1
00:00:02,080 --> 00:00:04,560
Speaker 1: Welcome to Ask Fear and Greed, where we answer questions

2
00:00:04,559 --> 00:00:08,639
Speaker 1: about business, investing, economics, politics and more. I'm Michael Thompson

3
00:00:08,760 --> 00:00:10,160
Speaker 1: and hello Adam Lang.

4
00:00:10,480 --> 00:00:13,400
Speaker 2: Hello, Michael. Here's me in an unusual position, standing in

5
00:00:13,440 --> 00:00:14,120
Speaker 2: for Sean.

6
00:00:14,520 --> 00:00:16,959
Speaker 1: But filling in as the expert. And that is something

7
00:00:16,960 --> 00:00:19,640
Speaker 1: that you are very qualified to do, particularly in this area,

8
00:00:19,680 --> 00:00:23,000
Speaker 1: because it is about data, it is about TV, and

9
00:00:23,160 --> 00:00:26,479
Speaker 1: you have worked an entire career in media, in TV

10
00:00:26,560 --> 00:00:29,400
Speaker 1: and radio and all of these and you love data.

11
00:00:29,440 --> 00:00:30,400
Speaker 2: So this feels like a.

12
00:00:30,440 --> 00:00:31,320
Speaker 1: Very natural fit.

13
00:00:31,560 --> 00:00:35,160
Speaker 2: Right, Yeah, all true, yep. Okay, tick tick tick, So far,

14
00:00:35,280 --> 00:00:36,680
Speaker 2: so good. Okay.

15
00:00:36,760 --> 00:00:38,839
Speaker 1: The question today is about something that a lot of

16
00:00:38,840 --> 00:00:42,239
Speaker 1: people hear about but not necessarily fully understand. Where are

17
00:00:42,240 --> 00:00:46,760
Speaker 1: going to talk about TV ratings, specifically how the measurements

18
00:00:46,840 --> 00:00:49,440
Speaker 1: are actually taken and what it means. For instance, when

19
00:00:49,440 --> 00:00:51,600
Speaker 1: we hear that say, one point two million people watch

20
00:00:51,680 --> 00:00:54,120
Speaker 1: Master Chef for the Voice or something, and you hear

21
00:00:54,200 --> 00:00:55,760
Speaker 1: about it a lot in the news, and we heard

22
00:00:55,760 --> 00:00:58,880
Speaker 1: about it this week as well, when there was a

23
00:00:59,000 --> 00:01:01,560
Speaker 1: lot of talk around the number of people still watching

24
00:01:01,640 --> 00:01:04,920
Speaker 1: free to air and how that was all measured. And

25
00:01:05,319 --> 00:01:09,600
Speaker 1: also when we're talking about the project being axed recently

26
00:01:09,640 --> 00:01:13,920
Speaker 1: on Channel ten and its replacement ten News Plus, which

27
00:01:14,120 --> 00:01:18,080
Speaker 1: launched with two hundred and ninety one thousand viewers, substantially

28
00:01:18,160 --> 00:01:20,560
Speaker 1: less than the project was getting. And all of a sudden,

29
00:01:20,600 --> 00:01:24,560
Speaker 1: these questions are asked, how are these numbers actually measured?

30
00:01:24,760 --> 00:01:27,600
Speaker 2: Yes? Where do they come from? So let's kick off

31
00:01:27,600 --> 00:01:31,360
Speaker 2: with one of my biggest problems in life. Michael acronyms

32
00:01:31,440 --> 00:01:35,200
Speaker 2: OSTAM O z TAM. What does it mean? Oz TAM

33
00:01:35,280 --> 00:01:38,760
Speaker 2: stands for the Australian Television Audience Measurement System. It's the

34
00:01:38,760 --> 00:01:42,200
Speaker 2: official provider of television audience ratings for the metropolitan markets.

35
00:01:42,440 --> 00:01:45,520
Speaker 2: So that's obviously covering Sydney, Melbourne, Brisbane, Adelaide and Perth.

36
00:01:45,959 --> 00:01:49,760
Speaker 2: Together with Regional TAM which looks after regional audiences and

37
00:01:49,880 --> 00:01:53,760
Speaker 2: Nielsen which collects the data, it forms a national view

38
00:01:53,840 --> 00:02:00,160
Speaker 2: of television consumption. Okay, so with me? So what I so?

