1
00:00:04,160 --> 00:00:07,520
Speaker 1: Welcome, Welcome, Welcome to this week's edition of the Bob

2
00:00:07,600 --> 00:00:11,360
Speaker 1: Left Sets podcast, not recorded live at the tune In

3
00:00:11,440 --> 00:00:15,240
Speaker 1: studio in Venice, California, but if the Music Media Summit

4
00:00:15,320 --> 00:00:18,560
Speaker 1: in Santa Barbara, California, back in May. My guest this

5
00:00:18,600 --> 00:00:22,880
Speaker 1: week is Steve Boom, who's head of Amazon Music. The

6
00:00:22,920 --> 00:00:25,119
Speaker 1: fact that you may not be familiar with his name,

7
00:00:25,640 --> 00:00:28,960
Speaker 1: you're certainly familiar with the Amazon Music. You should check

8
00:00:29,000 --> 00:00:32,080
Speaker 1: this out because it's a stealth operation and it's got

9
00:00:32,080 --> 00:00:34,400
Speaker 1: a lot of customers. You should know what's going on. So,

10
00:00:34,479 --> 00:00:37,840
Speaker 1: without further ado, Steve Boom is the Music Media Summit.

11
00:00:39,760 --> 00:00:41,960
Speaker 1: Last time I got together with Stevie was so formal

12
00:00:42,360 --> 00:00:43,839
Speaker 1: that I thought that was his image. Now we's so

13
00:00:44,000 --> 00:00:47,720
Speaker 1: relaxed after we evaluate my perception. Anyway, we were at

14
00:00:47,760 --> 00:00:51,400
Speaker 1: lunch and a friend of ours, the Worse for Concord Music,

15
00:00:51,440 --> 00:00:54,520
Speaker 1: which now owns Razor and Tie, said that the number

16
00:00:54,560 --> 00:00:59,400
Speaker 1: one streams music on your service is kids Bob. Is

17
00:00:59,440 --> 00:01:08,199
Speaker 1: that correct? No? Uh, because I said it was Garth Brooks. Uh.

18
00:01:08,440 --> 00:01:14,800
Speaker 1: Kids Bob's pretty up there. Okay, Uh, so's Garth Um.

19
00:01:14,840 --> 00:01:17,640
Speaker 1: I think our service the number one artists I have

20
00:01:17,720 --> 00:01:20,919
Speaker 1: to check, but most recently was Bruno Mars. Okay, stop

21
00:01:20,920 --> 00:01:23,039
Speaker 1: is up there. We have a lot of people, you know,

22
00:01:23,080 --> 00:01:26,119
Speaker 1: when you have an inexpensive device. A lot of people

23
00:01:26,120 --> 00:01:29,440
Speaker 1: have put Echo dots in their kids rooms, and we

24
00:01:29,640 --> 00:01:31,959
Speaker 1: family has always been a really important part of the

25
00:01:31,959 --> 00:01:35,479
Speaker 1: Amazon customer base. So UM, I think we make up

26
00:01:36,200 --> 00:01:38,959
Speaker 1: the converse of that, though, is true. I'm sure that

27
00:01:39,000 --> 00:01:42,000
Speaker 1: we're the number one streamer four kids bop. If I

28
00:01:42,040 --> 00:01:45,720
Speaker 1: looked across the different streaming services, I think that would

29
00:01:45,720 --> 00:01:49,600
Speaker 1: be a runaway. Well. If you look at Spotify, where

30
00:01:49,600 --> 00:01:52,000
Speaker 1: all everything is totally you can see the Spotify Top

31
00:01:52,000 --> 00:01:57,040
Speaker 1: fifty very dominated by urban music. Okay, and Apple does

32
00:01:57,040 --> 00:02:01,600
Speaker 1: not stop trumpeting how they're breaking records with their urban streams.

33
00:02:02,520 --> 00:02:06,840
Speaker 1: Rumor has it that the complexion of music on Amazon

34
00:02:07,040 --> 00:02:10,400
Speaker 1: that people listening to is different. Is that correct? That's

35
00:02:10,440 --> 00:02:13,320
Speaker 1: not a rumor, that's fact. Absolutely. Um. If you look

36
00:02:13,360 --> 00:02:15,880
Speaker 1: at if you just look at our charts, you would

37
00:02:15,880 --> 00:02:21,480
Speaker 1: see a much greater diverse profile of listening. Um. Urban

38
00:02:21,600 --> 00:02:24,240
Speaker 1: is important to our streaming service, like every other streaming service.

39
00:02:24,560 --> 00:02:26,240
Speaker 1: It's kind of strange to kind of cran my neck

40
00:02:26,280 --> 00:02:29,240
Speaker 1: here a little, but you'd see a much greater blend

41
00:02:29,280 --> 00:02:31,160
Speaker 1: you'd see a lot of country songs, you te rock,

42
00:02:31,320 --> 00:02:34,280
Speaker 1: you t pop, um, if you go down past the

43
00:02:34,320 --> 00:02:36,320
Speaker 1: top fifty you might even see a classical track or

44
00:02:36,320 --> 00:02:40,959
Speaker 1: two after Really yeah, Um, so you know it's it's

45
00:02:41,040 --> 00:02:44,239
Speaker 1: it is very different. I think when we see who

46
00:02:44,240 --> 00:02:47,040
Speaker 1: our customers are, you know, and we compare that to

47
00:02:47,160 --> 00:02:49,600
Speaker 1: the charts and the other services, we feel pretty confident

48
00:02:50,080 --> 00:02:52,480
Speaker 1: in saying that, you know, we're reaching new segments of

49
00:02:52,520 --> 00:02:55,560
Speaker 1: the of the of the streaming addressable market and bringing

50
00:02:55,600 --> 00:02:58,560
Speaker 1: those people into paid streaming. And a lot of people

51
00:02:58,560 --> 00:03:01,000
Speaker 1: don't know a lot about Amazon, you zick. So if

52
00:03:01,000 --> 00:03:04,360
Speaker 1: you have the Amazon Prime, what can you listen to?

53
00:03:05,160 --> 00:03:08,000
Speaker 1: If you listen? If you have Amazon Prime, you get

54
00:03:08,040 --> 00:03:11,280
Speaker 1: a catalog of about two million songs, But you get

55
00:03:11,320 --> 00:03:13,919
Speaker 1: two of the three major companies for all three majors.

56
00:03:13,960 --> 00:03:16,040
Speaker 1: Or you get all three majors. Now, when did the

57
00:03:16,080 --> 00:03:18,560
Speaker 1: third major come on board? Oh gosh, two and a

58
00:03:18,600 --> 00:03:21,440
Speaker 1: half three years ago, Yeah, quite a while ago. Um,

59
00:03:21,600 --> 00:03:25,079
Speaker 1: you get all three majors most indies. Um, but it's

60
00:03:25,080 --> 00:03:28,200
Speaker 1: a limited catalog. So you know, we launched Prime Music,

61
00:03:30,320 --> 00:03:33,120
Speaker 1: and the whole premise back then was you have to

62
00:03:33,160 --> 00:03:37,120
Speaker 1: remember dial back right. Spotify was much much smaller. Apple

63
00:03:37,240 --> 00:03:41,080
Speaker 1: Music didn't exist. There was a bunch of startups who

64
00:03:41,160 --> 00:03:44,760
Speaker 1: were offering ten dollars a month, and we knew we wanted,

65
00:03:44,840 --> 00:03:47,160
Speaker 1: we needed to be in streaming. But we also knew

66
00:03:47,160 --> 00:03:51,480
Speaker 1: from our own music store that back in very very

67
00:03:51,520 --> 00:03:55,440
Speaker 1: few people were actually spending anything close to twenty dollars

68
00:03:55,440 --> 00:03:57,200
Speaker 1: a year, which is what ten dollars a month adds

69
00:03:57,240 --> 00:04:01,520
Speaker 1: up to. In fact, the bottom of our customers, we're

70
00:04:01,560 --> 00:04:04,840
Speaker 1: spending about fifteen dollars a year a year, right, So

71
00:04:04,920 --> 00:04:07,040
Speaker 1: our idea behind Prime Music was, let's put out let's

72
00:04:07,080 --> 00:04:09,360
Speaker 1: give these people a lot of music. They're more casual

73
00:04:09,440 --> 00:04:13,360
Speaker 1: music listeners, but let's take out all that friction that

74
00:04:13,560 --> 00:04:15,240
Speaker 1: we talked to people. What do you not like about

75
00:04:15,240 --> 00:04:17,560
Speaker 1: the free music services. I don't like the ads, I

76
00:04:17,600 --> 00:04:19,359
Speaker 1: don't like the fact that I can't take it offline.

77
00:04:19,839 --> 00:04:21,480
Speaker 1: I don't like the fact that I can have limited

78
00:04:21,480 --> 00:04:23,880
Speaker 1: on my limited skips and all that stuff. So the

79
00:04:24,240 --> 00:04:27,560
Speaker 1: idea behind Prime Music was, let's make a music service

80
00:04:27,600 --> 00:04:30,440
Speaker 1: for everybody else because at the time, the only people

81
00:04:30,480 --> 00:04:32,160
Speaker 1: who were interested in ten dollars a month. And the

82
00:04:32,200 --> 00:04:35,680
Speaker 1: market has totally moved since then, um, but back then

83
00:04:35,760 --> 00:04:37,520
Speaker 1: it was it was very It was a small sliver

84
00:04:37,560 --> 00:04:39,440
Speaker 1: of people who wanted ten dollars a month, probably everyone

85
00:04:39,480 --> 00:04:43,120
Speaker 1: in this room, but you guys aren't representative of the

86
00:04:43,120 --> 00:04:47,440
Speaker 1: average consumer. And you know, out of the gate, the

87
00:04:47,480 --> 00:04:51,839
Speaker 1: whole industry misunderstood it, um, but consumers didn't because it

88
00:04:51,920 --> 00:04:56,359
Speaker 1: was adopted really really quickly. And yeah, so that and

89
00:04:56,360 --> 00:04:58,320
Speaker 1: there's a lot of curation involved. You know, we have

90
00:04:58,320 --> 00:05:01,520
Speaker 1: a team so that routine. How would you see the

91
00:05:01,520 --> 00:05:06,880
Speaker 1: market today, Um, there's definitely been so that that whole

92
00:05:06,880 --> 00:05:10,080
Speaker 1: segment still exists and is still growing rapidly. Um. And

93
00:05:10,160 --> 00:05:12,920
Speaker 1: we always got to remember that of the US population

94
00:05:13,040 --> 00:05:16,280
Speaker 1: or any other population historically hasn't spent anything on music

95
00:05:16,880 --> 00:05:19,719
Speaker 1: Lettleon ten bucks a month. Um, there's two. There's just

96
00:05:20,040 --> 00:05:22,560
Speaker 1: there's There's always been tress or radio, There's always been

97
00:05:23,480 --> 00:05:27,160
Speaker 1: almost always been cable music choice and YouTube and all

98
00:05:27,160 --> 00:05:30,839
Speaker 1: these other alternatives. Um. So that's still growing. But what

99
00:05:30,920 --> 00:05:33,120
Speaker 1: seems to have happened in the last three years is

100
00:05:33,440 --> 00:05:36,640
Speaker 1: a shift in mentality among consumers. I don't know if

101
00:05:36,640 --> 00:05:39,719
Speaker 1: there's this greater awareness of how what a great value

102
00:05:39,760 --> 00:05:42,880
Speaker 1: ten bucks a month really is for all that music.

103
00:05:43,480 --> 00:05:46,360
Speaker 1: I think I think Netflix and Hulu and all these

104
00:05:46,400 --> 00:05:49,800
Speaker 1: other services have helped. Right, people are used to subscribing

105
00:05:49,839 --> 00:05:52,280
Speaker 1: to things and not thinking that as I'm paying for music,

106
00:05:52,320 --> 00:05:55,640
Speaker 1: but I'm paying for entertainment. I think devices like the

107
00:05:55,680 --> 00:05:59,240
Speaker 1: Echo UM lower the barrier because it's something you use

108
00:05:59,279 --> 00:06:02,960
Speaker 1: so frequently and it's frictionless. And so we see that.

109
00:06:03,120 --> 00:06:06,719
Speaker 1: You know, the projections that existed for the size of

110
00:06:06,720 --> 00:06:10,359
Speaker 1: the ten dollar month market, um, you know those were

111
00:06:11,480 --> 00:06:13,240
Speaker 1: those are wrong now. I mean, it's clear that the

112
00:06:13,279 --> 00:06:15,599
Speaker 1: market's grown more quickly than anyone anticipated. And if the

113
00:06:15,640 --> 00:06:20,359
Speaker 1: percentage is on your service you have baked into Amazon

114
00:06:20,440 --> 00:06:23,680
Speaker 1: prompt you're not being charged per month you have are

115
00:06:24,560 --> 00:06:27,080
Speaker 1: to listen on an Echo, you have essentially a ten

116
00:06:27,120 --> 00:06:32,159
Speaker 1: dollar program to listen to Alla, Spotify, Apple Music. How

117
00:06:32,200 --> 00:06:38,599
Speaker 1: do the subscribers or the listeners breakdown amongst those three choices? Yeah,

118
00:06:38,680 --> 00:06:42,800
Speaker 1: I mean, so the three is really the same. It's

119
00:06:43,120 --> 00:06:45,920
Speaker 1: we have two services, Prime Music and Amazon Music Unlimited.

120
00:06:46,440 --> 00:06:50,320
Speaker 1: Prime is a limited catalog unlimited, as the name might suggest,

121
00:06:50,320 --> 00:06:53,120
Speaker 1: a full catalog service. UM. But one of the innovations

122
00:06:53,120 --> 00:06:56,640
Speaker 1: that we had was at launches, say, you know, can

123
00:06:56,720 --> 00:06:59,640
Speaker 1: we we think the Echo is incomplete without a full

124
00:06:59,640 --> 00:07:02,240
Speaker 1: catalog of music service. If you've ever used one. You've

125
00:07:02,279 --> 00:07:05,520
Speaker 1: got an intelligent assistant. You want to ask her anything

126
00:07:05,920 --> 00:07:09,159
Speaker 1: you know. And the analogy I always give people's imagine

127
00:07:09,200 --> 00:07:12,520
Speaker 1: if you said, hey, Alexa, you know what's the weather

128
00:07:12,520 --> 00:07:15,760
Speaker 1: in Santa Barbara and she'd say, well, I'm sorry, the

129
00:07:15,800 --> 00:07:18,760
Speaker 1: weather in Santa Barbara is not included with your prime membership.

130
00:07:19,240 --> 00:07:21,720
Speaker 1: I only have the weather in San Francisco and Seattle.

131
00:07:23,000 --> 00:07:26,239
Speaker 1: Not a great experience, and so we are. We've always

132
00:07:26,280 --> 00:07:29,920
Speaker 1: felt that for that device where it has no screen

133
00:07:30,920 --> 00:07:33,840
Speaker 1: where you can ask her anything, she's intelligent and always

134
00:07:33,840 --> 00:07:35,880
Speaker 1: getting more intelligent and you so you expect her to

135
00:07:35,880 --> 00:07:38,120
Speaker 1: be able to give you what you want. That it

136
00:07:38,400 --> 00:07:41,800
Speaker 1: demands a full catalog, and we took the approach of

137
00:07:41,840 --> 00:07:43,280
Speaker 1: saying went to the labels and said, you know, we

138
00:07:43,320 --> 00:07:46,840
Speaker 1: think there's a real opportunity here. Two for the first

139
00:07:46,840 --> 00:07:48,680
Speaker 1: time have what a lot of people called a mid

140
00:07:48,680 --> 00:07:52,240
Speaker 1: tier service, but not a dumb down service. It's a

141
00:07:52,280 --> 00:07:55,680
Speaker 1: full catalog, has all the features and functionality. The one

142
00:07:55,720 --> 00:07:59,560
Speaker 1: limitations that you're restricted to that single device. Um, but

143
00:07:59,600 --> 00:08:02,080
Speaker 1: it is Amazon Music Limit. There's abolutely nothing different about

144
00:08:02,080 --> 00:08:04,800
Speaker 1: it except that you can only play on that one echo. Uh.

145
00:08:05,040 --> 00:08:07,240
Speaker 1: That's been really successful for us, and we've seen a

146
00:08:07,240 --> 00:08:09,440
Speaker 1: pretty significant percentage of people who come on to that

147
00:08:09,480 --> 00:08:13,560
Speaker 1: on ramp leave and go to the full price plan,

148
00:08:14,160 --> 00:08:16,360
Speaker 1: whether an individual planks that would listen on their phone

149
00:08:16,840 --> 00:08:19,280
Speaker 1: or a family plan because they might have multiple echoes

150
00:08:19,320 --> 00:08:22,840
Speaker 1: and they like to have concurrent streams. Um. So Prime

151
00:08:22,920 --> 00:08:24,720
Speaker 1: Music has been around. To answer your question more directly,

152
00:08:24,800 --> 00:08:26,840
Speaker 1: I mean the Prime Music has been around for four years.

153
00:08:27,160 --> 00:08:30,560
Speaker 1: Next in the month, next month, next in June. Amazon

154
00:08:30,640 --> 00:08:35,160
Speaker 1: Music and Limited been around for eighteen months. Um. You

155
00:08:35,160 --> 00:08:38,080
Speaker 1: know it's it's uh, not quite fifty fifty, but it's

156
00:08:38,160 --> 00:08:41,319
Speaker 1: it's getting close. Um. And so Amazon Music Limb is

157
00:08:41,360 --> 00:08:45,079
Speaker 1: growing really really fast. Um, and Prime Music continues to

158
00:08:45,120 --> 00:08:49,319
Speaker 1: grow faster than Prime. So we're pretty happy there too. Okay,

159
00:08:49,400 --> 00:08:52,000
Speaker 1: let's go back. You don't come from the music business,

160
00:08:52,800 --> 00:08:56,000
Speaker 1: Uh No, although lass six and a half years I do. Okay.

161
00:08:56,040 --> 00:08:58,880
Speaker 1: So for we always like to get where someone's coming from.

162
00:08:59,360 --> 00:09:03,280
Speaker 1: We've discussed before. But for the people who are not here,

163
00:09:03,320 --> 00:09:07,840
Speaker 1: you grow up a lot of places. I was born

164
00:09:07,840 --> 00:09:11,439
Speaker 1: in New Jersey, grew up overseas and in New Jersey,

165
00:09:12,120 --> 00:09:15,720
Speaker 1: um until I was twelve, and then moved to Houston, Texas. Uh,

166
00:09:16,400 --> 00:09:18,840
Speaker 1: my parents are immigrants from Belgium, and so I spent

167
00:09:18,840 --> 00:09:21,440
Speaker 1: a lot of time in Europe growing up, and uh

168
00:09:21,559 --> 00:09:25,720
Speaker 1: then came out to California for college. And you know

169
00:09:25,800 --> 00:09:28,440
Speaker 1: my adult life, have lived a bunch more places, so

170
00:09:28,440 --> 00:09:31,120
Speaker 1: a bit all over. But after college you went to

171
00:09:31,200 --> 00:09:34,559
Speaker 1: law school, yep, I did. And when you went to

172
00:09:34,640 --> 00:09:38,920
Speaker 1: law school, what was your intention relative to practicing. So

173
00:09:39,040 --> 00:09:41,120
Speaker 1: my original plan, because I was an engineering guy. I

174
00:09:41,160 --> 00:09:43,880
Speaker 1: was an electrical engineer in college as well as a

175
00:09:43,920 --> 00:09:47,720
Speaker 1: history major. And you know, the life plan was, oh,

176
00:09:47,800 --> 00:09:49,680
Speaker 1: go work as an engineer for a few years, go

177
00:09:49,800 --> 00:09:52,720
Speaker 1: get an m b A and do that. And I

178
00:09:52,760 --> 00:09:56,160
Speaker 1: did work as an engineer for Compact Computer. If anybody

179
00:09:56,240 --> 00:10:00,000
Speaker 1: remembers that brand, um, yeah, there's enough people my agent here,

180
00:10:00,000 --> 00:10:03,559
Speaker 1: I certainly remember. Was I mean, I just was addressing Uh.

181
00:10:03,880 --> 00:10:06,600
Speaker 1: I was Amazon's got a small offense in Santa Barbara,

182
00:10:06,640 --> 00:10:07,840
Speaker 1: and I was going to talk to the people there

183
00:10:07,840 --> 00:10:09,400
Speaker 1: before coming here, and I was like, I think I'm

184
00:10:09,440 --> 00:10:13,560
Speaker 1: twenty years older than every single person in this room.

