520 --> 00:06:04,880 Speaker 1: of the NFL, there's a lot of different ways you 110 00:06:04,920 --> 00:06:07,159 Speaker 1: could do that. UM. So you could buy and add 111 00:06:07,160 --> 00:06:10,560 Speaker 1: in an NFL game. You could be an official league sponsor, 112 00:06:10,839 --> 00:06:14,040 Speaker 1: you know, like Microsoft or a Gatorade or Appose um. 113 00:06:14,120 --> 00:06:18,080 Speaker 1: You know, you could be a team sponsor um uh 114 00:06:18,240 --> 00:06:21,720 Speaker 1: you know at any of the local stadiums or or 115 00:06:21,760 --> 00:06:24,120 Speaker 1: you could be a broadcast sponsor. So with your the 116 00:06:24,200 --> 00:06:26,359 Speaker 1: NBC and the CPS and the Fox of the world. 117 00:06:26,960 --> 00:06:30,120 Speaker 1: UM and so I think increasingly with those options, you 118 00:06:30,160 --> 00:06:33,440 Speaker 1: actually need data to make those choices. UM. And so 119 00:06:33,600 --> 00:06:36,240 Speaker 1: for you know, us at high being able to produce 120 00:06:36,279 --> 00:06:39,080 Speaker 1: the data that isn't just whistle to whistle measurement on 121 00:06:39,120 --> 00:06:42,680 Speaker 1: where your brand is, but actually the land of your 122 00:06:42,720 --> 00:06:46,159 Speaker 1: sponsorship and branded content. More broadly, UM, being able to 123 00:06:46,200 --> 00:06:48,760 Speaker 1: put a value on how much that is worth helps 124 00:06:48,839 --> 00:06:51,719 Speaker 1: companies like Elevate work with their clients to be able 125 00:06:51,760 --> 00:06:54,760 Speaker 1: to make better decisions that are more informed with data. 126 00:06:57,040 --> 00:07:00,280 Speaker 1: So dan Um, some of these exposures are pretty much 127 00:07:00,279 --> 00:07:03,039 Speaker 1: by accident. Let's say that there's a bumper shot. We're 128 00:07:03,040 --> 00:07:05,480 Speaker 1: going to commercial break and they go outside the drone 129 00:07:05,560 --> 00:07:08,880 Speaker 1: or or a blimp at showing and you see Sofi, Sofi, 130 00:07:09,000 --> 00:07:12,280 Speaker 1: Sofi all over the place. That's just bonus on top 131 00:07:12,280 --> 00:07:16,840 Speaker 1: of what they pay for the naming rights. Correct. Uh, 132 00:07:16,920 --> 00:07:18,880 Speaker 1: it's a good question. I I don't know that it's 133 00:07:18,920 --> 00:07:22,560 Speaker 1: necessarily you know said differently, it's it's not necessarily committed 134 00:07:22,560 --> 00:07:25,280 Speaker 1: in contracts. But you know, you can bet that Sofi 135 00:07:25,360 --> 00:07:29,200 Speaker 1: I think paid million dollars for for a thirty year 136 00:07:29,280 --> 00:07:31,920 Speaker 1: naming rights, and a big piece of that was knowing 137 00:07:32,000 --> 00:07:34,280 Speaker 1: that that brand would be front and center, you know, 138 00:07:34,360 --> 00:07:36,920 Speaker 1: on screen. Um. You know was obviously a game like 139 00:07:37,040 --> 00:07:41,480 Speaker 1: yesterday being the largest exposure. UM, Sofi is actually an 140 00:07:41,600 --> 00:07:45,760 Speaker 1: interesting story. UM. You get given kind of the profile 141 00:07:45,840 --> 00:07:48,760 Speaker 1: of both the beautiful stadium in Los Angeles, but also 142 00:07:48,840 --> 00:07:52,160 Speaker 1: all of the funds that went into naming it. Um. 143 00:07:52,200 --> 00:07:54,480 Speaker 1: If you look at the exposure that sof I got 144 00:07:54,560 --> 00:07:57,520 Speaker 1: during the game yesterday, whistle to whistle, Um, it was 145 00:07:57,560 --> 00:08:00,880 Speaker 1: actually only about a third of what laugh Steers Stadium 146 00:08:00,960 --> 00:08:05,720 Speaker 1: naming rights sponsor Raymond James received in Tampa. UM. And 147 00:08:05,760 --> 00:08:07,880 Speaker 1: to your point, Mike, I think that, UM, you know 148 00:08:07,960 --> 00:08:11,800 Speaker 1: you can't control that perfectly, UM. But what's actually really interesting, 149 00:08:11,880 --> 00:08:14,400 Speaker 1: and I think why you're probably the most compelling part 150 00:08:14,520 --> 00:08:17,000 Speaker 1: of the data set UM and platform that we've built, 151 00:08:17,560 --> 00:08:19,280 Speaker 1: is there's no doubt that so far is going to 152 00:08:19,360 --> 00:08:21,880 Speaker 1: be a winner from this week UM. And we've already 153 00:08:21,880 --> 00:08:24,400 Speaker 1: seen it with all of the pregame coverage where you know, 154 00:08:24,480 --> 00:08:28,240 Speaker 1: not just sports but news and entertainment are broadcasting outside 155 00:08:28,240 --> 00:08:31,680 Speaker 1: of the stadium and essentially presenting UM. You have a 156 00:08:31,680 --> 00:08:34,720 Speaker 1: billboards for so fi UM, and so that ability you know, 157 00:08:34,760 --> 00:08:37,680 Speaker 1: even if it's not specifically committed, but to be able 158 00:08:37,720 --> 00:08:41,280 Speaker 1: to understand and value how much equivalent media value you're 159 00:08:41,320 --> 00:08:45,280 Speaker 1: getting from sponsorship placement UM for brand can help them 160 00:08:45,360 --> 00:08:49,000 Speaker 1: you essentially both measure you return on investment and return 161 00:08:49,040 --> 00:08:51,800 Speaker 1: on objective UM, but also pay the right amount of 162 00:08:51,880 --> 00:08:54,440 Speaker 1: money and help make those decisions UM. And then for 163 00:08:54,480 --> 00:08:56,840 Speaker 1: the rights holder, you know, if you know how much 164 00:08:57,520 --> 00:09:00,640 Speaker 1: value is being created from your assets, even if it's 165 00:09:00,640 --> 00:09:04,040 Speaker 1: not specifically what you've committed to delivering, that can actually 166 00:09:04,040 --> 00:09:07,320 Speaker 1: help inform how you price your assets. Is it a 167 00:09:07,400 --> 00:09:13,400 Speaker 1: mistake for advertisers to show off their ad online before 168 00:09:14,240 --> 00:09:18,440 Speaker 1: you see it on the Super Bowl? Because part of 169 00:09:18,440 --> 00:09:21,480 Speaker 1: the excitement of seeing the ads is that, hey, I 170 00:09:21,520 --> 00:09:24,840 Speaker 1: want to see it debuted. But sometimes it sneaks over 171 00:09:25,000 --> 00:09:30,120 Speaker 1: on onto on certain websites and it kind of takes 172 00:09:30,120 --> 00:09:32,240 Speaker 1: the luster away from it. Am I right or am 173 00:09:32,240 --> 00:09:37,800 Speaker 1: I wrong? I think the answer is probably in the 174 00:09:37,840 --> 00:09:42,520 Speaker 1: respective brands. UM. The challenge with the Super Bowl and 175 00:09:42,640 --> 00:09:45,520 Speaker 1: especially with commercials, you know, even though they're they're kind 176 00:09:45,520 --> 00:09:47,760 Speaker 1: of a second game in and of themselves, you know, 177 00:09:47,800 --> 00:09:50,800 Speaker 1: there's still lots of brands competing for attention, and you're 178 00:09:50,880 --> 00:09:53,960 Speaker 1: counting on that one thirty second moment in time to 179 00:09:54,000 --> 00:09:58,800 Speaker 1: be able to capture uh, the attention of the world. Uh. 180 00:09:58,840 --> 00:10:01,920 Speaker 1: And so the benefit of pre releases and post releases 181 00:10:02,160 --> 00:10:05,280 Speaker 1: is that creates reach and exposure, um so that you 182 00:10:05,280 --> 00:10:08,160 Speaker 1: have more opportunities to meet folks. But I think there 183 00:10:08,280 --> 00:10:11,320 Speaker 1: there's a broader interesting point of you know, if you're 184 00:10:11,400 --> 00:10:15,080 Speaker 1: kind of placing your bed on exposure on those thirty seconds, 185 00:10:15,080 --> 00:10:18,680 Speaker 1: that does kee up again the value in relative terms 186 00:10:18,720 --> 00:10:22,319 Speaker 1: of sponsorship placement. UM. So if you look at yesterday's game, 187 00:10:23,000 --> 00:10:26,600 Speaker 1: the top eight brands by duration if you take your 188 00:10:26,640 --> 00:10:30,640 Speaker 1: commercials and or time in the game, actually didn't air 189 00:10:30,679 --> 00:10:33,040 Speaker 1: a commercial in the game. UM. So if you take 190 00:10:33,080 --> 00:10:36,280 Speaker 1: a brand like Nike, they had a cumulative amount of 191 00:10:36,320 --> 00:10:39,160 Speaker 1: minutes that were more than forty six minutes of duration 192 00:10:39,400 --> 00:10:43,800 Speaker 