39
00:02:00,240 --> 00:02:02,240
Speaker 1: Yeah, I'm with you so far. But I'm thinking back

40
00:02:02,280 --> 00:02:04,920
Speaker 1: to when I was a kid. You would always hear

41
00:02:05,040 --> 00:02:09,680
Speaker 1: about those incredible people that were fortunate enough to get

42
00:02:09,760 --> 00:02:13,320
Speaker 1: a box that they plugged into their TV and it

43
00:02:13,600 --> 00:02:17,160
Speaker 1: somehow measured everything that they were watching, and that there

44
00:02:17,240 --> 00:02:19,360
Speaker 1: was like a thousand of these people and a thousand

45
00:02:19,360 --> 00:02:22,040
Speaker 1: of these boxes around the country, and that just by

46
00:02:22,120 --> 00:02:24,840
Speaker 1: encouraging them to watch a particular show, they could have

47
00:02:25,280 --> 00:02:29,400
Speaker 1: enormous influence on a show getting a second season or

48
00:02:29,400 --> 00:02:30,560
Speaker 1: a third season or.

49
00:02:30,480 --> 00:02:32,560
Speaker 2: Something like that. Really you knew who they were.

50
00:02:33,120 --> 00:02:35,520
Speaker 1: And how they got chosen in the first place. How

51
00:02:35,639 --> 00:02:38,239
Speaker 1: does OSTAM know what people are watching? Is this story

52
00:02:38,240 --> 00:02:41,360
Speaker 1: about the boxes being plugged into the TV actually based

53
00:02:41,400 --> 00:02:41,880
Speaker 1: on fact?

54
00:02:42,320 --> 00:02:45,119
Speaker 2: The magical device there is some truth to it. Os

55
00:02:45,200 --> 00:02:48,960
Speaker 2: TAM collects starter from a carefully selected panel Michael of

56
00:02:49,040 --> 00:02:51,600
Speaker 2: not a thousand, but more than two hundred and fifty

57
00:02:51,600 --> 00:02:55,320
Speaker 2: households in the metro areas, and they represent many thousands

58
00:02:55,320 --> 00:02:59,279
Speaker 2: of individuals who can watch TV content in those households.

59
00:03:00,040 --> 00:03:02,120
Speaker 2: All of them are very carefully chosen so that you

60
00:03:02,160 --> 00:03:06,720
Speaker 2: get not just the geography represented well, but each demographic, genders,

61
00:03:06,720 --> 00:03:10,639
Speaker 2: and so on. Each household has technology installed on their

62
00:03:10,680 --> 00:03:14,560
Speaker 2: television sets that captures the viewing data, including which program

63
00:03:14,639 --> 00:03:17,360
Speaker 2: is being watched, what channel, what time, for how long.

64
00:03:17,840 --> 00:03:20,960
Speaker 2: Viewers in the household then log in to indicate who

65
00:03:21,120 --> 00:03:24,000
Speaker 2: is watching at that time. That data is then weighted

66
00:03:24,320 --> 00:03:28,160
Speaker 2: to reflect the border metropolitan population, so.

67
00:03:28,120 --> 00:03:30,080
Speaker 1: It's not that far from what I was talking about,

68
00:03:30,200 --> 00:03:32,720
Speaker 1: I mean, but to be one of those.

69
00:03:32,520 --> 00:03:34,800
Speaker 2: Part from the thousand to two hundred and fifty year

70
00:03:34,840 --> 00:03:35,320
Speaker 2: of spot on.

71
00:03:35,520 --> 00:03:39,040
Speaker 1: Okay, all right, I'm assuming similar kind of thing than

72
00:03:39,120 --> 00:03:41,000
Speaker 1: for regional viewers. I had thought that it was going

73
00:03:41,080 --> 00:03:43,080
Speaker 1: to be mostly metropolitan, but of course it would have

74
00:03:43,160 --> 00:03:44,280
Speaker 1: to measure regional.

75
00:03:43,920 --> 00:03:47,360
Speaker 2: Too, absolutely so. Yes, Regional TAM runs a similar panel

76
00:03:47,400 --> 00:03:50,480
Speaker 2: in Region Australia. Together, oz TAM and Regional TAM provide

77
00:03:50,480 --> 00:03:54,400
Speaker 2: a comprehensive picture of television audiences right across the country. Now,

78
00:03:54,440 --> 00:03:59,120
Speaker 2: this data is obviously crucial in helping networks make programming decisions,

79
00:03:59,160 --> 00:04:03,000
Speaker 2: but also to help advertisers determine where they should put

80
00:04:03,000 --> 00:04:06,120
Speaker 2: their campaigns based on the size and the characteristics of

81
00:04:06,120 --> 00:04:07,800
Speaker 2: the audience that each show can reach.