185
00:10:13,600 --> 00:10:16,120
Speaker 1: But I realized I didn't really enjoy being an engineer,

186
00:10:16,200 --> 00:10:17,920
Speaker 1: so I decided to go to law school. So the

187
00:10:17,960 --> 00:10:20,120
Speaker 1: plan was always go practiced for a few years, but

188
00:10:20,640 --> 00:10:22,679
Speaker 1: just take a different path to the same end point,

189
00:10:22,720 --> 00:10:24,440
Speaker 1: which is to to get into the business world in

190
00:10:24,480 --> 00:10:27,079
Speaker 1: one way or another. And what kind of law did

191
00:10:27,080 --> 00:10:31,480
Speaker 1: you practice? Uh? Corporate law starting in Washington, d c.

192
00:10:31,720 --> 00:10:35,559
Speaker 1: And that was miserable. And then UM moved back out

193
00:10:35,600 --> 00:10:39,720
Speaker 1: to northern California and met at my five year college

194
00:10:39,720 --> 00:10:43,680
Speaker 1: reunion a partner in a very small tech law firm,

195
00:10:43,760 --> 00:10:46,360
Speaker 1: and UH, by the end of launch, I was ready

196
00:10:46,360 --> 00:10:50,800
Speaker 1: to come out and started there the day that Yahoo

197
00:10:50,840 --> 00:10:53,680
Speaker 1: went public and it was in this company. This law

198
00:10:53,679 --> 00:10:57,160
Speaker 1: firm represented Yahoo. It's a very exciting day at that

199
00:10:57,240 --> 00:10:58,840
Speaker 1: law firm is one of you know, that was the

200
00:10:58,840 --> 00:11:02,280
Speaker 1: beginning of the Internet. UM Netscape had gone public six

201
00:11:02,320 --> 00:11:05,079
Speaker 1: months or year prior, and it was just a crazy,

202
00:11:05,440 --> 00:11:07,480
Speaker 1: crazy time. So I worked with startups for about two

203
00:11:07,520 --> 00:11:08,959
Speaker 1: and a half three years. And what did you actually

204
00:11:09,000 --> 00:11:12,640
Speaker 1: do as the lawyer? UM? A variety of things. So,

205
00:11:12,720 --> 00:11:15,319
Speaker 1: you know, you do finance work, work with the venture

206
00:11:15,360 --> 00:11:19,200
Speaker 1: capitalists to raise money, take companies public, two mergers. But

207
00:11:19,280 --> 00:11:21,240
Speaker 1: the fun stuff that we did was actually we really

208
00:11:21,280 --> 00:11:26,040
Speaker 1: kind of acted as their outsourced general counsel, you know,

209
00:11:26,040 --> 00:11:28,520
Speaker 1: because those are small companies. They may have money in

210
00:11:28,520 --> 00:11:31,000
Speaker 1: the bank from Sequoia or one of these big vcs.

211
00:11:31,080 --> 00:11:35,040
Speaker 1: But um so when it came to doing partnerships commercial

212
00:11:35,040 --> 00:11:38,160
Speaker 1: partnerships with people, um we would get involved at a

213
00:11:38,240 --> 00:11:41,079
Speaker 1: much earlier stage than you would normally associate with the

214
00:11:41,160 --> 00:11:43,960
Speaker 1: law a legal team. Normally it's like, hey, we've negotiated

215
00:11:43,960 --> 00:11:47,080
Speaker 1: a deal paper it. Uh, that's not how we worked.

216
00:11:47,120 --> 00:11:49,000
Speaker 1: We were in there a lot of the guys and

217
00:11:49,040 --> 00:11:50,520
Speaker 1: this was the early days of the Internet, A lot

218
00:11:50,520 --> 00:11:52,599
Speaker 1: of the guys that were the busines, dev guys, the

219
00:11:52,600 --> 00:11:55,720
Speaker 1: business own guys that these companies. I didn't know crap,

220
00:11:55,760 --> 00:11:57,560
Speaker 1: I don't know anything about the Internet. No one did.

221
00:11:57,960 --> 00:12:00,160
Speaker 1: But we actually knew more just because you know, we

222
00:12:00,200 --> 00:12:03,760
Speaker 1: would represent ten companies, you would see ten things. All

223
00:12:03,840 --> 00:12:06,000
Speaker 1: these people were straight out of business school and they

224
00:12:06,000 --> 00:12:08,240
Speaker 1: were just in their little lane with their one company.

225
00:12:08,280 --> 00:12:11,760
Speaker 1: So we got involved very early in hand in hand

226
00:12:11,800 --> 00:12:13,400
Speaker 1: it was. It was a lot of fun. So you

227
00:12:13,559 --> 00:12:16,440
Speaker 1: enjoyed that as opposed to working in Washington, d C. Yeah,

228
00:12:16,600 --> 00:12:19,840
Speaker 1: I enjoyed it until I realized the learning curve started

229
00:12:19,840 --> 00:12:22,800
Speaker 1: to flatten out, you know, and thinking any job you

230
00:12:22,920 --> 00:12:26,000
Speaker 1: probably look up and say that the people you work

231
00:12:26,080 --> 00:12:29,679
Speaker 1: for do I want to be that person? And as

232
00:12:29,720 --> 00:12:31,400
Speaker 1: people I was would be happy to be them. They

233
00:12:31,400 --> 00:12:33,240
Speaker 1: were really nice guys, but I didn't want to be

234
00:12:33,280 --> 00:12:34,559
Speaker 1: in their job. I didn't want to be a partner

235
00:12:34,559 --> 00:12:37,000
Speaker 1: at that firm. So, so how'd you segue into your

236
00:12:37,040 --> 00:12:41,840
Speaker 1: next role? I reached out to some clients, and so

237
00:12:41,920 --> 00:12:44,439
Speaker 1: you were actively looking to get out? Yeah, I decided

238
00:12:44,440 --> 00:12:46,760
Speaker 1: I had one of those moments. I still remember it.

239
00:12:48,000 --> 00:12:50,679
Speaker 1: I was at a wedding of a friend of mine

240
00:12:51,080 --> 00:12:54,480
Speaker 1: back east, and uh, I was flying back with my

241
00:12:54,640 --> 00:12:58,120
Speaker 1: now wife and we're sitting watching a movie and I

242
00:12:58,160 --> 00:13:00,120
Speaker 1: just I wasn't watching the movie. My brain was just

243
00:13:00,200 --> 00:13:02,160
Speaker 1: going a mile a minute. And I remember just out

244
00:13:02,200 --> 00:13:05,880
Speaker 1: blurting out, I'm done. And she looked at me, she

245
00:13:06,200 --> 00:13:08,200
Speaker 1: what'd you say? I said, I'll tell you later watch

246
00:13:08,200 --> 00:13:09,959
Speaker 1: the movie. Um. Yeah, I just had one of those

247
00:13:10,000 --> 00:13:12,120
Speaker 1: moments where like, I'm I don't want to do this anymore,

248
00:13:13,080 --> 00:13:15,319
Speaker 1: And so I started reaching out to clients. Now at

249
00:13:15,320 --> 00:13:18,520
Speaker 1: the time, was your soon to be wife. Was she working?

250
00:13:19,840 --> 00:13:22,560
Speaker 1: So was there any issue of economic instability or you

251
00:13:22,600 --> 00:13:26,160
Speaker 1: say I'm not leaving the law until I find another thing. Yeah,

252
00:13:26,160 --> 00:13:28,199
Speaker 1: I didn't. I didn't leave until I found a job

253
00:13:28,280 --> 00:13:30,440
Speaker 1: that was a lesson my My father taught me. It's like,

254
00:13:30,800 --> 00:13:33,280
Speaker 1: I've got more leverage if you're still working. So okay,

255
00:13:33,280 --> 00:13:34,959
Speaker 1: So you reach out your clients. What do you find

256
00:13:36,520 --> 00:13:40,200
Speaker 1: a lot of interests, UM and I, you know, I

257
00:13:40,240 --> 00:13:42,640
Speaker 1: talked to both startups and then I talked to Yahoo.

258
00:13:42,679 --> 00:13:49,240
Speaker 1: And Yahoo at that time was a newly public startup. Basically, um.

259
00:13:49,320 --> 00:13:51,080
Speaker 1: You know, it's hard a lot of people here are

260
00:13:51,120 --> 00:13:53,160
Speaker 1: old enough to remember, but it was the hottest company

261
00:13:53,160 --> 00:13:57,680
Speaker 1: in the world bar none. Um and UH. They were

262
00:13:57,679 --> 00:14:01,000
Speaker 1: looking for someone at the time. They're starting to expand

263
00:14:01,000 --> 00:14:04,400
Speaker 1: in Europe and they Europe generally was a couple of

264
00:14:04,440 --> 00:14:07,679
Speaker 1: years behind the US from an Internet accepting except in Scandinavia,

265
00:14:07,760 --> 00:14:10,240
Speaker 1: but in Maine, you know, Big five was kind of

266
00:14:10,280 --> 00:14:13,160
Speaker 1: behind the US, and so there weren't They've been looking

267
00:14:13,200 --> 00:14:15,439
Speaker 1: and it couldn't find anyone. And they're looking for someone

268
00:14:15,440 --> 00:14:18,240
Speaker 1: to run business development, and uh, I have a European

269
00:14:18,240 --> 00:14:21,880
Speaker 1: background and and and so that helped, and they said,

270
00:14:21,920 --> 00:14:23,640
Speaker 1: do you want to give it a shot? And like,

271
00:14:23,720 --> 00:14:25,200
Speaker 1: if you'll give a shot on me, I'll take it.

272
00:14:25,280 --> 00:14:29,360
Speaker 1: And so we moved to London. And so if you're

273
00:14:29,480 --> 00:14:32,480
Speaker 1: moving in London, you're you know, eight time zones away,

274
00:14:32,840 --> 00:14:36,640
Speaker 1: so one would think you're pretty much running your own show. Yeah,

275
00:14:36,680 --> 00:14:40,120
Speaker 1: you get a lot of autonomy. Um, you know, you

276
00:14:40,120 --> 00:14:43,120
Speaker 1: you spend a lot of time back in California the

277
00:14:43,200 --> 00:14:45,480
Speaker 1: company of that age, and doing business to all means

278
00:14:45,520 --> 00:14:48,840
Speaker 1: like doing partnerships that doesn't mean selling advertising means like

279
00:14:48,880 --> 00:14:53,080
Speaker 1: product type integrations, right and which means you need engineering support,

280
00:14:53,120 --> 00:14:55,160
Speaker 1: which happens in California. So you spent a lot of

281
00:14:55,200 --> 00:14:58,760
Speaker 1: time on Uh just say you get you get a

282
00:14:58,800 --> 00:15:00,240
Speaker 1: lot of phone calls when you're ready to go to

283
00:15:00,280 --> 00:15:02,920
Speaker 1: bed from people, right, and then you're bringing his firing

284
00:15:03,000 --> 00:15:05,800
Speaker 1: and you can't go exactly, So I supposed loved it.

285
00:15:05,880 --> 00:15:09,320
Speaker 1: It was a great four years in London and ultimately

286
00:15:09,320 --> 00:15:12,720
Speaker 1: a success or a frustration in terms of executing on

287
00:15:12,880 --> 00:15:16,600
Speaker 1: your role. Oh it was great. No, there were frustrations,

288
00:15:16,600 --> 00:15:19,680
Speaker 1: but I haven't had a job that doesn't have frustrations.

289
00:15:19,720 --> 00:15:23,480
Speaker 1: So but the net, the net output was great. And

290
00:15:23,560 --> 00:15:27,480
Speaker 1: when you were done four years later, our Yang and

291
00:15:27,600 --> 00:15:31,960
Speaker 1: his original partners still in charge. Oh yeah, yeah, Well

292
00:15:32,680 --> 00:15:35,400
Speaker 1: Jerry was there when I left the company. He he

293
00:15:35,440 --> 00:15:40,480
Speaker 1: had just become CEO. Um, we were at our second

294
00:15:40,520 --> 00:15:43,080
Speaker 1: CEO and said Tim Coogel was the original CEO of

295
00:15:43,080 --> 00:15:46,160
Speaker 1: of Yahoo and then Terry Simul had joined while I

296
00:15:46,240 --> 00:15:49,840
Speaker 1: was based in London. Okay, so how do you decide

297
00:15:49,880 --> 00:15:53,920
Speaker 1: we're at the end of Yahoo. Well, first they brought

298
00:15:53,920 --> 00:15:56,280
Speaker 1: me back, got promoted, did a bunch of other things,

299
00:15:56,320 --> 00:15:59,560
Speaker 1: spent I spent totally ten years there, first forward in London.

300
00:16:00,080 --> 00:16:02,000
Speaker 1: Then I may maybe I misunderstood, I forgot. So the

301
00:16:02,040 --> 00:16:04,120
Speaker 1: next six years, when you're back in the valley, what

302
00:16:04,280 --> 00:16:08,040
Speaker 1: is your role? It evolved to be head of UM

303
00:16:08,400 --> 00:16:12,400
Speaker 1: Mobile effectively, so I was the s VP of Mobile

304
00:16:13,080 --> 00:16:16,920
Speaker 1: to date myself. This was mostly in the feature phone era.

305
00:16:17,000 --> 00:16:19,440
Speaker 1: We did a lot of J two me apps, We

306
00:16:19,800 --> 00:16:26,440
Speaker 1: used whap browsers. Um. Uh, it's like getting flashbacks. Um.

307
00:16:27,280 --> 00:16:32,320
Speaker 1: The I left Yahoo two months after the app store launched. Okay,

308
00:16:32,360 --> 00:16:36,120
Speaker 1: so so we were but we were there on Jerry

309
00:16:36,200 --> 00:16:39,280
Speaker 1: was on stage with Steve when the iPhone launched. Yeah,

310
00:16:39,280 --> 00:16:43,040
Speaker 1: who was a big part of that launch. UM Yahoo

311
00:16:43,080 --> 00:16:46,280
Speaker 1: Mail was embedded in the service and to the Yahoo

312
00:16:46,320 --> 00:16:50,640
Speaker 1: the stocks and weather apps, though they were called widgets

313
00:16:50,680 --> 00:16:54,800
Speaker 1: back then by Apple. We're all powered by Yahoo. So, um,

314
00:16:54,960 --> 00:16:56,760
Speaker 1: what's when we knew the world had changed? Like the

315
00:16:56,800 --> 00:17:00,000
Speaker 1: first day when iPhones actually hit the market in June

316
00:17:00,040 --> 00:17:03,760
Speaker 1: two thousand seven. You may remember this, but they went

317
00:17:03,760 --> 00:17:06,080
Speaker 1: on sale at six pm, but six pm and each

318
00:17:06,119 --> 00:17:09,919
Speaker 1: time zone. So we sat in California, they were on

319
00:17:09,960 --> 00:17:13,560
Speaker 1: sale in New York on the East coast, and we

320
00:17:13,600 --> 00:17:15,760
Speaker 1: just sat with the engineers and just watched the data

321
00:17:15,840 --> 00:17:18,639
Speaker 1: of people using it, and it just it blew us

322
00:17:18,680 --> 00:17:21,399
Speaker 1: away because you know, you were like for years the

323
00:17:21,480 --> 00:17:24,119
Speaker 1: perennial question that someone to ask you. It's probably similar

324
00:17:24,160 --> 00:17:26,400
Speaker 1: to what was going on streams, Like you could take

325
00:17:26,400 --> 00:17:29,399
Speaker 1: this story and apply to streaming. But every year, you know,

326
00:17:29,440 --> 00:17:31,960
Speaker 1: you have your business plan review and Jerry Yang or

327
00:17:32,040 --> 00:17:35,440
Speaker 1: Terry selling, when is mobile actually finally going to be big?

328
00:17:35,840 --> 00:17:38,680
Speaker 1: And you're like, it's two years away? Every years, two years.

329
00:17:39,040 --> 00:17:41,960
Speaker 1: The analogy I always use is digital photography. We heard

330
00:17:42,000 --> 00:17:44,640
Speaker 1: for ten years the digital photography is going to come

331
00:17:44,640 --> 00:17:47,520
Speaker 1: in and kill Kodak, and then all of a sudden,

332
00:17:47,560 --> 00:17:51,359
Speaker 1: one year it happened everything and it's like wow, And

333
00:17:51,440 --> 00:17:53,879
Speaker 1: when iPhone happened and we and we had you know,

334
00:17:54,480 --> 00:17:57,879
Speaker 1: we've seen blackberries were the most used devices for mobile

335
00:17:57,920 --> 00:18:01,360
Speaker 1: internet then, but they were really horrible for mobile internet.

336
00:18:01,400 --> 00:18:04,760
Speaker 1: You know, they weren't designed for it, but but most

337
00:18:04,800 --> 00:18:06,760
Speaker 1: people had them were being their companies were paying for

338
00:18:06,800 --> 00:18:10,120
Speaker 1: their data, so you'd use it anyway. And then iPhone

339
00:18:10,160 --> 00:18:13,000
Speaker 1: came in and despite their being you know how many

340
00:18:13,160 --> 00:18:16,320
Speaker 1: few devices actually went online that day is like these

341
00:18:16,320 --> 00:18:19,240
Speaker 1: spikes and we all sat around like the world changed,

342
00:18:19,560 --> 00:18:22,520
Speaker 1: changed forever, and that, by the way, it's what changed

343
00:18:22,640 --> 00:18:26,080
Speaker 1: for music as well. I mean the iPhone smartphones are

344
00:18:26,119 --> 00:18:29,280
Speaker 1: really the foundation of a streaming of the streaming evolution

345
00:18:29,280 --> 00:18:33,240
Speaker 1: over the last ten years. Okay, looking at Yahoo which

346
00:18:33,240 --> 00:18:38,159
Speaker 1: has now been sold, what's it savable? And if it

347
00:18:38,240 --> 00:18:43,240
Speaker 1: was savable, what should they have done differently? Was it savable?

348
00:18:43,320 --> 00:18:45,960
Speaker 1: I don't think it was by the time. By the

349
00:18:46,040 --> 00:18:49,840
Speaker 1: time it got to that point, I think Yahoo suffered.

350
00:18:49,880 --> 00:18:51,520
Speaker 1: And one of the things that attracted me about coming

351
00:18:51,520 --> 00:18:57,480
Speaker 1: to Amazon, um it never had the kind of visionary CEO.

352
00:18:58,000 --> 00:19:00,800
Speaker 1: Jerry is an amazing guy, for he's never the CEO,

353
00:19:01,119 --> 00:19:03,200
Speaker 1: never wanted to be, and he was only when he

354
00:19:03,480 --> 00:19:05,000
Speaker 1: was forced to because there was no one else who

355
00:19:05,000 --> 00:19:10,240
Speaker 1: wanted the job. Um he's an amazing guy, and uh

356
00:19:10,760 --> 00:19:13,000
Speaker 1: had a good had a really good vision, but he

357
00:19:13,000 --> 00:19:16,360
Speaker 1: he wasn't the CEO that could just galvanize the whole

358
00:19:16,359 --> 00:19:18,320
Speaker 1: company behind it. And and yeah, who got stuck. Are

359
00:19:18,320 --> 00:19:20,240
Speaker 1: we a media company or a technology company? And it

360
00:19:20,359 --> 00:19:24,280
Speaker 1: was never never land Um had it decided that years before?

361
00:19:25,080 --> 00:19:29,159
Speaker 1: Perhaps savable, but I think by the time Jerry became CEO,

362
00:19:29,400 --> 00:19:31,400
Speaker 1: I don't think it was. And you could see look

363
00:19:31,400 --> 00:19:34,400
Speaker 1: at the succession of CEOs after that, they all followed

364
00:19:34,600 --> 00:19:36,840
Speaker 1: despite saying they were doing a new strategy, was pretty

365
00:19:36,920 --> 00:19:41,800
Speaker 1: much the same strategy. And Terry Summel big mistake or

366
00:19:41,960 --> 00:19:44,920
Speaker 1: nothing he could done. I love Terry, Terry is a

367
00:19:44,920 --> 00:19:47,000
Speaker 1: great guy. I don't want to I'm not here to talk,

368
00:19:47,400 --> 00:19:49,560
Speaker 1: you know. No, It's just interesting because we see this

369
00:19:49,600 --> 00:19:53,000
Speaker 1: in the music business, both famously with Andy lack Now

370
00:19:53,040 --> 00:19:55,879
Speaker 1: I was back in the news business. Came in and

371
00:19:56,000 --> 00:19:58,399
Speaker 1: he really didn't understand the business. So we look at

372
00:19:58,520 --> 00:20:01,240
Speaker 1: Terry Semmel, who came from enter Tinman. Was he a

373
00:20:01,280 --> 00:20:03,560
Speaker 1: fish out of water and really did not understand the

374
00:20:03,600 --> 00:20:08,520
Speaker 1: technology business? Um. You know, I think they're probably people

375
00:20:08,560 --> 00:20:10,119
Speaker 1: who are in better position to answer that than me.

