1
00:00:00,240 --> 00:00:03,280
Speaker 1: Donald Trump has called for a boycott of all Apple

2
00:00:03,320 --> 00:00:05,880
Speaker 1: products until they cooperate. Though I would like to know.

3
00:00:06,440 --> 00:00:09,000
Speaker 1: I saw his tweets and he has still been tweeting

4
00:00:09,000 --> 00:00:11,760
Speaker 1: from his iPhone, so he personally hasn't kept up with

5
00:00:11,760 --> 00:00:22,239
Speaker 1: this boycott, but it's out there. Hi, and welcome back

6
00:00:22,239 --> 00:00:25,439
Speaker 1: to Bloomberg Benchmark, a podcast about the global economy. It

7
00:00:25,600 --> 00:00:30,120
Speaker 1: is Thursday, March seventeen. I'm Tori Stillwell and economics reporter

8
00:00:30,200 --> 00:00:33,200
Speaker 1: with Bloomberg News in d C. And I am flying

9
00:00:33,280 --> 00:00:36,440
Speaker 1: solo today, but I am getting help from not one,

10
00:00:36,479 --> 00:00:39,000
Speaker 1: but two great guests. They are going to help me

11
00:00:39,080 --> 00:00:41,760
Speaker 1: unpack a pretty interesting topic given that we are in

12
00:00:41,840 --> 00:00:48,000
Speaker 1: the throes of this ever fascinating, sometimes intensely depressing election season.

13
00:00:48,479 --> 00:00:50,480
Speaker 1: It's almost like I can't even remember what my life

14
00:00:50,640 --> 00:00:53,400
Speaker 1: before the election cycle was like. But in the studio

15
00:00:53,840 --> 00:00:56,600
Speaker 1: with me, I have Kurt Carlson and Chris Hidoch of

16
00:00:56,720 --> 00:01:01,319
Speaker 1: Georgetown Institute for Consumer Research. Hey guys, how are you doing? Hi?

17
00:01:01,440 --> 00:01:05,520
Speaker 1: Good beer? So On a related note to the election frenzy,

18
00:01:05,760 --> 00:01:09,360
Speaker 1: we've had some situations in recent memory where companies have

19
00:01:09,480 --> 00:01:12,920
Speaker 1: taken political stances, and it's possible that we could see

20
00:01:12,920 --> 00:01:14,679
Speaker 1: a bit more of that, maybe a lot more of

21
00:01:14,720 --> 00:01:18,360
Speaker 1: that as the election rhetoric heats up further. And so

22
00:01:18,440 --> 00:01:20,880
Speaker 1: you guys have actually done some research on some of

23
00:01:20,880 --> 00:01:24,440
Speaker 1: the economic consequences of that. You know, how do consumers

24
00:01:24,480 --> 00:01:28,920
Speaker 1: respond when companies weighed into politics. But before we get started,

25
00:01:29,200 --> 00:01:32,520
Speaker 1: I drew up a short list of a few examples

26
00:01:32,560 --> 00:01:34,160
Speaker 1: that came off the top of my head, so we

27
00:01:34,200 --> 00:01:37,120
Speaker 1: can jog everyone's memories together. So the first one I

28
00:01:37,200 --> 00:01:42,160
Speaker 1: thought of, given my love for it, was Chipotle. So

29
00:01:42,640 --> 00:01:46,480
Speaker 1: two years ago, a representative or representatives of a group

30
00:01:46,560 --> 00:01:49,640
Speaker 1: called Open Kerry Texas took an armed trip to a

31
00:01:49,760 --> 00:01:55,280
Speaker 1: Dallas area Chipotle and they had military style assault rifles

32
00:01:55,320 --> 00:01:57,960
Speaker 1: with them, like, took pictures and stuff, which would be

33
00:01:58,080 --> 00:02:01,080
Speaker 1: I don't know, I would probably be terrified happened here,

34
00:02:01,080 --> 00:02:03,320
Speaker 1: And I mean it couldn't happen here. I guess in

35
00:02:03,400 --> 00:02:07,000
Speaker 1: d C. Right, it's probably a much lower tolerance stubble

36
00:02:07,040 --> 00:02:11,840
Speaker 1: for that here. So Chipotle came out and it asked

37
00:02:12,120 --> 00:02:16,360
Speaker 1: its customers not to bring guns into its restaurants unless

38
00:02:16,400 --> 00:02:20,440
Speaker 1: they were authorized law enforcement personnel. And do you guys

39
00:02:20,440 --> 00:02:25,160
Speaker 1: remember hearing about this Adida's example from February It had

40
00:02:25,240 --> 00:02:29,360
Speaker 1: to do with Valentine's Day. Our listeners may remember if

41
00:02:29,400 --> 00:02:33,400
Speaker 1: you follow Adida's on Instagram, they posted a couple a

42
00:02:33,400 --> 00:02:36,320
Speaker 1: picture of a couple that appeared to be both women,

43
00:02:36,520 --> 00:02:40,240
Speaker 1: and a commenter threatened to start buying Nike instead, like,

44
00:02:40,240 --> 00:02:42,400
Speaker 1: how could you do this on Valentine's Day? It's for

45
00:02:42,560 --> 00:02:45,359
Speaker 1: like boys and boys and girls, not girls and girls whatever,

46
00:02:45,960 --> 00:02:50,520
Speaker 1: And Adida's responded with the handwave emoji, like essentially saying

47
00:02:50,560 --> 00:02:53,600
Speaker 1: like by Felicia to this comment, so we don't care.