1: that there were slushes on jerseys, on cleats, on gloves. Um. 193 00:10:44,000 --> 00:10:45,719 Speaker 1: And if you go down the list, um, you know, 194 00:10:46,160 --> 00:10:48,880 Speaker 1: I think in total we had uh eight or nine 195 00:10:48,920 --> 00:10:51,880 Speaker 1: brands had more than a minute of exposure. Um. And 196 00:10:51,920 --> 00:10:53,959 Speaker 1: obviously you don't have the side and sound in the 197 00:10:53,960 --> 00:10:56,400 Speaker 1: theater of telling a commercial. But if you think of 198 00:10:56,440 --> 00:11:00,320 Speaker 1: opportunities to associate your brand with the NFL and just 199 00:11:00,440 --> 00:11:02,840 Speaker 1: be top of mind with the world's audience, Um, there's 200 00:11:02,840 --> 00:11:08,480 Speaker 1: were really compelling opportunity with sponsorships and grand content. Do 201 00:11:08,600 --> 00:11:10,880 Speaker 1: companies reach out to you to say or to ask, 202 00:11:10,920 --> 00:11:14,400 Speaker 1: how can I be the next Nike to affiliate myself 203 00:11:14,520 --> 00:11:18,960 Speaker 1: align myself more closely with the NFL? Yeah? So so 204 00:11:19,080 --> 00:11:21,840 Speaker 1: so at high of our our business is really focused. 205 00:11:21,920 --> 00:11:26,320 Speaker 1: So UM one set back work predominantly. UM. You a 206 00:11:26,360 --> 00:11:30,000 Speaker 1: technology company in the AI space, UM, you know, high 207 00:11:30,000 --> 00:11:33,680 Speaker 1: health company use AI to interpret video, image, text, and 208 00:11:33,720 --> 00:11:37,160 Speaker 1: audio UM and historically clients and build their own solutions 209 00:11:37,160 --> 00:11:40,440 Speaker 1: around our technology for diverse out of use cases, whether 210 00:11:40,480 --> 00:11:43,320 Speaker 1: that's you know, out of domain like content moderation for 211 00:11:43,400 --> 00:11:48,440 Speaker 1: social networks or content based on targeting for video publishers. UM. And. 212 00:11:48,480 --> 00:11:50,400 Speaker 1: Part of our focus over the last couple of years 213 00:11:50,520 --> 00:11:53,720 Speaker 1: has been selectively building an application where UM you have 214 00:11:53,760 --> 00:11:56,800 Speaker 1: for ourselves for select use cases. UM. And in this 215 00:11:56,880 --> 00:12:00,240 Speaker 1: space specifically, we saw market where the adoption of quote 216 00:12:00,320 --> 00:12:03,240 Speaker 1: unquote AI was early put, the demand for data and 217 00:12:03,320 --> 00:12:07,200 Speaker 1: insights AI could produced was very UNDERSTOBDU and so the 218 00:12:07,240 --> 00:12:10,600 Speaker 1: media and advertising industry broadly was was an area UM 219 00:12:10,640 --> 00:12:13,120 Speaker 1: yet that we saw opportunity in and within its sports 220 00:12:13,120 --> 00:12:17,120 Speaker 1: sponsorship was an area that was right for disruption historically 221 00:12:17,880 --> 00:12:21,840 Speaker 1: characterized by very ad hoc and mostly manual measurement, which 222 00:12:21,880 --> 00:12:23,920 Speaker 1: was frustrating clients. UM. You know, we would have to 223 00:12:23,960 --> 00:12:26,400 Speaker 1: wait weeks long for data and still only have part 224 00:12:26,400 --> 00:12:28,800 Speaker 1: of the picture. UM. And so we took you know, 225 00:12:28,880 --> 00:12:32,319 Speaker 1: kind of our core technologies of world class logo detection, 226 00:12:32,520 --> 00:12:36,320 Speaker 1: object detection, speech text models is building blocks UM and 227 00:12:36,320 --> 00:12:39,160 Speaker 1: then actually set up our own content ingestion pipeline so 228 00:12:39,200 --> 00:12:42,800 Speaker 1: that we could feed always on data into those models, UH, 229 00:12:42,840 --> 00:12:45,280 Speaker 1: and then built out a point like platform to put 230 00:12:45,320 --> 00:12:49,040 Speaker 1: your more comprehensive and granular data in the hands of brands, 231 00:12:49,080 --> 00:12:52,400 Speaker 1: agencies and rightholders. UM. So today we worked with with 232 00:12:52,520 --> 00:12:55,520 Speaker 1: the broad and diverse set of rights holders and TV 233 00:12:55,640 --> 