1 00:00:07,960 --> 00:00:12,480 Speaker 1: Welcome to Strictly Business Varieties, weekly podcasts featuring conversations with 2 00:00:12,560 --> 00:00:16,759 Speaker 1: industry leaders about the business of media and entertainment. I'm 3 00:00:16,800 --> 00:00:20,680 Speaker 1: Cynthia Littleton, co editor in chief of Variety Today. My 4 00:00:20,760 --> 00:00:24,239 Speaker 1: guest is Adam Ware, vice president and General Manager of 5 00:00:24,360 --> 00:00:28,880 Speaker 1: National Networks and Platforms for Sinclair Broadcast Group, where is 6 00:00:28,920 --> 00:00:32,520 Speaker 1: knee deep in the streaming wars, but rather than global domination, 7 00:00:32,800 --> 00:00:35,879 Speaker 1: he's fighting for AD dollars in local markets around the country. 8 00:00:36,600 --> 00:00:40,959 Speaker 1: Sinclair is investing big in Stir, an AD supported platform 9 00:00:41,040 --> 00:00:44,800 Speaker 1: that aggregates local newscasts and other content from Sinclair's nearly 10 00:00:44,840 --> 00:00:49,360 Speaker 1: two hundred TV stations, where, who previously worked in distribution 11 00:00:49,440 --> 00:00:52,879 Speaker 1: for Fox in its early days and for Barry Diller's 12 00:00:53,000 --> 00:00:57,320 Speaker 1: nineteen nineties media ventures, shares insights from the experience of 13 00:00:57,400 --> 00:01:00,480 Speaker 1: building Stir over the past two years. In our com versation. 14 00:01:00,880 --> 00:01:04,880 Speaker 1: Adam Ware, vice president and General manager of Sinclair Broadcast 15 00:01:04,920 --> 00:01:09,200 Speaker 1: Groups National Networks and Platforms Group, thank you so much 16 00:01:09,240 --> 00:01:13,080 Speaker 1: for joining us. You're welcome. I think the podcast is 17 00:01:13,120 --> 00:01:15,399 Speaker 1: now concluded with the length of my title, and I 18 00:01:15,400 --> 00:01:18,480 Speaker 1: want to start by talking about one of the services 19 00:01:18,520 --> 00:01:21,520 Speaker 1: that you've run, which is called Stir and it's a 20 00:01:21,720 --> 00:01:25,160 Speaker 1: it's a streaming platform and a supported streaming platform. And 21 00:01:25,200 --> 00:01:27,200 Speaker 1: why it was intriguing to me and I wanted to 22 00:01:27,200 --> 00:01:30,479 Speaker 1: talk to you today was that we have the press 23 00:01:30,520 --> 00:01:33,480 Speaker 1: certainly is guilty of sort of shaping the streaming wars 24 00:01:33,680 --> 00:01:37,880 Speaker 1: as certainly a global race, a global chase that is 25 00:01:37,959 --> 00:01:41,760 Speaker 1: unprecedented in its in its geographical scope, and it is 26 00:01:41,800 --> 00:01:43,760 Speaker 1: definitely one of the things that is changing the game 27 00:01:43,880 --> 00:01:47,440 Speaker 1: for the the biggest media conglomerates. But that doesn't mean 28 00:01:47,440 --> 00:01:50,120 Speaker 1: that there isn't a you know, a ground game to 29 00:01:50,200 --> 00:01:53,480 Speaker 1: be had in streaming in local markets. And that is 30 00:01:53,520 --> 00:01:57,560 Speaker 1: where Stir and Sinclair with its many many stations comes in. 31 00:01:58,080 --> 00:02:02,480 Speaker 1: Tell us tell us about Stir, which is, if I'm 32 00:02:02,480 --> 00:02:05,920 Speaker 1: not mistaken, coming on about two years old, and tell 33 00:02:06,000 --> 00:02:08,920 Speaker 1: us sort of all the all the elements that you 34 00:02:09,000 --> 00:02:11,360 Speaker 1: have built in to stirre and tell us how this 35 00:02:11,360 --> 00:02:14,760 Speaker 1: this AD supported business is doing in this you know, 36 00:02:14,840 --> 00:02:17,640 Speaker 1: as we get here to the end of there is 37 00:02:17,680 --> 00:02:22,040 Speaker 1: a it's a national service, and I think the line 38 00:02:22,040 --> 00:02:24,240 Speaker 1: I like to use to explain it is it's streaming 39 00:02:24,240 --> 00:02:28,880 Speaker 1: TV from your local TV station for free, so as 40 00:02:28,919 --> 00:02:33,239 Speaker 1: opposed to being sort of this national service coming from somewhere. Uh, 41 00:02:33,840 --> 00:02:35,760 Speaker 1: I would love that in a focus group, if I 42 00:02:35,800 --> 00:02:40,960 Speaker 1: were to ask them where is stir made, they would go, oh, 43 00:02:41,000 --> 00:02:46,440 Speaker 1: that's that's from Fox right or or Como in Seattle, like, 44 00:02:46,600 --> 00:02:49,120 Speaker 1: that's my from my local TV station. So at the 45 00:02:49,320 --> 00:02:54,360 Speaker 1: at the core, that was putting content that was uniquely local, 46 00:02:54,680 --> 00:02:58,560 Speaker 1: front and center on a platform on a service. UM. 47 00:02:59,000 --> 00:03:02,360 Speaker 1: Stir is not an afronym for anything. Ster literally came 48 00:03:02,520 --> 00:03:06,040 Speaker 1: from two parts. One is the challenger side of it, 49 00:03:06,160 --> 00:03:08,919 Speaker 1: like stirring it up, and the other part is as 50 00:03:08,960 --> 00:03:12,800 Speaker 1: a mix of content, so stirring up the content. And 51 00:03:13,760 --> 00:03:16,480 Speaker 1: at the core of this was local news as as 52 00:03:16,520 --> 00:03:22,960 Speaker 1: a as a fundamental you know, uh, foundation of the service, 53 00:03:23,720 --> 00:03:30,320 Speaker 1: complimented by other local programming, a complimented by the local 54 00:03:30,360 --> 00:03:34,040 Speaker 1: syndicated hits that the stations owned and have the streaming 55 00:03:34,120 --> 00:03:38,240 Speaker 1: rights to in their marketplace. Uh. And then go uh 56 00:03:38,600 --> 00:03:42,040 Speaker 1: and build out a free service out of that, but 57 00:03:42,200 --> 00:03:45,120 Speaker 1: not not an on demand service because at the core 58 00:03:45,200 --> 00:03:48,000 Speaker 1: of this was a couple a couple of sort of 59 00:03:48,080 --> 00:03:55,280 Speaker 1: key factors. The first factor was, Okay, do you have 60 00:03:55,360 --> 00:03:57,640 Speaker 1: to have stations the top d M A s to 61 00:03:57,720 --> 00:04:03,400 Speaker 1: make this work? And the reality is that when you 62 00:04:03,440 --> 00:04:07,480 Speaker 1: look at where streaming is the strongest. It doesn't match 63 00:04:07,680 --> 00:04:12,520 Speaker 1: up to the top d m A right, so UM, 64 00:04:13,120 --> 00:04:17,320 Speaker 1: there's a there's Nielsen put out an interesting study last year. 65 00:04:17,360 --> 00:04:20,720 Speaker 1: I think they analyze where are the strongest d m 66 00:04:20,760 --> 00:04:26,520 Speaker 1: as for streaming? UM. The number one d m A 67 00:04:26,600 --> 00:04:30,640 Speaker 1: for streaming I think is Austin. SE. Of that d 68 00:04:30,800 --> 00:04:36,280 Speaker 1: m A streams, Cleveland watches the most amount per day 69 00:04:36,600 --> 00:04:41,000 Speaker 1: on a streaming basis. UM. Austin and Salt Lake City 70 00:04:41,000 --> 00:04:43,680 Speaker 1: are tied for number two among the meter markets for 71 00:04:44,400 --> 00:04:48,520 Speaker 1: the most that owned streaming devices right now. New York, 72 00:04:48,680 --> 00:04:51,200 Speaker 1: l A and Chicago are up there always because they're 73 00:04:51,279 --> 00:04:56,960 Speaker 1: huge populations, but it's actually it's a different footprint when 74 00:04:56,960 --> 00:04:59,880 Speaker 1: you look at streaming, and Saint Claire's footprint matched up 75 00:05:00,040 --> 00:05:04,200 Speaker 1: really nicely with that. So Austin we have a pretty 76 00:05:04,200 --> 00:05:08,760 Speaker 1: strong TV station in Austin, UH and Salt Lake City 77 00:05:08,760 --> 00:05:10,840 Speaker 1: we have a pretty strong TV station in Salt Lake 78 00:05:10,839 --> 00:05:14,039 Speaker 1: City and so on. So that served as the basis 79 00:05:14,160 --> 00:05:17,800 Speaker 1: of the footprint for can we launch a national service 80 00:05:17,880 --> 00:05:23,120 Speaker 1: that was locally targeted at scale and and appeal to 81 00:05:23,560 --> 00:05:28,039 Speaker 1: markets where they were more likely to stream? Right? I 82 00:05:28,080 --> 00:05:31,920 Speaker 1: think the second part of streaming is that um Nielsen, 83 00:05:32,200 --> 00:05:37,320 Speaker 1: the same Nielsen study, I think the stat was somewhere 84 00:05:37,360 --> 00:05:44,960 Speaker 1: around fifty or so. Uh watch traditional local TV news mhm. Right, 85 00:05:44,960 --> 00:05:48,280 Speaker 1: So there's always assumption in streamers don't watch news at 86 00:05:48,279 --> 00:05:51,919 Speaker 1: all and don't watch TV stations. You're watching short form 87 00:05:52,000 --> 00:05:56,120 Speaker 1: content produced for five cents on YouTube. That's right, That's right. 88 00:05:56,200 --> 00:05:58,720 Speaker 1: And and the reality is I'm sure people are, but 89 00:06:00,000 --> 00:06:04,400 Speaker 1: they're actually watching local TV news um. And so that 90 00:06:04,480 --> 00:06:08,440 Speaker 1: became the basic fundamentals. Did we have the markets? Did 91 00:06:08,480 --> 00:06:10,480 Speaker 1: we have a footprint that can make this work at 92 00:06:10,520 --> 00:06:13,640 Speaker 1: scale in the right d M s? And the answer 93 00:06:13,720 --> 00:06:18,279 Speaker 1: is yes, right, did we um? Did we have the 94 00:06:18,360 --> 00:06:23,520 Speaker 1: right genres to work locally? Yeah? Right? And Stir features 95 00:06:23,520 --> 00:06:28,360 Speaker 1: a hundred thousand hours of live local news a year. Uh. 96 00:06:28,560 --> 00:06:33,240 Speaker 1: Did we have a corporate owner that was willing to 97 00:06:33,320 --> 00:06:37,640 Speaker 1: invest uh and not look for an immediate r o 98 00:06:37,800 --> 00:06:41,719 Speaker 1: I that year because streaming takes investment. Absolutely, because Sinclair 99 00:06:41,720 --> 00:06:44,680 Speaker 1: as a history of that. All those ingredients went into start. 100 00:06:45,279 --> 00:06:47,479 Speaker 1: Let me ask you how does it work with the 101 00:06:47,520 --> 00:06:51,200 Speaker 1: station's how did the state? How do how does the 102 00:06:51,240 --> 00:06:55,120 Speaker 1: monetization work? Does the monitors that you know, if if 103 00:06:55,160 --> 00:07:00,160 Speaker 1: if the COMO six o'clock News gets you know, five 104 00:07:00,240 --> 00:07:02,599 Speaker 1: hundred thousand views. How do they get Is there a 105 00:07:02,600 --> 00:07:05,000 Speaker 1: process that they get credit for that? Or is that? 106 00:07:05,360 --> 00:07:08,760 Speaker 1: Or do or do the stations like you know, they 107 00:07:08,800 --> 00:07:11,680 Speaker 1: can sort of contribute their their news and their advertising 108 00:07:11,720 --> 00:07:14,960 Speaker 1: to the greater good of the broader Sinclair Broadcast Group. 109 00:07:15,000 --> 00:07:16,640 Speaker 1: Can you talk about how that works just on a 110 00:07:16,680 --> 00:07:21,200 Speaker 1: business proposition with having that many stations contributing to this service? Sure? 111 00:07:21,400 --> 00:07:24,400 Speaker 1: Sure so. Uh there's two parts that one part is 112 00:07:24,480 --> 00:07:29,880 Speaker 1: that um, local O T T O T T revenues 113 00:07:30,840 --> 00:07:35,800 Speaker 1: UH are exploding on a local basis. And and and 114 00:07:35,840 --> 00:07:39,120 Speaker 1: that's just the sale of O T T inventory. Um, 115 00:07:39,240 --> 00:07:43,000 Speaker 1: you actually get a higher CPM on a local basis 116 00:07:43,000 --> 00:07:46,040 Speaker 1: than you would on a national basis. It's a similar 117 00:07:46,080 --> 00:07:50,040 Speaker 1: between network and local spot right, the same sort of differences. 