1 00:00:07,600 --> 00:00:11,119 Speaker 1: Welcome to Strictly Business Varieties, weekly podcast featuring conversations with 2 00:00:11,160 --> 00:00:14,120 Speaker 1: industry leaders about the business of media and entertainment. I'm 3 00:00:14,160 --> 00:00:18,280 Speaker 1: Tyler Aquallina with Luminated Intelligence formerly known as Variety Intelligence Platform. 4 00:00:18,520 --> 00:00:20,799 Speaker 1: If you followed the TV industry in recent years, you 5 00:00:20,840 --> 00:00:22,640 Speaker 1: know that there's been more and more controversy over the 6 00:00:22,720 --> 00:00:25,439 Speaker 1: Nielsen ratings system that has long measured TV viewership in 7 00:00:25,480 --> 00:00:27,800 Speaker 1: the US. With the rise of streaming, a handful of 8 00:00:27,800 --> 00:00:30,760 Speaker 1: companies have begun to challenge Nielsen's dominance of TV ratings 9 00:00:30,840 --> 00:00:34,000 Speaker 1: and their use in programming and advertising decisions. One of 10 00:00:34,080 --> 00:00:36,760 Speaker 1: those companies is video Amp, which leverages first party data 11 00:00:36,760 --> 00:00:40,120 Speaker 1: to measure audiences across platforms. My guest today is Jenny Wall, 12 00:00:40,400 --> 00:00:42,800 Speaker 1: video AM's chief marketing officer, who's leading the charge for 13 00:00:42,840 --> 00:00:46,240 Speaker 1: adoption of antocurrency. Jenny comes from a long and storied 14 00:00:46,240 --> 00:00:48,240 Speaker 1: background in the TV business. She was part of the 15 00:00:48,280 --> 00:00:50,640 Speaker 1: team that coined It's not TV, It's HBO back in 16 00:00:50,680 --> 00:00:53,360 Speaker 1: the nineties, and later helped both Netflix and Hulu roll 17 00:00:53,400 --> 00:00:56,240 Speaker 1: out their slates of premium original content. We talked about 18 00:00:56,240 --> 00:00:58,520 Speaker 1: both what it takes to bring audiences to shows and 19 00:00:58,560 --> 00:01:00,720 Speaker 1: what it takes to measure those audiences in our complex 20 00:01:00,760 --> 00:01:04,000 Speaker 1: era of TV. Jenny Wall, Welcome to Strictly Business. It's 21 00:01:04,000 --> 00:01:08,680 Speaker 1: great to have you. Thank you here. So obviously there's 22 00:01:08,959 --> 00:01:11,840 Speaker 1: a lot to talk about with video amp and the 23 00:01:12,240 --> 00:01:16,360 Speaker 1: landscape of TV measurement right now we're having this conversation 24 00:01:16,440 --> 00:01:20,959 Speaker 1: in the midst of yet another controversy over that. But 25 00:01:21,400 --> 00:01:23,920 Speaker 1: first I wanted to talk about your background a little bit, 26 00:01:24,240 --> 00:01:27,600 Speaker 1: just because you've had a front row seat to so 27 00:01:27,720 --> 00:01:31,880 Speaker 1: many of the biggest, you know, transformations in the TV 28 00:01:32,000 --> 00:01:35,400 Speaker 1: landscape over the last couple of decades. You came from 29 00:01:35,720 --> 00:01:39,040 Speaker 1: marketing at HBO when it was launching its first original series, 30 00:01:39,480 --> 00:01:42,280 Speaker 1: same thing at Netflix when it was launching its slate 31 00:01:42,319 --> 00:01:45,600 Speaker 1: of originals, and then the same thing again at Hulu. 32 00:01:45,680 --> 00:01:49,200 Speaker 1: So I'm curious how have those experiences shaped your perspective 33 00:01:49,280 --> 00:01:51,480 Speaker 1: on the business and your approach to what you do. 34 00:01:51,680 --> 00:01:54,360 Speaker 2: I'd like to first say that I've just been super 35 00:01:54,480 --> 00:01:57,520 Speaker 2: lucky by chance to be at all those places during 36 00:01:57,560 --> 00:02:00,600 Speaker 2: the disruption, and also being able to help the those 37 00:02:00,640 --> 00:02:04,040 Speaker 2: brands and to what they what they stand for now, 38 00:02:04,680 --> 00:02:07,000 Speaker 2: and being able to launch shows that actually helped the 39 00:02:07,080 --> 00:02:11,240 Speaker 2: identity was just just an incredible experience for me. So 40 00:02:11,960 --> 00:02:14,799 Speaker 2: I think I've always believed, you know, that that TV 41 00:02:14,960 --> 00:02:18,680 Speaker 2: can change the world, and that you know, emotionally connecting 42 00:02:18,760 --> 00:02:23,200 Speaker 2: people is is really really important. And I think being 43 00:02:23,240 --> 00:02:25,840 Speaker 2: able to be at HBO and just trying to find 44 00:02:26,280 --> 00:02:29,960 Speaker 2: at each place what is the thing that makes it 45 00:02:30,040 --> 00:02:33,799 Speaker 2: different and why is it worth your time and how 46 00:02:33,840 --> 00:02:36,760 Speaker 2: will this change your life? So, for example, at HBO, 47 00:02:36,919 --> 00:02:39,280 Speaker 2: I think you know, it's not TV. At HBO was 48 00:02:39,360 --> 00:02:43,280 Speaker 2: really born out of that. It was everything TV was not. 49 00:02:43,480 --> 00:02:46,360 Speaker 2: It did not have commercials, you could swear you know, 50 00:02:46,400 --> 00:02:49,760 Speaker 2: you could show sex on TV, and they were just different. 51 00:02:50,080 --> 00:02:53,360 Speaker 2: So I think being able to utilize that tagline that 52 00:02:53,480 --> 00:02:56,400 Speaker 2: says so much and so little is this that it's 53 00:02:56,520 --> 00:02:59,960 Speaker 2: it's not what your regular television is, it's something better. 