82
00:04:08,560 --> 00:04:11,880
Speaker 1: All right, so that system would have been great a

83
00:04:11,920 --> 00:04:16,440
Speaker 1: decade ago. Yeah, twenty years ago, thirty years ago, forty

84
00:04:16,520 --> 00:04:19,839
Speaker 1: years ago. What about the fact that we just people

85
00:04:19,880 --> 00:04:22,680
Speaker 1: just don't watch live TV anymore as well, certainly not

86
00:04:22,760 --> 00:04:24,680
Speaker 1: as much as they used to. They do still watch

87
00:04:24,680 --> 00:04:27,400
Speaker 1: live TV, That's not right, they don't watch it as

88
00:04:27,480 --> 00:04:29,919
Speaker 1: much as they did. How does OzTAM handle that?

89
00:04:30,600 --> 00:04:34,279
Speaker 2: Yeah, it's been remarkable change, and it's an accelerating change, Michael,

90
00:04:34,480 --> 00:04:37,159
Speaker 2: as you're alluding to. In addition to the overnight ratings,

91
00:04:37,160 --> 00:04:40,279
Speaker 2: which measure live and same day viewing, os TAM also

92
00:04:40,520 --> 00:04:44,600
Speaker 2: provides something called consolidated seven and consolidated twenty eight ratings,

93
00:04:44,640 --> 00:04:47,520
Speaker 2: and they capture time shift of viewing for seven or

94
00:04:47,560 --> 00:04:50,400
Speaker 2: twenty eight days after the broadcast, so it's a cumulative

95
00:04:50,440 --> 00:04:53,200
Speaker 2: total as to who watched the programs, So you get

96
00:04:53,200 --> 00:04:53,880
Speaker 2: a picture.

97
00:04:53,640 --> 00:04:58,240
Speaker 1: Then over time, so time shifted being so you're watching

98
00:04:58,240 --> 00:05:00,480
Speaker 1: it on nine now or one of those one you're watching,

99
00:05:00,520 --> 00:05:03,080
Speaker 1: say Lego Masters a week after it went to air,

100
00:05:03,360 --> 00:05:06,080
Speaker 1: that would still count in the consolidated seven.

101
00:05:06,640 --> 00:05:11,080
Speaker 2: Yes, yeah, okay, quite right. And then sometimes two programs

102
00:05:11,120 --> 00:05:12,839
Speaker 2: are replayed at different.

103
00:05:12,560 --> 00:05:15,600
Speaker 1: Times, okay, yeah, and so they're able to kind of

104
00:05:16,120 --> 00:05:20,960
Speaker 1: console aggregate pictures. Yes, Now what about streaming then, Adam

105
00:05:21,000 --> 00:05:24,760
Speaker 1: and everyone watching shows on mobile devices and laptops and everything,

106
00:05:24,800 --> 00:05:27,280
Speaker 1: because we are getting further and further away now from

107
00:05:27,320 --> 00:05:29,599
Speaker 1: that box just capturing free to air data.

108
00:05:30,000 --> 00:05:32,320
Speaker 2: Yeah, we're no longer limited to a set in a

109
00:05:32,400 --> 00:05:34,880
Speaker 2: lounge room at all. So os TAM has expanded its

110
00:05:34,920 --> 00:05:37,640
Speaker 2: measurement through two key initiatives. The first is OOZ and

111
00:05:37,680 --> 00:05:41,760
Speaker 2: that's Virtual Australia vo Z and that integrate STATU from

112
00:05:41,800 --> 00:05:46,440
Speaker 2: oz TM, Regional TAM and video player measurement across connected devices.

113
00:05:46,800 --> 00:05:50,320
Speaker 2: And the second is called Streamscape, which provides insights into

114
00:05:50,320 --> 00:05:54,239
Speaker 2: what Australians are watching on major streaming platforms like Netflix, Disney, Plast,

115
00:05:54,320 --> 00:05:57,000
Speaker 2: Prime Video on. More So, while it does not report

116
00:05:57,080 --> 00:06:01,000
Speaker 2: audience numbers for specific programs, it does give a clear

117
00:06:01,040 --> 00:06:04,919
Speaker 2: picture of what genres and platforms are popular, including free

118
00:06:05,040 --> 00:06:08,039
Speaker 2: video on demand services like nine Now seven Plus and

119
00:06:08,200 --> 00:06:11,320
Speaker 2: ABC I View I should mention ten players well, of

120
00:06:11,320 --> 00:06:15,400
Speaker 2: course and SBS on demand. Oh god, big favorite here?

121
00:06:15,839 --> 00:06:16,040
Speaker 2: Is it?