118 00:07:50,160 --> 00:07:55,480 Speaker 1: And the TV stations are have sales teams on the 119 00:07:55,520 --> 00:08:00,480 Speaker 1: street talking to local TV advertisers who want to be 120 00:08:01,040 --> 00:08:04,240 Speaker 1: in O T T UH in this kind of the 121 00:08:04,280 --> 00:08:06,240 Speaker 1: same way. Those same aviturs way back when wanted to 122 00:08:06,240 --> 00:08:08,840 Speaker 1: be in cable. But back then the TV station wasn't 123 00:08:08,880 --> 00:08:11,880 Speaker 1: selling cable, they were just selling their TV station. Well, 124 00:08:11,880 --> 00:08:14,360 Speaker 1: now they're selling their TV station and they're selling O 125 00:08:14,520 --> 00:08:18,480 Speaker 1: T T inventory and the conversations are within largely with 126 00:08:18,640 --> 00:08:24,960 Speaker 1: endemic advertisers. Uh. Yes, in large parts about endemic advertisers. 127 00:08:25,520 --> 00:08:30,760 Speaker 1: Um that want to now find campaigns across multiple platforms. 128 00:08:31,240 --> 00:08:35,360 Speaker 1: But then you also see new advertisers. Um, I'll give you. 129 00:08:35,360 --> 00:08:39,680 Speaker 1: I'll give you an example. Right, So in Bowie, Texas, 130 00:08:40,800 --> 00:08:44,120 Speaker 1: which is located between Fort Worth and at Ardmore, I've 131 00:08:44,280 --> 00:08:47,520 Speaker 1: I've actually been there a long time ago. I've been there, 132 00:08:47,840 --> 00:08:52,200 Speaker 1: and the stations in Texas we have, we have stations 133 00:08:52,200 --> 00:08:57,360 Speaker 1: in San Antonio, Austin, Abilene, to Oklahoma and so on. Uh. 134 00:08:58,080 --> 00:09:03,600 Speaker 1: That client is a horse auction client, and that horse 135 00:09:03,640 --> 00:09:07,320 Speaker 1: auction client was buying advertising locally to get people to 136 00:09:07,440 --> 00:09:12,280 Speaker 1: show up to the auction. They were using Facebook Live 137 00:09:12,640 --> 00:09:15,360 Speaker 1: as a means of streaming to those that couldn't get 138 00:09:15,400 --> 00:09:21,360 Speaker 1: to the auction. All of a sudden, COVID hits unless 139 00:09:21,440 --> 00:09:26,560 Speaker 1: people are showing up to the auction and the station 140 00:09:26,800 --> 00:09:31,839 Speaker 1: while liking the client, while liking Facebook Live. It was like, 141 00:09:32,480 --> 00:09:35,000 Speaker 1: you know, it's okay, but what more can we do? 142 00:09:35,080 --> 00:09:38,160 Speaker 1: We like, we like TV. We know TV advertising is 143 00:09:39,720 --> 00:09:43,439 Speaker 1: really powerful, and so what the stations in in that 144 00:09:43,559 --> 00:09:46,080 Speaker 1: territory did they met with the clients, they said, let's 145 00:09:46,200 --> 00:09:48,360 Speaker 1: let's brainstorm about how we can take advente of STIR 146 00:09:48,960 --> 00:09:51,920 Speaker 1: And so they came up with a really cool idea 147 00:09:52,240 --> 00:09:55,920 Speaker 1: to make a seven channel out of it. And so 148 00:09:56,360 --> 00:09:59,080 Speaker 1: there is a channel now called the Horse Shopping Channel. 149 00:09:59,679 --> 00:10:05,679 Speaker 1: It's on stir. Uh. It features live auctions of horse 150 00:10:05,720 --> 00:10:08,720 Speaker 1: auctions throughout a month, and then when that programming is 151 00:10:08,720 --> 00:10:11,640 Speaker 1: it on, it features other sort of related content on 152 00:10:11,760 --> 00:10:15,760 Speaker 1: that channel. And it is a completely paid for by 153 00:10:15,840 --> 00:10:20,680 Speaker 1: the client channel. And so that client, that local client, 154 00:10:20,920 --> 00:10:23,760 Speaker 1: instead of just buying thirty second commercials or using Facebook, 155 00:10:24,240 --> 00:10:27,400 Speaker 1: they now have their own television channel. And I mean 156 00:10:27,600 --> 00:10:30,120 Speaker 1: and the obviously the r o I is good enough 157 00:10:30,120 --> 00:10:33,600 Speaker 1: for them to continue it, like did they see a bounce? 158 00:10:34,920 --> 00:10:37,400 Speaker 1: It has been so far, you know. I think part 159 00:10:37,440 --> 00:10:39,800 Speaker 1: of how they measure their r o I is, you know, 160 00:10:39,880 --> 00:10:42,839 Speaker 1: do we sell more horses? Right? That's one way. I think. 161 00:10:42,880 --> 00:10:45,440 Speaker 1: The other is have they grown their brand? Have they 162 00:10:45,520 --> 00:10:50,160 Speaker 1: enhanced their brand? Uh? And they have a business model 163 00:10:50,240 --> 00:10:52,680 Speaker 1: that there's a lot of horse auctions out there. So 164 00:10:53,000 --> 00:10:56,040 Speaker 1: part of their business model is to actually now be 165 00:10:56,120 --> 00:10:59,960 Speaker 1: the conduit for other horse auctions who will then pay 166 00:10:59,840 --> 00:11:03,840 Speaker 1: the end to be on this channel, right, so they're 167 00:11:03,840 --> 00:11:06,440 Speaker 1: play a little broker. So as an example, that's a 168 00:11:06,440 --> 00:11:10,040 Speaker 1: completely new type of advertiser that's buying this OTT inventory. 