376
00:20:10,160 --> 00:20:11,760
Speaker 1: To be honest with you, I didn't work that closely

377
00:20:11,800 --> 00:20:14,600
Speaker 1: with Terry Um. I was off kind of doing my

378
00:20:14,600 --> 00:20:17,000
Speaker 1: own thing in mobile and he was okay. So you

379
00:20:17,040 --> 00:20:18,680
Speaker 1: wake up one day on a plane and say I'm

380
00:20:18,680 --> 00:20:22,359
Speaker 1: done at Yahoo. Uh. It was coming for a while

381
00:20:22,440 --> 00:20:29,120
Speaker 1: longer than that. You know, the company got bigger, and UM,

382
00:20:29,280 --> 00:20:30,920
Speaker 1: I don't know, just I kind of had an itch

383
00:20:31,000 --> 00:20:34,720
Speaker 1: to go do something smaller. I think politics had changed

384
00:20:34,720 --> 00:20:36,560
Speaker 1: in the company. It wasn't as fun as it once was.

385
00:20:37,320 --> 00:20:40,560
Speaker 1: Um and uh I kind of waited around, you know,

386
00:20:41,400 --> 00:20:44,880
Speaker 1: because I remember Microsoft bid for Yahoo and a hostile

387
00:20:44,960 --> 00:20:48,760
Speaker 1: takeover thing, and then carl Icon got involved. And that

388
00:20:48,840 --> 00:20:50,400
Speaker 1: was a moment where you like, I never thought I'd

389
00:20:50,400 --> 00:20:53,919
Speaker 1: worked for a company that carl Icon was making a

390
00:20:53,960 --> 00:20:56,720
Speaker 1: bid for it. Just it just it was time. It

391
00:20:56,800 --> 00:20:59,399
Speaker 1: was time to do something different. And the next step

392
00:20:59,600 --> 00:21:02,680
Speaker 1: was so I went to a couple of different startups.

393
00:21:02,720 --> 00:21:06,199
Speaker 1: I really wanted to be CEO of something, and so

394
00:21:06,240 --> 00:21:08,879
Speaker 1: I went to one company that I stayed in the

395
00:21:08,920 --> 00:21:11,639
Speaker 1: mobile world, and it was a social networking app that

396
00:21:11,920 --> 00:21:14,959
Speaker 1: had taken off. I was on feature phones and um

397
00:21:15,560 --> 00:21:19,119
Speaker 1: that was it was called meg thirty three, and you know,

398
00:21:19,240 --> 00:21:21,720
Speaker 1: Android was almost non existent at this point. This is

399
00:21:21,760 --> 00:21:27,040
Speaker 1: now fall of two eight, Um and Uh. It had

400
00:21:27,040 --> 00:21:31,480
Speaker 1: taken off in places like Indonesia, India, Malaysia, a little

401
00:21:31,480 --> 00:21:36,560
Speaker 1: bit in South Africa, and we ended up moving the

402
00:21:36,600 --> 00:21:40,200
Speaker 1: company to Singapore because it was just I didn't move

403
00:21:40,240 --> 00:21:43,320
Speaker 1: with it. Um. Well, it was the motivation. It was

404
00:21:43,560 --> 00:21:45,920
Speaker 1: impossible to run a company in that part of the

405
00:21:45,960 --> 00:21:49,120
Speaker 1: world from California. It was just happenstance that the customers

406
00:21:49,119 --> 00:21:51,920
Speaker 1: were there. The r poo's out of those customers don't

407
00:21:51,960 --> 00:21:56,520
Speaker 1: support California engineering costs. Um, you're not close. You know.

408
00:21:56,600 --> 00:21:59,240
Speaker 1: The thing is, none of our engineers are. Probably people

409
00:21:59,240 --> 00:22:01,560
Speaker 1: really used the product because it was a social networking thing.

410
00:22:01,560 --> 00:22:06,359
Speaker 1: They're all on Facebook and there, so they don't know

411
00:22:06,440 --> 00:22:08,240
Speaker 1: their own product in a way that you can only

412
00:22:08,280 --> 00:22:10,360
Speaker 1: know you in the internet. If you don't, if you're

413
00:22:10,400 --> 00:22:12,760
Speaker 1: not close to your customer, you're just not gonna have

414
00:22:12,800 --> 00:22:15,959
Speaker 1: a successful service. And uh so it started to languish

415
00:22:16,000 --> 00:22:18,040
Speaker 1: in terms of product innovation, so we decided to move

416
00:22:18,040 --> 00:22:21,760
Speaker 1: it there. It ultimately Um that company ultimately got listed

417
00:22:21,760 --> 00:22:24,240
Speaker 1: on the Australian Exchange and then got bought out and

418
00:22:24,400 --> 00:22:26,040
Speaker 1: I'm not sure what's going on with it, and kept

419
00:22:26,119 --> 00:22:28,840
Speaker 1: up with it, um. And then I went to another

420
00:22:28,880 --> 00:22:32,639
Speaker 1: company called Looped, which was one of the original apps

421
00:22:32,880 --> 00:22:39,320
Speaker 1: around social location sharing and social location sharing, which ultimately

422
00:22:39,320 --> 00:22:42,120
Speaker 1: got sold. Um. You know the name of that was

423
00:22:42,920 --> 00:22:46,439
Speaker 1: that was looped l O O P T. Yeah, it

424
00:22:46,520 --> 00:22:50,560
Speaker 1: ultimately got sold. Um mainly that the company had its

425
00:22:51,160 --> 00:22:53,960
Speaker 1: moment in the sun, like internet companies do or consumer

426
00:22:54,000 --> 00:22:56,480
Speaker 1: companies do, and they either kind of continue on that

427
00:22:56,520 --> 00:23:00,080
Speaker 1: trajectory they flat line, it started to flat line, and

428
00:23:00,280 --> 00:23:02,840
Speaker 1: it got it got bought out, primarily for the tech

429
00:23:02,880 --> 00:23:05,600
Speaker 1: talent that was in the company. That's an Amazon called.

430
00:23:09,560 --> 00:23:11,840
Speaker 1: We'll take a quick break and come back with more

431
00:23:11,880 --> 00:23:15,680
Speaker 1: of my conversation with VP of the Amazon Music Steve Boom,

432
00:23:15,800 --> 00:23:18,840
Speaker 1: recorded live at the Music Media Summit in Santa Barbara,

433
00:23:18,920 --> 00:23:25,359
Speaker 1: California this week. I'm speaking with Steve Boom. Over the

434
00:23:25,400 --> 00:23:27,879
Speaker 1: last couple of months, I've interviewed the lead singer of

435
00:23:27,960 --> 00:23:31,680
Speaker 1: Free and Bad Company, Paul Rodgers, and social media expert

436
00:23:31,720 --> 00:23:35,199
Speaker 1: at U t A. Kendall Lostro. We try to provide

437
00:23:35,240 --> 00:23:38,640
Speaker 1: a balance of entertaining and informative content for you here

438
00:23:38,680 --> 00:23:41,520
Speaker 1: on the Bob Left Steps podcast. Be the first to

439
00:23:41,560 --> 00:23:44,440
Speaker 1: hear next week's episode by subscribing to the podcast on

440
00:23:44,600 --> 00:23:49,240
Speaker 1: tune in, Apple Podcast or your podcast Apple choice. While

441
00:23:49,240 --> 00:23:54,440
Speaker 1: you're there, please rate and review the podcast. Okay, let's

442
00:23:54,480 --> 00:23:59,520
Speaker 1: get back to my conversation with Steve Boom, Amazon called

443
00:23:59,560 --> 00:24:02,320
Speaker 1: you what was the gig they were looking for you

444
00:24:02,359 --> 00:24:06,159
Speaker 1: to fill. Well, it's kind of a funny story, um,

445
00:24:06,200 --> 00:24:08,920
Speaker 1: at least for me. Uh. They called said, well, we're

446
00:24:09,080 --> 00:24:11,800
Speaker 1: starting to invest heavily in digital media. This is two

447
00:24:11,800 --> 00:24:16,760
Speaker 1: thousand eleven and so um the Prime Video service had

448
00:24:16,800 --> 00:24:21,840
Speaker 1: only recently launched and the Amazon Cloud locker had just

449
00:24:22,160 --> 00:24:24,480
Speaker 1: recently launched and I and I remember reading about that

450
00:24:24,520 --> 00:24:27,640
Speaker 1: because it caused a bit of kerfuffle in the industry

451
00:24:27,640 --> 00:24:30,600
Speaker 1: because it was unlicensed, and I think that's why it

452
00:24:30,680 --> 00:24:33,360
Speaker 1: made all the tech news. And they said, look, we're

453
00:24:33,400 --> 00:24:36,719
Speaker 1: we're investing in digital media. We're looking for some executives

454
00:24:36,720 --> 00:24:39,240
Speaker 1: to come build this out. And I said, well, you

455
00:24:39,280 --> 00:24:43,000
Speaker 1: can see from my LinkedIn that I don't have any

456
00:24:43,119 --> 00:24:48,280
Speaker 1: background in music or video. And the answer was, yes,

457
00:24:48,800 --> 00:24:52,679
Speaker 1: that's probably that's probably not a bad thing. And their

458
00:24:52,760 --> 00:24:56,119
Speaker 1: view was, you know, at a company like Amazon, you know,

459
00:24:56,200 --> 00:24:59,520
Speaker 1: your traditional music industry exactly, the hit rate was going

460
00:24:59,560 --> 00:25:01,359
Speaker 1: to be low for them to succeed at a company

461
00:25:01,359 --> 00:25:04,800
Speaker 1: like Amazon. Um, they really wanted someone more with a

462
00:25:04,800 --> 00:25:07,840
Speaker 1: more tech background because that the roles involved running engineering

463
00:25:07,840 --> 00:25:10,480
Speaker 1: teams and product teams and someone maybe came from a

464
00:25:10,480 --> 00:25:13,760
Speaker 1: more data driven background. And so what was your were

465
00:25:13,760 --> 00:25:16,600
Speaker 1: your responsibilities when you finally got the gig and went

466
00:25:16,640 --> 00:25:19,919
Speaker 1: into the building. Well before I joined, I thought it

467
00:25:19,960 --> 00:25:26,880
Speaker 1: was gonna be all of music, including physical music. Um.

468
00:25:26,920 --> 00:25:28,720
Speaker 1: But I had dinner with my boss a month before

469
00:25:28,760 --> 00:25:30,040
Speaker 1: I joined, said, Hey, I just won't let you know.

470
00:25:30,080 --> 00:25:34,080
Speaker 1: There's a re orc coming. The company's gonna split out,

471
00:25:34,119 --> 00:25:37,080
Speaker 1: split the physical and digital businesses altogether, not just in music,

472
00:25:37,080 --> 00:25:40,600
Speaker 1: but across the board. Just realize how fundamentally different they

473
00:25:40,600 --> 00:25:43,720
Speaker 1: are other than the fact that your partners are the same, um,

474
00:25:43,760 --> 00:25:46,199
Speaker 1: but from a running a business perspective, they're They're just

475
00:25:46,480 --> 00:25:50,280
Speaker 1: totally different. Uh. And he said, I don't I doubt

476
00:25:50,280 --> 00:25:52,320
Speaker 1: if you're too upset about not having to run the

477
00:25:52,320 --> 00:25:55,679
Speaker 1: physical business. And I was like, you know, I'm just

478
00:25:55,720 --> 00:25:58,879
Speaker 1: excited to be joining Amazon. Whatever, It's fine. So my

479
00:25:59,040 --> 00:26:01,760
Speaker 1: when I joined, my my my role and was and

480
00:26:01,760 --> 00:26:06,240
Speaker 1: continues to be to run Amazon's digital music business, um

481
00:26:06,280 --> 00:26:08,080
Speaker 1: from soup to nuts. And that's the way the company

482
00:26:08,200 --> 00:26:12,919
Speaker 1: organizes itself. It really has true general managers that have

483
00:26:13,520 --> 00:26:17,040
Speaker 1: product and engineering and marketing and finance and business development

484
00:26:17,080 --> 00:26:20,800
Speaker 1: and you know, licensing, label relations. All that stuff rolls

485
00:26:20,880 --> 00:26:22,600
Speaker 1: up into a single leader and that's the way the

486
00:26:22,600 --> 00:26:25,280
Speaker 1: company has always organized itself. Now there's a point where

487
00:26:25,320 --> 00:26:28,560
Speaker 1: you go to Bezos with a pitch. Why don't you

488
00:26:28,600 --> 00:26:35,159
Speaker 1: tell that story? Well, I mean we, um, you know,

489
00:26:35,240 --> 00:26:37,880
Speaker 1: we Amazon had been in digital music since two thousand seven,

490
00:26:37,880 --> 00:26:40,760
Speaker 1: it launched the MP three stores, the first first guy

491
00:26:40,880 --> 00:26:45,680
Speaker 1: to launch with DRM. Without DRM, I should say, um,

492
00:26:45,720 --> 00:26:50,120
Speaker 1: but you know, honestly, had had had modest success in

493
00:26:50,119 --> 00:26:54,199
Speaker 1: in the download business, and um, it was clearly a

494
00:26:54,240 --> 00:26:57,439
Speaker 1: segment that was being fairly well dominated by one player

495
00:26:57,720 --> 00:27:00,920
Speaker 1: given the device ecosystem, we knew we needed to get

496
00:27:00,960 --> 00:27:03,480
Speaker 1: into streaming. And the pitch was when I basically just

497
00:27:03,680 --> 00:27:09,480
Speaker 1: you know, basically kind of described with Prime Music, which is, um, Jeff,

498
00:27:09,480 --> 00:27:11,640
Speaker 1: we should get into streaming. That's where our customers are going.

499
00:27:11,680 --> 00:27:14,240
Speaker 1: And they know Amazon everything is customer first, customer first,

500
00:27:14,240 --> 00:27:17,960
Speaker 1: customer first. We saw what our customers were doing, and uh,

501
00:27:18,119 --> 00:27:20,240
Speaker 1: you know, we had seen that Prime the Prime Video service,

502
00:27:20,280 --> 00:27:22,280
Speaker 1: this is you know, this was now we're in early

503
00:27:23,960 --> 00:27:26,480
Speaker 1: the time frame that I'm talking about, and and um,

504
00:27:26,520 --> 00:27:28,600
Speaker 1: we could tell that Prime Video seemed to be getting

505
00:27:28,600 --> 00:27:31,639
Speaker 1: traction and the company was starting to invest more in

506
00:27:31,680 --> 00:27:33,920
Speaker 1: the Prime Video service and was really starting to put

507
00:27:33,920 --> 00:27:38,680
Speaker 1: its weight behind it UM. And you know, Jeff, we

508
00:27:38,680 --> 00:27:40,080
Speaker 1: we had talked to him before, like how do you

509
00:27:40,119 --> 00:27:44,080
Speaker 1: consider what do you think about adding things to Prime?

510
00:27:44,160 --> 00:27:46,560
Speaker 1: And you know, obviously the things you want to add

511
00:27:46,600 --> 00:27:49,880
Speaker 1: to a service like Prime or things that have broad appeal,

512
00:27:50,960 --> 00:27:55,280
Speaker 1: and what has broader appealed in music? Really nothing? And

513
00:27:55,960 --> 00:27:57,960
Speaker 1: people have been speculating for a long time, when is

514
00:27:58,000 --> 00:27:59,920
Speaker 1: Amazon going to add a music service to Prime? When

515
00:28:00,160 --> 00:28:03,440
Speaker 1: you know it's got to be coming soon, and so

516
00:28:03,640 --> 00:28:07,159
Speaker 1: we do what you do at Amazon. We spent several months.

517
00:28:07,200 --> 00:28:09,520
Speaker 1: We have a certain process that we follow there which

518
00:28:09,560 --> 00:28:15,080
Speaker 1: is different than another companies. And what we do is

519
00:28:15,080 --> 00:28:19,520
Speaker 1: we write a press release, one page press release of

520
00:28:20,160 --> 00:28:23,159
Speaker 1: explain to the consumer what you're about to launch, and

521
00:28:23,240 --> 00:28:25,400
Speaker 1: you polish that because if you can't do that, then

522
00:28:25,440 --> 00:28:26,920
Speaker 1: you don't know what you know, you haven't figured out

523
00:28:26,920 --> 00:28:29,040
Speaker 1: what is you want to do. And then behind that

524
00:28:29,080 --> 00:28:32,399
Speaker 1: one page press release UM, we call this document a

525
00:28:32,480 --> 00:28:34,119
Speaker 1: p R f a Q. There's an f a Q

526
00:28:34,320 --> 00:28:37,760
Speaker 1: Frequently Asked Questions section after that, and you write your

527
00:28:37,760 --> 00:28:40,120
Speaker 1: own questions and answers, and then we call a meeting

528
00:28:40,880 --> 00:28:43,680
Speaker 1: UM and there's then financial support and exhibits and all

529
00:28:43,680 --> 00:28:45,120
Speaker 1: that kind of stuff, and we call a meeting, and

530
00:28:45,120 --> 00:28:47,840
Speaker 1: we called a meeting with Jeff um with our CFO

531
00:28:47,920 --> 00:28:51,120
Speaker 1: at the time, um kind named Tom Scoot Tach who

532
00:28:51,280 --> 00:28:54,080
Speaker 1: is not our Brian. ALSOFSKI is the currency, a CFO,

533
00:28:54,800 --> 00:28:57,880
Speaker 1: and and a couple and several other you know, senior

534
00:28:57,960 --> 00:29:02,680
Speaker 1: leaders at the company spent ninety minutes first thirty minutes

535
00:29:02,680 --> 00:29:05,040
Speaker 1: of that meeting. You know, it's a bunch of middle

536
00:29:05,080 --> 00:29:08,680
Speaker 1: aged people with reading glasses sitting around staring at this

537
00:29:08,840 --> 00:29:11,760
Speaker 1: document and reading it because we don't we don't power

538
00:29:11,800 --> 00:29:14,000
Speaker 1: point at Amazon. We don't believe in it. Except if

539
00:29:14,040 --> 00:29:15,520
Speaker 1: I were, if I were giving you a speech, I

540
00:29:15,520 --> 00:29:17,880
Speaker 1: would power point. But then what's the difference. Why no

541
00:29:17,960 --> 00:29:21,640
Speaker 1: power point inside the building and power point outside the building? Well,

542
00:29:21,640 --> 00:29:24,080
Speaker 1: because if you're if the purpose of a meeting is

543
00:29:24,120 --> 00:29:27,000
Speaker 1: to to make a decision, power points are not a

544
00:29:27,000 --> 00:29:28,600
Speaker 1: good it's not a good meeting is a good way

545
00:29:28,600 --> 00:29:32,000
Speaker 1: to tell a story and present something, But if you

546
00:29:32,040 --> 00:29:35,520
Speaker 1: want to make a decision, you know there's two things.

547
00:29:35,560 --> 00:29:38,240
Speaker 1: One empower point. It's really easy to have bullet points

548
00:29:39,240 --> 00:29:41,560
Speaker 1: and to b as your way through things, right, It's

549
00:29:41,560 --> 00:29:43,480
Speaker 1: like try to do that when you have to write

550
00:29:43,520 --> 00:29:45,960
Speaker 1: complete sentences in a paragraph form and make it a

551
00:29:46,040 --> 00:29:49,719
Speaker 1: narrative that stretches over six pages. You find yourself testing

552
00:29:49,720 --> 00:29:52,040
Speaker 1: your your own thinking is refined and refined and refined

553
00:29:52,120 --> 00:29:54,400
Speaker 1: until it all hangs. The other part is when you

554
00:29:54,440 --> 00:29:57,960
Speaker 1: give a presentation. If we were to try to decide

555
00:29:57,960 --> 00:30:00,680
Speaker 1: something in this room, all of us together, some of

556
00:30:00,720 --> 00:30:02,640
Speaker 1: you would know what I'm talking about before I even

557
00:30:02,680 --> 00:30:05,360
Speaker 1: got up here, maybe more than I do. And then

558
00:30:05,400 --> 00:30:07,800
Speaker 1: some of you would know nothing about the topic, and

559
00:30:07,840 --> 00:30:10,280
Speaker 1: I'd be trying to give a presentation. Hands would be

560
00:30:10,320 --> 00:30:13,440
Speaker 1: going up, and you'd be asking questions about slide twenty seven,

561
00:30:13,440 --> 00:30:15,920
Speaker 1: even though on slide seven, and there's someone who's still

562
00:30:15,920 --> 00:30:18,880
Speaker 1: trying to figure out slide three, and you have a

563
00:30:18,920 --> 00:30:23,600
Speaker 1: complete mismatch of information. So the conversation is not even handed.