48
00:02:54,160 --> 00:02:56,040
Speaker 1: And then Chick fil A. Maybe you guys can talk

49
00:02:56,040 --> 00:02:58,480
Speaker 1: about the Chick fil A one because I remember this,

50
00:02:58,800 --> 00:03:00,919
Speaker 1: It still comes up today and a lot of conversations

51
00:03:00,919 --> 00:03:03,640
Speaker 1: that I have with Ppo, so so yeah, chick floy

52
00:03:03,800 --> 00:03:07,399
Speaker 1: Is is definitely the incidents that motivated this whole research project.

53
00:03:08,000 --> 00:03:11,360
Speaker 1: One of our our co authors was heard about the

54
00:03:11,400 --> 00:03:14,640
Speaker 1: story um and obviously we acknowledge that Chick fil A,

55
00:03:14,720 --> 00:03:16,240
Speaker 1: we were all talking about it in the news at

56
00:03:16,280 --> 00:03:18,800
Speaker 1: that point. But we again to wonder what is the

57
00:03:18,800 --> 00:03:22,280
Speaker 1: effect on consumers. Do consumers even care about this at all?

58
00:03:23,200 --> 00:03:24,840
Speaker 1: Are they just going to look past this and and

59
00:03:24,919 --> 00:03:27,280
Speaker 1: never think about it again, or is there going to

60
00:03:27,360 --> 00:03:30,120
Speaker 1: be some some kind of net effect on in terms

61
00:03:30,160 --> 00:03:32,960
Speaker 1: of a positive or negative result in terms of increased

62
00:03:33,000 --> 00:03:36,000
Speaker 1: or decreased visits to Chick fil A after after their

63
00:03:36,840 --> 00:03:39,640
Speaker 1: anti gay marriage stands, right, And so that's the game

64
00:03:39,720 --> 00:03:42,400
Speaker 1: what really drove this project. Yeah, and that was all

65
00:03:42,400 --> 00:03:44,200
Speaker 1: the way back in twelve It's hard to believe that

66
00:03:44,240 --> 00:03:47,160
Speaker 1: was that long ago, but the CEO, Chick fil A

67
00:03:47,280 --> 00:03:50,720
Speaker 1: CEO came out and said he was guilty as charged

68
00:03:50,840 --> 00:03:54,080
Speaker 1: in his religion based opposition to gay marriage, and as

69
00:03:54,120 --> 00:03:57,800
Speaker 1: a result, same sex marriage supporters protested at Chick fil

70
00:03:57,840 --> 00:04:00,839
Speaker 1: A locations, while those who would agree with him sort

71
00:04:00,840 --> 00:04:02,720
Speaker 1: of crammed into Chick fil A stores this year their

72
00:04:02,720 --> 00:04:06,240
Speaker 1: support and actually, fun fact, in an interview two years later,

73
00:04:06,480 --> 00:04:10,960
Speaker 1: Kathy actually seemed to regret waiting into that and said

74
00:04:11,000 --> 00:04:13,560
Speaker 1: that Chick fil A had no place in culture wars.

75
00:04:13,800 --> 00:04:18,400
Speaker 1: So um lots to talk about. I don't wanna neglect

76
00:04:18,480 --> 00:04:21,159
Speaker 1: mentioning apple and privacy, but we'll get into that later

77
00:04:21,200 --> 00:04:25,000
Speaker 1: since that's a sort of a recent area of discussion here.

78
00:04:25,240 --> 00:04:27,159
Speaker 1: So in some of the cases that we've talked about,

79
00:04:27,400 --> 00:04:29,120
Speaker 1: it seemed like they were sort of forced to take

80
00:04:29,160 --> 00:04:32,640
Speaker 1: a stance because something happened in their store. So I

81
00:04:32,640 --> 00:04:34,919
Speaker 1: mean how does that, how does what does the company

82
00:04:34,960 --> 00:04:37,800
Speaker 1: do with that? How does that affect them? So that's

83
00:04:38,000 --> 00:04:40,680
Speaker 1: that's an interesting question, I think. Uh, one of the

84
00:04:40,720 --> 00:04:43,400
Speaker 1: things I've actually thought about with chick Folio itself is

85
00:04:44,120 --> 00:04:47,640
Speaker 1: uh that they are privately run business. They're not too

86
00:04:47,640 --> 00:04:49,920
Speaker 1: shy about the fact that religion does play a big

87
00:04:49,960 --> 00:04:52,360
Speaker 1: part in how they operate their business. For example, they're

88
00:04:52,400 --> 00:04:56,680
Speaker 1: not open on Sundays, um, and so their stands when

89
00:04:56,680 --> 00:04:58,920
Speaker 1: it came to a gay marriage kind of fit with

90
00:04:59,040 --> 00:05:03,680
Speaker 1: the beliefs that have UM exerted at other points in operating.

91
00:05:03,720 --> 00:05:07,160
Speaker 1: And so it becomes really unclear if if that will

92
00:05:07,240 --> 00:05:12,800
Speaker 1: be something that um that differentiates a four stance from

93
00:05:12,839 --> 00:05:16,200
Speaker 1: a voluntary stance. Yeah, I would just I would just

94
00:05:16,279 --> 00:05:19,360
Speaker 1: chime in that you've got the entire spectrum operating here.