54 00:03:00,600 --> 00:03:03,680 Speaker 2: And I think just also just having incredible shows to 55 00:03:03,760 --> 00:03:07,800 Speaker 2: work with and incredible material, and then also having creators 56 00:03:07,800 --> 00:03:10,040 Speaker 2: that are very willing to work with you in all 57 00:03:10,080 --> 00:03:13,720 Speaker 2: the places that I've been has been really incredible, and 58 00:03:14,280 --> 00:03:17,799 Speaker 2: I think they all just connect authentically with the audiences 59 00:03:17,880 --> 00:03:20,280 Speaker 2: there the choices that were made, and I would say 60 00:03:20,280 --> 00:03:25,040 Speaker 2: at Netflix again, we had to prove that this new 61 00:03:25,080 --> 00:03:29,720 Speaker 2: behavior of dropping everything at once also streaming was worth 62 00:03:29,760 --> 00:03:34,200 Speaker 2: your time and so leaning into those behaviors with like 63 00:03:34,400 --> 00:03:36,960 Speaker 2: being lucky enough to launch House of Cards with David 64 00:03:36,960 --> 00:03:40,680 Speaker 2: Fincher and being able to prove that you might binge 65 00:03:40,720 --> 00:03:43,360 Speaker 2: it all at once, but we can also help you 66 00:03:43,480 --> 00:03:48,000 Speaker 2: find additional shows that you will love, and that model worked. 67 00:03:48,360 --> 00:03:51,360 Speaker 2: We used a lot of the new behaviors like binging, 68 00:03:51,640 --> 00:03:55,560 Speaker 2: watching ahead in all of our campaigns, So not only 69 00:03:55,600 --> 00:03:59,120 Speaker 2: were we launching the shows, we were launching the new 70 00:03:59,160 --> 00:04:01,960 Speaker 2: behavior to show how this could fit into your life. 71 00:04:02,520 --> 00:04:05,080 Speaker 2: And then at Hulu, you know, we had to also 72 00:04:05,120 --> 00:04:07,600 Speaker 2: show why are we different and we're not trying to 73 00:04:07,680 --> 00:04:11,960 Speaker 2: replace Netflix, but why you should also add us because 74 00:04:12,000 --> 00:04:15,960 Speaker 2: we're an incredible supplement to it because you could get 75 00:04:16,080 --> 00:04:19,800 Speaker 2: shows next day. And then also our original programming, like 76 00:04:20,200 --> 00:04:22,520 Speaker 2: I was lucky enough to work on Handmaid's Tale and 77 00:04:22,680 --> 00:04:25,640 Speaker 2: that just dropped at a very cultural moment with the 78 00:04:25,680 --> 00:04:30,080 Speaker 2: twenty sixteen election, and being able to you know, relate 79 00:04:30,400 --> 00:04:33,800 Speaker 2: sometimes on a bad way, but really catch the cultural 80 00:04:33,880 --> 00:04:37,200 Speaker 2: zeitdeist of what was going on, and having those women 81 00:04:37,279 --> 00:04:39,840 Speaker 2: walk around, you know, at south By Southwest and the 82 00:04:39,880 --> 00:04:44,320 Speaker 2: red robes and the bonnets not speaking to anyone. Actually, 83 00:04:44,720 --> 00:04:47,080 Speaker 2: there was a headline that said, Hulu is scaring the 84 00:04:47,120 --> 00:04:49,520 Speaker 2: shit out of people here, and so it's again it's 85 00:04:49,520 --> 00:04:54,480 Speaker 2: just eliciting and emotion and connection and a relatability in 86 00:04:54,560 --> 00:04:58,159 Speaker 2: some way, and then also just things like we have 87 00:04:58,200 --> 00:05:01,120 Speaker 2: all seasons of Seinfeld. We're there just always trying to 88 00:05:01,120 --> 00:05:04,520 Speaker 2: find what is different and why people should care. So 89 00:05:04,560 --> 00:05:07,040 Speaker 2: I think that's what I've learned on those being at 90 00:05:07,040 --> 00:05:09,080 Speaker 2: those places, you know, is. 91 00:05:09,040 --> 00:05:11,839 Speaker 1: That that differentiation, it sounds like, is really what's the 92 00:05:11,880 --> 00:05:15,160 Speaker 1: key in terms of establishing a network or a streamer 93 00:05:15,240 --> 00:05:17,560 Speaker 1: as a viewing destination. Is that right? 94 00:05:18,000 --> 00:05:18,919 Speaker 3: Yeah? I think it is. 95 00:05:18,960 --> 00:05:21,480 Speaker 2: And I'll just use another Netflix example, like the watching 96 00:05:21,480 --> 00:05:23,760 Speaker 2: a head one. We listened to our consumers. That's the 97 00:05:23,760 --> 00:05:25,760 Speaker 2: other thing is a brand is not what you say 98 00:05:25,800 --> 00:05:27,880 Speaker 2: it is, it's what they say it is. And so 99 00:05:28,000 --> 00:05:31,240 Speaker 2: if you see a behavior like Netflix was watching ahead, 100 00:05:31,400 --> 00:05:34,240 Speaker 2: and so we did a whole commercial about lie to 101 00:05:34,279 --> 00:05:36,240 Speaker 2: your partner that you didn't watch ahead, but it was 102 00:05:36,279 --> 00:05:39,080 Speaker 2: all there for you, so you kind of people were lying, 103 00:05:39,600 --> 00:05:43,440 Speaker 2: And so we coined this term Netflix adultery, and we 104 00:05:43,480 --> 00:05:47,200 Speaker 2: actually interviewed like a couple thousand people and asked them 105 00:05:47,240 --> 00:05:50,000 Speaker 2: if they've ever cheated on their partner or friend and 106 00:05:50,080 --> 00:05:52,240 Speaker 2: it was like fifty six percent that people had and 107 00:05:52,279 --> 00:05:54,960 Speaker 2: then we were able to get Brian Williams on MSNBC 108 00:05:55,120 --> 00:05:57,200 Speaker 2: to read it as if it was a true stat 109 00:05:57,440 --> 00:06:00,480 Speaker 2: So again it's like having not taking yourself too seriously 110 00:06:01,000 --> 00:06:03,600 Speaker 2: as well, but also just listening to your consumer Handmais 111 00:06:03,640 --> 00:06:06,839 Speaker 2: Tell is another great example. People were terrified, and so 112 00:06:06,960 --> 00:06:08,839 Speaker 2: we were going to market that one way, and then 113 00:06:08,920 --> 00:06:12,800 Speaker 2: with women's rights and LGBTQ rights, et cetera, a little 114 00:06:12,839 --> 00:06:15,800 Speaker 2: bit more at stake. I'll say during that time we 115 00:06:15,880 --> 00:06:18,599 Speaker 2: really leaned into that and that's again why we put 116 00:06:18,600 --> 00:06:20,440 Speaker 2: those women out there to scare the shit out of people, 117 00:06:20,480 --> 00:06:23,240 Speaker 2: to say that this could be real. Yeah, I think 118 00:06:23,240 --> 00:06:25,920 Speaker 2: it's just connecting on those levels of behavior and sort 119 00:06:25,920 --> 00:06:27,360 Speaker 2: of an emotional feeling. 