169 00:11:10,240 --> 00:11:12,800 Speaker 1: And in that scenario, do the Texas stations have any 170 00:11:12,840 --> 00:11:16,000 Speaker 1: piece of the horse auction channel or is that yes, 171 00:11:17,480 --> 00:11:19,120 Speaker 1: Well theyn't have a piece of the channel, but they 172 00:11:19,160 --> 00:11:21,360 Speaker 1: get a ship. They get a commission on the revenue 173 00:11:21,640 --> 00:11:24,640 Speaker 1: because they were the people that execute the agreement. When 174 00:11:24,679 --> 00:11:30,920 Speaker 1: the inventory is sold um on stir the state. If 175 00:11:30,960 --> 00:11:34,280 Speaker 1: the station is selling the package to local advertiser, they 176 00:11:34,280 --> 00:11:38,079 Speaker 1: will get their share of that package. If the if 177 00:11:38,120 --> 00:11:41,280 Speaker 1: it's sold through programmatic, the station doesn't get that share 178 00:11:41,280 --> 00:11:44,400 Speaker 1: because it's not the station did the local sales through programmatic. 179 00:11:45,240 --> 00:11:47,320 Speaker 1: Um And then what we do is you have a 180 00:11:47,360 --> 00:11:50,320 Speaker 1: second piece of this is that we also return. So 181 00:11:50,400 --> 00:11:53,079 Speaker 1: that's the form of a commission. Then the other thing 182 00:11:53,160 --> 00:11:56,240 Speaker 1: we do is our whole model is a revenue share. 183 00:11:57,200 --> 00:12:00,439 Speaker 1: So any partner who's on our platform there as a 184 00:12:00,520 --> 00:12:04,360 Speaker 1: station or it's a third party partner, based on their 185 00:12:04,400 --> 00:12:08,199 Speaker 1: delivery and based on the revenue attached their delivery, they 186 00:12:08,240 --> 00:12:12,599 Speaker 1: get the revenues from Star. So that is that is 187 00:12:12,640 --> 00:12:17,320 Speaker 1: the second model for them. Um uh which I guess 188 00:12:17,320 --> 00:12:20,240 Speaker 1: it is a way they're selling ads. But even if 189 00:12:20,280 --> 00:12:22,800 Speaker 1: they don't sell an ad, they still get if they're 190 00:12:22,840 --> 00:12:25,200 Speaker 1: not the ones selling the ad, they'll still get their 191 00:12:25,240 --> 00:12:28,880 Speaker 1: share based on the popularity of programming. Most of your 192 00:12:29,040 --> 00:12:32,400 Speaker 1: stations in addition to making the newscasts on STIR, if 193 00:12:32,440 --> 00:12:35,640 Speaker 1: I go to Como or w j l A in 194 00:12:35,800 --> 00:12:38,440 Speaker 1: d C, do most of them offer a live stream 195 00:12:38,559 --> 00:12:42,000 Speaker 1: of a of a live newscast, Yeah, they do. They 196 00:12:42,200 --> 00:12:45,520 Speaker 1: What the what again? Where they started? And this goes 197 00:12:45,520 --> 00:12:46,959 Speaker 1: back to sort of again why they were sort of 198 00:12:47,000 --> 00:12:49,600 Speaker 1: early in streaming. What they first did is they put 199 00:12:49,640 --> 00:12:55,520 Speaker 1: the live stream on their website and um, people would 200 00:12:55,520 --> 00:13:00,280 Speaker 1: watch it, but you know, it really wasn't the primary 201 00:13:00,320 --> 00:13:03,120 Speaker 1: people were watching the live news. They were the primaryy 202 00:13:03,200 --> 00:13:07,559 Speaker 1: they were watching live news was on television. Um. Then 203 00:13:07,600 --> 00:13:09,760 Speaker 1: there would be a live stream in their local app, 204 00:13:09,800 --> 00:13:12,680 Speaker 1: but again the local app really was used more for 205 00:13:13,800 --> 00:13:20,440 Speaker 1: breaking news or weather or things like that. So what 206 00:13:20,480 --> 00:13:23,840 Speaker 1: we did with the live news was, instead of just 207 00:13:23,920 --> 00:13:26,960 Speaker 1: putting up a live stream of it, we said, all 208 00:13:27,040 --> 00:13:30,360 Speaker 1: these stations do anywhere from you know, four to six 209 00:13:30,440 --> 00:13:33,280 Speaker 1: hours of live local news a day, even more eight 210 00:13:33,280 --> 00:13:35,520 Speaker 1: hours on the high end, live local news a day. 211 00:13:36,920 --> 00:13:40,120 Speaker 1: Why don't we actually create a channel out of it. 212 00:13:40,200 --> 00:13:43,400 Speaker 1: They're already on a channel right there. They have a channel, 213 00:13:43,640 --> 00:13:45,600 Speaker 1: and then they're going to syndicated shows, and they go 214 00:13:45,640 --> 00:13:47,520 Speaker 1: on through network shows and so on. They have a 215 00:13:47,520 --> 00:13:50,640 Speaker 1: twenty four seven channel. Why don't we do the same thing. 216 00:13:51,480 --> 00:13:53,920 Speaker 1: Why don't we do this seventy three times? Because we 217 00:13:53,960 --> 00:13:56,679 Speaker 1: have seventy three stations that do all this local news 218 00:13:56,880 --> 00:13:59,320 Speaker 1: as part of the lineup, And so we came up 219 00:13:59,360 --> 00:14:02,040 Speaker 1: with the channel called the stir City Channel. And so 220 00:14:02,120 --> 00:14:05,480 Speaker 1: the stir City Channel is a localized channel. It's in 221 00:14:05,480 --> 00:14:09,280 Speaker 1: the first position on the platform, it's the first position 222 00:14:09,320 --> 00:14:14,320 Speaker 1: on the EPG. It's powered by the station. So in Baltimore, 223 00:14:14,400 --> 00:14:18,400 Speaker 1: it's it's stir City powered by Fox. In Seattle, it's 224 00:14:18,440 --> 00:14:22,240 Speaker 1: you know, stir City powered by Como News, and the 225 00:14:22,360 --> 00:14:26,840 Speaker 1: local news will run live on the TV station and 226 00:14:27,200 --> 00:14:31,760 Speaker 1: on their stir City channel. Then let's use Seattle as 227 00:14:31,800 --> 00:14:34,880 Speaker 1: an example. If they, let's say, have their morning news 228 00:14:34,920 --> 00:14:37,880 Speaker 1: from five to seven am, and then at seven am 229 00:14:38,000 --> 00:14:40,520 Speaker 1: they would go to Good Morning America. Well, on the 230 00:14:40,560 --> 00:14:43,280 Speaker 1: stir City channel, we wouldn't go to Good Morning America. 