95
00:05:19,400 --> 00:05:21,839
Speaker 1: You can imagine at one end of the spectrum, you've

96
00:05:21,839 --> 00:05:25,760
Speaker 1: got a divisive political issue that has nothing to do

97
00:05:25,839 --> 00:05:29,520
Speaker 1: with the business at hand, and the company simply chooses

98
00:05:29,520 --> 00:05:33,799
Speaker 1: to enter into the conversation, perhaps because the CEO thinks

99
00:05:33,839 --> 00:05:37,080
Speaker 1: that it would be wise to share that opinion on

100
00:05:37,200 --> 00:05:40,560
Speaker 1: social media, or because um they think that somehow it

101
00:05:40,560 --> 00:05:44,039
Speaker 1: will draw attention and bode well for the company, or

102
00:05:44,080 --> 00:05:45,719
Speaker 1: they're just not even thinking. And then maybe they're not

103
00:05:45,720 --> 00:05:48,240
Speaker 1: even thinking about it right six and one, half a

104
00:05:48,279 --> 00:05:50,200
Speaker 1: dozen of the other maybe it hurts some, helps some,

105
00:05:50,279 --> 00:05:52,160
Speaker 1: they're not worried too much about it. On the other

106
00:05:52,240 --> 00:05:55,120
Speaker 1: end of the spectrum, you've got you've got instances like

107
00:05:55,520 --> 00:05:59,280
Speaker 1: people carrying semi automatic machine guns into your store and

108
00:05:59,520 --> 00:06:03,200
Speaker 1: potentially scaring off your average patron. And so now you're

109
00:06:03,320 --> 00:06:05,159
Speaker 1: it really does seem like you're being forced into it.

110
00:06:05,240 --> 00:06:08,320
Speaker 1: And you mentioned, um, you mentioned the case of Apple.

111
00:06:08,760 --> 00:06:11,480
Speaker 1: I think that you know that's also an instance where

112
00:06:11,320 --> 00:06:13,839
Speaker 1: they're being forced in by by the government requesting that

113
00:06:13,880 --> 00:06:17,719
Speaker 1: they actually do work on behalf of the government's request

114
00:06:18,200 --> 00:06:20,720
Speaker 1: that would violate its current policy. So you've got the

115
00:06:20,800 --> 00:06:25,400
Speaker 1: spectrum out there, and in some of these instances, when

116
00:06:25,520 --> 00:06:28,280
Speaker 1: we opt to weigh it in, like Chris said, it's

117
00:06:28,320 --> 00:06:31,280
Speaker 1: going to be much more central to whatever our business practices.

118
00:06:31,320 --> 00:06:33,520
Speaker 1: And you could make the claim that to the extent

119
00:06:33,600 --> 00:06:37,440
Speaker 1: that the typical consumer at Chick fil A sees themselves

120
00:06:38,000 --> 00:06:42,200
Speaker 1: as someone who's you know, faith abiding, that they might

121
00:06:42,240 --> 00:06:46,440
Speaker 1: actually they might actually appreciate the stance taken taken by

122
00:06:46,480 --> 00:06:48,360
Speaker 1: the CEO, and it seems like a lot of them did.

123
00:06:48,480 --> 00:06:50,960
Speaker 1: I mean, I remember reading reports about people sort of

124
00:06:51,000 --> 00:06:53,640
Speaker 1: like waiting out the door of lines wrapping around those

125
00:06:53,680 --> 00:06:56,960
Speaker 1: stores when this happened in show and show of support

126
00:06:57,000 --> 00:06:59,680
Speaker 1: for that. Yep. So then that you know, the question

127
00:06:59,720 --> 00:07:03,160
Speaker 1: that that that we were focused on is if you

128
00:07:03,240 --> 00:07:08,360
Speaker 1: take any particular divisive issue and there's two sides to it,

129
00:07:08,400 --> 00:07:10,000
Speaker 1: we're just we're gonna let's just define it that with

130
00:07:10,080 --> 00:07:11,880
Speaker 1: Let's just say, Okay, a divisive issue has two sides,

131
00:07:11,880 --> 00:07:14,040
Speaker 1: and it doesn't mean that it has to lanmages, but

132
00:07:14,080 --> 00:07:16,160
Speaker 1: that let's play in that, in that in that sandbox.

133
00:07:16,880 --> 00:07:22,000
Speaker 1: And it's interesting because there's about on each side of

134
00:07:22,000 --> 00:07:24,480
Speaker 1: the issue. It's it's hard to come up with divisive

135
00:07:24,520 --> 00:07:28,119
Speaker 1: issues where people agree, right, I mean, it just seems

136
00:07:28,160 --> 00:07:30,640
Speaker 1: like it's not terribly divisive. It's an issue, but not

137
00:07:30,760 --> 00:07:35,000
Speaker 1: terribly divisive. So if you've got you know, a sizeable

138
00:07:35,520 --> 00:07:38,080
Speaker 1: percentage of people on either side of a divisive issue,

139
00:07:38,640 --> 00:07:42,280
Speaker 1: you can ask the question, what happens when this brand

140
00:07:42,720 --> 00:07:45,160
Speaker 1: or this company that may or may not need to

141
00:07:45,200 --> 00:07:49,920
Speaker 1: wade into this adopts one side of this, Right, some

142
00:07:50,000 --> 00:07:51,880
Speaker 1: of the people are going to agree with that, and

143
00:07:52,000 --> 00:07:55,120
Speaker 1: some are going to disagree for example, what are the

144
00:07:55,200 --> 00:07:58,160
Speaker 1: reactions of those two groups going to be and and

145
00:07:58,360 --> 00:08:01,960
Speaker 1: will they be equal? They'll almost certainly be opposite, right,

146
00:08:02,000 --> 00:08:04,600
Speaker 1: they have to be opposite, But will they be equal?