120 00:06:27,920 --> 00:06:30,960 Speaker 1: I'm also curious about kind of the art of turning 121 00:06:31,360 --> 00:06:34,200 Speaker 1: a good show into a hit show. You know, how 122 00:06:34,200 --> 00:06:37,880 Speaker 1: how has that process changed as the TV landscape has 123 00:06:37,920 --> 00:06:39,919 Speaker 1: really expanded and become more and more crowded. 124 00:06:40,680 --> 00:06:43,039 Speaker 2: Well, the sad thing is is there's so many good 125 00:06:43,040 --> 00:06:46,800 Speaker 2: shows now, so to make a hit again, I think 126 00:06:46,800 --> 00:06:50,080 Speaker 2: it's just even more important that you have to break 127 00:06:50,080 --> 00:06:53,320 Speaker 2: through that zeitgeist, especially with the event of social and 128 00:06:53,440 --> 00:06:56,480 Speaker 2: influencers like Hunting Wives is a great example. I didn't 129 00:06:56,520 --> 00:06:59,920 Speaker 2: work on that, but that was the soapiest, bingeable sh 130 00:07:00,040 --> 00:07:03,239 Speaker 2: show that I think was living on a different network 131 00:07:03,279 --> 00:07:06,560 Speaker 2: and they actually brought it over to Netflix and it 132 00:07:06,600 --> 00:07:10,480 Speaker 2: was a huge hit. But basically as people were talking 133 00:07:10,560 --> 00:07:12,920 Speaker 2: about it and it had sort of the red blue, 134 00:07:12,960 --> 00:07:13,360 Speaker 2: it had. 135 00:07:13,240 --> 00:07:14,600 Speaker 3: Just had all the right ingredients. 136 00:07:14,640 --> 00:07:18,760 Speaker 2: So I do think that just marketing alone, like spending 137 00:07:18,800 --> 00:07:21,240 Speaker 2: money on marketing, doesn't work anymore. You really have to 138 00:07:21,280 --> 00:07:23,480 Speaker 2: figure out how do I get the right people to 139 00:07:23,520 --> 00:07:27,000 Speaker 2: talk about this, And so I think that's what's changed 140 00:07:27,040 --> 00:07:29,760 Speaker 2: to make something hit is to get the right people 141 00:07:29,920 --> 00:07:32,840 Speaker 2: and the right momentum and catch that wave to make 142 00:07:32,880 --> 00:07:36,480 Speaker 2: it actually spread. And the great thing about streaming is 143 00:07:36,520 --> 00:07:40,320 Speaker 2: that you can watch it three weeks later, so that 144 00:07:40,360 --> 00:07:43,440 Speaker 2: can continue to just move on. So you're hopefully happy, 145 00:07:43,800 --> 00:07:45,200 Speaker 2: lucky enough to grab that wave. 146 00:07:45,520 --> 00:07:47,720 Speaker 1: I think that's a good transition into talking about your 147 00:07:47,960 --> 00:07:50,760 Speaker 1: work at video Amp. You've kind of moved from this 148 00:07:50,840 --> 00:07:55,400 Speaker 1: business of bringing audiences to these shows to measuring the 149 00:07:55,440 --> 00:07:59,080 Speaker 1: audiences for those shows, and you know the content out there, 150 00:07:59,080 --> 00:08:00,559 Speaker 1: and how did you end up taking that path? 151 00:08:01,280 --> 00:08:04,360 Speaker 2: Oh, I'm always looking for new things to do or disrupt, 152 00:08:05,040 --> 00:08:07,200 Speaker 2: and even I know we didn't talk about my time 153 00:08:07,240 --> 00:08:10,080 Speaker 2: at Gimlet, but I did decide to take a podcasting 154 00:08:10,120 --> 00:08:13,160 Speaker 2: the CMO job because I didn't understand the EAR and 155 00:08:13,200 --> 00:08:15,320 Speaker 2: I understood the I, but I was like, why is 156 00:08:15,360 --> 00:08:20,640 Speaker 2: the ear so like less expensive and less important? And 157 00:08:20,800 --> 00:08:23,320 Speaker 2: I was lucky enough again to work with advertisers to 158 00:08:23,720 --> 00:08:27,960 Speaker 2: create podcasts, to actually tie a podcast like with ancestry 159 00:08:27,960 --> 00:08:30,840 Speaker 2: dot com, or to work with networks to do I 160 00:08:30,840 --> 00:08:33,960 Speaker 2: always would say, like, why are you leaving your consumer 161 00:08:34,000 --> 00:08:35,959 Speaker 2: when they go in the car, Like if they're watching 162 00:08:36,000 --> 00:08:37,800 Speaker 2: a TV show, why don't you follow them in the 163 00:08:37,840 --> 00:08:42,120 Speaker 2: car so you can keep engagement up. So always going somewhere, 164 00:08:42,160 --> 00:08:44,839 Speaker 2: I think that I'm learning and for this next, you 165 00:08:44,920 --> 00:08:46,800 Speaker 2: know I did. I spent the last three years prior 166 00:08:46,760 --> 00:08:50,920 Speaker 2: to this as CMO of Nickelodeon and then my boss 167 00:08:50,960 --> 00:08:53,760 Speaker 2: from HBO days. Actually he's still to this day, and 168 00:08:54,000 --> 00:08:56,280 Speaker 2: I love him for saying that Jenny and I came 169 00:08:56,360 --> 00:08:59,679 Speaker 2: up with it's not TV, it's HBO, but I didn't 170 00:08:59,679 --> 00:09:00,560 Speaker 2: come up with it by. 171 00:09:00,480 --> 00:09:03,920 Speaker 3: The way he did. But he still says that we 172 00:09:04,000 --> 00:09:05,200 Speaker 3: did it together, which I love. 173 00:09:05,520 --> 00:09:09,079 Speaker 1: That's a refreshing moment of sharing credit in this industry exactly. 