564
00:30:23,640 --> 00:30:26,440
Speaker 1: And so what happens. The way we do things. You

565
00:30:26,480 --> 00:30:29,080
Speaker 1: walk into the room, you hand out this, you make whatever,

566
00:30:29,160 --> 00:30:32,000
Speaker 1: twin copies, twenty copies. However, however, many people are in

567
00:30:32,000 --> 00:30:36,840
Speaker 1: the meeting, and we all then read. And the idea

568
00:30:36,880 --> 00:30:39,760
Speaker 1: is when we're done reading, some people will still have

569
00:30:39,840 --> 00:30:42,800
Speaker 1: more information than others, but everyone will have the same baseline,

570
00:30:42,800 --> 00:30:45,120
Speaker 1: and that baseline should be sufficient to make the decision

571
00:30:45,120 --> 00:30:48,040
Speaker 1: that we're asking you to make, UM, and so we'll

572
00:30:48,080 --> 00:30:50,040
Speaker 1: all sit there and read it ahead of time. And

573
00:30:50,040 --> 00:30:52,600
Speaker 1: I heard Jeff explain why don't you read it in advance?

574
00:30:53,320 --> 00:30:55,240
Speaker 1: I think there's two answers, one as no one has time,

575
00:30:56,280 --> 00:30:58,240
Speaker 1: and the other is and this I laughed when I

576
00:30:58,280 --> 00:31:00,760
Speaker 1: heard this, because I was just listening to this um

577
00:31:00,920 --> 00:31:03,720
Speaker 1: in some speech he gave recent. He said, because everyone

578
00:31:03,720 --> 00:31:05,680
Speaker 1: in the room is really smart, and they won't read

579
00:31:05,720 --> 00:31:07,160
Speaker 1: it ahead of time, but then they'll b as their

580
00:31:07,200 --> 00:31:10,720
Speaker 1: way through it and act like they did. And so

581
00:31:10,800 --> 00:31:12,920
Speaker 1: this way you're forced to sit there and you know,

582
00:31:13,080 --> 00:31:14,520
Speaker 1: what else are you gonna do? You know, there's this

583
00:31:14,520 --> 00:31:17,880
Speaker 1: thing in front of you. So we spent ninety minutes. Uh,

584
00:31:17,880 --> 00:31:20,640
Speaker 1: and so once again, how long are do people spend reading?

585
00:31:20,880 --> 00:31:23,320
Speaker 1: Thirty minutes? Okay? But I just remember, you know, like

586
00:31:23,360 --> 00:31:25,959
Speaker 1: being in school, you're always uptight or you fast? Are

587
00:31:25,960 --> 00:31:28,240
Speaker 1: you slow? You're gonna be ahead of this person. It's

588
00:31:28,280 --> 00:31:32,880
Speaker 1: almost like you feel a pressure. You know, we're we're

589
00:31:32,880 --> 00:31:36,360
Speaker 1: all friends and colleagues. So um, you know, you wait

590
00:31:36,480 --> 00:31:38,080
Speaker 1: if your if it's your meeting, you kind of look

591
00:31:38,120 --> 00:31:40,720
Speaker 1: around and you say, okay, it looks like does anyone

592
00:31:40,760 --> 00:31:43,480
Speaker 1: need more time, or sometimes you'll say, look, we're gonna

593
00:31:43,480 --> 00:31:44,960
Speaker 1: read for thirty minutes and then and we're going to

594
00:31:45,080 --> 00:31:48,200
Speaker 1: talk after that, and yeah, if you haven't read every word,

595
00:31:48,200 --> 00:31:50,120
Speaker 1: it's not the end of the world. And then we

596
00:31:50,440 --> 00:31:52,520
Speaker 1: talked about it for the next I think it was

597
00:31:52,560 --> 00:31:54,760
Speaker 1: a ninety minute meeting probably, and they asked a bunch

598
00:31:54,760 --> 00:31:59,600
Speaker 1: of questions, talked about the numbers, etcetera, etcetera. The product

599
00:31:59,680 --> 00:32:03,600
Speaker 1: that merrily and okay, let's do this. And you know

600
00:32:04,720 --> 00:32:06,920
Speaker 1: that's for me pre remarkable. I've worked in a number

601
00:32:06,960 --> 00:32:10,560
Speaker 1: of places and too. It was you know, we we

602
00:32:10,600 --> 00:32:12,480
Speaker 1: had prepared. So it's not like we didn't come in

603
00:32:12,560 --> 00:32:14,560
Speaker 1: half prepared, because that could have been a go back

604
00:32:14,560 --> 00:32:16,240
Speaker 1: and think about this and that and the other thing.

605
00:32:16,840 --> 00:32:18,960
Speaker 1: But it was, you know, we thought about it, thought

606
00:32:18,960 --> 00:32:21,960
Speaker 1: it through and uh had a decision taken in in

607
00:32:22,040 --> 00:32:25,720
Speaker 1: that meeting and lunch. You know, everybody at this point

608
00:32:25,800 --> 00:32:29,000
Speaker 1: you talk about a CEO with vision at this point,

609
00:32:29,000 --> 00:32:31,200
Speaker 1: with the death of Steve Jobs, in the retirement of

610
00:32:31,200 --> 00:32:35,200
Speaker 1: other people, uh, the two people two people people focus

611
00:32:35,280 --> 00:32:39,040
Speaker 1: on our elon Musk and Bezos. So of all the

612
00:32:39,080 --> 00:32:46,520
Speaker 1: CEO as you've dealt with, what does Jeff do differently. Um,

613
00:32:46,560 --> 00:32:50,680
Speaker 1: I think he's just is he very demanding? It's very

614
00:32:50,720 --> 00:32:55,560
Speaker 1: great clarity. Uh, And I think he he talks the

615
00:32:55,640 --> 00:32:57,680
Speaker 1: talk and walks the walk. So we we've set out

616
00:32:57,800 --> 00:33:01,080
Speaker 1: broad principles that we we managed by at the company.

617
00:33:01,600 --> 00:33:06,360
Speaker 1: He reiterates them, Um, explains them when he feels necessary.

618
00:33:07,360 --> 00:33:10,520
Speaker 1: But mostly what I think he does that's great is

619
00:33:10,560 --> 00:33:13,360
Speaker 1: he he lets his leaders lead. So if we were

620
00:33:13,360 --> 00:33:15,239
Speaker 1: to get him on the phone right now and we

621
00:33:15,240 --> 00:33:18,560
Speaker 1: were to talk about some details of Amazon Music, would

622
00:33:18,560 --> 00:33:23,080
Speaker 1: he be familiar with those? He dives down into all

623
00:33:23,120 --> 00:33:28,200
Speaker 1: the product verticals. So from the time you decided that

624
00:33:28,280 --> 00:33:30,920
Speaker 1: you wanted to do this until you gotta yes, how

625
00:33:30,960 --> 00:33:36,000
Speaker 1: long was that? Uh? Well, the time the yes was

626
00:33:36,040 --> 00:33:38,320
Speaker 1: in that meeting, I don't know when I'm talking about

627
00:33:38,440 --> 00:33:40,960
Speaker 1: from the time you said months, a few months, don't know.

628
00:33:41,280 --> 00:33:44,840
Speaker 1: And then you built everything from scratch. You didn't buy anything. No,

629
00:33:44,960 --> 00:33:48,120
Speaker 1: we haven't bought anything in music. But that's interesting because

630
00:33:48,160 --> 00:33:52,200
Speaker 1: everybody else is buying services. You know, Apple bought beats

631
00:33:52,760 --> 00:33:54,960
Speaker 1: and other things to give it leg up. Why do

632
00:33:55,040 --> 00:33:57,760
Speaker 1: you decide with certain players in the marketplace that you're

633
00:33:57,760 --> 00:34:02,240
Speaker 1: going to start from scratch. There's lots of reasons. I mean,

634
00:34:02,440 --> 00:34:05,800
Speaker 1: you know, well, now we already have an infrastructured so

635
00:34:06,200 --> 00:34:08,520
Speaker 1: if I were buying something, it would be to buy subscribers.

636
00:34:08,840 --> 00:34:12,799
Speaker 1: I haven't come across other than the biggest of the

637
00:34:12,800 --> 00:34:15,000
Speaker 1: big I haven't come across companies that can that can

638
00:34:15,000 --> 00:34:17,480
Speaker 1: really accelerate our growth. We're doing just fine, thank you,

639
00:34:17,760 --> 00:34:22,239
Speaker 1: um and UM. But in the earlier days, look, it's

640
00:34:23,440 --> 00:34:25,560
Speaker 1: you can spend as much time trying to integrate their

641
00:34:25,600 --> 00:34:29,319
Speaker 1: systems into the Amazon systems as it will take you

642
00:34:29,360 --> 00:34:32,520
Speaker 1: just to build it from scratch. And uh and you know,

643
00:34:32,560 --> 00:34:35,279
Speaker 1: so we looked, we did look at companies and either

644
00:34:35,360 --> 00:34:37,720
Speaker 1: the prices didn't make sense for what you were getting,

645
00:34:38,320 --> 00:34:41,160
Speaker 1: or we didn't think the technology was all that great. Um.

646
00:34:41,200 --> 00:34:43,800
Speaker 1: That happens a lot a lot of a lot of startups.

647
00:34:43,800 --> 00:34:45,960
Speaker 1: You know, the biggest thing when you buy them. And

648
00:34:46,000 --> 00:34:47,760
Speaker 1: I saw this at Yahoo all the time because y'aha

649
00:34:48,000 --> 00:34:52,160
Speaker 1: yah who operated an incredible scale. UM. And we bought

650
00:34:52,160 --> 00:34:54,280
Speaker 1: a lot of companies in the in the late nineties,

651
00:34:54,320 --> 00:34:56,040
Speaker 1: and the first thing you'd end up doing half the

652
00:34:56,120 --> 00:34:58,120
Speaker 1: time is having to rebuild half the technology because it

653
00:34:58,200 --> 00:35:01,560
Speaker 1: just couldn't scale. It's a lot for now because everyone

654
00:35:01,640 --> 00:35:04,759
Speaker 1: runs on Amazon Web Services, so thinks scale seamlessly. But

655
00:35:04,800 --> 00:35:07,840
Speaker 1: back then that didn't exist. Um, you know some of

656
00:35:07,840 --> 00:35:10,360
Speaker 1: the technology some of these companies that are trying to

657
00:35:10,360 --> 00:35:12,480
Speaker 1: sell themselves, maybe their technology is just based on an

658
00:35:12,480 --> 00:35:15,000
Speaker 1: older technology stack. You know, they've been around for a

659
00:35:15,080 --> 00:35:17,759
Speaker 1: few years and they're using older technologies that, yeah, we're

660
00:35:17,800 --> 00:35:20,239
Speaker 1: gonna have to replace that. So what's the point. And

661
00:35:20,280 --> 00:35:22,120
Speaker 1: do you hire outside people to build it or you

662
00:35:22,160 --> 00:35:26,520
Speaker 1: have inside engineers the Amazon to build your music service? Yeah?

663
00:35:26,520 --> 00:35:28,760
Speaker 1: Now we build it in house and we've we've staffed

664
00:35:28,840 --> 00:35:30,920
Speaker 1: up our team, but we don't use out we don't

665
00:35:31,000 --> 00:35:34,680
Speaker 1: use third parties. It's all it's all internal. Okay. So

666
00:35:36,040 --> 00:35:39,279
Speaker 1: from the time you launch it, at what point is

667
00:35:39,280 --> 00:35:45,439
Speaker 1: the Echo introduced? Um? Five months later? It turns out,

668
00:35:45,480 --> 00:35:48,200
Speaker 1: so we launched in June two thousand fourteen Prime Music

669
00:35:48,239 --> 00:35:50,760
Speaker 1: in the United States. The Echo launched on a beta

670
00:35:50,920 --> 00:35:54,960
Speaker 1: invitation only basis in November or late October, early to

671
00:35:55,000 --> 00:35:58,239
Speaker 1: mid November, somewhere in that range two thousand fourteen. And

672
00:35:58,280 --> 00:36:01,320
Speaker 1: at what point did you feel this is the future?

673
00:36:03,320 --> 00:36:08,040
Speaker 1: Probably March? And what was what was the lightbulb moment?

674
00:36:09,440 --> 00:36:12,120
Speaker 1: There are a couple of lifebub moments, um, I mean,

675
00:36:12,160 --> 00:36:14,799
Speaker 1: the first was just being consumers ourselves and being in

676
00:36:14,840 --> 00:36:18,160
Speaker 1: the music game. So you know, we had echoes those

677
00:36:18,400 --> 00:36:20,200
Speaker 1: some of us on the on the on the music

678
00:36:20,239 --> 00:36:24,000
Speaker 1: team during the when no one knew this product even existed.

679
00:36:24,040 --> 00:36:29,319
Speaker 1: But it's a beta product, it's an alpha product, and

680
00:36:29,400 --> 00:36:31,880
Speaker 1: you know, it works and some days it works, some

681
00:36:31,960 --> 00:36:34,040
Speaker 1: days it doesn't work, like any product that's in development,

682
00:36:34,760 --> 00:36:37,440
Speaker 1: so you don't really get that full customer experience. The

683
00:36:37,480 --> 00:36:42,560
Speaker 1: magic wasn't happening just yet. Um. But then you know,

684
00:36:42,680 --> 00:36:45,560
Speaker 1: once it started shipping, then of course we all had them.

685
00:36:45,560 --> 00:36:48,520
Speaker 1: And what I tell everybody is because we we've given

686
00:36:48,520 --> 00:36:51,160
Speaker 1: a lot of people echoes, and you know, when we

687
00:36:51,280 --> 00:36:53,080
Speaker 1: visit the labels like here, you should have one of this.

688
00:36:53,160 --> 00:36:55,440
Speaker 1: And what I tell people is if I come back

689
00:36:55,480 --> 00:36:57,040
Speaker 1: and it's sitting in your office, I'm taking it back

690
00:36:57,080 --> 00:36:59,920
Speaker 1: with me. Put it in your house, because it's not

691
00:37:00,120 --> 00:37:02,520
Speaker 1: meant to be in your Office's not that's not where

692
00:37:02,560 --> 00:37:03,920
Speaker 1: I mean you can put on there. It's great, but

693
00:37:04,760 --> 00:37:07,000
Speaker 1: if you want to understand the magic of a of

694
00:37:07,040 --> 00:37:09,000
Speaker 1: the voice interface and you have to have it in

695
00:37:09,040 --> 00:37:11,440
Speaker 1: your home, it has to be in a an area

696
00:37:11,480 --> 00:37:14,160
Speaker 1: where you're going about your business doing other things, it's

697
00:37:14,160 --> 00:37:16,400
Speaker 1: in a high traffic area, it's in a communal area,

698
00:37:17,360 --> 00:37:19,520
Speaker 1: and so we started using them in our homes, right,

699
00:37:19,560 --> 00:37:21,080
Speaker 1: And so when it was in beta, we weren't really

700
00:37:21,160 --> 00:37:22,920
Speaker 1: using them in our homes because you never know who's

701
00:37:22,920 --> 00:37:25,960
Speaker 1: gonna pop into your house that kind of thing. So, uh,

702
00:37:26,160 --> 00:37:28,680
Speaker 1: part of this, we were just consumers and we started

703
00:37:28,680 --> 00:37:31,880
Speaker 1: to understand the possibility. The other part was we started

704
00:37:31,880 --> 00:37:36,960
Speaker 1: to look at data and we could see of the

705
00:37:37,120 --> 00:37:40,160
Speaker 1: very few people that had gotten echoes in the very

706
00:37:40,239 --> 00:37:42,440
Speaker 1: early part of two thousand fifteen because they were in

707
00:37:42,600 --> 00:37:48,279
Speaker 1: very short supply, um, just how much they were being

708
00:37:48,360 --> 00:37:53,040
Speaker 1: used for music, and the different ways in which they're

709
00:37:53,040 --> 00:37:55,080
Speaker 1: being used for music, the ways the way people that

710
00:37:55,239 --> 00:37:58,320
Speaker 1: the ways that people are asking to to have Alexa

711
00:37:58,360 --> 00:38:01,400
Speaker 1: play music for them, in many cases very different than

712
00:38:01,440 --> 00:38:03,920
Speaker 1: you would expect them to do if they had a

713
00:38:04,360 --> 00:38:07,279
Speaker 1: visual app like an iPhone or an Android app. And

714
00:38:07,320 --> 00:38:09,799
Speaker 1: that's when we kind of realized and put all that

715
00:38:09,840 --> 00:38:15,239
Speaker 1: stuff together like this is this is profound. And I've

716
00:38:15,239 --> 00:38:16,839
Speaker 1: been around the block a couple of times and I've

717
00:38:16,840 --> 00:38:20,319
Speaker 1: seen these platforms shifts happen, and it was Okay, I

718
00:38:20,360 --> 00:38:24,799
Speaker 1: remember the shift from you know, uh button to touch

719
00:38:24,840 --> 00:38:28,680
Speaker 1: interface and and the impact that had fundamentally and mobile,

720
00:38:29,480 --> 00:38:31,960
Speaker 1: and we just started to you know, extrapolate out and

721
00:38:32,560 --> 00:38:35,360
Speaker 1: dream a little bit and say, you know, is voice

722
00:38:36,880 --> 00:38:40,120
Speaker 1: that level of of of a shift in platform and

723
00:38:40,160 --> 00:38:45,040
Speaker 1: the way people compute interact with computers, And you know,

724
00:38:45,520 --> 00:38:48,319
Speaker 1: we thought it would be, and particularly we thought it

725
00:38:48,320 --> 00:38:51,080
Speaker 1: would be for interacting with digital media, because we just

726
00:38:51,239 --> 00:38:54,399
Speaker 1: once you use it, you're like, it's just easier, it's

727
00:38:54,440 --> 00:38:56,760
Speaker 1: so much better. It's you know, there's so much less friction.

728
00:38:57,160 --> 00:38:59,600
Speaker 1: The first time. I'm sure all of you guys have

729
00:38:59,600 --> 00:39:03,600
Speaker 1: have you voice controls at some point, but man, the

730
00:39:03,640 --> 00:39:09,400
Speaker 1: first time you show someone of any technical background from

731
00:39:09,480 --> 00:39:14,240
Speaker 1: my mother in law to an engineer. She's not an engineer,

732
00:39:14,239 --> 00:39:15,800
Speaker 1: by the way, so I mean like she's got the

733
00:39:15,880 --> 00:39:18,480
Speaker 1: less technical background of those two people, and you just

734
00:39:18,520 --> 00:39:21,600
Speaker 1: say Alexa play and name a song and it comes out.