147
00:08:04,920 --> 00:08:06,760
Speaker 1: And so that was sort of where we entered. We

148
00:08:06,800 --> 00:08:09,120
Speaker 1: came in and we said, let's look in a broad

149
00:08:09,280 --> 00:08:13,320
Speaker 1: range of context, with a broad range of issues, and

150
00:08:13,360 --> 00:08:17,200
Speaker 1: then let's see what happens to those that agree with

151
00:08:17,240 --> 00:08:19,320
Speaker 1: the position they took and those that disagree. What what

152
00:08:19,400 --> 00:08:22,800
Speaker 1: does that do to attitude towards the brand and willingness

153
00:08:22,800 --> 00:08:25,320
Speaker 1: to buy the brand? That was our question, right, So

154
00:08:25,400 --> 00:08:28,400
Speaker 1: I mean, let's look at at one of those buckets first.

155
00:08:28,440 --> 00:08:33,560
Speaker 1: And so in a situation where a company representatives just

156
00:08:33,600 --> 00:08:36,160
Speaker 1: sort of like Yolo, let's let's take a stance here,

157
00:08:37,000 --> 00:08:39,520
Speaker 1: what happens to them? What happens to their business? Chris,

158
00:08:40,440 --> 00:08:46,160
Speaker 1: It's time for the big reveal. So when when those representatives,

159
00:08:46,160 --> 00:08:49,560
Speaker 1: with the CEO or anyone on anyone high enough up

160
00:08:49,559 --> 00:08:53,520
Speaker 1: to garner some attention, takes that stance. Um, what we

161
00:08:53,600 --> 00:08:55,240
Speaker 1: ended up seeing is we saw this kind of by

162
00:08:55,360 --> 00:08:59,400
Speaker 1: valent reaction among consumers. Uh. Some obviously are gonna support that,

163
00:08:59,480 --> 00:09:02,760
Speaker 1: some are going to oppose that. Uh. What we see

164
00:09:02,920 --> 00:09:05,960
Speaker 1: is that those consumers who support the stance, we see

165
00:09:05,960 --> 00:09:08,480
Speaker 1: a small kind of increase in their attitude towards the

166
00:09:08,520 --> 00:09:12,360
Speaker 1: brand um. But more importantly what we see is those

167
00:09:12,360 --> 00:09:16,520
Speaker 1: consumers that oppose the stance that that that company member took,

168
00:09:17,360 --> 00:09:21,440
Speaker 1: we see this significant, much more significant decrease in attitude

169
00:09:21,440 --> 00:09:24,440
Speaker 1: towards the brands. Just thinking in my own personal life,

170
00:09:24,480 --> 00:09:27,520
Speaker 1: I know people who to this day refused to eat

171
00:09:27,520 --> 00:09:30,240
Speaker 1: at Chick fil A, even though that happened almost four

172
00:09:30,320 --> 00:09:33,280
Speaker 1: years ago. Now they still will not eat there um,

173
00:09:33,440 --> 00:09:37,280
Speaker 1: despite the fact that they love their chick that happening.

174
00:09:37,320 --> 00:09:39,920
Speaker 1: I mean, it's a perfect example. So you get you

175
00:09:39,960 --> 00:09:43,040
Speaker 1: get the you get the maybe slight positive increase in

176
00:09:43,080 --> 00:09:46,480
Speaker 1: the attitude for those that agree with the position on

177
00:09:46,559 --> 00:09:49,720
Speaker 1: this case opposing gay marriage, and you get this really

178
00:09:49,760 --> 00:09:53,800
Speaker 1: strong aversive reaction to the people that that disagree. And

179
00:09:53,800 --> 00:09:56,000
Speaker 1: so we're finding that in the attitude measures and the

180
00:09:56,080 --> 00:09:58,280
Speaker 1: choice and the willingness to pay measures that there's just

181
00:09:58,400 --> 00:10:01,960
Speaker 1: not a whole lot of upside. Right, the subset that

182
00:10:01,960 --> 00:10:04,280
Speaker 1: that aligns with the position you're going to take as

183
00:10:04,280 --> 00:10:08,040
Speaker 1: you wade into this divisive political issue. The subset that

184
00:10:08,040 --> 00:10:10,319
Speaker 1: that that aligns with it just isn't gonna do that

185
00:10:10,440 --> 00:10:13,200
Speaker 1: much to help you out. I do that because they've

186
00:10:13,240 --> 00:10:15,520
Speaker 1: are already eating their one chicken sandwich a week, right,

187
00:10:15,559 --> 00:10:18,400
Speaker 1: and they're just they've got a quota any more than

188
00:10:18,440 --> 00:10:21,240
Speaker 1: one chicken sand much a week or that. There's just

189
00:10:21,440 --> 00:10:23,920
Speaker 1: there's just they're not going to reward you for for

190
00:10:23,920 --> 00:10:26,959
Speaker 1: for wading into that. On the other side, man, people,

191
00:10:27,040 --> 00:10:29,480
Speaker 1: when when you wade into one of these divisive political issues,

192
00:10:29,480 --> 00:10:32,200
Speaker 1: the people that disagree with it seem like they like

193
00:10:32,240 --> 00:10:35,840
Speaker 1: they've found a reason to choose an alternative over you.