231 00:14:43,520 --> 00:14:48,320 Speaker 1: We go to other programming, and so Stir actually programs 232 00:14:48,320 --> 00:14:53,520 Speaker 1: out a seven channel. It's very much like an it's 233 00:14:53,520 --> 00:14:57,200 Speaker 1: a network. It's the ster City network with local affiliates 234 00:14:58,080 --> 00:15:01,240 Speaker 1: that put in their live local news. And the reason 235 00:15:01,280 --> 00:15:03,480 Speaker 1: we did that was because we believe so firmly that 236 00:15:03,600 --> 00:15:09,600 Speaker 1: linear was the way people wanted to consume uh, streaming 237 00:15:09,680 --> 00:15:14,800 Speaker 1: video that so much so that there wasn't even we 238 00:15:14,840 --> 00:15:17,640 Speaker 1: knew it was happening, but the industry couldn't figure out 239 00:15:17,680 --> 00:15:19,480 Speaker 1: a term for it. Right, it was called a VOD 240 00:15:20,640 --> 00:15:24,360 Speaker 1: So so if you had a linear a what what 241 00:15:24,360 --> 00:15:29,040 Speaker 1: what is that? And sure enough Pluto was in the 242 00:15:29,120 --> 00:15:33,760 Speaker 1: linear business, Zumo was in the linear business, Stirs in 243 00:15:33,800 --> 00:15:36,440 Speaker 1: the linear business, Peacocks in the linear business. And on 244 00:15:36,480 --> 00:15:39,480 Speaker 1: every road who channels now in the linear business. The 245 00:15:39,600 --> 00:15:42,960 Speaker 1: record Netflix in their own way, is in the linear business. 246 00:15:43,000 --> 00:15:47,880 Speaker 1: They're testing a linear channel, right, I think of France. Uh, 247 00:15:48,000 --> 00:15:52,160 Speaker 1: and an auto play from one episode to the next 248 00:15:52,400 --> 00:15:55,400 Speaker 1: is a linear experience, right, It's sitting on the couch 249 00:15:55,680 --> 00:16:00,080 Speaker 1: doing less work, someone curating something for you and and 250 00:16:00,720 --> 00:16:03,120 Speaker 1: uh And so ster City became the embodied and how 251 00:16:03,120 --> 00:16:04,800 Speaker 1: we were going to take this live local news and 252 00:16:04,840 --> 00:16:09,560 Speaker 1: put it into a ster City just for clarification. If 253 00:16:09,600 --> 00:16:14,000 Speaker 1: I'm sitting in UM St. Louis and I pull up STIR, 254 00:16:14,160 --> 00:16:18,480 Speaker 1: I'm going to get a St. Louis focused stream of information, 255 00:16:18,600 --> 00:16:22,080 Speaker 1: or I will get a pastiche of different Sinclair newscasts 256 00:16:22,080 --> 00:16:25,760 Speaker 1: from around the country. In St. Louis, you will get 257 00:16:25,960 --> 00:16:30,600 Speaker 1: a mixt right um. In Austin you will get a 258 00:16:30,720 --> 00:16:34,120 Speaker 1: local news okay, and and that's dependent on where you 259 00:16:34,120 --> 00:16:37,560 Speaker 1: have Staying Okay, go where we have news affiliates. So 260 00:16:38,680 --> 00:16:41,080 Speaker 1: that's actually the next sort of phase for US now 261 00:16:41,320 --> 00:16:46,800 Speaker 1: is to add affiliates and markets where we're not in UH. 262 00:16:46,840 --> 00:16:50,760 Speaker 1: And maybe that's multiple affiliates in markets where we're in 263 00:16:51,280 --> 00:16:57,000 Speaker 1: right um or or filling markets where we're not in UH. 264 00:16:58,080 --> 00:17:00,720 Speaker 1: That either comes from partnering with a Stay and we 265 00:17:00,760 --> 00:17:04,000 Speaker 1: are in pretty advanced talks with a couple to have 266 00:17:04,280 --> 00:17:07,000 Speaker 1: them come on join a STIR affiliates filling in some 267 00:17:07,080 --> 00:17:11,560 Speaker 1: of the bigger markets. Um Or it comes from producing 268 00:17:11,600 --> 00:17:15,320 Speaker 1: your own news in the market. So in Ohio, for instance, 269 00:17:15,320 --> 00:17:19,560 Speaker 1: we have stations and Cincinnati Columbus, so we don't have 270 00:17:19,600 --> 00:17:23,639 Speaker 1: a station in Cleveland. But the idea of using that 271 00:17:23,760 --> 00:17:27,160 Speaker 1: infrastructure to produce a news that would be relevant for 272 00:17:27,200 --> 00:17:32,399 Speaker 1: people in Cleveland or Ohio. That's clearly a path. Do 273 00:17:32,480 --> 00:17:35,879 Speaker 1: you have any national sales layer on this? Do you 274 00:17:36,200 --> 00:17:39,080 Speaker 1: like do old fashioned like barter? You know, you bundle 275 00:17:39,119 --> 00:17:42,359 Speaker 1: all the inventory that you have from your stations and 276 00:17:42,400 --> 00:17:45,600 Speaker 1: try to sell it to National spot buyers? Do you do? 277 00:17:46,640 --> 00:17:51,639 Speaker 1: Is that a factor? So there's yes. So there's multiple 278 00:17:51,640 --> 00:17:54,840 Speaker 1: pieces to it. Like one first pieces is local sales 279 00:17:55,080 --> 00:17:59,560 Speaker 1: staff going into local advertisers selling the equivalent of local 280 00:17:59,640 --> 00:18:04,200 Speaker 1: spot uh um O t T inventory. They're either selling 281 00:18:04,280 --> 00:18:09,640 Speaker 1: stir or they're selling inventory that we've purchased from Broku 282 00:18:09,840 --> 00:18:14,120 Speaker 1: for instance. UM that isn't in anything we own, but 283 00:18:14,160 --> 00:18:16,920 Speaker 1: it's we're in a better position to sell that inventory 284 00:18:16,960 --> 00:18:20,639 Speaker 1: than Roku is, and so we're arbitrary in a local newscast. Right, 285 00:18:22,200 --> 00:18:26,399 Speaker 1: it could be in you know, a cable networks app 286 00:18:26,560 --> 00:18:30,800 Speaker 1: for instance. UM, if they have inventory, we're in a 287 00:18:30,800 --> 00:18:33,600 Speaker 