122
00:06:16,080 --> 00:06:17,960
Speaker 1: Really? Of course it would be.

123
00:06:18,360 --> 00:06:20,840
Speaker 2: Yeah. They all have great catalogs. I think each of

124
00:06:20,880 --> 00:06:21,280
Speaker 2: them do.

125
00:06:21,480 --> 00:06:24,919
Speaker 1: Yeah. And it was surprising earlier this week we actually

126
00:06:25,000 --> 00:06:28,360
Speaker 1: saw the data from Streamscape that showed how many people

127
00:06:28,480 --> 00:06:31,840
Speaker 1: are still watching free to air TV and it.

128
00:06:31,839 --> 00:06:34,440
Speaker 2: Was sixty yeah.

129
00:06:34,600 --> 00:06:38,599
Speaker 1: Yeah, of minutes watched, we're still free to air TV,

130
00:06:38,720 --> 00:06:41,640
Speaker 1: and nine percent was Netflix and then the rest was

131
00:06:41,760 --> 00:06:44,560
Speaker 1: kind of after that. And so, I mean, clearly the

132
00:06:45,760 --> 00:06:47,920
Speaker 1: talk of the death of free to air TV has

133
00:06:48,000 --> 00:06:51,240
Speaker 1: probably been a little exaggerated at this point.

134
00:06:51,279 --> 00:06:51,599
Speaker 2: Adam.

135
00:06:51,600 --> 00:06:53,840
Speaker 1: But things it certainly have changed, right.

136
00:06:53,960 --> 00:06:56,039
Speaker 2: Yeah, definitely, and we're a long way from the death

137
00:06:56,080 --> 00:06:59,720
Speaker 2: of linear or aerial TV and it is the mothership

138
00:06:59,720 --> 00:07:03,479
Speaker 2: that's apply so much content in general. So yeah, it's

139
00:07:03,480 --> 00:07:05,960
Speaker 2: hard to look at it as just aerial TV and

140
00:07:06,080 --> 00:07:07,520
Speaker 2: just streaming in isolation.

141
00:07:08,080 --> 00:07:10,280
Speaker 1: Okay, but it is safe to say that os TAM

142
00:07:10,320 --> 00:07:13,680
Speaker 1: measuring measuring that audience. It is not just about live

143
00:07:13,720 --> 00:07:14,440
Speaker 1: TV anymore.

144
00:07:14,560 --> 00:07:18,720
Speaker 2: It's not that, is correct. It's really about understanding the

145
00:07:18,840 --> 00:07:22,280
Speaker 2: quite full picture do you like that of visual content

146
00:07:22,360 --> 00:07:24,760
Speaker 2: consumption in Australia, And that is a cross of course

147
00:07:24,800 --> 00:07:28,280
Speaker 2: free tooware, subscription TV, all the catch up platforms and

148
00:07:28,360 --> 00:07:29,600
Speaker 2: the streaming devices.

149
00:07:30,120 --> 00:07:32,480
Speaker 1: I'm sorry if that joke didn't get the reception you

150
00:07:32,560 --> 00:07:35,280
Speaker 1: were hoping for. I think it got the reception it deserved.

151
00:07:35,560 --> 00:07:38,360
Speaker 1: There we go, how about that all right? Thanks very much, Adam,

152
00:07:38,640 --> 00:07:40,560
Speaker 1: Thank you Igel. Now, if you've got your own question

153
00:07:40,640 --> 00:07:42,920
Speaker 1: for Fear and Greed, jump onto the website Fear and

154
00:07:43,000 --> 00:07:46,440
Speaker 1: Greed dot com dot au. It can be anything if

155
00:07:46,440 --> 00:07:48,280
Speaker 1: you want to. I mean, it doesn't need to just

156
00:07:48,320 --> 00:07:51,400
Speaker 1: be about audience measurement, but hey, go for it. So

157
00:07:51,560 --> 00:07:54,080
Speaker 1: if you can find a way to stump the data guru.

158
00:07:54,400 --> 00:07:58,160
Speaker 2: I could do radio printed website. It's all sorts of things.

159
00:07:58,240 --> 00:08:01,960
Speaker 1: Outdoor media, yep, any of the above, all right, send you,

160
00:08:02,040 --> 00:08:04,400
Speaker 1: we send you a question through the website fearinggreed dot

161
00:08:04,440 --> 00:08:06,320
Speaker 1: com today you or any of the social media platforms.

162
00:08:06,320 --> 00:08:08,440
Speaker 1: I'm Michael Thompson and this is ask fear and greet

163
00:08:10,680 --> 00:08:10,720
Speaker 2: H