194
00:10:36,520 --> 00:10:39,600
Speaker 1: And so you could start to ask the question, which

195
00:10:39,600 --> 00:10:42,320
Speaker 1: maybe we'll get into in a bit, is what's the

196
00:10:42,360 --> 00:10:44,480
Speaker 1: net net of this right? You can start to ask,

197
00:10:44,640 --> 00:10:47,640
Speaker 1: and the answer to that is probably gonna come down

198
00:10:47,679 --> 00:10:51,719
Speaker 1: to the composition of your your customer base. Right, if

199
00:10:52,440 --> 00:10:54,680
Speaker 1: your customers agree with the stance you took, maybe the

200
00:10:54,760 --> 00:11:01,040
Speaker 1: slight benefit right added up over those for you works out.

201
00:11:01,240 --> 00:11:03,520
Speaker 1: You lose more on the ten percent they don't come

202
00:11:03,559 --> 00:11:05,839
Speaker 1: to you anymore at all, but but they coming to

203
00:11:05,880 --> 00:11:09,120
Speaker 1: you one more time a month from offsets it. But

204
00:11:09,200 --> 00:11:11,280
Speaker 1: remember what we said to start this, right, is that

205
00:11:11,400 --> 00:11:14,439
Speaker 1: these are divisive political issues. So there there are issues

206
00:11:14,800 --> 00:11:18,160
Speaker 1: that are divisive by definition, meaning there's a good chunk

207
00:11:18,160 --> 00:11:21,120
Speaker 1: of people on each side, to the extent that there's

208
00:11:21,160 --> 00:11:23,800
Speaker 1: about fifty fifty or sixty forty, it's going to be

209
00:11:23,880 --> 00:11:28,200
Speaker 1: really hard for this small positive effect to outweigh the

210
00:11:28,240 --> 00:11:31,320
Speaker 1: big negative effect that we're seeing. So yeah, so I

211
00:11:31,320 --> 00:11:33,880
Speaker 1: think with national brands that's definitely the case. You can

212
00:11:33,920 --> 00:11:36,560
Speaker 1: imagine maybe maybe a smaller brand in a local area

213
00:11:37,200 --> 00:11:40,959
Speaker 1: um that has where maybe nationally again that this is

214
00:11:41,040 --> 00:11:44,760
Speaker 1: a debate in this local area, that might be and

215
00:11:44,840 --> 00:11:47,400
Speaker 1: maybe those smaller brands are able to take advantage of this.

216
00:11:47,520 --> 00:11:51,600
Speaker 1: So maybe Pete's local bait shop in North Carolina might

217
00:11:51,640 --> 00:11:54,280
Speaker 1: be able to take advantage of certain issues that a

218
00:11:54,360 --> 00:11:57,160
Speaker 1: national brand like Starbucks or Target could not. Yeah, I mean,

219
00:11:57,960 --> 00:12:01,560
Speaker 1: thinking again of my own personal life. I live in

220
00:12:01,640 --> 00:12:04,640
Speaker 1: DuPont near DuPont Circle here in d C. And for

221
00:12:04,679 --> 00:12:07,440
Speaker 1: our listeners who aren't familiar with DC, it's a very

222
00:12:07,480 --> 00:12:10,960
Speaker 1: gay friendly neighborhood. Has all has been that way for

223
00:12:11,080 --> 00:12:15,199
Speaker 1: decades now. The annual Pride parade stretches across many DuPont streets.

224
00:12:15,480 --> 00:12:19,040
Speaker 1: We have a yearly high heel race where drag queens

225
00:12:19,080 --> 00:12:22,160
Speaker 1: will race each other uh down a street like right

226
00:12:22,200 --> 00:12:25,120
Speaker 1: next to my house. Um and year round, a lot

227
00:12:25,240 --> 00:12:29,400
Speaker 1: of businesses have rainbow flags or rainbow stickers on their doors,

228
00:12:29,559 --> 00:12:32,040
Speaker 1: and I've got to believe that's in some sense taking

229
00:12:32,040 --> 00:12:36,079
Speaker 1: a political stance. So would they benefit in a situation

230
00:12:36,120 --> 00:12:39,280
Speaker 1: like that. I think that's the perfect example, um that

231
00:12:39,360 --> 00:12:41,679
Speaker 1: a lot of these local businesses around here, Uh, they

232
00:12:41,720 --> 00:12:45,920
Speaker 1: will take the stance that they know pretty much everybody

233
00:12:45,920 --> 00:12:49,640
Speaker 1: in DC supports UM And you don't see the national

234
00:12:49,679 --> 00:12:51,600
Speaker 1: businesses do it, but you do see the local brands

235
00:12:51,600 --> 00:12:55,240
Speaker 1: do it. Right. And so if we're thinking back then

236
00:12:55,360 --> 00:12:57,760
Speaker 1: to our sort of second scenario where a company is

237
00:12:57,920 --> 00:13:02,440
Speaker 1: forced into doing this, um, so a Chipotle or Starbucks

238
00:13:02,440 --> 00:13:05,000
Speaker 1: in this situation where people are just sort of bringing

239
00:13:05,080 --> 00:13:08,800
Speaker 1: these big scary guns and small inoffensive guns I guess

240
00:13:08,840 --> 00:13:11,360
Speaker 1: into their into their stores. I mean, how did they

241
00:13:11,400 --> 00:13:14,960
Speaker 1: figure out what to do? Then? Wow, that's a great question.