174 00:09:09,120 --> 00:09:10,760 Speaker 2: But he was my boss when I was in my 175 00:09:10,840 --> 00:09:14,560 Speaker 2: twenties and very pivotal, and he was on the board 176 00:09:14,600 --> 00:09:18,320 Speaker 2: of this company, and he's a marketer at heart. And 177 00:09:18,800 --> 00:09:23,360 Speaker 2: I've always been just really upset that cmos get fired 178 00:09:23,400 --> 00:09:28,880 Speaker 2: every three years because they can't necessarily justify their spend 179 00:09:29,559 --> 00:09:33,480 Speaker 2: very well, and that I think measurement is broken. I 180 00:09:33,600 --> 00:09:36,720 Speaker 2: think that we should not have a monopoly. No other 181 00:09:37,040 --> 00:09:40,040 Speaker 2: country has a monopoly. You would never put all your 182 00:09:40,080 --> 00:09:45,240 Speaker 2: stock in one stock like we need diversification, we need optionality. 183 00:09:45,840 --> 00:09:49,680 Speaker 2: And so I was coming in to disrupt to say 184 00:09:49,679 --> 00:09:53,800 Speaker 2: there should be another source of truth because I think 185 00:09:53,880 --> 00:09:58,880 Speaker 2: that everything is getting misrepresented and it's by one person. 186 00:09:59,200 --> 00:10:01,720 Speaker 2: I also think that we waste forty percent of our 187 00:10:01,760 --> 00:10:04,400 Speaker 2: dollars still, and I want to help cmos keep their 188 00:10:04,480 --> 00:10:07,120 Speaker 2: job and I want to help people be able to 189 00:10:07,200 --> 00:10:10,679 Speaker 2: talk with their CFO about cross channel measurement. And I 190 00:10:10,720 --> 00:10:13,959 Speaker 2: spend this money and I have an outcome, whether it's 191 00:10:13,960 --> 00:10:16,960 Speaker 2: a sale or subscription or visit to a website, I 192 00:10:17,040 --> 00:10:20,560 Speaker 2: actually can show that cross these channels that I actually 193 00:10:21,080 --> 00:10:25,360 Speaker 2: created a sale. And I want to help marketers and 194 00:10:25,480 --> 00:10:29,880 Speaker 2: marketing departments look like revenue generators, not cost centers, and 195 00:10:29,920 --> 00:10:33,920 Speaker 2: they're mostly seen as cost centers. So he asked me 196 00:10:33,960 --> 00:10:36,679 Speaker 2: to come over here, and I was like, let's do 197 00:10:36,800 --> 00:10:39,640 Speaker 2: it so and we want to sort of like take 198 00:10:39,679 --> 00:10:41,959 Speaker 2: on the man to be honest David and Goliath story. 199 00:10:42,240 --> 00:10:44,560 Speaker 2: I love that type of thing of being able to 200 00:10:44,960 --> 00:10:46,560 Speaker 2: show that I think there's a better way. 201 00:10:46,880 --> 00:10:49,959 Speaker 1: You've been alluding a lot to the Nielsen ratings and 202 00:10:50,040 --> 00:10:53,079 Speaker 1: the dominance they've had over the TV measurement space for 203 00:10:53,320 --> 00:10:56,600 Speaker 1: most of the history of TV in the United States. Really, 204 00:10:57,160 --> 00:10:59,319 Speaker 1: I think people may know the name of video Amp 205 00:10:59,320 --> 00:11:02,439 Speaker 1: if they've been reading about these Nielsen alternatives that have 206 00:11:02,480 --> 00:11:05,440 Speaker 1: been emerging. But makes you guys different in terms of 207 00:11:05,440 --> 00:11:07,079 Speaker 1: what you do well. 208 00:11:07,320 --> 00:11:10,319 Speaker 2: First and foremost, we've been doing big data for or 209 00:11:10,440 --> 00:11:13,280 Speaker 2: ten years, and as Peter likes to say, they're in 210 00:11:13,280 --> 00:11:16,320 Speaker 2: their rookie season with big data, so this is their 211 00:11:16,360 --> 00:11:19,080 Speaker 2: first year. Actually they're doing big data plus panel and 212 00:11:19,160 --> 00:11:21,480 Speaker 2: as we've seen, there's been a lot If you looked 213 00:11:21,480 --> 00:11:24,920 Speaker 2: at the Wall Street Journal NFL story yesterday where the 214 00:11:25,000 --> 00:11:28,200 Speaker 2: NFL thinks they're being undercounted and our numbers do show 215 00:11:28,280 --> 00:11:31,760 Speaker 2: higher numbers per NFL, but that's because our numbers are 216 00:11:31,920 --> 00:11:35,120 Speaker 2: higher fidelity. We use a much bigger base. So we 217 00:11:35,280 --> 00:11:38,839 Speaker 2: have forty million homes, sixty five million devices. They were 218 00:11:38,840 --> 00:11:42,080 Speaker 2: measuring everything off of a forty two thousand panel home. 219 00:11:42,920 --> 00:11:45,440 Speaker 2: Now they've brought in big data on top of that, 220 00:11:46,400 --> 00:11:48,960 Speaker 2: but those are still weighted. You should ask Nielsen how 221 00:11:49,000 --> 00:11:51,320 Speaker 2: they wait those numbers, because I don't know exactly. 222 00:11:51,920 --> 00:11:54,839 Speaker 1: Just to clarify quickly, So big data, that's first party 223 00:11:54,920 --> 00:11:59,040 Speaker 1: data coming from companies like Roku and comcasts that are 224 00:11:59,160 --> 00:12:01,080 Speaker 1: actually carrying this content. 225 00:12:02,160 --> 00:12:04,439 Speaker 2: Yes, it's all of that, and it's all the way 226 00:12:04,480 --> 00:12:06,120 Speaker 2: down to like we work with cap to fy to 227 00:12:06,160 --> 00:12:10,000 Speaker 2: look at search intent, we work with you know, Circona 228 00:12:10,080 --> 00:12:11,920 Speaker 2: to look at food traffic. So it's just springing in 229 00:12:11,960 --> 00:12:14,480 Speaker 2: tons of data. And now that you're talking data, also, 230 00:12:14,600 --> 00:12:17,200 Speaker 2: we have the only patented clean room, which has six 231 00:12:17,240 --> 00:12:21,880 Speaker 2: different identity providers, which provides an identity spine that it 232 00:12:21,880 --> 00:12:25,240 Speaker 2: gets about a ninety percent match rate of when you bring. 