00:12:58,640 Speaker 1: networks you know like Disney, UM, some of the world's 234 00:12:58,679 --> 00:13:02,200 Speaker 1: largest and most active and and sponsorship like Anheuser Bush 235 00:13:02,240 --> 00:13:05,720 Speaker 1: or Walmart UM and a whole host of agencies and 236 00:13:05,720 --> 00:13:10,360 Speaker 1: control Soultency partners including Elevate Sports Ventures, who we published 237 00:13:10,679 --> 00:13:13,480 Speaker 1: last night's report with who can kind of take our 238 00:13:13,559 --> 00:13:16,240 Speaker 1: data but then use that with their clients to turn 239 00:13:16,280 --> 00:13:20,880 Speaker 1: it into really actionable insights. Dan, can you put a 240 00:13:21,000 --> 00:13:26,319 Speaker 1: value on the promotional spots run by NBC last night 241 00:13:26,480 --> 00:13:31,240 Speaker 1: promoting Peacock, the Crime Time shows, uh, their newscasts. I 242 00:13:31,280 --> 00:13:35,600 Speaker 1: saw that we were promoted, UM, the Olympics and anything 243 00:13:35,600 --> 00:13:39,800 Speaker 1: else that's going to run in Telemundo. UM. You know, 244 00:13:40,000 --> 00:13:43,360 Speaker 1: they're giving up seven million dollars every thirty seconds to 245 00:13:43,440 --> 00:13:47,079 Speaker 1: run a promotional spot for which they received no monetary 246 00:13:47,200 --> 00:13:51,600 Speaker 1: value immediately. But is there a long term of uptick 247 00:13:51,679 --> 00:13:55,520 Speaker 1: for them? It's a great question, and that's that's always 248 00:13:55,520 --> 00:13:58,640 Speaker 1: the opportunity cost of promotional units as you know, the 249 00:13:58,640 --> 00:14:02,040 Speaker 1: opportunity to advantage your own platform, um, you know, versus 250 00:14:02,080 --> 00:14:05,600 Speaker 1: to realize revenue UM. I think historically and and it's 251 00:14:05,600 --> 00:14:08,280 Speaker 1: probably only become even more more the case in a 252 00:14:08,320 --> 00:14:12,520 Speaker 1: streaming world with Peacock and Disney Class and HBO Max um. 253 00:14:12,520 --> 00:14:15,240 Speaker 1: But many shows launched through the Super Bowl UM and 254 00:14:15,320 --> 00:14:19,120 Speaker 1: historically your Last Night NBC let Intee Olympics. But for 255 00:14:19,160 --> 00:14:22,880 Speaker 1: many decades networks have kind of taken their biggest bet 256 00:14:23,160 --> 00:14:27,120 Speaker 1: on on essentially the show that follows the Super Bowl. UM. 257 00:14:27,200 --> 00:14:29,680 Speaker 1: And so it's a delicate balance between what you sell 258 00:14:29,880 --> 00:14:34,040 Speaker 1: versus what did you use? Um. But but but definitely 259 00:14:34,120 --> 00:14:40,080 Speaker 1: something that creates now you either way. Dan Klvin, who 260 00:14:40,240 --> 00:14:44,600 Speaker 1: is with Hive Enterprise. Dan, you are just full of 261 00:14:44,640 --> 00:14:47,800 Speaker 1: knowledge when it comes to advertising, and I appreciate you 262 00:14:48,200 --> 00:14:50,960 Speaker 1: just taking the time out and and giving me a 263 00:14:51,000 --> 00:14:54,080 Speaker 1: good education. We appreciate it. Thank you so much, Da, 264 00:14:55,120 --> 00:14:57,600 Speaker 1: thanks so much. Appreciate talking with you all and enjoyed 265 00:14:57,640 --> 00:14:59,560 Speaker 1: the game last night and fun to get to extended 266 00:14:59,560 --> 00:15:03,960 Speaker 1: into mon in morning. Thank you. This is the Bloomberg 267 00:15:03,960 --> 00:15:07,400 Speaker 1: Business of Sports podcast. Catch us here each and every Monday, 268 00:15:07,400 --> 00:15:10,000 Speaker 1: Wednesday and Thursday. Exploring the world of money in sports 269 00:15:10,040 --> 00:15:12,880 Speaker 1: on Michael Barr. Catch me on Twitter at Big Bark Sports. 270 00:15:13,160 --> 00:15:15,480 Speaker 1: I'm Scarlet Fou. You can follow me on Twitter at 271 00:15:15,520 --> 00:15:17,880 Speaker 1: Scarlet Fou. And I'm Mike Lynch. You can follow me 272 00:15:17,920 --> 00:15:21,080 Speaker 1: at Lynch e w CPV. You're listening to Bloomberg Business 273 00:15:21,080 --> 00:15:23,880 Speaker 1: of Sports on Bloomberg Radio around the world.