242
00:13:15,240 --> 00:13:20,440
Speaker 1: UM know that that based upon our results, it's it's

243
00:13:20,480 --> 00:13:23,400
Speaker 1: not going to buy you too much with those that

244
00:13:23,440 --> 00:13:25,079
Speaker 1: are aligned already with the position, and it's going to

245
00:13:25,200 --> 00:13:28,079
Speaker 1: hurt you. On the other side, if you look at

246
00:13:28,320 --> 00:13:33,920
Speaker 1: other research and behavior economics, people are extremely forgiving of

247
00:13:34,120 --> 00:13:38,480
Speaker 1: actions that businesses take that they didn't have a choice

248
00:13:38,480 --> 00:13:42,160
Speaker 1: in taking UM. Just as an example, the single best

249
00:13:42,240 --> 00:13:46,280
Speaker 1: way to increase your price is to tell people that

250
00:13:46,320 --> 00:13:48,719
Speaker 1: you had no choice because your costs one up. Have

251
00:13:48,800 --> 00:13:53,120
Speaker 1: you increase price because demand is high. It's called price cougy,

252
00:13:53,120 --> 00:13:55,400
Speaker 1: and you end up in front of Congress, right right. So,

253
00:13:55,559 --> 00:13:59,840
Speaker 1: But if if you like attract the ire of everyone

254
00:14:00,000 --> 00:14:02,560
Speaker 1: around you, if we were to make a prescription in

255
00:14:02,559 --> 00:14:05,280
Speaker 1: this context, it would be, you know, take the position

256
00:14:05,520 --> 00:14:08,160
Speaker 1: that applies to your values. Know that there's going to

257
00:14:08,200 --> 00:14:10,760
Speaker 1: be a subset of your customer base that probably is

258
00:14:10,760 --> 00:14:13,200
Speaker 1: not going to like that, and do your best to

259
00:14:13,240 --> 00:14:16,200
Speaker 1: communicate to them that that you really didn't have a

260
00:14:16,280 --> 00:14:18,640
Speaker 1: choice in this, not not in the choice of which

261
00:14:18,640 --> 00:14:20,920
Speaker 1: direction to go, but that you were forced to make

262
00:14:20,960 --> 00:14:23,240
Speaker 1: a choice. And I think that will probably buy you

263
00:14:23,800 --> 00:14:29,280
Speaker 1: a certain amount of insulation against retribution. UM. Let's talk

264
00:14:29,280 --> 00:14:32,800
Speaker 1: a little bit more about Apple because it has become

265
00:14:32,920 --> 00:14:37,000
Speaker 1: a pretty hot topic lately, and in case our listeners

266
00:14:37,000 --> 00:14:40,440
Speaker 1: haven't been following. Apple was served with a court order

267
00:14:40,600 --> 00:14:44,120
Speaker 1: last month to help the FBI unlock a phone used

268
00:14:44,160 --> 00:14:47,000
Speaker 1: by one of two attackers who killed fourteen people in

269
00:14:47,120 --> 00:14:51,680
Speaker 1: San Bernardino, California. Apple has refused to do so, saying

270
00:14:51,720 --> 00:14:54,560
Speaker 1: that creating software to help the FBI would set a

271
00:14:54,560 --> 00:14:58,160
Speaker 1: really bad precedent and open the door for other foreign

272
00:14:58,200 --> 00:15:01,600
Speaker 1: governments to make similar demand. And they've gotten a ton

273
00:15:01,640 --> 00:15:06,080
Speaker 1: of backup from other tech giants, including Amazon, Google, Microsoft,

274
00:15:06,200 --> 00:15:09,840
Speaker 1: And meanwhile, the US government's argument is that, you know,

275
00:15:09,920 --> 00:15:13,480
Speaker 1: one of the world's most technologically savvy companies can easily

276
00:15:13,520 --> 00:15:16,960
Speaker 1: help it with one one little phone without risking the

277
00:15:17,000 --> 00:15:20,640
Speaker 1: security of its operations or the privacy of its customers.

278
00:15:20,640 --> 00:15:23,640
Speaker 1: So I mean, walk walk me through how you guys

279
00:15:24,120 --> 00:15:28,000
Speaker 1: might see this and in any possible economic consequences, good

280
00:15:28,120 --> 00:15:31,720
Speaker 1: or bad, that could befall Apple, because Donald Trump has

281
00:15:31,760 --> 00:15:35,160
Speaker 1: called for a boycott of all Apple products until they cooperate.

282
00:15:35,280 --> 00:15:37,920
Speaker 1: Though I would like to know. I saw his tweets

283
00:15:37,960 --> 00:15:40,520
Speaker 1: and he has still been tweeting from his iPhone, so

284
00:15:40,560 --> 00:15:44,160
Speaker 1: he personally hasn't kept up with this boycott, but it's

285
00:15:44,160 --> 00:15:48,040
Speaker 1: out there. Yeah, there's there's the boycott on purchase, the boycott,

286
00:15:48,120 --> 00:15:51,800
Speaker 1: and then there's the boycott on use, two totally different things, apparently.