735
00:39:22,920 --> 00:39:27,200
Speaker 1: That's just magic. And the first time, now it's the

736
00:39:27,239 --> 00:39:31,120
Speaker 1: best innovation seemed commonplace three or four years later, um,

737
00:39:31,160 --> 00:39:33,279
Speaker 1: and like, well, of course, but I was not. And

738
00:39:33,360 --> 00:39:36,080
Speaker 1: of course a few years ago and it truly that

739
00:39:36,120 --> 00:39:39,399
Speaker 1: I remember showing to you know, record label executives. Their

740
00:39:39,400 --> 00:39:44,080
Speaker 1: eyes popped out, you know, and and that magic. Once

741
00:39:44,080 --> 00:39:46,160
Speaker 1: we understood that magic, we realized this is this is

742
00:39:46,200 --> 00:39:49,160
Speaker 1: a great this is just the way that you can

743
00:39:49,200 --> 00:39:51,719
Speaker 1: interact with digital media. It's just better. And do you

744
00:39:51,760 --> 00:39:55,160
Speaker 1: think at this point the music industry is up to

745
00:39:55,239 --> 00:39:59,160
Speaker 1: speed on what a huge breakthrough this is at this

746
00:39:59,239 --> 00:40:02,200
Speaker 1: point now and the eighteen Oh yeah, totally. Do you

747
00:40:02,200 --> 00:40:05,160
Speaker 1: think people understand that because there have been historically late

748
00:40:05,200 --> 00:40:10,000
Speaker 1: to everything, whether it be file trading, digital download streaming. Yeah,

749
00:40:10,040 --> 00:40:13,120
Speaker 1: I gotta say I, you know you're right, And UM,

750
00:40:13,160 --> 00:40:16,359
Speaker 1: I have to you know, I I'm not getting paid

751
00:40:16,400 --> 00:40:18,040
Speaker 1: to say this, but I have to take my hat

752
00:40:18,080 --> 00:40:21,120
Speaker 1: off to the labels because we went to go talk

753
00:40:21,160 --> 00:40:24,120
Speaker 1: about Amazon Music Unlimited in the very beginning of two

754
00:40:24,120 --> 00:40:27,440
Speaker 1: thousand and sixteen, so this is after the very first

755
00:40:27,520 --> 00:40:30,600
Speaker 1: Echo Christmas, but it was a smallish Echo Christmas. The

756
00:40:30,600 --> 00:40:33,200
Speaker 1: device was a year old, and you know, we went

757
00:40:33,280 --> 00:40:35,120
Speaker 1: to go pitch them on the deals and we came

758
00:40:35,160 --> 00:40:38,480
Speaker 1: with suitcases full of Echoes to hand out to everybody,

759
00:40:38,760 --> 00:40:41,240
Speaker 1: and I gave my little speech. But what we found

760
00:40:41,360 --> 00:40:44,960
Speaker 1: was that to a t or two to a person,

761
00:40:45,040 --> 00:40:48,480
Speaker 1: rather they had all bought them already. They had gifted

762
00:40:48,480 --> 00:40:52,399
Speaker 1: them to friends over the over the holiday they all

763
00:40:52,480 --> 00:40:57,239
Speaker 1: were super up to date on it and understood the opportunity, so,

764
00:40:57,440 --> 00:41:01,040
Speaker 1: you know, very collaborative conversations from the get go. It

765
00:41:01,160 --> 00:41:05,040
Speaker 1: wasn't It wasn't I think what maybe conversations were in

766
00:41:05,120 --> 00:41:09,040
Speaker 1: previous generations, and I think that's a lot of streaming

767
00:41:09,040 --> 00:41:13,399
Speaker 1: obviously was advancing, and the label saw that, um, this

768
00:41:13,480 --> 00:41:15,560
Speaker 1: was going to be their business going forward. And then

769
00:41:15,560 --> 00:41:17,600
Speaker 1: they saw this device and I think they used it

770
00:41:17,640 --> 00:41:20,680
Speaker 1: as consumers and they understood the power of it. Well,

771
00:41:20,800 --> 00:41:22,360
Speaker 1: I just know this is one of the products that

772
00:41:22,400 --> 00:41:24,160
Speaker 1: was sold by word of mouth. First of all, there

773
00:41:24,160 --> 00:41:27,960
Speaker 1: was theoretically limited availability, but yeah, I was liking theoretically

774
00:41:29,520 --> 00:41:31,040
Speaker 1: I'll tell you know, I'll tell you I So I

775
00:41:31,080 --> 00:41:33,239
Speaker 1: had one, but I ordered it in November when it

776
00:41:33,239 --> 00:41:36,840
Speaker 1: first came out in novemb It showed up on my

777
00:41:36,880 --> 00:41:40,320
Speaker 1: doorstep in May the following year, so it really was limited.

778
00:41:40,360 --> 00:41:42,759
Speaker 1: It started to be they ramped up production, you know

779
00:41:42,840 --> 00:41:45,279
Speaker 1: that year at some point, well, Gary Dela bat I

780
00:41:45,280 --> 00:41:46,840
Speaker 1: was talking to Me's really in the producer of the

781
00:41:46,840 --> 00:41:50,680
Speaker 1: Howard Stern Show, and he's it was such zeal I

782
00:41:50,719 --> 00:41:52,759
Speaker 1: had to get one, and it was sort of like,

783
00:41:53,160 --> 00:41:55,239
Speaker 1: first of all, we're more of a software era than

784
00:41:55,239 --> 00:41:58,040
Speaker 1: a hardware era. But his excitement made me feel that

785
00:41:58,080 --> 00:42:00,920
Speaker 1: I wanted to get one same thing. In terms of

786
00:42:01,280 --> 00:42:04,719
Speaker 1: Amazon Music Unlimited, doesn't seem like there's a lot of

787
00:42:04,880 --> 00:42:10,000
Speaker 1: advertising outside of the Amazon ecosystem, but talk about the

788
00:42:10,080 --> 00:42:13,000
Speaker 1: little triggers you have in your system to try to

789
00:42:13,040 --> 00:42:19,880
Speaker 1: get people to upgrade. Yeah. So, um, you know, one

790
00:42:19,880 --> 00:42:21,600
Speaker 1: of the things we worked on for the launch was

791
00:42:21,640 --> 00:42:25,319
Speaker 1: we wanted to make sure the subscription process was as

792
00:42:25,560 --> 00:42:29,799
Speaker 1: as simple as possible. Um. We obviously, like one of

793
00:42:29,800 --> 00:42:34,440
Speaker 1: our competitors have you know, customer, lots of customers, credit

794
00:42:34,480 --> 00:42:37,399
Speaker 1: card accounts. People buy stuff from Amazon, that's what they do.

795
00:42:37,440 --> 00:42:41,280
Speaker 1: We have a commerce space relationship with them, and um,

796
00:42:41,320 --> 00:42:42,880
Speaker 1: you know, we wanted to make sure they could just

797
00:42:43,200 --> 00:42:46,480
Speaker 1: talk to Alexa to subscribe, so you can do that,

798
00:42:46,960 --> 00:42:53,920
Speaker 1: and um, we're pretty confident that that's the the if

799
00:42:53,960 --> 00:42:56,800
Speaker 1: this is sounds like an oxymoron, but the most frictionless,

800
00:42:57,520 --> 00:42:59,799
Speaker 1: the least amount of friction in any subscription that I've

801
00:42:59,840 --> 00:43:02,279
Speaker 1: are seen. And so one of the things we do.

802
00:43:02,400 --> 00:43:04,160
Speaker 1: You know, if you were to ask for a track,

803
00:43:04,440 --> 00:43:06,920
Speaker 1: and say you're a prime member, if you were to

804
00:43:06,920 --> 00:43:09,400
Speaker 1: ask for a track that's not in Prime Music, so

805
00:43:09,440 --> 00:43:12,839
Speaker 1: it's not part of those two million odd songs. Um,

806
00:43:13,040 --> 00:43:16,440
Speaker 1: you would hear Alexas say something like, you know that

807
00:43:16,520 --> 00:43:20,240
Speaker 1: song is not in Prime Music. It's available in Amazon

808
00:43:20,320 --> 00:43:23,320
Speaker 1: Music Unlimited along with tens of millions of other songs

809
00:43:23,400 --> 00:43:29,319
Speaker 1: or something like that. Uh, free trial for thirty days

810
00:43:29,320 --> 00:43:36,000
Speaker 1: after that as month, should I start your free trial? Yes,

811
00:43:36,800 --> 00:43:39,600
Speaker 1: that's all you have to say, and music will start playing.

812
00:43:40,520 --> 00:43:43,400
Speaker 1: And I don't know if it gets an easier than that.

813
00:43:43,480 --> 00:43:45,759
Speaker 1: And so we do that. And that's that's very effective,

814
00:43:45,840 --> 00:43:48,400
Speaker 1: you know, because you're it's always more effective to to

815
00:43:48,480 --> 00:43:51,200
Speaker 1: get someone to upgrade to something when they're in the moment.

816
00:43:52,120 --> 00:43:54,880
Speaker 1: Then they're already they're already so far down that funnel

817
00:43:55,400 --> 00:43:57,759
Speaker 1: in consideration that it's it doesn't take a lot to

818
00:43:57,760 --> 00:44:00,560
Speaker 1: get them over the last hurdle. If if you're having

819
00:44:00,600 --> 00:44:03,440
Speaker 1: to spend you know, two or fifty million dollars creating

820
00:44:03,440 --> 00:44:07,520
Speaker 1: a brand for yourself, that's just creating awareness. So once

821
00:44:07,520 --> 00:44:09,319
Speaker 1: they're on the echo device, you know, we do that.

822
00:44:09,440 --> 00:44:13,320
Speaker 1: We do things if um, if if you have multiple

823
00:44:13,320 --> 00:44:15,560
Speaker 1: echoes in your home and say you're listening in one

824
00:44:15,640 --> 00:44:18,439
Speaker 1: room and your kids listening and wants to listen, well,

825
00:44:18,520 --> 00:44:20,279
Speaker 1: let's put the other way. Your kids listening in one

826
00:44:20,360 --> 00:44:21,640
Speaker 1: room and then you're in the other room and you

827
00:44:21,680 --> 00:44:24,480
Speaker 1: try to listen, and Alex will say, um, you know,

828
00:44:24,480 --> 00:44:26,560
Speaker 1: because we're limit you're limited to one stream at a

829
00:44:26,560 --> 00:44:29,840
Speaker 1: time and all these music services, that's that's a condition

830
00:44:29,840 --> 00:44:33,160
Speaker 1: of the labels. She'd say something like, you know, music

831
00:44:33,239 --> 00:44:36,120
Speaker 1: is playing on the other device. Um, but if you

832
00:44:36,200 --> 00:44:37,880
Speaker 1: upgrade to the Family Plan, you can have up to

833
00:44:37,920 --> 00:44:42,320
Speaker 1: six concurrent streams. And well, it turns out that's pretty effective,

834
00:44:42,600 --> 00:44:44,719
Speaker 1: you know, um, because if you really want to listen

835
00:44:44,760 --> 00:44:46,560
Speaker 1: to music and your time, and you maybe didn't even

836
00:44:46,560 --> 00:44:49,239
Speaker 1: know the Family Plan existed, right, and now he's like,

837
00:44:49,239 --> 00:44:52,160
Speaker 1: oh cool, well you have four echoes, I got three kids. Great,

838
00:44:52,200 --> 00:44:56,480
Speaker 1: let's do it. And also, assuming someone's not asking for

839
00:44:56,600 --> 00:44:59,680
Speaker 1: something that's not in the two million catalog you do

840
00:44:59,760 --> 00:45:04,880
Speaker 1: have of periodic adds, shall we say them to upgrade?

841
00:45:05,560 --> 00:45:07,800
Speaker 1: Well we we you know, we communicate with our customers,

842
00:45:07,800 --> 00:45:13,200
Speaker 1: but Alexa doesn't run ads, so you're communicating saying, hey,

843
00:45:13,239 --> 00:45:17,560
Speaker 1: this opportunity is here, um through normal like email and

844
00:45:17,600 --> 00:45:21,680
Speaker 1: push messaging channels, but not there's you know, Alexa's personality

845
00:45:21,760 --> 00:45:25,080
Speaker 1: is it's very it's it's very carefully guarded. She's not

846
00:45:25,120 --> 00:45:26,759
Speaker 1: going to be you know, she's not meant there to

847
00:45:26,840 --> 00:45:29,320
Speaker 1: hawk products, you know, and and she's not meant to

848
00:45:29,320 --> 00:45:32,480
Speaker 1: be too sales. So if you're just you won't what

849
00:45:32,520 --> 00:45:34,719
Speaker 1: you won't see is or here I should say. So,

850
00:45:34,800 --> 00:45:38,279
Speaker 1: if you're listening to a playlist, you're not going to

851
00:45:38,360 --> 00:45:41,000
Speaker 1: get interrupted in the middle in between songs and say, hey,

852
00:45:41,040 --> 00:45:42,759
Speaker 1: by the way, there's this thing called am some music

853
00:45:42,760 --> 00:45:45,480
Speaker 1: on Limit. There's no advertising on Echo and we don't

854
00:45:45,480 --> 00:45:48,120
Speaker 1: advertise like that either. It's because it's just contextual. There's

855
00:45:48,120 --> 00:45:52,200
Speaker 1: no pushing of the unlimited service on Alexa unless you

856
00:45:52,239 --> 00:45:54,160
Speaker 1: ask for something that is not there. Yeah, unless you're

857
00:45:54,280 --> 00:45:57,759
Speaker 1: unless you're really in the moment of wanting music and

858
00:45:58,080 --> 00:46:00,480
Speaker 1: we think we can improve your experience. Okay, So, in

859
00:46:00,520 --> 00:46:06,080
Speaker 1: the world today of selling music, not literally but marketing music,

860
00:46:06,640 --> 00:46:11,680
Speaker 1: playlists are thought to be king. How does someone enter

861
00:46:11,960 --> 00:46:19,760
Speaker 1: the Amazon ecosystem and get their songs heard? Um? Well,

862
00:46:19,800 --> 00:46:21,600
Speaker 1: first of all, we have a team of programmers who

863
00:46:21,640 --> 00:46:25,759
Speaker 1: are out looking for music and deciding themselves how many

864
00:46:25,760 --> 00:46:31,560
Speaker 1: people are there? Tensa um and they're out and you know,

865
00:46:31,600 --> 00:46:35,800
Speaker 1: they're in different cities and assigned to different genres. Um.

866
00:46:35,840 --> 00:46:38,280
Speaker 1: You know, our country programmers are in are in Nashville,

867
00:46:38,280 --> 00:46:42,200
Speaker 1: not a big surprise, and um, they're out doing what

868
00:46:42,239 --> 00:46:45,480
Speaker 1: those guys do. They go out to listen to new

869
00:46:45,520 --> 00:46:48,160
Speaker 1: bands play and new artists and they listen for music.

870
00:46:48,640 --> 00:46:51,640
Speaker 1: We obviously meet with the record labels, we meet with

871
00:46:51,719 --> 00:46:56,560
Speaker 1: artists management, and we get played a lot of music. Um.

872
00:46:56,640 --> 00:46:59,759
Speaker 1: And you know, it's ultimate editorial decision. You know, what

873
00:46:59,880 --> 00:47:01,200
Speaker 1: is it that we want to what is it that

874
00:47:01,239 --> 00:47:05,000
Speaker 1: we want to play? And you know, we'll promote music

875
00:47:05,040 --> 00:47:07,279
Speaker 1: when it comes. If if there's an artist that we

876
00:47:07,520 --> 00:47:09,239
Speaker 1: want to get behind, we work with the label to

877
00:47:09,280 --> 00:47:12,520
Speaker 1: promote them. Um. But ultimately the decision of what and

878
00:47:12,560 --> 00:47:15,279
Speaker 1: where to put something in a playlist comes down to

879
00:47:15,320 --> 00:47:19,440
Speaker 1: the editorial team. Okay. But if you're a manager, there

880
00:47:19,520 --> 00:47:23,160
Speaker 1: is someone you can meet with. Yeah, absolutely okay. And

881
00:47:23,200 --> 00:47:26,239
Speaker 1: then you subsequently look at the data and there for

882
00:47:26,360 --> 00:47:29,239
Speaker 1: a massage what gets played and what's not, What gets

883
00:47:29,239 --> 00:47:31,680
Speaker 1: added and gets dropped from playlist based on the number

884
00:47:31,719 --> 00:47:36,279
Speaker 1: of streams. Sure, sure, okay. And Amazon has seen someone

885
00:47:36,320 --> 00:47:39,600
Speaker 1: of as a black hole. Now Spotify is now public,

886
00:47:39,840 --> 00:47:42,799
Speaker 1: they're releasing a lot of information. First and foremost, if

887
00:47:42,840 --> 00:47:45,200
Speaker 1: I am an artist on Amazon, do you have a

888
00:47:45,280 --> 00:47:48,160
Speaker 1: dashboard where I can see all my data? Not at

889
00:47:48,160 --> 00:47:51,000
Speaker 1: the current time. So well, we eventually we will. We

890
00:47:51,040 --> 00:47:52,839
Speaker 1: just don't have it yet. We've been more focused on,

891
00:47:53,600 --> 00:47:56,000
Speaker 1: you know, getting big enough that artists would want to

892
00:47:56,000 --> 00:47:59,120
Speaker 1: come look at a dashboard on Amazon. Okay, And then

893
00:47:59,400 --> 00:48:02,400
Speaker 1: you have Apple, as I say, trumpeting how many urban

894
00:48:02,520 --> 00:48:05,719
Speaker 1: streams they have, And we don't really know what's going

895
00:48:05,760 --> 00:48:09,759
Speaker 1: on in Amazon. The first question is what is going on?

896
00:48:09,960 --> 00:48:11,960
Speaker 1: And second is there a way for us to find

897
00:48:12,000 --> 00:48:18,600
Speaker 1: out on a regular basis. I can't come here every day. Sorry, Um,

898
00:48:19,280 --> 00:48:21,880
Speaker 1: what is going on? Lots of lots is going on.

899
00:48:22,000 --> 00:48:25,120
Speaker 1: But yeah, as a company, we tend to be more

900
00:48:25,160 --> 00:48:28,480
Speaker 1: reticent to share data. Is just across the board. I

901
00:48:28,560 --> 00:48:32,680
Speaker 1: value my job, so I try not to share too much. Um.

902
00:48:33,760 --> 00:48:38,200
Speaker 1: Ultimately we we we will, uh created an avenue for

903
00:48:39,000 --> 00:48:41,240
Speaker 1: for artists to see what's going on in real time.

904
00:48:41,360 --> 00:48:44,400
Speaker 1: I mean, we obviously give reports to all the labels

905
00:48:44,400 --> 00:48:48,600
Speaker 1: and so the labels know what's going on in our service. Um,

906
00:48:48,840 --> 00:48:50,799
Speaker 1: but we we don't make it as public as some

907
00:48:50,840 --> 00:48:54,640
Speaker 1: of the other services. We also don't just generally beat

908
00:48:54,640 --> 00:48:57,200
Speaker 1: our chest as much and try to like you know,

909
00:48:57,280 --> 00:48:59,400
Speaker 1: talk about how many streams x artists did in the

910
00:48:59,400 --> 00:49:02,680
Speaker 1: first weekend just sort of not it's just not really

911
00:49:02,680 --> 00:49:10,000
Speaker 1: what we do as much. We'll pause here for a

912
00:49:10,040 --> 00:49:12,600
Speaker 1: brief moment and get right back to VP of the

913
00:49:12,640 --> 00:49:17,560
Speaker 1: Amazon Music Steve Boom. As most of you know, I'm

914
00:49:17,560 --> 00:49:19,560
Speaker 1: a writer and you can read my work at left

915
00:49:19,560 --> 00:49:22,960
Speaker 1: sets dot com in addition to reading my commentary on

916
00:49:23,160 --> 00:49:25,799
Speaker 1: music tech in the world at large. Will be the

917
00:49:25,840 --> 00:49:28,360
Speaker 1: first to find out when we've published a new podcast.

918
00:49:28,719 --> 00:49:30,840
Speaker 1: Go to left sets dot com and sign up for

919
00:49:30,880 --> 00:49:34,360
Speaker 1: the news letter. Now more of the VP of the

920
00:49:34,360 --> 00:49:38,400
Speaker 1: Amazon Music Steve Boom, recorded live the Music Media Summit

921
00:49:38,440 --> 00:49:45,319
Speaker 1: in Santa Barbara, California. What can you say? We talked

922
00:49:45,360 --> 00:49:49,040
Speaker 1: about this a little earlier, and I'll use the word counterintuitive.

923
00:49:49,440 --> 00:49:51,800
Speaker 1: What do we learn about what's happening on the Amazon

924
00:49:51,920 --> 00:49:59,239
Speaker 1: service as opposed to its competitors. UM, I'm not even

925
00:49:59,239 --> 00:50:02,080
Speaker 1: sure how to answer. That's such a broad question. Specifically,

926
00:50:02,440 --> 00:50:07,719
Speaker 1: are there different genres that are emphasized? Uh, yeah, you'll

927
00:50:07,760 --> 00:50:10,880
Speaker 1: see different Like I said, you'll see different genres. Um.