1: better position to sell it locally and take advantage of that. 288 00:18:34,320 --> 00:18:38,760 Speaker 1: So there is local spots sales, then there is National 289 00:18:38,800 --> 00:18:41,480 Speaker 1: spots sales, and that National Spot sales goes through a 290 00:18:41,520 --> 00:18:44,720 Speaker 1: company that we have that's called Compulsor t T. And 291 00:18:44,760 --> 00:18:47,080 Speaker 1: what that does is we go to advertisers in New 292 00:18:47,160 --> 00:18:50,480 Speaker 1: York that are interested in buying TV and O T 293 00:18:50,480 --> 00:18:54,840 Speaker 1: T in San Antonio, and we we go to that 294 00:18:54,880 --> 00:18:57,320 Speaker 1: agency with a package, and that agency then goes by 295 00:18:57,400 --> 00:19:03,280 Speaker 1: the market and that follows the spot you know, traditional 296 00:19:03,400 --> 00:19:05,840 Speaker 1: national spot business. It applies out to T as well. 297 00:19:06,400 --> 00:19:09,080 Speaker 1: Then there are advertisers that want to buy the whole 298 00:19:09,200 --> 00:19:12,200 Speaker 1: the whole country, want to buy just just one ftprint, 299 00:19:12,240 --> 00:19:16,479 Speaker 1: want to buy the platform and so on and uh. 300 00:19:16,760 --> 00:19:19,240 Speaker 1: That can come in the form of a sponsorship of 301 00:19:19,240 --> 00:19:24,680 Speaker 1: a channel or of the platform, or they own their 302 00:19:24,720 --> 00:19:27,760 Speaker 1: own channel like the horse Shopping channel is a national 303 00:19:27,840 --> 00:19:35,600 Speaker 1: channel as an example. UM. And and because we're linear, 304 00:19:36,359 --> 00:19:39,760 Speaker 1: because stir City is actually programmed day date and time, 305 00:19:41,040 --> 00:19:45,439 Speaker 1: it fits into a network format. So we can actually 306 00:19:45,480 --> 00:19:49,360 Speaker 1: sell a schedule to an advertiser based on a network 307 00:19:49,480 --> 00:19:53,120 Speaker 1: basis because it's day, date and time. What is your 308 00:19:54,280 --> 00:19:56,960 Speaker 1: what is your most important metric? Is it? I'm guessing 309 00:19:57,000 --> 00:19:59,760 Speaker 1: it's at this point it's not just raw viewership? Is 310 00:19:59,800 --> 00:20:03,760 Speaker 1: it engagement? Is it time spent with the programming? Like 311 00:20:03,800 --> 00:20:08,760 Speaker 1: what what do you look to measure your growth? Um? 312 00:20:09,040 --> 00:20:16,120 Speaker 1: Organic downloads and usage versus us buying them? Um uh 313 00:20:17,080 --> 00:20:19,800 Speaker 1: churn you know how many are we keeping and how 314 00:20:19,920 --> 00:20:23,000 Speaker 1: how how how deep are they getting into the service? 315 00:20:23,960 --> 00:20:26,040 Speaker 1: So are they spending not just that they spending a 316 00:20:26,080 --> 00:20:28,200 Speaker 1: lot of time, but are they doing a lot of discovery? 317 00:20:28,800 --> 00:20:32,400 Speaker 1: And when you say churn in an ad supported environment, 318 00:20:32,440 --> 00:20:35,119 Speaker 1: do you mean just engagement? Like if they go for 319 00:20:35,440 --> 00:20:38,040 Speaker 1: like you would cull churn, if they don't touch the 320 00:20:38,080 --> 00:20:41,240 Speaker 1: aft for a week or two or something like that, correct, 321 00:20:41,280 --> 00:20:45,400 Speaker 1: they stop using it, Yeah, which is which is quite common, right, 322 00:20:46,200 --> 00:20:49,280 Speaker 1: turn and turn in the subscription part or in the 323 00:20:49,280 --> 00:20:55,159 Speaker 1: ad supporter part is fairly significant. And um, you'll see 324 00:20:55,920 --> 00:20:59,679 Speaker 1: people in the marketplace, you know, having campaigns in rocou 325 00:20:59,760 --> 00:21:03,960 Speaker 1: store or Prime Video or whatever, uh or in the 326 00:21:04,000 --> 00:21:11,000 Speaker 1: fire TV app store weekly. Right, they're constantly refreshing the churn. 327 00:21:11,119 --> 00:21:15,800 Speaker 1: They're not just growing, they're refreshing the churn. And um, 328 00:21:15,840 --> 00:21:19,680 Speaker 1: that's one model you know where you're you're throwing tons 329 00:21:19,680 --> 00:21:22,159 Speaker 1: of money against something and you're bringing in tons of 330 00:21:22,240 --> 00:21:26,200 Speaker 1: viewers and keeping them for some part and then hopefully 331 00:21:26,240 --> 00:21:27,880 Speaker 1: getting them to watch a little bit more, a little 332 00:21:27,920 --> 00:21:30,080 Speaker 1: bit more, but most a lot of them are going 333 00:21:30,119 --> 00:21:33,280 Speaker 1: doesn't leave. That's the nature of what's happening right now. 334 00:21:33,520 --> 00:21:36,959 Speaker 1: There's a tremendous amount of sampling going on, so so 335 00:21:37,000 --> 00:21:40,240 Speaker 1: as as an example of what happened with COVID, Right, 336 00:21:41,080 --> 00:21:43,760 Speaker 1: everyone all of a sudden was at home. People were 337 00:21:43,800 --> 00:21:48,400 Speaker 1: looking for alternatives to Netflix. Right, Netflix was no longer 338 00:21:48,440 --> 00:21:53,920 Speaker 1: altern they were looking form. That was Jimmy Kimmel's joke, Right, 339 00:21:53,960 --> 00:21:59,200 Speaker 1: It was like I watched I finished Netflix last last night. Right. Um, 340 00:21:59,320 --> 00:22:02,880 Speaker 1: So you had people then sampling like crazy, and if 341 00:22:02,880 --> 00:22:06,119 Speaker 1: you were free, they sampled even more. And so the 342 00:22:06,200 --> 00:22:08,439 Speaker 1: key question for us is we always sort of knew 343 00:22:08,480 --> 00:22:12,119 Speaker 1: that that would be sort of a moment in time 344 00:22:13,000 --> 00:22:16,240 Speaker 1: and what would now what would happen after, not meaning 345 00:22:16,240 --> 00:22:19,840 Speaker 1: after COVID ended, but meaning after you So that spike 346 00:22:20,080 --> 00:22:22,960 Speaker 1: of people looking for alternatives, we knew it would settle. 