287
00:15:52,440 --> 00:15:55,440
Speaker 1: So I think when we look at this example, there's

288
00:15:55,440 --> 00:16:00,720
Speaker 1: two sides there. There's the um Apple logistically wanting to

289
00:16:00,840 --> 00:16:03,680
Speaker 1: ensure the privacy of their phones and ensure that ensure

290
00:16:03,680 --> 00:16:06,040
Speaker 1: that their consumers that their their data that they transmit

291
00:16:06,080 --> 00:16:09,160
Speaker 1: on their phones and contain on their phones UM is private.

292
00:16:09,520 --> 00:16:11,440
Speaker 1: And then you all can also look at this as

293
00:16:11,640 --> 00:16:14,400
Speaker 1: as kind of Apple taking a stance for privacy more general,

294
00:16:14,960 --> 00:16:18,160
Speaker 1: UM more generally, and I think that is uh partially

295
00:16:18,200 --> 00:16:21,120
Speaker 1: what they're doing by blowing this issue up. UM. They

296
00:16:21,200 --> 00:16:22,760
Speaker 1: look at this as a great chance to build up

297
00:16:22,760 --> 00:16:26,560
Speaker 1: a reputation for a company that champions privacy UM. And

298
00:16:26,640 --> 00:16:28,600
Speaker 1: so when we especially when we look at it in

299
00:16:28,600 --> 00:16:31,160
Speaker 1: that sense, we can look at again, how how is

300
00:16:31,160 --> 00:16:34,000
Speaker 1: this going to affect consumers? And we ended up running

301
00:16:34,000 --> 00:16:36,240
Speaker 1: a study trying to look at this exact thing with

302
00:16:36,240 --> 00:16:39,360
Speaker 1: with privacy rights and technology companies, and we see the

303
00:16:39,360 --> 00:16:42,440
Speaker 1: exact same effects that we saw another studies are grand

304
00:16:42,440 --> 00:16:47,560
Speaker 1: with immigration or gun rights or healthcare. Again, we see

305
00:16:47,600 --> 00:16:51,440
Speaker 1: the same pattern where consumers who supported the stance they

306
00:16:51,480 --> 00:16:53,960
Speaker 1: there was a bumping attitudes was bumping kind of willingness

307
00:16:53,960 --> 00:16:57,640
Speaker 1: to purchase for those brands UM, and for the consumers

308
00:16:57,640 --> 00:17:01,680
Speaker 1: who opposed, we see the significant decreasing in so we

309
00:17:01,680 --> 00:17:03,200
Speaker 1: we kind of end up at the same place that

310
00:17:03,280 --> 00:17:06,440
Speaker 1: we think this will have a very h a much

311
00:17:06,480 --> 00:17:08,920
Speaker 1: bigger effect on those who oppose Apple stands than those

312
00:17:08,920 --> 00:17:11,239
Speaker 1: who support it. And then it comes down to do

313
00:17:11,320 --> 00:17:15,040
Speaker 1: more consumers support or oppose apples stands here? Right? And

314
00:17:15,080 --> 00:17:18,160
Speaker 1: that also would purchase their products to begin with? Because

315
00:17:18,160 --> 00:17:21,200
Speaker 1: I guess if if they if they're like Samsung users,

316
00:17:21,240 --> 00:17:23,479
Speaker 1: this doesn't really affect them. Maybe they were never going

317
00:17:23,520 --> 00:17:25,800
Speaker 1: to buy an Apple phone to begin with and they

318
00:17:25,880 --> 00:17:28,359
Speaker 1: just disagree with that. So I mean that's when when

319
00:17:28,400 --> 00:17:30,920
Speaker 1: we look at it or yeah, if the disagree as yeah,

320
00:17:31,080 --> 00:17:33,960
Speaker 1: or you can as canned, Apple use this to attract

321
00:17:33,960 --> 00:17:37,040
Speaker 1: some Samsung users over to their side. Right. So we

322
00:17:37,080 --> 00:17:40,680
Speaker 1: talked about a loyalty effect earlier, Um, could this help

323
00:17:41,320 --> 00:17:45,919
Speaker 1: sort of engender greater loyalty among people who already have

324
00:17:46,080 --> 00:17:49,240
Speaker 1: Apple products? I mean, I don't even really know what

325
00:17:49,400 --> 00:17:52,280
Speaker 1: encrypted phones mean. I just know I have like my

326
00:17:52,320 --> 00:17:56,200
Speaker 1: little four number password here on the phone and hopes

327
00:17:56,280 --> 00:17:58,400
Speaker 1: that I hope that takes care of the problem. But

328
00:17:58,800 --> 00:18:01,280
Speaker 1: I mean, what sort of loyalty effects are we looking

329
00:18:01,280 --> 00:18:04,720
Speaker 1: at here? Well? So this is a really interesting question.

330
00:18:05,320 --> 00:18:09,000
Speaker 1: What are the long run consequences of of adopting a

331
00:18:09,040 --> 00:18:13,320
Speaker 1: position that that someone agrees with based upon something that

332
00:18:13,359 --> 00:18:15,160
Speaker 1: doesn't necessarily have a whole lot to do with the

333
00:18:15,200 --> 00:18:19,760
Speaker 1: business that the company's in. UM. In different work work

334
00:18:19,840 --> 00:18:23,399
Speaker 1: that that that I've done with Shani b Energy is

335
00:18:23,400 --> 00:18:26,439
Speaker 1: at the University of Texas, San Antonio. We look at

336
00:18:26,440 --> 00:18:30,480
Speaker 1: the question of what is it that makes consumers fiercely loyal?