928
00:50:11,040 --> 00:50:12,919
Speaker 1: I can look at our charts. They just they look

929
00:50:13,000 --> 00:50:17,200
Speaker 1: very different. They look wildly different. Would you say, therefore,

930
00:50:17,200 --> 00:50:19,840
Speaker 1: that Amazon is reaching a different segment of the public

931
00:50:20,200 --> 00:50:25,520
Speaker 1: or a more representative segment of the public. Uh, that's

932
00:50:25,520 --> 00:50:28,239
Speaker 1: a tough question to answer. I think it's a broader

933
00:50:28,520 --> 00:50:32,400
Speaker 1: cross section of the public. Um, if your goal is

934
00:50:32,440 --> 00:50:37,320
Speaker 1: to be, you know, a service for the most popular

935
00:50:37,440 --> 00:50:40,399
Speaker 1: music right now in terms of streaming, you know, then

936
00:50:40,640 --> 00:50:45,360
Speaker 1: you're going to be focused on nothing but hip hop. Um,

937
00:50:45,400 --> 00:50:48,040
Speaker 1: I think it's a more representative cross section of of

938
00:50:48,200 --> 00:50:51,840
Speaker 1: the country. And you know, also, I can tell you know,

939
00:50:51,840 --> 00:50:56,319
Speaker 1: if you think about Amazon and our customer base. At

940
00:50:56,320 --> 00:51:00,879
Speaker 1: our core, we sell people things, and there were our

941
00:51:00,960 --> 00:51:07,040
Speaker 1: average customer buys things. Therefore has disposable income and a

942
00:51:07,080 --> 00:51:11,480
Speaker 1: credit card. So therefore our customer base excuse a bit

943
00:51:11,560 --> 00:51:15,120
Speaker 1: older than the other guys. That doesn't mean it's old,

944
00:51:15,239 --> 00:51:17,480
Speaker 1: It just means it starts more at a young adult

945
00:51:17,800 --> 00:51:22,319
Speaker 1: and goes up from there. Right, we're we don't have

946
00:51:22,400 --> 00:51:26,600
Speaker 1: a free tier, so well, essentially you do because it's

947
00:51:26,600 --> 00:51:32,600
Speaker 1: baked into the now nine Amazon Prime that you have

948
00:51:32,680 --> 00:51:34,800
Speaker 1: to be a Prime member and that's not an unlimited

949
00:51:35,120 --> 00:51:38,440
Speaker 1: basil said, you know, they're a hundred million Prime members

950
00:51:38,280 --> 00:51:40,920
Speaker 1: that global number. Yeah, right, Well, how many countries is

951
00:51:40,960 --> 00:51:45,360
Speaker 1: Amazon Music in at this point around forty and you

952
00:51:45,360 --> 00:51:49,360
Speaker 1: can get unlimited in all those forty countries, um, all

953
00:51:49,400 --> 00:51:53,000
Speaker 1: but one, but that's coming yeah pretty much. Okay, So

954
00:51:53,120 --> 00:51:57,200
Speaker 1: but essentially it feels free to the consumer unless you

955
00:51:57,239 --> 00:52:00,399
Speaker 1: have prime. If you have prime, okay, we to of course,

956
00:52:00,440 --> 00:52:03,719
Speaker 1: the original sales pitch is the two day delivery, which

957
00:52:03,800 --> 00:52:06,839
Speaker 1: I think with its original prices seventy nine dollars was real.

958
00:52:06,960 --> 00:52:09,880
Speaker 1: Now that it's going up, you're looking at the add ons. Okay,

959
00:52:10,040 --> 00:52:13,800
Speaker 1: so what do you see right now? Despite protestations of

960
00:52:13,880 --> 00:52:18,960
Speaker 1: the minor players, is essentially a three horse race between Apple, Spotify,

961
00:52:19,000 --> 00:52:23,320
Speaker 1: and Amazon. What do you foresee foreseeing the future relative

962
00:52:23,320 --> 00:52:30,160
Speaker 1: to the competition of those three UM, I can speak

963
00:52:30,160 --> 00:52:33,000
Speaker 1: to us. I mean, I I like where we sit.

964
00:52:33,680 --> 00:52:37,120
Speaker 1: You know, people, you know, we've we've grown pretty dramatically

965
00:52:37,120 --> 00:52:42,640
Speaker 1: over the last uh two or three years and to

966
00:52:42,719 --> 00:52:45,080
Speaker 1: the point where you know, it's it's it's quite clear

967
00:52:45,120 --> 00:52:47,320
Speaker 1: that we're in that small group that you just mentioned.

968
00:52:48,000 --> 00:52:52,239
Speaker 1: And you know, we think, we think we have a

969
00:52:52,239 --> 00:52:55,799
Speaker 1: good trajectory and we have a pretty sound strategy. I

970
00:52:55,800 --> 00:52:58,080
Speaker 1: think there's some secular trends that work in our favors,

971
00:52:58,120 --> 00:53:02,360
Speaker 1: such as UM this plat form shifts to voice. So

972
00:53:02,760 --> 00:53:05,400
Speaker 1: you know, we see ourselves continuing to grow pretty rapidly.

973
00:53:05,480 --> 00:53:10,799
Speaker 1: I know there's this narrative out there that everything in

974
00:53:10,840 --> 00:53:14,080
Speaker 1: the Internet is a winner take all um. I don't

975
00:53:14,080 --> 00:53:15,960
Speaker 1: really buy into that when it comes at least to

976
00:53:16,520 --> 00:53:19,560
Speaker 1: digital media. I can see that where there are you know,

977
00:53:19,719 --> 00:53:22,400
Speaker 1: where network effects are the strongest thing in your business,

978
00:53:22,480 --> 00:53:29,360
Speaker 1: like search, um or social networking, you know, arguably it's

979
00:53:29,400 --> 00:53:32,440
Speaker 1: winner take all, even though there are many very successful

980
00:53:32,440 --> 00:53:35,839
Speaker 1: social networking companies UM. I don't think that's the case

981
00:53:35,880 --> 00:53:38,360
Speaker 1: of music. I do think it will be a small

982
00:53:38,440 --> 00:53:43,800
Speaker 1: number continue to be a small number um of players globally.

983
00:53:45,280 --> 00:53:48,160
Speaker 1: Is it those three? Is there gonna be a fourth? Ye?

984
00:53:48,800 --> 00:53:50,560
Speaker 1: I don't know. I don't have a crystal ball. I

985
00:53:50,840 --> 00:53:52,919
Speaker 1: know that will be up there if we look historically,

986
00:53:53,360 --> 00:53:58,239
Speaker 1: you know, Google has se Search, Facebook, a lot of

987
00:53:58,239 --> 00:54:02,879
Speaker 1: companies a dominant players of the marketplace because that's where

988
00:54:02,920 --> 00:54:04,920
Speaker 1: all your friends are. There is a network effects thing.

989
00:54:05,360 --> 00:54:08,200
Speaker 1: So I have all the services. I know how to

990
00:54:08,280 --> 00:54:11,080
Speaker 1: share a song on Spotify. I don't know how to

991
00:54:11,120 --> 00:54:13,960
Speaker 1: share a song on Apple okay, and I think, and

992
00:54:13,960 --> 00:54:15,479
Speaker 1: then of course if I share it with someone who's

993
00:54:15,480 --> 00:54:18,680
Speaker 1: not a member, they can't listen. So I think these

994
00:54:18,680 --> 00:54:23,200
Speaker 1: are important factors moving towards dominance of one of the services.

995
00:54:24,400 --> 00:54:27,560
Speaker 1: You don't agree. I don't agree that it's going to

996
00:54:27,640 --> 00:54:30,040
Speaker 1: be a single No, I wouldn't be doing this if

997
00:54:30,040 --> 00:54:31,960
Speaker 1: we thought the game was over. Well, I would think that,

998
00:54:32,360 --> 00:54:34,160
Speaker 1: you know, from an outside observer, I don't mean this

999
00:54:34,239 --> 00:54:37,120
Speaker 1: in a negative way. I would say that Amazon is

1000
00:54:37,160 --> 00:54:41,200
Speaker 1: the stealth player with both deep pockets, big ecosystem, the

1001
00:54:41,320 --> 00:54:45,000
Speaker 1: prime etcetera. They're the ones. It's they're frequently ignored. Like

1002
00:54:45,040 --> 00:54:48,120
Speaker 1: talk to Daniel Glass, you know, six or eight months ago.

1003
00:54:48,160 --> 00:54:50,239
Speaker 1: He says, you know, the sleeper is Amazon, and he

1004
00:54:50,280 --> 00:54:52,000
Speaker 1: talks about meeting with you with the other team and

1005
00:54:52,040 --> 00:54:54,839
Speaker 1: the people who have been at the forefront from way

1006
00:54:54,920 --> 00:54:58,200
Speaker 1: longer than six But the people have been the forefront

1007
00:54:58,239 --> 00:55:00,919
Speaker 1: have been in serious whatever they talk about Amazon being

1008
00:55:00,920 --> 00:55:03,839
Speaker 1: the sleeper. But by the same time that by the way,

1009
00:55:05,800 --> 00:55:08,040
Speaker 1: but as I say, it's hard to fathom. And one

1010
00:55:08,160 --> 00:55:10,640
Speaker 1: also would say that that's who we have to you know,

1011
00:55:11,040 --> 00:55:14,319
Speaker 1: Spotify as a standalone product. I don't see it as

1012
00:55:14,360 --> 00:55:17,800
Speaker 1: a standalone company. A long way down the line. What

1013
00:55:17,960 --> 00:55:20,680
Speaker 1: we look with the apples, they have everybody's credit card,

1014
00:55:21,200 --> 00:55:23,719
Speaker 1: but who do they market to after they don't have

1015
00:55:23,760 --> 00:55:26,080
Speaker 1: the free tier? And I always go back to the

1016
00:55:26,080 --> 00:55:28,920
Speaker 1: original example of A O L and MSN Network. Everyone

1017
00:55:28,960 --> 00:55:31,279
Speaker 1: thought MSN Network was gonna kill A O L and

1018
00:55:31,320 --> 00:55:33,359
Speaker 1: it did not. So the fact that you have a

1019
00:55:33,400 --> 00:55:37,360
Speaker 1: previous history does not necessarily mean success in the future.

1020
00:55:37,480 --> 00:55:39,759
Speaker 1: In addition, I don't believe there's a visionary leader at

1021
00:55:39,760 --> 00:55:43,920
Speaker 1: Apple where there is a visionary leader at at Amazon. Therefore,

1022
00:55:44,080 --> 00:55:47,239
Speaker 1: it's something I'm certainly paying attention to. But getting off

1023
00:55:47,280 --> 00:55:50,400
Speaker 1: of my little soapbox here, one of the things that

1024
00:55:50,520 --> 00:55:56,440
Speaker 1: amazed me when we met is that if I go

1025
00:55:56,520 --> 00:56:00,800
Speaker 1: on Spotify, which is the big huna this week, they

1026
00:56:00,840 --> 00:56:03,680
Speaker 1: break down the playlist down into certain things, but in

1027
00:56:03,719 --> 00:56:06,920
Speaker 1: reality it's more granular on the Amazon that what you

1028
00:56:06,920 --> 00:56:10,319
Speaker 1: can say like play rockets of can you tell the

1029
00:56:10,320 --> 00:56:13,600
Speaker 1: audience more about that? Yeah, And that's I mean, that's

1030
00:56:13,640 --> 00:56:17,239
Speaker 1: a that's actually what we saw customers doing. Right. So

1031
00:56:17,480 --> 00:56:19,160
Speaker 1: again when we looked at the date of what are

1032
00:56:19,160 --> 00:56:22,440
Speaker 1: people doing on Alexa, the way I think about is

1033
00:56:22,480 --> 00:56:24,960
Speaker 1: if if you have a visual app, your iPhone app,

1034
00:56:25,000 --> 00:56:30,000
Speaker 1: your desktop app, your Android app, it's very powerful, it's

1035
00:56:30,000 --> 00:56:34,520
Speaker 1: also very constrained, right, there's the product. Managers decided how

1036
00:56:34,520 --> 00:56:36,560
Speaker 1: you're going to listen to music, whether you realize it

1037
00:56:36,680 --> 00:56:41,480
Speaker 1: or not. There's a search bar, there's a browse hierarchy

1038
00:56:41,520 --> 00:56:44,200
Speaker 1: of how you browse through music, and they fill the

1039
00:56:44,200 --> 00:56:46,800
Speaker 1: buckets of content for you, and not much not suggesting

1040
00:56:46,840 --> 00:56:48,560
Speaker 1: that's a bad thing. It is what it is, though,

1041
00:56:48,680 --> 00:56:52,000
Speaker 1: and um, that's how you're going to listen to music.

1042
00:56:53,000 --> 00:56:54,560
Speaker 1: When you have a head lit what we call a

1043
00:56:54,560 --> 00:56:57,720
Speaker 1: headless device, just nothing. There's no screen on an Echo.

1044
00:56:59,239 --> 00:57:03,080
Speaker 1: You're completely unconstrained. The way you want to interact with

1045
00:57:03,160 --> 00:57:07,200
Speaker 1: music is limited only by your own imagination. And lo

1046
00:57:07,400 --> 00:57:10,480
Speaker 1: and behold. When people are unconstrained, they act in an

1047
00:57:10,520 --> 00:57:14,600
Speaker 1: unconstrained way, and they ask Alexa things. And you know

1048
00:57:14,680 --> 00:57:17,160
Speaker 1: what we saw was that. The way I like think

1049
00:57:17,200 --> 00:57:18,880
Speaker 1: about is if you read the reviews of the Echo

1050
00:57:18,920 --> 00:57:21,040
Speaker 1: in the early days and still today, you'd see people

1051
00:57:21,080 --> 00:57:25,080
Speaker 1: saying things like I love Alexa, Alexa is my friend,

1052
00:57:25,160 --> 00:57:27,880
Speaker 1: she's my best friend, Alexa is a member of my family.

1053
00:57:28,880 --> 00:57:31,840
Speaker 1: And so we tried to translate, kind of translate that

1054
00:57:31,880 --> 00:57:37,680
Speaker 1: into music and say, well, it makes sense that people

1055
00:57:37,680 --> 00:57:40,280
Speaker 1: are asking for things in a much more natural way

1056
00:57:40,280 --> 00:57:42,000
Speaker 1: than you would get in and app because they think

1057
00:57:42,000 --> 00:57:43,800
Speaker 1: of her as a friend. So they're going to talk

1058
00:57:43,880 --> 00:57:45,320
Speaker 1: to her like you're talking to You're gonna talk to

1059
00:57:45,400 --> 00:57:48,160
Speaker 1: her like you talked to your friend about music. And

1060
00:57:48,200 --> 00:57:51,240
Speaker 1: so people were asking for things. They're asking for songs

1061
00:57:51,280 --> 00:57:53,080
Speaker 1: because they only know a few words to the song.

1062
00:57:53,160 --> 00:57:55,480
Speaker 1: They can't remember the title of the artist. So they

1063
00:57:55,480 --> 00:57:57,760
Speaker 1: asked for by lyrics, They asked for the by mood.

1064
00:57:57,840 --> 00:58:02,439
Speaker 1: They ask you know, play pearl jam from um, play

1065
00:58:02,480 --> 00:58:07,360
Speaker 1: YouTube from the eighties, or play me some sad country music. Um.

1066
00:58:07,480 --> 00:58:09,320
Speaker 1: Or I'm having a dinner party, Alexa, can you play

1067
00:58:09,360 --> 00:58:12,600
Speaker 1: me some music, some jazz? And it's that kind of

1068
00:58:12,600 --> 00:58:14,920
Speaker 1: stuff where it's like music becoming part of what you

1069
00:58:15,000 --> 00:58:19,120
Speaker 1: do and responding to how you think about music. Um,

1070
00:58:19,160 --> 00:58:22,120
Speaker 1: it's not always and and and As great as playlists

1071
00:58:22,120 --> 00:58:24,120
Speaker 1: are and I know they're the currency du jour and

1072
00:58:24,600 --> 00:58:27,920
Speaker 1: maybe for a long time to come, they're not the

1073
00:58:27,960 --> 00:58:31,240
Speaker 1: answer to every type of situation that you find yourself

1074
00:58:31,240 --> 00:58:33,160
Speaker 1: in wanting to listen to music. There's plenty of times

1075
00:58:33,160 --> 00:58:36,080
Speaker 1: you may uh not want to listen to a playlist.

1076
00:58:36,120 --> 00:58:38,920
Speaker 1: And so when you say, you know, play YouTube from

1077
00:58:38,920 --> 00:58:41,960
Speaker 1: the eighties, we just make a playlist on the fly

1078
00:58:42,120 --> 00:58:44,800
Speaker 1: for you. Um, there isn't We don't go deep into

1079
00:58:44,840 --> 00:58:47,440
Speaker 1: We didn't have programmers creating you know, all these things.

1080
00:58:48,360 --> 00:58:51,520
Speaker 1: We spent a lot of time cleaning up metadata. Um,

1081
00:58:51,560 --> 00:58:54,160
Speaker 1: with all respect to the my label friends here or

1082
00:58:54,240 --> 00:58:58,520
Speaker 1: who may listen to a recording of this. Um, metadata

1083
00:58:58,800 --> 00:59:01,640
Speaker 1: sucks and it's a known problem in the industry. It

1084
00:59:01,720 --> 00:59:07,280
Speaker 1: tends to be incorrect or incomplete and certainly insufficient to

1085
00:59:07,280 --> 00:59:09,240
Speaker 1: to to respond to the kind of request that people

1086
00:59:09,240 --> 00:59:11,880
Speaker 1: are asking for. Like, even if all the metadata from

1087
00:59:11,880 --> 00:59:13,840
Speaker 1: the labels were correct, they don't give us metadata that

1088
00:59:13,920 --> 00:59:15,880
Speaker 1: says this song is sad, or this song is happy,

1089
00:59:16,000 --> 00:59:19,280
Speaker 1: this is upbeat, um, this is this is suitable for

1090
00:59:19,320 --> 00:59:21,680
Speaker 1: a dinner party. Right, So that's that's metadata we have

1091
00:59:21,720 --> 00:59:24,120
Speaker 1: to go out and create, and we do that through

1092
00:59:24,120 --> 00:59:28,520
Speaker 1: a combination of brute force with humans and then deep learning.

1093
00:59:28,560 --> 00:59:34,200
Speaker 1: Pretty much every song has metadata beyond writer, etcetera. Yeah,

1094
00:59:34,320 --> 00:59:38,640
Speaker 1: and we've taken we've taken humans to to to to

1095
00:59:38,720 --> 00:59:42,080
Speaker 1: take sample data sets and then use machine learning algorithms

1096
00:59:42,120 --> 00:59:46,560
Speaker 1: to to learn and you apply that against the greater catalog. Obviously,

1097
00:59:46,600 --> 00:59:49,080
Speaker 1: with catalog of tens of millions of tracks, it would

1098
00:59:49,080 --> 00:59:52,000
Speaker 1: take humans years to go do this, Um, but it

1099
00:59:52,000 --> 00:59:54,680
Speaker 1: doesn't take machines years. But then we have human curious

1100
00:59:54,720 --> 00:59:57,360
Speaker 1: that checking in on the mic. No, that one wasn't good,

1101
00:59:57,400 --> 01:00:02,120
Speaker 1: And you're constantly improving the model, and that enables us

1102
01:00:02,120 --> 01:00:05,920
Speaker 1: to do more fun things when people talk to Alexa

1103
01:00:05,960 --> 01:00:08,160
Speaker 1: and make it more natural. And believe me, we've got

1104
01:00:08,160 --> 01:00:10,040
Speaker 1: a long way to go. I mean we've we've scratched

1105
01:00:10,040 --> 01:00:13,360
Speaker 1: the surface with what people want. Okay, So when I asked,

1106
01:00:13,400 --> 01:00:18,360
Speaker 1: like some rock music for sixty, it creates a playlist

1107
01:00:18,400 --> 01:00:21,680
Speaker 1: on the fly. There is no person existing there maybe

1108
01:00:21,720 --> 01:00:24,760
Speaker 1: there maybe one. But if there's a pre existing playlist

1109
01:00:24,880 --> 01:00:27,200
Speaker 1: that someone, you know, some curator created for something, we

1110
01:00:27,280 --> 01:00:30,640
Speaker 1: might pull from there. But we also know you're listening

1111
01:00:30,640 --> 01:00:33,800
Speaker 1: habits and um, maybe that's not the right one for you,

1112
01:00:33,840 --> 01:00:35,680
Speaker 1: So we'll create one on the fly, and then we'll

1113
01:00:35,760 --> 01:00:39,080
Speaker 1: personalize the sequence. So generally speaking, if I'm talking to Alexa,

1114
01:00:39,320 --> 01:00:44,440
Speaker 1: I can talk year, I can talk act, yeah, era,

1115
01:00:45,840 --> 01:00:49,600
Speaker 1: gen genre, moved, what else? Smooth activity? What are you

1116
01:00:49,640 --> 01:00:52,520
Speaker 1: doing right now? You know, go to yoga, you're gonna

1117
01:00:52,560 --> 01:00:56,120
Speaker 1: have a dinner party, studying. So there's enough metadata that

1118
01:00:56,160 --> 01:00:58,640
Speaker 1: it will then just pull on that metadata to make

1119
01:00:58,640 --> 01:01:01,960
Speaker 1: a playlist on the on the fly. And I only

1120
01:01:02,040 --> 01:01:05,720
Speaker 1: know this from meeting with you previously. How is anybody's

1121
01:01:05,720 --> 01:01:08,160
Speaker 1: supposed to know this or theoretically they're developing a new

1122
01:01:08,160 --> 01:01:10,560
Speaker 1: way to interact with Alexa and they're learning a new

1123
01:01:10,600 --> 01:01:13,560
Speaker 1: way of thinking about music. Well, the whole idea is

1124
01:01:13,600 --> 01:01:15,960
Speaker 1: to make it natural. So, like I said, we're most

1125
01:01:16,000 --> 01:01:18,000
Speaker 1: of what we're doing is stuff that people already wanting

1126
01:01:18,040 --> 01:01:21,560
Speaker 1: to do. Um. You know, we recently launched the ability

1127
01:01:21,600 --> 01:01:25,720
Speaker 1: for you to make playlists just using your voice on Alexa,

1128
01:01:26,080 --> 01:01:28,600
Speaker 1: and sure enough, I mean, people were trying to do it.