347 00:22:23,880 --> 00:22:25,880 Speaker 1: And the question for us is would we go back 348 00:22:25,920 --> 00:22:29,639 Speaker 1: to where we were they just come and leave, or 349 00:22:29,800 --> 00:22:33,400 Speaker 1: would we maintain some percentage of it? So for us, 350 00:22:34,160 --> 00:22:37,359 Speaker 1: going back to the metrics that we cared about, we're 351 00:22:37,720 --> 00:22:41,680 Speaker 1: sitting now. The peak for us was somewhere in May 352 00:22:42,160 --> 00:22:45,600 Speaker 1: June forty five days I would say of late May 353 00:22:45,640 --> 00:22:51,359 Speaker 1: through early July was the peak. And um, they were 354 00:22:51,400 --> 00:22:54,000 Speaker 1: downloading us for all sorts of reasons, and we weren't 355 00:22:54,119 --> 00:22:57,920 Speaker 1: buying anything. We had no media running during that time 356 00:22:58,560 --> 00:23:01,320 Speaker 1: we had we were showing up in stores, listings and 357 00:23:01,359 --> 00:23:03,879 Speaker 1: things like that, and so they were downloading us for 358 00:23:03,960 --> 00:23:06,639 Speaker 1: local news. They were downloading us because it was free 359 00:23:06,680 --> 00:23:09,520 Speaker 1: TV and we had all this sampling. We got to 360 00:23:09,560 --> 00:23:13,240 Speaker 1: this peak. And when that happens, your session time tanks. 361 00:23:14,520 --> 00:23:17,800 Speaker 1: So on average we're at about forty minutes or so 362 00:23:18,000 --> 00:23:21,119 Speaker 1: per session time. You bring in tons of downloads, your 363 00:23:21,160 --> 00:23:23,920 Speaker 1: session time is going almost some drop because you've got 364 00:23:23,960 --> 00:23:29,879 Speaker 1: people click and gone basically. And and now I would 365 00:23:29,880 --> 00:23:33,719 Speaker 1: say we started to drop posts then and then in 366 00:23:33,760 --> 00:23:38,000 Speaker 1: August September, in October we've settled out in at a 367 00:23:38,040 --> 00:23:42,359 Speaker 1: certain level. End results were about a hundred and fifty 368 00:23:42,840 --> 00:23:46,240 Speaker 1: higher than we were pre COVID. Can you give me, 369 00:23:46,359 --> 00:23:48,400 Speaker 1: can you give me any kind of a ballpark of 370 00:23:48,440 --> 00:23:53,320 Speaker 1: what you're what that aggregated audience is sure, so you 371 00:23:53,359 --> 00:23:56,920 Speaker 1: know we're doing it about forty minutes session time. We 372 00:23:56,960 --> 00:23:59,920 Speaker 1: have about six million, a little bit over six billion 373 00:24:00,080 --> 00:24:04,560 Speaker 1: downloads of three and a half million of them are 374 00:24:04,760 --> 00:24:09,800 Speaker 1: are active. Um. That dates back from January one through 375 00:24:10,840 --> 00:24:13,760 Speaker 1: uh not that not yes, I haven't done yesterday yet, 376 00:24:13,760 --> 00:24:18,959 Speaker 1: but the day before yesterday. Um, And we're in the 377 00:24:19,040 --> 00:24:28,240 Speaker 1: neighborhood of you know, somewhere over a million monthly uniques. Um. Again, 378 00:24:28,280 --> 00:24:31,040 Speaker 1: that will fluctuate. You'll see it go signficalarly higher, you 379 00:24:31,119 --> 00:24:33,439 Speaker 1: see it go below somewhere. So I would say somewhere 380 00:24:33,440 --> 00:24:38,520 Speaker 1: in that range right now, um, which if you go 381 00:24:38,600 --> 00:24:41,399 Speaker 1: back and look where Pluto and Zumo and the others 382 00:24:41,520 --> 00:24:47,400 Speaker 1: were with with far less competition after two years, um, 383 00:24:47,600 --> 00:24:50,640 Speaker 1: we're right in line based on our understanding of where 384 00:24:50,640 --> 00:24:53,200 Speaker 1: their numbers were back then. And where does that in 385 00:24:53,720 --> 00:24:56,240 Speaker 1: terms of your plane has would you say the pandemic 386 00:24:56,280 --> 00:24:58,720 Speaker 1: the conditions of the pandemic hav acceller are you like 387 00:24:58,800 --> 00:25:00,879 Speaker 1: ahead of ahead of war you expected to be at 388 00:25:00,880 --> 00:25:05,040 Speaker 1: this point because yeah, yeah, like eighteen months ahead, so 389 00:25:06,119 --> 00:25:10,119 Speaker 1: with no marketing money, right, so we we we really 390 00:25:10,160 --> 00:25:12,960 Speaker 1: have yet to turn on the marketing part. And the 391 00:25:13,000 --> 00:25:15,719 Speaker 1: marketing part really comes in two ways. It's it's us 392 00:25:15,760 --> 00:25:18,800 Speaker 1: going in and spending money in the stores, but it's 393 00:25:18,880 --> 00:25:23,880 Speaker 1: really the local stations promoting us. And the local stations 394 00:25:25,040 --> 00:25:27,399 Speaker 1: have been promoting us a little bit as relates to 395 00:25:27,440 --> 00:25:30,720 Speaker 1: go to stir to watch your local news, because they're 396 00:25:30,760 --> 00:25:33,400 Speaker 1: also promoting their app, they're also promoting their website they're 397 00:25:33,400 --> 00:25:36,439 Speaker 1: also quoting Tonight on their own news on the station, 398 00:25:37,200 --> 00:25:41,480 Speaker 1: and then we just rolled out their syndicated programming. So 399 00:25:42,080 --> 00:25:44,200 Speaker 1: in Baltimore again, I think they own the rights to 400 00:25:44,280 --> 00:25:50,040 Speaker 1: Judge Duty, Family Feud and maybe maybe Wheel in Jeopardy. 