233 00:12:25,040 --> 00:12:26,000 Speaker 3: That first party data. 234 00:12:26,040 --> 00:12:28,600 Speaker 2: So we do have first party data that we bring 235 00:12:28,640 --> 00:12:31,040 Speaker 2: in from all the publishers and they trust us with 236 00:12:31,080 --> 00:12:33,720 Speaker 2: that data because of our patented clean room, which no 237 00:12:33,760 --> 00:12:34,560 Speaker 2: one else has. 238 00:12:34,720 --> 00:12:37,440 Speaker 1: Now you've touched on this a little bit, but you know, 239 00:12:37,480 --> 00:12:40,080 Speaker 1: can you expand on why is there this need in 240 00:12:40,240 --> 00:12:44,960 Speaker 1: the industry from your perspective for these new viewership currencies 241 00:12:45,000 --> 00:12:48,120 Speaker 1: and kind of a new way of looking at these audiences. 242 00:12:48,679 --> 00:12:50,280 Speaker 2: I'm going to just go all the way down to 243 00:12:50,280 --> 00:12:53,120 Speaker 2: the consumer. There's going to be less shows because shows 244 00:12:53,120 --> 00:12:55,280 Speaker 2: are going to get canceled. Quilbeer got canceled, they said 245 00:12:55,320 --> 00:12:57,440 Speaker 2: because it costs too much. Well, when we did our 246 00:12:57,440 --> 00:13:00,440 Speaker 2: analysis that I can send over to you, we showed 247 00:13:00,559 --> 00:13:04,000 Speaker 2: that our ratings were significantly higher in twenty five to 248 00:13:04,000 --> 00:13:08,319 Speaker 2: fifty four, and if you model that with advertising, the 249 00:13:08,360 --> 00:13:11,440 Speaker 2: show wouldn't have lost money. So we did the same 250 00:13:11,480 --> 00:13:13,560 Speaker 2: thing for Fox News. So I had a liberal and 251 00:13:13,600 --> 00:13:16,240 Speaker 2: a conservative side, and we showed higher numbers for Fox News. 252 00:13:17,440 --> 00:13:19,000 Speaker 2: I in the end, think there's going to be less 253 00:13:19,040 --> 00:13:21,880 Speaker 2: choice for consumers. I think some of the volatility that's 254 00:13:21,920 --> 00:13:24,839 Speaker 2: going on with the numbers right now is it might 255 00:13:24,880 --> 00:13:27,199 Speaker 2: put the long tails out of business, so we might 256 00:13:27,240 --> 00:13:29,080 Speaker 2: not have the hallmarks and the A and e's of 257 00:13:29,120 --> 00:13:31,800 Speaker 2: the world, and that really, as a consumer and a 258 00:13:31,880 --> 00:13:33,439 Speaker 2: lover of entertainment. 259 00:13:33,840 --> 00:13:35,920 Speaker 3: Really really scares me. 260 00:13:36,679 --> 00:13:39,720 Speaker 2: So I think in the next year we could see 261 00:13:39,840 --> 00:13:42,160 Speaker 2: a big change if we don't get the numbers right. 262 00:13:42,240 --> 00:13:45,319 Speaker 2: Because right now, as you've seen in the press, the 263 00:13:45,440 --> 00:13:49,920 Speaker 2: numbers with Nielsen and big data and panel extremely volatile. 264 00:13:50,400 --> 00:13:52,800 Speaker 2: So when you're trying to plan on an upfront and 265 00:13:52,880 --> 00:13:56,720 Speaker 2: sell your advertising and then those numbers flip back and forth, 266 00:13:57,080 --> 00:13:59,280 Speaker 2: you may not have any more ad space to sell. 267 00:13:59,320 --> 00:14:02,800 Speaker 2: You can't fill your aus. It's a huge problem. And 268 00:14:02,840 --> 00:14:05,680 Speaker 2: so I think having optionality and our numbers we don't 269 00:14:05,720 --> 00:14:08,480 Speaker 2: promise are bigger because sometimes they're not bigger than Nielsen's. 270 00:14:08,800 --> 00:14:11,959 Speaker 2: We just have a different methodology that we use. And 271 00:14:12,040 --> 00:14:14,679 Speaker 2: like for the NFL, though we have our numbers or 272 00:14:14,679 --> 00:14:18,800 Speaker 2: twenty two percent higher than Nielsen, So the NFL is thinking, god, 273 00:14:18,800 --> 00:14:22,200 Speaker 2: my audience is more popular or than we think it is. 274 00:14:22,480 --> 00:14:24,960 Speaker 2: And we're not saying put Nielsen out of business. What 275 00:14:25,000 --> 00:14:27,520 Speaker 2: we're saying is you need to have optionality to be 276 00:14:27,520 --> 00:14:30,880 Speaker 2: able to compare what you believe. And also I think 277 00:14:30,960 --> 00:14:32,960 Speaker 2: just have leverage in the marketplace. If you have one 278 00:14:33,040 --> 00:14:37,920 Speaker 2: person that is dominating and with contracts, you don't really 279 00:14:37,920 --> 00:14:41,840 Speaker 2: have much leveraging negotiating power. And then I would like 280 00:14:41,880 --> 00:14:43,720 Speaker 2: to go back to the out of home thing, because 281 00:14:43,760 --> 00:14:47,440 Speaker 2: like with football, coming up. That's thirteen percent or fifteen 282 00:14:47,480 --> 00:14:50,880 Speaker 2: percent of football games are watched in bars and restaurants. 