1129
01:01:28,600 --> 01:01:30,080
Speaker 1: It's a very natural thing to want to do in

1130
01:01:30,080 --> 01:01:33,760
Speaker 1: a music service. It's pretty complicated to to do by voice,

1131
01:01:33,800 --> 01:01:37,120
Speaker 1: but it works really well. And lo and behold, people

1132
01:01:37,160 --> 01:01:39,280
Speaker 1: are already trying to do it, so instead of failing

1133
01:01:39,320 --> 01:01:42,120
Speaker 1: it now succeeded and so millions of playlists are created

1134
01:01:42,240 --> 01:01:46,480
Speaker 1: really really quickly. Um. There are certain things, yeah, that

1135
01:01:46,720 --> 01:01:50,120
Speaker 1: you know, people have to learn as possible, but but

1136
01:01:50,240 --> 01:01:52,800
Speaker 1: the idea is that you know, by and large, people

1137
01:01:52,800 --> 01:01:56,200
Speaker 1: will stumble upon it when when that's how they want

1138
01:01:56,200 --> 01:01:57,640
Speaker 1: to listen to music, when that's how they want to

1139
01:01:57,640 --> 01:02:01,040
Speaker 1: ask for something. UM. I do think in over time,

1140
01:02:01,040 --> 01:02:04,000
Speaker 1: you'll see us another services probably get better at helping

1141
01:02:04,040 --> 01:02:07,400
Speaker 1: customers understand what features are available, but most of the

1142
01:02:07,400 --> 01:02:10,520
Speaker 1: stuff we've launched to date has been you know, that's

1143
01:02:10,560 --> 01:02:12,640
Speaker 1: just how people were already asking for. People were saying

1144
01:02:12,680 --> 01:02:16,120
Speaker 1: things like, you know, play me the song that goes

1145
01:02:16,320 --> 01:02:19,320
Speaker 1: blah blah blah, whatever the lyric is, and so we

1146
01:02:19,440 --> 01:02:21,120
Speaker 1: looked at that. It's like, well that people are failing

1147
01:02:21,200 --> 01:02:24,560
Speaker 1: because Alexa couldn't understand that. So we went out and

1148
01:02:24,600 --> 01:02:28,680
Speaker 1: created the ability to quickly look through lyrics databases and

1149
01:02:28,720 --> 01:02:31,479
Speaker 1: find that song or you know, play the new song

1150
01:02:32,080 --> 01:02:35,600
Speaker 1: you know by Mumford and Sons with Daniels here and

1151
01:02:35,640 --> 01:02:37,560
Speaker 1: hopefully they're gonna have a new album sometimes soon because

1152
01:02:37,560 --> 01:02:40,480
Speaker 1: we've been waiting for three years. Um, I don't know,

1153
01:02:41,440 --> 01:02:46,320
Speaker 1: but I'm a big fan. And uh, you know, that's

1154
01:02:46,320 --> 01:02:48,840
Speaker 1: really easy to understand when it's the first single off

1155
01:02:48,880 --> 01:02:51,880
Speaker 1: the record, But when it's the third track off the

1156
01:02:51,880 --> 01:02:55,440
Speaker 1: record that Daniels promoting and that's one at radio right now,

1157
01:02:55,600 --> 01:02:58,280
Speaker 1: you know which song is still Alexa pull. They all

1158
01:02:58,320 --> 01:03:01,640
Speaker 1: have the same release date from the label. They're all

1159
01:03:01,840 --> 01:03:03,600
Speaker 1: have the same release date of the record of the album.

1160
01:03:03,680 --> 01:03:07,560
Speaker 1: So you know, we worked with labels and ourselves and

1161
01:03:07,720 --> 01:03:11,160
Speaker 1: created this concept of radio impact date in our in

1162
01:03:11,160 --> 01:03:14,240
Speaker 1: our metadata for songs, so that when I say because that,

1163
01:03:14,360 --> 01:03:15,960
Speaker 1: the whole idea is I was listening to the radio.

1164
01:03:16,000 --> 01:03:18,000
Speaker 1: I heard the new song by Mumford and Sons. Don't

1165
01:03:18,000 --> 01:03:19,880
Speaker 1: know the title, but it's the one that's on the

1166
01:03:19,960 --> 01:03:23,240
Speaker 1: radio that that that Daniel's promoting. Alexa played the new

1167
01:03:23,240 --> 01:03:25,280
Speaker 1: song by Mumford and Sons, She's going to know which

1168
01:03:25,280 --> 01:03:27,520
Speaker 1: one to get. And so our focus has been primarily

1169
01:03:27,560 --> 01:03:30,360
Speaker 1: on things that people are doing already. Um and there's,

1170
01:03:30,440 --> 01:03:32,160
Speaker 1: like I said, there's a lot more to come. You know.

1171
01:03:32,240 --> 01:03:35,200
Speaker 1: The ideas it should be as natural as speaking to

1172
01:03:35,200 --> 01:03:36,960
Speaker 1: your best friend about music. If you and I were

1173
01:03:36,960 --> 01:03:39,120
Speaker 1: to go have a beer and just talk about music,

1174
01:03:39,160 --> 01:03:41,480
Speaker 1: not about the music business, but about artists and songs

1175
01:03:41,520 --> 01:03:44,520
Speaker 1: and stuff. We want Alexa to be able to to

1176
01:03:44,040 --> 01:03:46,960
Speaker 1: to hang with you and to and to be your

1177
01:03:46,960 --> 01:03:49,240
Speaker 1: guide and to be your friend and to be able

1178
01:03:49,280 --> 01:03:51,600
Speaker 1: to respond to that. Well, some of this Stele stuff.

1179
01:03:51,640 --> 01:03:53,680
Speaker 1: I know that Randy arranged for us to get some

1180
01:03:53,920 --> 01:03:58,040
Speaker 1: echo shows, and I had the default service has Spotify,

1181
01:03:58,240 --> 01:04:01,040
Speaker 1: which sorry, most people don't really know how to change.

1182
01:04:01,360 --> 01:04:03,720
Speaker 1: But once you got the Echo Show, and it can

1183
01:04:03,800 --> 01:04:07,040
Speaker 1: show the lyrics made the default service Amazon Music, because

1184
01:04:07,040 --> 01:04:14,560
Speaker 1: I want to see the lyrics. We'll take a quick

1185
01:04:14,600 --> 01:04:17,320
Speaker 1: break and come back with more of my conversation with

1186
01:04:17,440 --> 01:04:21,080
Speaker 1: VP of the Amazon Music Steve Boom, recorded live at

1187
01:04:21,120 --> 01:04:27,400
Speaker 1: the Music Media Summit in Santa Barbara, California. I hope

1188
01:04:27,400 --> 01:04:30,000
Speaker 1: you're enjoying listening to this episode of the Bob Left

1189
01:04:29,960 --> 01:04:33,000
Speaker 1: Stats podcast. If you want to listen to sound bites

1190
01:04:33,080 --> 01:04:35,960
Speaker 1: from the interviews and see some of my guests like

1191
01:04:36,040 --> 01:04:39,040
Speaker 1: Shirley me Instid of Garbage or Paul Rodgers of Bad

1192
01:04:39,080 --> 01:04:44,000
Speaker 1: Company and Free check it out at tune in on Twitter, Facebook,

1193
01:04:44,080 --> 01:04:48,360
Speaker 1: and Instagram. Now more of my chat with the head

1194
01:04:48,360 --> 01:04:51,360
Speaker 1: of the Amazon Music Steve Boom on the Bob Left

1195
01:04:51,400 --> 01:04:55,880
Speaker 1: and It's podcast. At this point, why don't we open

1196
01:04:55,920 --> 01:04:59,200
Speaker 1: it up to questions? Sure people have certain things. Jim

1197
01:04:59,240 --> 01:05:02,360
Speaker 1: has the mic once again, Let's try to limit statements

1198
01:05:02,360 --> 01:05:07,800
Speaker 1: and make it more about questions for Steve. Here has Steve.

1199
01:05:08,400 --> 01:05:11,520
Speaker 1: My question is, as you talk about the ecosystem between

1200
01:05:12,000 --> 01:05:15,480
Speaker 1: the Amazon Music streaming service and the Echo do you

1201
01:05:15,640 --> 01:05:21,200
Speaker 1: you do you view it more as a feature or product. Um,

1202
01:05:21,200 --> 01:05:25,080
Speaker 1: you know, we view Amazon Music as a service. Um.

1203
01:05:25,120 --> 01:05:28,600
Speaker 1: You know, Alexa itself is a platform that you can

1204
01:05:28,760 --> 01:05:32,600
Speaker 1: or you know, it allows you to have other services available.

1205
01:05:32,640 --> 01:05:37,880
Speaker 1: So um, and we Amazon Musics available on iOS, on Android,

1206
01:05:38,480 --> 01:05:42,560
Speaker 1: on web, on TV platforms. So you know, we're building

1207
01:05:42,800 --> 01:05:46,160
Speaker 1: a self standing music service. It just so happens. Our

1208
01:05:46,280 --> 01:05:49,160
Speaker 1: focus is to make it the best voice forward music

1209
01:05:49,200 --> 01:05:52,360
Speaker 1: service in the world. We've brought voice controls into our

1210
01:05:53,040 --> 01:05:55,480
Speaker 1: mobile phone apps, so on iOS and Android you can

1211
01:05:55,480 --> 01:06:00,000
Speaker 1: speak with Alexa. Um. That's how we think we really

1212
01:06:00,440 --> 01:06:07,520
Speaker 1: rise above the crowd. Um that it's a service onto itself. Yeah, Stephen,

1213
01:06:09,040 --> 01:06:12,080
Speaker 1: you know, Hey Shapiro, I mean, how does everybody's gonna

1214
01:06:12,080 --> 01:06:16,520
Speaker 1: mike here? It's a cousin of kind of your core business.

1215
01:06:16,520 --> 01:06:20,120
Speaker 1: But I know Amazon was looking at ticketing and ticketing

1216
01:06:20,120 --> 01:06:24,959
Speaker 1: in music, and uh maybe the only time Amazon had

1217
01:06:24,960 --> 01:06:29,960
Speaker 1: to pull back from entering a new vertical. And I

1218
01:06:29,960 --> 01:06:32,080
Speaker 1: don't know if you can give us color of the

1219
01:06:32,120 --> 01:06:36,960
Speaker 1: experience that Amazon happened had looking at going into music ticketing,

1220
01:06:37,040 --> 01:06:39,680
Speaker 1: and you had entered in Europe, I think, but now

1221
01:06:39,720 --> 01:06:44,160
Speaker 1: pretty publicly said hey, we're gonna pull back from that. Uh. Yeah,

1222
01:06:44,240 --> 01:06:47,120
Speaker 1: I wish I could give you shed insight. Yeah, we

1223
01:06:47,120 --> 01:06:49,360
Speaker 1: we did have a small ticketing business in the UK.

1224
01:06:49,440 --> 01:06:53,080
Speaker 1: It really started in the West End with theater, dabbled

1225
01:06:53,720 --> 01:06:57,360
Speaker 1: with some concerts. Um I wasn't part of the decision

1226
01:06:57,360 --> 01:06:59,800
Speaker 1: process as to why the company pulled out, so I'm

1227
01:06:59,800 --> 01:07:02,240
Speaker 1: so I can't really tell you much. But one thing

1228
01:07:02,480 --> 01:07:05,400
Speaker 1: a g They had the Hyde Park shows they were

1229
01:07:05,400 --> 01:07:08,000
Speaker 1: tied in with his Amazon last summer and they said

1230
01:07:08,000 --> 01:07:11,320
Speaker 1: that Amazon sold tickets that they couldn't sell. That you

1231
01:07:11,440 --> 01:07:13,840
Speaker 1: reached people that they didn't reach. It was actually a

1232
01:07:13,880 --> 01:07:16,920
Speaker 1: benefit to it as opposed to people thinking, well, Amazon

1233
01:07:17,040 --> 01:07:20,360
Speaker 1: is going to come in and take our business. When

1234
01:07:20,400 --> 01:07:25,760
Speaker 1: Bob wants to replay his rock from does Amazon store

1235
01:07:25,840 --> 01:07:28,720
Speaker 1: that so that he could get the exact same playlist

1236
01:07:28,800 --> 01:07:31,520
Speaker 1: again or will it fabricate a new one. It's a

1237
01:07:31,560 --> 01:07:34,760
Speaker 1: great question. Uh the next time probably Fabrica knewhim. But

1238
01:07:34,760 --> 01:07:36,640
Speaker 1: when he's done listening, you could ask Alexa to save

1239
01:07:36,680 --> 01:07:40,120
Speaker 1: it as a playlist and then he would access it

1240
01:07:40,160 --> 01:07:43,720
Speaker 1: by saying I want my June playlist. When he creates one,

1241
01:07:43,880 --> 01:07:46,040
Speaker 1: Shell asked how to what what names? She will ask

1242
01:07:46,080 --> 01:07:49,080
Speaker 1: how to store to sign a name to it? Yeah? Nice? Yeah, Okay,

1243
01:07:49,080 --> 01:07:51,240
Speaker 1: Before we move on, how many people in the room

1244
01:07:51,680 --> 01:07:56,480
Speaker 1: have an echo of some stripe. Wow. Okay. How many

1245
01:07:56,520 --> 01:08:01,040
Speaker 1: people have a Google Home yea? How many people have

1246
01:08:01,080 --> 01:08:13,280
Speaker 1: a HomePod? Okay? Okay? Uh? Who has the bike now? Jim? Okay, Hey,

1247
01:08:13,280 --> 01:08:16,599
Speaker 1: how you doing um with everything going on with Cambridge

1248
01:08:16,600 --> 01:08:19,800
Speaker 1: Analytica and everything on Facebook? Now? You put a microphone

1249
01:08:20,040 --> 01:08:25,800
Speaker 1: in your house on all the time? Any thoughts on that?

1250
01:08:27,479 --> 01:08:30,439
Speaker 1: You know? I want to comment on that because this

1251
01:08:30,479 --> 01:08:34,480
Speaker 1: is the type of thing that makes me fucking crazy

1252
01:08:34,760 --> 01:08:37,719
Speaker 1: and that I hear I still, at this late date,

1253
01:08:37,760 --> 01:08:40,439
Speaker 1: gets saying I'm not gonna have streaming? What if I'm

1254
01:08:40,479 --> 01:08:45,320
Speaker 1: out of cellular service? Now for almost ten years they've

1255
01:08:45,320 --> 01:08:47,040
Speaker 1: had it, so it seeks to your phone, so you

1256
01:08:47,080 --> 01:08:49,800
Speaker 1: have to pay every month. They have ownership. You can't

1257
01:08:49,800 --> 01:08:52,719
Speaker 1: get that message through when it comes to the Echo

1258
01:08:52,800 --> 01:08:56,160
Speaker 1: devices until they hear a lection the code word the

1259
01:08:56,280 --> 01:09:02,960
Speaker 1: microphone is not on. Isn't that correct? That's correct. So

1260
01:09:04,080 --> 01:09:10,960
Speaker 1: there's a basically a small processor on the device that

1261
01:09:11,040 --> 01:09:13,559
Speaker 1: all it does is listen for ALEXA. It's not connected

1262
01:09:13,600 --> 01:09:18,000
Speaker 1: to the cloud. When it hears ALEXA, it opens up

1263
01:09:18,040 --> 01:09:20,800
Speaker 1: a connection to the cloud to capture what you say.

1264
01:09:20,800 --> 01:09:24,599
Speaker 1: Next converts that into wave file and then interpreted into

1265
01:09:24,720 --> 01:09:29,120
Speaker 1: text and it comes back down. Um. So the reason

1266
01:09:29,160 --> 01:09:35,439
Speaker 1: there's a blue light so you know she's listening. If

1267
01:09:35,439 --> 01:09:38,920
Speaker 1: you ever want to make sure that nothing like if

1268
01:09:39,000 --> 01:09:41,720
Speaker 1: one of the kids blurts out Alexa and you and

1269
01:09:41,760 --> 01:09:44,519
Speaker 1: you were on a super confidential conference call for work

1270
01:09:44,560 --> 01:09:47,680
Speaker 1: or something, there's a mute button which physically cuts the

1271
01:09:47,720 --> 01:09:51,640
Speaker 1: circuit of the microphones, physically impossible for any sound to

1272
01:09:51,640 --> 01:09:54,040
Speaker 1: get back to Amazon. So privacy has been thought of

1273
01:09:54,040 --> 01:09:56,240
Speaker 1: in the very design of the device from from day one,

1274
01:09:56,280 --> 01:09:59,280
Speaker 1: both in its construction of the device as well as

1275
01:09:59,680 --> 01:10:05,000
Speaker 1: the usual cues to let you know when Alexa is listening. So, um,

1276
01:10:05,040 --> 01:10:08,640
Speaker 1: it's something we take really, really seriously. I'm not the

1277
01:10:08,680 --> 01:10:10,960
Speaker 1: one in charge of that stuff, but it's something that

1278
01:10:11,400 --> 01:10:14,760
Speaker 1: I've heard described and it's it's as I described to you.

1279
01:10:14,760 --> 01:10:19,040
Speaker 1: It's something you know, Amazon the customer obsession and customer

1280
01:10:19,080 --> 01:10:23,040
Speaker 1: trust is at the center of our entire business. It

1281
01:10:23,080 --> 01:10:25,040
Speaker 1: has drilled into you from day one that you walk

1282
01:10:25,080 --> 01:10:28,679
Speaker 1: into the company, and we know that trust is something

1283
01:10:29,400 --> 01:10:31,720
Speaker 1: hard to earn an easy to lose, and it's not

1284
01:10:31,800 --> 01:10:34,479
Speaker 1: something that Amazon takes lightly. A lot of people have

1285
01:10:34,520 --> 01:10:38,120
Speaker 1: trusted us for years with purchasing a lot of important

1286
01:10:38,160 --> 01:10:42,200
Speaker 1: things in their lives, and yeah, we're not doing anything

1287
01:10:42,200 --> 01:10:44,439
Speaker 1: to mess with that. But having said that, the other

1288
01:10:44,439 --> 01:10:47,400
Speaker 1: half of his question is important. You have an incredible

1289
01:10:47,439 --> 01:10:50,880
Speaker 1: amount of data and knowledge of us. You know, as

1290
01:10:50,920 --> 01:10:53,080
Speaker 1: I say, on Google, they can literally they say you

1291
01:10:53,080 --> 01:10:56,559
Speaker 1: want to get someone you know, cough up something, just

1292
01:10:56,600 --> 01:10:59,920
Speaker 1: say you threatened them with release of their Google search history.