401 00:25:50,040 --> 00:25:53,760 Speaker 1: I forget, it's all four those shows are now available 402 00:25:53,840 --> 00:25:58,040 Speaker 1: on and on demand basis in Baltimore on Stir, and 403 00:25:58,080 --> 00:26:02,440 Speaker 1: they're only available on Stir. Was that a fight with 404 00:26:02,480 --> 00:26:06,520 Speaker 1: those distributors to get those rights? Did you? Did you 405 00:26:06,560 --> 00:26:10,800 Speaker 1: have to write a bigger check for those rights? I'm 406 00:26:10,800 --> 00:26:13,320 Speaker 1: not going to comment on the terms of an agreement, right, 407 00:26:13,440 --> 00:26:16,920 Speaker 1: but suffice it to say that that I think everybody 408 00:26:17,040 --> 00:26:21,600 Speaker 1: walked away quite happy. Um and if anything, it was 409 00:26:21,640 --> 00:26:28,119 Speaker 1: a natural evolution of the partnership between you know, syndicators 410 00:26:28,119 --> 00:26:33,159 Speaker 1: and the station group first started. Sorry, sorry, just to 411 00:26:33,200 --> 00:26:36,600 Speaker 1: get very geeky syndication. Does you know Barter is a 412 00:26:36,640 --> 00:26:40,720 Speaker 1: part of all big syndication shows. Does the Barter component 413 00:26:41,480 --> 00:26:45,000 Speaker 1: continue into the into the Stir telecat you know, the 414 00:26:45,040 --> 00:26:52,280 Speaker 1: Stir simulcast. Absolutely, it's not a Stir simulcast you said 415 00:26:52,320 --> 00:26:57,639 Speaker 1: on demand, it's an on demand a stir a stir 416 00:26:58,840 --> 00:27:02,119 Speaker 1: in pattern play because I like using the word in 417 00:27:02,160 --> 00:27:06,439 Speaker 1: pattern versus the word simulcast. A stirt in pattern play 418 00:27:07,160 --> 00:27:10,720 Speaker 1: is next, so we have the we have the rights 419 00:27:10,760 --> 00:27:13,880 Speaker 1: to do that as well. The first step of this 420 00:27:14,240 --> 00:27:17,320 Speaker 1: was to roll out catch up viewing. So is it 421 00:27:17,440 --> 00:27:19,560 Speaker 1: like the next day you can get the next day's 422 00:27:19,560 --> 00:27:25,240 Speaker 1: episode midnight? I think ye. So yeah. Is there any 423 00:27:25,320 --> 00:27:29,760 Speaker 1: tension for the stations in terms of in terms of 424 00:27:30,080 --> 00:27:32,239 Speaker 1: you know, having the potential to have what you call 425 00:27:32,280 --> 00:27:35,640 Speaker 1: an in pattern telecast at you know? At the same time, 426 00:27:35,680 --> 00:27:38,400 Speaker 1: is there is there a gut level of I don't 427 00:27:38,440 --> 00:27:41,719 Speaker 1: want to let my signal out beyond my you know, 428 00:27:41,920 --> 00:27:45,520 Speaker 1: linear station, or are your general managers like they're looking 429 00:27:45,560 --> 00:27:47,840 Speaker 1: at the future and saying we've got to get We've 430 00:27:47,840 --> 00:27:52,840 Speaker 1: got to be in here too. So I think, um, so, 431 00:27:52,880 --> 00:27:54,280 Speaker 1: I think just two parts. That one is I just 432 00:27:54,320 --> 00:27:59,480 Speaker 1: think as a company, we're looking sort of at allways 433 00:27:59,520 --> 00:28:03,160 Speaker 1: of district lution of of our station and the programming 434 00:28:03,200 --> 00:28:07,200 Speaker 1: on our station and uh and then in particularly we're 435 00:28:07,200 --> 00:28:11,679 Speaker 1: looking at our signals as a as a method of streaming, 436 00:28:11,680 --> 00:28:14,920 Speaker 1: because that's really what ATFC three DONA is about. Next 437 00:28:14,960 --> 00:28:18,359 Speaker 1: gen TV is the next generation of a broadcast signal. 438 00:28:18,400 --> 00:28:23,200 Speaker 1: It's all about streaming. So all of that is consistent thinking, 439 00:28:23,400 --> 00:28:28,919 Speaker 1: right as a as A as someone who's on the line, 440 00:28:29,480 --> 00:28:34,400 Speaker 1: you know, selling day in, day out, inventory and so on, 441 00:28:34,480 --> 00:28:36,800 Speaker 1: so a general manager, general sales manager and so on. 442 00:28:37,119 --> 00:28:41,440 Speaker 1: I think there's always a nervousness about seeing your programming, 443 00:28:41,560 --> 00:28:43,720 Speaker 1: even though it's on something else you may own. There's 444 00:28:43,760 --> 00:28:47,200 Speaker 1: always a nervousness that it in some way will hurt 445 00:28:47,320 --> 00:28:52,840 Speaker 1: your primary way they're viewing, which I get. But the 446 00:28:52,880 --> 00:28:56,479 Speaker 1: reality is if they're not going to watch you over there, 447 00:28:56,520 --> 00:28:59,800 Speaker 1: they're gonna watch someone else over there right right, and 448 00:29:00,360 --> 00:29:04,360 Speaker 1: and that's what's happening. People are moving that. I mean, 449 00:29:04,400 --> 00:29:07,120 Speaker 1: I gave you some stats from Nielsen, right, there's so much, 450 00:29:07,240 --> 00:29:09,760 Speaker 1: so much. The viewing is now going on either on 451 00:29:09,800 --> 00:29:13,320 Speaker 1: an only O T T basis, or on a O 452 00:29:13,560 --> 00:29:17,480 Speaker 1: T A basis, or a combination of O T T 453 00:29:17,840 --> 00:29:22,240 Speaker 1: and streaming, UH and cable. But it's it's the viewing 454 00:29:22,280 --> 00:29:29,560 Speaker 1: is no longer dominated by one single input, and you 455 00:29:29,600 --> 00:29:37,960 Speaker 1: need to be in all of them. Thanks for listening. 456 00:29:38,200 --> 00:29:41,200 Speaker 1: Please leave us a review at Apple Podcasts. We love 457 00:29:41,240 --> 00:29:43,800 Speaker 1: to hear from listeners. Be sure to tune in next 458 00:29:43,840 --> 00:29:46,200 Speaker 1: week for another episode of Strictly Business.