283 00:14:51,320 --> 00:14:53,480 Speaker 3: And the out of home. 284 00:14:53,280 --> 00:14:56,640 Speaker 2: Product that we have that's very different than our competitor, 285 00:14:56,720 --> 00:15:00,680 Speaker 2: our Legacy, is we are in hundreds of thousands. We 286 00:15:00,720 --> 00:15:03,120 Speaker 2: have hundreds of thousands of TVs in bars, and we 287 00:15:03,200 --> 00:15:07,120 Speaker 2: use geo targeting or fencing to figure out who's actually there, 288 00:15:07,720 --> 00:15:11,800 Speaker 2: and the Legacy partner uses a people meter that relies 289 00:15:11,840 --> 00:15:15,600 Speaker 2: on sound, and from the last data that I have, 290 00:15:15,800 --> 00:15:17,640 Speaker 2: I think thirteen percent of bars actually even have the 291 00:15:17,680 --> 00:15:22,640 Speaker 2: sound on. So if you're missing fifteen percent of an 292 00:15:22,680 --> 00:15:25,760 Speaker 2: audience for a live football game, that is pretty big 293 00:15:25,800 --> 00:15:28,160 Speaker 2: for brands, and pretty big for the NFL, and pretty 294 00:15:28,200 --> 00:15:30,920 Speaker 2: big for the teams, and pretty big for the advertisers 295 00:15:30,960 --> 00:15:33,840 Speaker 2: if you're missing. And then the second piece is we're 296 00:15:33,840 --> 00:15:37,160 Speaker 2: the clear winner in advanced audiences. And I just have 297 00:15:37,240 --> 00:15:39,640 Speaker 2: to say, I don't know why anybody buys on demo 298 00:15:40,000 --> 00:15:43,840 Speaker 2: anymore unless you're a toilet paper or a chip company, 299 00:15:44,120 --> 00:15:47,000 Speaker 2: because we have the opportunity to buy on advanced audiences, 300 00:15:47,040 --> 00:15:49,160 Speaker 2: meaning that you can get much more efficient. And then 301 00:15:49,160 --> 00:15:52,120 Speaker 2: you have these infinite pods on like Amazon and Netflix 302 00:15:52,600 --> 00:15:54,840 Speaker 2: where you could you could serve the ad to the 303 00:15:54,880 --> 00:15:56,480 Speaker 2: right person and get a better outcome. 304 00:15:56,880 --> 00:15:59,640 Speaker 1: You're talking in terms of audience targeting rather than relying 305 00:15:59,680 --> 00:16:00,600 Speaker 1: on graphics. 306 00:16:00,840 --> 00:16:03,400 Speaker 2: Yeah, people are still buying P two plus, you know, 307 00:16:03,600 --> 00:16:06,080 Speaker 2: or eighteen to forty nine. It's mind boggling to me, 308 00:16:06,160 --> 00:16:08,720 Speaker 2: to be honest, that more people don't buy advanceed audiences. 309 00:16:08,760 --> 00:16:11,560 Speaker 2: But we are the clear winner with all of our 310 00:16:11,600 --> 00:16:15,920 Speaker 2: partners in delivering advanced audiences and outcomes that go with that. 311 00:16:16,480 --> 00:16:19,840 Speaker 1: So what is your relationship or what are your relationships 312 00:16:19,920 --> 00:16:23,360 Speaker 1: like with some of these partners, because I think from 313 00:16:23,360 --> 00:16:25,560 Speaker 1: what I've read, and you're not trying to replace Nielsen, 314 00:16:25,720 --> 00:16:27,760 Speaker 1: it's kind of bringing you guys on as a supplement 315 00:16:27,800 --> 00:16:30,040 Speaker 1: to Nielsen an option. So you know, what are those 316 00:16:30,080 --> 00:16:33,720 Speaker 1: conversations that you have with these companies. What do you 317 00:16:33,720 --> 00:16:35,840 Speaker 1: guys talk about in terms of what can bring to 318 00:16:35,880 --> 00:16:38,680 Speaker 1: the table and how you guys can be used as 319 00:16:38,680 --> 00:16:39,280 Speaker 1: another option. 320 00:16:39,960 --> 00:16:41,920 Speaker 2: One is the advanced audiences for sure, is that we 321 00:16:41,960 --> 00:16:44,320 Speaker 2: can help you target to people and efficiently spend your 322 00:16:44,360 --> 00:16:45,760 Speaker 2: dollars to get the outcomes you want. 323 00:16:46,000 --> 00:16:47,040 Speaker 3: That's the big one. 324 00:16:47,120 --> 00:16:49,920 Speaker 2: I think the other one is a clear we call 325 00:16:49,960 --> 00:16:51,720 Speaker 2: it valid, but our identity spine. 326 00:16:51,760 --> 00:16:53,680 Speaker 3: So first party data is like. 327 00:16:53,680 --> 00:16:55,920 Speaker 2: King in right now right, and there's all these wall 328 00:16:55,920 --> 00:16:59,240 Speaker 2: of gardens that are grading their own homework. We've broken 329 00:16:59,280 --> 00:17:02,200 Speaker 2: through those walkgard gardens because people trust us with their data. 330 00:17:02,760 --> 00:17:05,439 Speaker 2: And also I think advertisers are asking now for not 331 00:17:05,560 --> 00:17:08,399 Speaker 2: a third party to at least validate those numbers that 332 00:17:08,440 --> 00:17:09,840 Speaker 2: are coming from first party data. 333 00:17:10,200 --> 00:17:11,159 Speaker 3: But what people want. 334 00:17:11,040 --> 00:17:13,160 Speaker 2: To do is figure out how to use their first 335 00:17:13,160 --> 00:17:14,760 Speaker 2: party data, so they have tons of it. 336 00:17:14,840 --> 00:17:15,080 Speaker 3: Right. 337 00:17:15,119 --> 00:17:19,600 Speaker 2: So if we had a partner when they're a large 338 00:17:19,760 --> 00:17:23,240 Speaker 2: television provider, and they gave us their first party data, 339 00:17:23,280 --> 00:17:26,639 Speaker 2: and you know if without using o ID spine, they 340 00:17:26,640 --> 00:17:30,000 Speaker 2: had a thirty four percent match rate, meaning once it 341 00:17:30,119 --> 00:17:31,840 Speaker 2: went through and went out to the internet and tried 342 00:17:31,880 --> 00:17:35,359 Speaker 2: to find those people in a privacy complainant way, it 343 00:17:35,440 --> 00:17:39,160 Speaker 2: only actually reached thirty four percent of them. In through 344 00:17:39,160 --> 00:17:41,520 Speaker 2: our clean room with our sex identity spines, we reached 345 00:17:41,600 --> 00:17:44,119 Speaker 2: we got them up to ninety percent. So one of 346 00:17:44,160 --> 00:17:46,040 Speaker 2: the things is we're actually going to help you reach 347 00:17:46,080 --> 00:17:48,080 