1293
01:11:00,400 --> 01:11:04,240
Speaker 1: But you literally have the purchase history. How do we

1294
01:11:04,360 --> 01:11:07,400
Speaker 1: know that you're not going to use that to our

1295
01:11:07,680 --> 01:11:11,080
Speaker 1: detriment or to brainwash us, or to get us to

1296
01:11:11,080 --> 01:11:21,479
Speaker 1: do something we don't want to do. That's a music conference. Uh,

1297
01:11:21,600 --> 01:11:24,160
Speaker 1: you know, I'm happy to get our public policy people here,

1298
01:11:24,280 --> 01:11:28,080
Speaker 1: but um, I think we're the most trusted brand in

1299
01:11:28,120 --> 01:11:32,240
Speaker 1: America for a reason. And I kind of would leave

1300
01:11:32,240 --> 01:11:35,240
Speaker 1: it at that. You know, I'm not I'm not here

1301
01:11:35,240 --> 01:11:37,120
Speaker 1: really to talk about data. Place say, I don't need

1302
01:11:37,160 --> 01:11:39,200
Speaker 1: to press his expecting answer. But I think the other

1303
01:11:39,240 --> 01:11:41,719
Speaker 1: half of the question, the non technical question, is something

1304
01:11:41,720 --> 01:11:45,000
Speaker 1: that's in everybody's minds that certainly needs to be in

1305
01:11:45,040 --> 01:11:48,439
Speaker 1: the marketplace, if not a chilling effect on the abuse

1306
01:11:48,520 --> 01:11:51,200
Speaker 1: of data. Not that Amazon has a history there, but

1307
01:11:51,280 --> 01:11:54,880
Speaker 1: we want to put that in everybody's mind. Jake, Um,

1308
01:11:54,880 --> 01:11:58,320
Speaker 1: you know Steve brought up something interesting, Steve about the

1309
01:11:58,439 --> 01:12:04,360
Speaker 1: other Steve about playlists. So Bob does a great playlist

1310
01:12:04,520 --> 01:12:08,680
Speaker 1: of rock from sixty nine, and uh, those of us

1311
01:12:08,800 --> 01:12:11,320
Speaker 1: really like Bob's taste, so we want to listen to

1312
01:12:11,360 --> 01:12:15,800
Speaker 1: Bob's playlist from nineteen nine. Does Amazon currently and I

1313
01:12:15,840 --> 01:12:20,320
Speaker 1: don't know or will it allow third party playlists to

1314
01:12:20,400 --> 01:12:23,080
Speaker 1: be made on the service where other people can go

1315
01:12:23,120 --> 01:12:27,240
Speaker 1: and listen to other curators beside your own playlists, I

1316
01:12:27,280 --> 01:12:32,360
Speaker 1: mean playlist sharing. Yeah, playlists sharing or for that matter. Um,

1317
01:12:32,640 --> 01:12:34,719
Speaker 1: I don't know if they're on your but Majestic Casual

1318
01:12:34,840 --> 01:12:37,439
Speaker 1: is a great example of people that make playlist They've

1319
01:12:37,439 --> 01:12:40,440
Speaker 1: been doing it for years. They started on YouTube. You

1320
01:12:40,439 --> 01:12:43,400
Speaker 1: you go into I go into my son nos playlist

1321
01:12:43,439 --> 01:12:46,960
Speaker 1: search and I do Majestic Casual and Deezer comes up with,

1322
01:12:47,080 --> 01:12:49,599
Speaker 1: you know, a Hunter playlists, and Apple Music comes up

1323
01:12:49,600 --> 01:12:53,320
Speaker 1: with a Hunter playlists, and Spotify the same thing, and uh,

1324
01:12:53,360 --> 01:12:55,840
Speaker 1: and they're just a playlist kind of brand. We have

1325
01:12:55,920 --> 01:13:01,800
Speaker 1: some of two questions. The first question is playlist sharing. Uh, yes, Um,

1326
01:13:01,840 --> 01:13:07,719
Speaker 1: that's something we either do or about to enable. Um, okay,

1327
01:13:07,800 --> 01:13:12,320
Speaker 1: we enable that with voice. We'll work through that. Okay.

1328
01:13:12,800 --> 01:13:16,680
Speaker 1: The second thing is third party playlists. Yeah, we have

1329
01:13:16,760 --> 01:13:18,240
Speaker 1: some of those brands in our serves. I don't know

1330
01:13:18,280 --> 01:13:20,640
Speaker 1: about Majestic Casual per Se, but I know that we

1331
01:13:20,720 --> 01:13:22,599
Speaker 1: have some of the other ones in our service. So

1332
01:13:22,600 --> 01:13:25,600
Speaker 1: so so one of the things when Troy Carter was

1333
01:13:25,640 --> 01:13:28,480
Speaker 1: here the other day, he said, you know, we concentrate

1334
01:13:28,840 --> 01:13:32,559
Speaker 1: mostly on our own playlists, and they're kind of pushing

1335
01:13:32,600 --> 01:13:36,720
Speaker 1: back against third party playlists because they're afraid of graft

1336
01:13:37,120 --> 01:13:40,160
Speaker 1: payola to get on those those bigger playlists. And I

1337
01:13:40,280 --> 01:13:42,559
Speaker 1: just trying to get your sort of take on the

1338
01:13:42,640 --> 01:13:45,479
Speaker 1: same thing. Troy is a really smart guy, and I

1339
01:13:45,520 --> 01:13:48,320
Speaker 1: agree with him. And you know, there's there's two angles

1340
01:13:48,320 --> 01:13:51,720
Speaker 1: to that. One is worrying about those types of things, um,

1341
01:13:51,800 --> 01:13:53,920
Speaker 1: but also you have to understand that we're a music

1342
01:13:54,000 --> 01:13:58,479
Speaker 1: service and in a in a world where all of

1343
01:13:58,560 --> 01:14:00,840
Speaker 1: us have very similar music alogues, we are going to

1344
01:14:01,240 --> 01:14:04,160
Speaker 1: differentiate ourselves through a variety of means, and one of

1345
01:14:04,200 --> 01:14:07,639
Speaker 1: those is our own curation. And so it's it's only

1346
01:14:07,720 --> 01:14:11,240
Speaker 1: natural that a music service would want to, you know,

1347
01:14:11,640 --> 01:14:14,000
Speaker 1: invest heavily in its own creation to make sure it's

1348
01:14:14,040 --> 01:14:16,800
Speaker 1: really great. But you know, and and we know that

1349
01:14:16,840 --> 01:14:18,760
Speaker 1: we won't be doing Payola and Graft and all that

1350
01:14:18,800 --> 01:14:21,000
Speaker 1: other stuff. So I don't know what goes on in

1351
01:14:21,040 --> 01:14:25,040
Speaker 1: the other companies. So that is a concern. Next person

1352
01:14:25,040 --> 01:14:27,800
Speaker 1: with the microphone. Yeah, so actually you just answered part

1353
01:14:27,800 --> 01:14:30,880
Speaker 1: of my question. Um, the question was my my thought.

1354
01:14:30,920 --> 01:14:33,160
Speaker 1: My my question is about where do you think the

1355
01:14:33,200 --> 01:14:38,839
Speaker 1: responsibility lies for actual curation and promotion on the platform? Um,

1356
01:14:39,160 --> 01:14:42,439
Speaker 1: specifically with with regard to Voice. Um, how much of

1357
01:14:42,439 --> 01:14:44,320
Speaker 1: it is or I know you don't like to share numbers,

1358
01:14:44,320 --> 01:14:47,799
Speaker 1: but how much of the traffic is organic, purely organic?

1359
01:14:47,840 --> 01:14:49,320
Speaker 1: I want to play this now, And how much of

1360
01:14:49,360 --> 01:14:51,519
Speaker 1: it is driven by your curation? And what direction is

1361
01:14:51,560 --> 01:14:55,080
Speaker 1: that moving? And how do you think about that? Yeah,

1362
01:14:55,120 --> 01:14:58,360
Speaker 1: a substantial percentage of our our of our listening is

1363
01:14:58,439 --> 01:15:02,920
Speaker 1: through curation. Um. I think Troy might have mentioned some

1364
01:15:03,000 --> 01:15:06,960
Speaker 1: numbers the other day or recently, and you know they

1365
01:15:07,280 --> 01:15:10,400
Speaker 1: seemed in line with what we kind of see at

1366
01:15:10,439 --> 01:15:16,479
Speaker 1: Amazon Music in that general range. Um, what we see

1367
01:15:16,479 --> 01:15:23,080
Speaker 1: in voice is interesting behavior that you see the same

1368
01:15:23,120 --> 01:15:27,120
Speaker 1: person will will Will go from a very casual lean back,

1369
01:15:28,880 --> 01:15:30,920
Speaker 1: just play me some music or play a genre playing

1370
01:15:31,000 --> 01:15:34,439
Speaker 1: artist whatever, to then like go straight deep down into

1371
01:15:34,479 --> 01:15:40,559
Speaker 1: the catalog and want that specific track and so just invert.

1372
01:15:40,640 --> 01:15:44,680
Speaker 1: But but of course by just sheer volume when you're

1373
01:15:44,680 --> 01:15:46,360
Speaker 1: in the lean back mode, you're going to hear more

1374
01:15:46,439 --> 01:15:49,200
Speaker 1: music than It's more tiring to say, play this track,

1375
01:15:49,240 --> 01:15:51,600
Speaker 1: play that track, but you know it takes you a

1376
01:15:51,640 --> 01:15:53,920
Speaker 1: long time to play. If that's fifteen requests you have

1377
01:15:54,000 --> 01:15:55,680
Speaker 1: to come up with to to listen to an hour

1378
01:15:55,680 --> 01:15:59,840
Speaker 1: of music. Um, so we do see invoice people tending

1379
01:16:00,040 --> 01:16:04,120
Speaker 1: to listen to more hours, longer sessions, and a higher

1380
01:16:04,439 --> 01:16:09,120
Speaker 1: incidents of curated music for sure. Now, my girlfriend always says,

1381
01:16:09,160 --> 01:16:12,720
Speaker 1: I do these back exercises and I have thirty second timers,

1382
01:16:13,000 --> 01:16:14,560
Speaker 1: and she says, well, you can set a series of

1383
01:16:14,760 --> 01:16:17,760
Speaker 1: continuous timers. I've yet have been able to do that.

1384
01:16:18,000 --> 01:16:21,639
Speaker 1: But can I load Alexa for your voice? Can I say,

1385
01:16:21,680 --> 01:16:26,719
Speaker 1: play the Rolling Stones, then play Jesus Jones and play Drake?

1386
01:16:26,920 --> 01:16:30,839
Speaker 1: Is there a way to do that? You mean a cue?

1387
01:16:30,880 --> 01:16:35,240
Speaker 1: I mean or just looking getting there but not yet? Okay,

1388
01:16:35,240 --> 01:16:38,479
Speaker 1: it's coming. And are there anybody else with raised hands here?

1389
01:16:38,840 --> 01:16:47,800
Speaker 1: Jim over here? Uh? In terms of statistics, how significant

1390
01:16:47,960 --> 01:16:52,679
Speaker 1: is music? Is a us A case for uh? The echo?

1391
01:16:53,360 --> 01:16:57,560
Speaker 1: In terms of versus other user activity like asking for

1392
01:16:57,600 --> 01:17:01,160
Speaker 1: the weather or recipes or podcasts, and where do you

1393
01:17:01,200 --> 01:17:06,439
Speaker 1: see those statistics going in the future. Yeah, so it's

1394
01:17:07,360 --> 01:17:10,719
Speaker 1: an extremely important use case among all things that people

1395
01:17:10,760 --> 01:17:15,400
Speaker 1: do on Alexa are on Echo. I like to remind

1396
01:17:15,439 --> 01:17:20,320
Speaker 1: my team that, you know, we sell a speaker that

1397
01:17:20,400 --> 01:17:22,479
Speaker 1: has an intelligent assistant in it who can do a

1398
01:17:22,520 --> 01:17:25,960
Speaker 1: lot of different things, but the main vehicle that we're

1399
01:17:26,000 --> 01:17:28,719
Speaker 1: delivering that intelligent assistant to the home is a speaker.

1400
01:17:29,640 --> 01:17:32,519
Speaker 1: And so not surprisingly, music is super important on a

1401
01:17:32,560 --> 01:17:36,400
Speaker 1: speaker because that's what people like to do on speakers. UM.

1402
01:17:36,439 --> 01:17:40,080
Speaker 1: So it's one of the top at all times. How

1403
01:17:40,080 --> 01:17:42,720
Speaker 1: do I see that evolving over time? I think that

1404
01:17:42,800 --> 01:17:45,760
Speaker 1: will stay the case as long for for devices where

1405
01:17:45,800 --> 01:17:49,760
Speaker 1: speakers are really the delivery vehicle for the intelligent assistant.

1406
01:17:49,920 --> 01:17:53,960
Speaker 1: I think if there are other devices that are less

1407
01:17:54,040 --> 01:17:57,080
Speaker 1: music centric than a speaker, I think that percentage would

1408
01:17:57,120 --> 01:18:02,960
Speaker 1: be different. Um. But in the smart speaker category, I

1409
01:18:03,200 --> 01:18:06,960
Speaker 1: expect music to continue to be up there no matter

1410
01:18:06,960 --> 01:18:10,840
Speaker 1: how many more skills are added to Alexa. UM. And

1411
01:18:10,880 --> 01:18:13,559
Speaker 1: it's the thing that you know, people use it not

1412
01:18:13,680 --> 01:18:17,360
Speaker 1: just a lot in terms of hours, but it's frequency

1413
01:18:17,439 --> 01:18:21,760
Speaker 1: and repetition and coming back to it. UM. It the

1414
01:18:21,800 --> 01:18:23,920
Speaker 1: only you know the other skills like that that you know,

1415
01:18:23,960 --> 01:18:28,240
Speaker 1: whether yes, smart home something, if you control your lights

1416
01:18:28,280 --> 01:18:30,240
Speaker 1: you know you do turn them off and on fairly frequently,

1417
01:18:30,240 --> 01:18:34,280
Speaker 1: so you'll repeat that. But music is has an incredible

1418
01:18:35,680 --> 01:18:41,240
Speaker 1: engagement level on the device now on the really regular

1419
01:18:41,280 --> 01:18:46,920
Speaker 1: Amazon Prime, the more people listen, it costs you more money. Okay,

1420
01:18:47,000 --> 01:18:49,600
Speaker 1: So is there any talk at the company of dissuading

1421
01:18:49,680 --> 01:18:53,280
Speaker 1: people from listening because you literally have to pay for that.

1422
01:18:54,920 --> 01:18:59,200
Speaker 1: Uh No, I mean our we we know the value

1423
01:18:59,200 --> 01:19:01,800
Speaker 1: that it generates for Amazon. You know, we know that

1424
01:19:01,840 --> 01:19:05,360
Speaker 1: our Prime members who use Prime Music are better Prime

1425
01:19:05,360 --> 01:19:10,400
Speaker 1: members and they they renew their Prime memberships at a

1426
01:19:10,479 --> 01:19:13,400
Speaker 1: higher rate, They come out of their free trials of

1427
01:19:13,520 --> 01:19:15,920
Speaker 1: Amazon Prime at a higher rate than than than do

1428
01:19:16,040 --> 01:19:19,040
Speaker 1: people who don't use Prime Music. And you know, we

1429
01:19:19,040 --> 01:19:22,160
Speaker 1: we carefully watch that and and understand the value that

1430
01:19:22,200 --> 01:19:24,559
Speaker 1: it's generating. And you know, we're not trying to dissuade

1431
01:19:24,560 --> 01:19:29,080
Speaker 1: people from from listening at all. And yes, um so

1432
01:19:29,360 --> 01:19:33,120
Speaker 1: serious sex sums done a great job of facilitating uh

1433
01:19:33,360 --> 01:19:37,000
Speaker 1: festival and concert live streaming. Red Bull TV has been

1434
01:19:37,000 --> 01:19:39,439
Speaker 1: doing it from a video perspective as well as others.

1435
01:19:39,439 --> 01:19:42,400
Speaker 1: All the Red bullis got out. Um, does Amazon have

1436
01:19:42,439 --> 01:19:47,880
Speaker 1: any intentions of getting into the live music streaming business, uh,

1437
01:19:48,280 --> 01:19:52,519
Speaker 1: via artists directly or festivals. Yeah. I mean I'm not

1438
01:19:52,520 --> 01:19:55,200
Speaker 1: going to talk about things here that we haven't done

1439
01:19:55,280 --> 01:19:57,840
Speaker 1: yet that we might do if we you know, this

1440
01:19:57,880 --> 01:20:01,280
Speaker 1: isn't the forum where I'm gonna disclose something like that. Um.

1441
01:20:01,400 --> 01:20:03,960
Speaker 1: What I would say is we've been doing some live

1442
01:20:04,640 --> 01:20:09,000
Speaker 1: broadcasts lately with working with some of the labels and

1443
01:20:09,080 --> 01:20:13,280
Speaker 1: doing some really interesting promotions around new records by Justin

1444
01:20:13,320 --> 01:20:16,439
Speaker 1: timber Lake, by Elton John just had these tribute albums

1445
01:20:16,800 --> 01:20:18,200
Speaker 1: as well as by you two in the in the

1446
01:20:18,280 --> 01:20:23,920
Speaker 1: in the Winter that are a combination of uh, interviews

1447
01:20:23,920 --> 01:20:26,479
Speaker 1: and music and and it's it's it's really kind of

1448
01:20:26,479 --> 01:20:29,280
Speaker 1: like a live radio show. Um. But in terms of

1449
01:20:29,280 --> 01:20:31,599
Speaker 1: whether we're gonna do live concert stream that's not This

1450
01:20:31,640 --> 01:20:34,320
Speaker 1: isn't the forum for me to talk about that. Yeah.

1451
01:20:34,360 --> 01:20:37,320
Speaker 1: Another question you were talking about, UM, some of the

1452
01:20:37,360 --> 01:20:39,920
Speaker 1: metadata that you have to create on your own and

1453
01:20:40,080 --> 01:20:43,960
Speaker 1: I've been recently reading articles about tags for your songs

1454
01:20:44,040 --> 01:20:45,880
Speaker 1: and like you know, I work with indie artists who

1455
01:20:45,880 --> 01:20:49,040
Speaker 1: work with tune Core and CD Baby in places like that.

1456
01:20:49,640 --> 01:20:53,240
Speaker 1: Are you gonna now go to some of these aggregators

1457
01:20:53,280 --> 01:20:58,920
Speaker 1: and potentially have a different metadata form for when you're

1458
01:20:58,920 --> 01:21:01,759
Speaker 1: submitting your music. You can say this is a sad song,

1459
01:21:01,920 --> 01:21:04,360
Speaker 1: this is an upbeat dance song, and those kind of

1460
01:21:04,400 --> 01:21:08,080
Speaker 1: tags to help you guys with your service. Yeah, we've

1461
01:21:08,080 --> 01:21:11,360
Speaker 1: been actually working with d dex um to try to

1462
01:21:11,560 --> 01:21:14,599
Speaker 1: update the DDX standard to include more fields that are

1463
01:21:15,479 --> 01:21:17,840
Speaker 1: relevant for voice and so that would be you know,

1464
01:21:17,880 --> 01:21:22,120
Speaker 1: it would be in the d dex standard. Okay, any

1465
01:21:22,120 --> 01:21:27,280
Speaker 1: other people with questions here, Okay. The thing about this

1466
01:21:27,360 --> 01:21:29,519
Speaker 1: is we've learned a lot about Amazon and as I

1467
01:21:29,560 --> 01:21:32,280
Speaker 1: even though I have the service, I'm still learning things,

1468
01:21:32,840 --> 01:21:35,320
Speaker 1: which speaks you know, we have the music. People say, oh,

1469
01:21:35,360 --> 01:21:37,599
Speaker 1: market the hell out of it, but it's a stealth

1470
01:21:37,680 --> 01:21:41,000
Speaker 1: operation and something you definitely have to pay attention. And

1471
01:21:41,080 --> 01:21:43,080
Speaker 1: thanks so much d for coming and sharing, Thank you

1472
01:21:43,120 --> 01:21:52,360
Speaker 1: for having me. That wraps up this week's episode of

1473
01:21:52,400 --> 01:21:56,080
Speaker 1: the Bob left Set podcast, recorded live the Music Media

1474
01:21:56,160 --> 01:21:59,320
Speaker 1: Summit in Santa Barbara, California, and produced by tune In.

1475
01:22:00,120 --> 01:22:02,439
Speaker 1: I hope you enjoyed this conversation with VP of the

1476
01:22:02,439 --> 01:22:05,680
Speaker 1: Amazon Music s feed Boom. I found it fascinating how

1477
01:22:05,760 --> 01:22:09,680
Speaker 1: Amazon Music uses data to its advantage. What part of

1478
01:22:09,720 --> 01:22:13,680
Speaker 1: the interview is interesting to you. Your feedback is always appreciated.

1479
01:22:14,040 --> 01:22:16,840
Speaker 1: You can email me at Bob at left sets dot com.

1480
01:22:16,920 --> 01:22:24,400
Speaker 1: Until next time, I'm Bob left Sets than reads. Don't

1481
01:22:24,520 --> 01:22:31,680
Speaker 1: know exactly must be out