Speaker 2: the people and not waste money. So I say a 348 00:17:48,080 --> 00:17:51,240 Speaker 2: lot of things is waste less, sell more. Or even 349 00:17:51,280 --> 00:17:55,199 Speaker 2: when I went down to St. Jude's nonprofit helping kids, 350 00:17:55,280 --> 00:17:57,920 Speaker 2: I said, waste less, save more kids. And I think 351 00:17:58,160 --> 00:18:01,199 Speaker 2: with everything on the line right now, the better matching 352 00:18:01,240 --> 00:18:03,760 Speaker 2: you can get, the better outcomes. And that's what we 353 00:18:03,800 --> 00:18:07,440 Speaker 2: provide with our high fidelity and we're you know, our 354 00:18:07,480 --> 00:18:11,760 Speaker 2: promise is to provide transparency with don't think other people 355 00:18:11,760 --> 00:18:15,800 Speaker 2: do by transparency, be a great client partner, very transparent 356 00:18:15,880 --> 00:18:19,199 Speaker 2: that help automate the system and make your life easier. 357 00:18:19,240 --> 00:18:21,720 Speaker 2: We have APIs that people can work directly with. We 358 00:18:21,800 --> 00:18:24,720 Speaker 2: have a lot of people in our planner, so it's 359 00:18:24,720 --> 00:18:27,159 Speaker 2: a one stop shop for media buyer. So it's make 360 00:18:27,200 --> 00:18:29,520 Speaker 2: your life a hell of a lot easier. We can 361 00:18:29,760 --> 00:18:34,960 Speaker 2: just better calculate what that audience is and hopefully drive 362 00:18:35,480 --> 00:18:38,640 Speaker 2: larger sales or larger people showing up at the movie theater. 363 00:18:39,119 --> 00:18:42,719 Speaker 1: People love to complain about Nielsen, but what is your 364 00:18:42,760 --> 00:18:46,320 Speaker 1: sense of really the appetite in the marketplace for bringing 365 00:18:46,320 --> 00:18:48,840 Speaker 1: a new currency to the table in this industry that 366 00:18:48,920 --> 00:18:52,520 Speaker 1: has been so entrenched in this one standard for so long. 367 00:18:52,640 --> 00:18:54,760 Speaker 3: This is what baffles me a lot. 368 00:18:55,080 --> 00:18:58,520 Speaker 2: And as a marketer, I'm trying to help people understand 369 00:18:58,600 --> 00:19:01,719 Speaker 2: that change is heart. That's the one one of the reasons, 370 00:19:02,040 --> 00:19:04,439 Speaker 2: and I think people are afraid to be honest with you, 371 00:19:04,480 --> 00:19:06,600 Speaker 2: I think they're afraid to rock to brod. I think 372 00:19:06,600 --> 00:19:09,080 Speaker 2: a lot of these people have five year contracts, so 373 00:19:09,160 --> 00:19:11,680 Speaker 2: they think they don't have any more money and they're 374 00:19:11,720 --> 00:19:15,440 Speaker 2: kind of locked in. But what we try to help 375 00:19:15,440 --> 00:19:18,600 Speaker 2: people understand is even if you actually could take a 376 00:19:18,680 --> 00:19:22,760 Speaker 2: very small amount it and we're our models different, we 377 00:19:22,800 --> 00:19:25,960 Speaker 2: don't have a flat fee, were based on usage, so 378 00:19:26,800 --> 00:19:28,480 Speaker 2: in the end you're going to get more return on 379 00:19:28,520 --> 00:19:31,480 Speaker 2: your money. But I think that people there's a lot 380 00:19:31,480 --> 00:19:33,640 Speaker 2: of people out there that are still four years from 381 00:19:33,680 --> 00:19:35,920 Speaker 2: retirement or like and I'm just going to not rock 382 00:19:35,960 --> 00:19:39,840 Speaker 2: the boat, or everything's going crazy in all the mergers, etc. 383 00:19:40,320 --> 00:19:43,639 Speaker 3: That this just adds another what they think is a 384 00:19:43,640 --> 00:19:47,880 Speaker 3: piece of complexity. Change is hard, but it's worth it. 385 00:19:48,160 --> 00:19:50,400 Speaker 2: And that's what I'm trying to prove or help prove, 386 00:19:50,560 --> 00:19:53,239 Speaker 2: is that it is absolutely worth it. One for your 387 00:19:53,359 --> 00:19:58,240 Speaker 2: job and two for this industry. We have to save shows, 388 00:19:58,359 --> 00:20:02,080 Speaker 2: and in order to do that, advertising is the thing 389 00:20:02,160 --> 00:20:05,600 Speaker 2: that keeps this boat moving. I have a speech I 390 00:20:05,680 --> 00:20:07,920 Speaker 2: give where I say advertising is going to save the world, 391 00:20:07,960 --> 00:20:09,840 Speaker 2: and part of it is I've worked at the places 392 00:20:09,880 --> 00:20:11,000 Speaker 2: that we're trying to destroy it. 393 00:20:11,040 --> 00:20:13,320 Speaker 3: I worked at HBO with no advertising. I worked at 394 00:20:13,320 --> 00:20:14,520 Speaker 3: Netflix no advertising. 395 00:20:15,240 --> 00:20:17,960 Speaker 2: But what everyone realized once they got into the game 396 00:20:18,000 --> 00:20:21,840 Speaker 2: and Netflix also is that subscriber fees are not going 397 00:20:21,920 --> 00:20:24,200 Speaker 2: to keep it alive. 398 00:20:24,320 --> 00:20:25,160 Speaker 3: There's just no way. 399 00:20:25,880 --> 00:20:28,360 Speaker 2: And so you see, like even when I was at Hulu, 400 00:20:28,400 --> 00:20:30,960 Speaker 2: we had a paid, an ad free tier, and a 401 00:20:30,960 --> 00:20:33,800 Speaker 2: AD tier, and the ARPU is higher on the AD tier, 402 00:20:34,200 --> 00:20:38,040 Speaker 2: so meaning you get subscription fees and you got advertising fees, 403 00:20:38,080 --> 00:20:41,000 Speaker 2: and so you know, you see some people pushing people 404 00:20:41,040 --> 00:20:44,600 Speaker 2: into the paid things, like even Amazon flipped the switch 405 00:20:44,600 --> 00:20:48,320 Speaker 2: and you had to opt opt out to get ads, 406 00:20:48,480 --> 00:20:52,160 Speaker 2: so they're there. We're realizing that advertising is this thing 407 00:20:52,200 --> 00:20:54,720 Speaker 2: that keeps it going. And if we get advertising right, 408 00:20:55,000 --> 00:20:58,199 Speaker 2: and also if we get CTV right where we're not, 409 00:20:58,520 --> 00:21:01,479 Speaker 2: people are buying Reach and free Quincy still, which is 410 00:21:01,480 --> 00:21:04,159 Speaker 2: not bad, but in certain instances, as you know, you 411 00:21:04,280 --> 00:21:08,119 Speaker 2: probably watch CTV and you're like, if they show me 412 00:21:08,160 --> 00:21:11,000 Speaker 2: that ad one more time, I am going to like 413 00:21:11,359 --> 00:21:14,160 Speaker 2: throw something at the TV. And what people don't understand 414 00:21:14,240 --> 00:21:16,760 Speaker 2: is that they're reaching their frequency numbers, but it's to 415 00:21:16,800 --> 00:21:19,280 Speaker 2: the same person like thirty times and guess what that's 416 00:21:19,320 --> 00:21:22,880 Speaker 2: brand damaging. So it's like we have to get advertising right, 417 00:21:22,920 --> 00:21:24,520 Speaker 2: we have to get the frequency right, we have to 418 00:21:24,560 --> 00:21:27,359 Speaker 2: get targeting right, and we have to deliver on the 419 00:21:27,400 --> 00:21:30,440 Speaker 2: promises that we said. And I think everybody's just caught 420 00:21:30,520 --> 00:21:34,480 Speaker 2: up in the middle between advertisers and media, buyers and sellers. 421 00:21:34,640 --> 00:21:37,080 Speaker 3: And there is a better way, and there is a 422 00:21:37,080 --> 00:21:37,600 Speaker 3: simpler way. 423 00:21:37,680 --> 00:21:40,080 Speaker 2: And I think bottom line is your life can be 424 00:21:40,280 --> 00:21:42,200 Speaker 2: much easier if if. 425 00:21:42,080 --> 00:21:45,280 Speaker 3: You just put a little work into it. And it's 426 00:21:45,320 --> 00:21:46,440 Speaker 3: not really that much tech work. 427 00:21:46,440 --> 00:21:47,879 Speaker 2: I think a lot of people think that they have 428 00:21:47,920 --> 00:21:49,639 Speaker 2: to integrate new systems and it's not. 429 00:21:50,359 --> 00:21:53,639 Speaker 1: My final question is how do you envision or what 430 00:21:53,680 --> 00:21:57,359 Speaker 1: are your hopes for the industry, you know, realistically kind 431 00:21:57,400 --> 00:22:01,479 Speaker 1: of embracing these alternative currencies and being more willing to 432 00:22:01,760 --> 00:22:02,800 Speaker 1: rock the boat, as you say. 433 00:22:02,920 --> 00:22:06,080 Speaker 2: My hope in the end is that we all hold 434 00:22:06,080 --> 00:22:11,280 Speaker 2: hands together and realize that the customer needs a good experience. 435 00:22:11,880 --> 00:22:16,159 Speaker 2: The customer also wants to get ads that actually pertain 436 00:22:16,240 --> 00:22:18,880 Speaker 2: to them. That's what the brands want. They don't want 437 00:22:18,920 --> 00:22:20,960 Speaker 2: us to sell something to somebody that doesn't need that. 438 00:22:21,560 --> 00:22:24,400 Speaker 2: My goal is I hope cmos keep their job longer 439 00:22:24,480 --> 00:22:26,560 Speaker 2: than three years because they're able to look like revenue 440 00:22:26,600 --> 00:22:30,000 Speaker 2: generators and show they actually do increase sales, and then 441 00:22:30,359 --> 00:22:32,960 Speaker 2: also that people don't just rely on mmms. You know, 442 00:22:33,080 --> 00:22:35,639 Speaker 2: I can't believe it's still around. It's a fine tool, 443 00:22:36,160 --> 00:22:38,879 Speaker 2: a media mixed model. A lot of people can't afford it, 444 00:22:38,920 --> 00:22:40,720 Speaker 2: and they can only do it once or twice a year. 445 00:22:40,720 --> 00:22:45,000 Speaker 2: And it's backwards looking, so you should be planning for 446 00:22:45,080 --> 00:22:49,200 Speaker 2: your future, not on backwards information that's probably seasonal. So 447 00:22:49,600 --> 00:22:51,360 Speaker 2: you should be able to be and we have real 448 00:22:51,400 --> 00:22:54,560 Speaker 2: time attribution data, you should be able to pivot pretty 449 00:22:54,600 --> 00:22:58,120 Speaker 2: quickly and easily in an API environment as we get 450 00:22:58,359 --> 00:23:02,080 Speaker 2: closer to AI your media to optimize it in real time. 451 00:23:02,160 --> 00:23:05,159 Speaker 2: My end goal would be to get marketers smarter and 452 00:23:05,280 --> 00:23:09,080 Speaker 2: marketers like a lethal weapon, to be honest in the 453 00:23:09,080 --> 00:23:11,480 Speaker 2: C suite, to be able to justify what we do. 454 00:23:12,480 --> 00:23:15,240 Speaker 1: It's a long road ahead, I'm sure, but it sounds 455 00:23:15,280 --> 00:23:18,439 Speaker 1: like let's have a good, good plan of attack. I 456 00:23:18,440 --> 00:23:20,840 Speaker 1: want to thank you again for joining us today and 457 00:23:20,880 --> 00:23:21,920 Speaker 1: thanks for great conversation. 458 00:23:22,520 --> 00:23:24,160 Speaker 3: Thank you, Tyler, I really appreciate it. 459 00:23:24,400 --> 00:23:28,040 Speaker 2: Thanks for listening. Please leave a review at the podcast 460 00:23:28,040 --> 00:23:30,879 Speaker 2: platform of your choice. We love to hear from listeners. 461 00:23:31,119 --> 00:23:33,439 Speaker 1: Please go to Variety dot com and sign up for 462 00:23:33,520 --> 00:23:37,600 Speaker 1: the free weekly Strictly Business newsletter, and don't forget to 463 00:23:37,640 --> 00:23:40,720 Speaker 2: Tune in next week for another episode of Strictly Business.