337
00:18:30,720 --> 00:18:32,840
Speaker 1: Like I mean, and this is by first of all,

338
00:18:32,960 --> 00:18:36,639
Speaker 1: we mean irrationally loyal. The people that will defend a

339
00:18:36,720 --> 00:18:40,520
Speaker 1: brand even when the evidence is stacked up against it.

340
00:18:41,000 --> 00:18:44,000
Speaker 1: The people that used to think of as sort of

341
00:18:44,040 --> 00:18:48,520
Speaker 1: like Harley David said, um writers, and and maybe some

342
00:18:48,640 --> 00:18:52,000
Speaker 1: people early in the days of Starbucks. Um Dan, I

343
00:18:52,040 --> 00:18:55,560
Speaker 1: think our my coast would definitely fall into this category,

344
00:18:56,560 --> 00:18:58,800
Speaker 1: and that a lot of a lot of apples consumers

345
00:18:58,800 --> 00:19:01,000
Speaker 1: too would fit that as well. And so we studied this.

346
00:19:01,040 --> 00:19:02,920
Speaker 1: We we said, what is it that makes these people

347
00:19:03,000 --> 00:19:05,960
Speaker 1: unique over people that just buy a product quite frequently?

348
00:19:06,400 --> 00:19:09,400
Speaker 1: And what we found was that, um it's different. It's

349
00:19:09,400 --> 00:19:12,359
Speaker 1: a form of love, but it's different than sort of

350
00:19:12,400 --> 00:19:15,120
Speaker 1: puppy dog love, because you can you can love your

351
00:19:15,119 --> 00:19:18,280
Speaker 1: puppy and you can also love the neighbor's puppy. But

352
00:19:18,400 --> 00:19:22,720
Speaker 1: in these instances, these fiercely loyal consumers. They loved their

353
00:19:22,800 --> 00:19:29,119
Speaker 1: brand and they hated the alternatives. So what we discovered

354
00:19:29,359 --> 00:19:31,520
Speaker 1: as part of studying this is that that in order

355
00:19:31,560 --> 00:19:34,320
Speaker 1: to create this sort of fierce loyalty, there had to

356
00:19:34,359 --> 00:19:36,600
Speaker 1: be some antagonists. There had to be there had to

357
00:19:36,600 --> 00:19:38,679
Speaker 1: be both the brand that you could fall in love with,

358
00:19:38,720 --> 00:19:41,679
Speaker 1: but then something else that was pushing you towards it

359
00:19:41,720 --> 00:19:45,119
Speaker 1: that you were you were in some sense disgusted with.

360
00:19:45,640 --> 00:19:48,439
Speaker 1: And so in this context, that's not another brand, but

361
00:19:48,520 --> 00:19:56,000
Speaker 1: that that's the federal government. And so so it's entirely

362
00:19:56,040 --> 00:20:00,239
Speaker 1: possible that that we won't see a huge uptick in

363
00:20:00,359 --> 00:20:05,200
Speaker 1: sales or necessarily even attitudes, but we will see some

364
00:20:05,280 --> 00:20:09,040
Speaker 1: of these loyal Apple consumers convert into what we might

365
00:20:09,080 --> 00:20:13,280
Speaker 1: call fiercely loyal, like rationally loyal consumers, and that could

366
00:20:13,280 --> 00:20:16,840
Speaker 1: bode well for them in the future upsell cross sell,

367
00:20:17,040 --> 00:20:20,760
Speaker 1: insulating them from mistakes they might make in the future,

368
00:20:20,800 --> 00:20:24,280
Speaker 1: insulating them from bricing mistakes where they raise price without

369
00:20:24,359 --> 00:20:28,720
Speaker 1: raising costs, all because fiercely loyal consumers are just really

370
00:20:28,760 --> 00:20:32,399
Speaker 1: really forgiving of all kinds of mistakes that companies would make.

371
00:20:32,440 --> 00:20:35,600
Speaker 1: So to the extent that that the federal government is

372
00:20:35,640 --> 00:20:38,399
Speaker 1: going to act in the mind of the consumer as

373
00:20:38,760 --> 00:20:43,000
Speaker 1: this sort of antagonist. Then this adopting this position might

374
00:20:43,040 --> 00:20:47,679
Speaker 1: actually work well to convert some of Apple's borderline loyal

375
00:20:47,720 --> 00:20:53,200
Speaker 1: fiercely loyal to really fiercely loyal consumers. Fascinating. UH. When

376
00:20:53,200 --> 00:20:56,159
Speaker 1: we were talking earlier, one of your research associates and

377
00:20:56,320 --> 00:21:01,600
Speaker 1: Wilson mentioned how there are actually apps that let you

378
00:21:01,720 --> 00:21:06,680
Speaker 1: see political stances that companies support UM, so I researched

379
00:21:06,720 --> 00:21:08,879
Speaker 1: some of the ones that she talked about. There's boycott,

380
00:21:09,359 --> 00:21:12,480
Speaker 1: which has a built in bar code scanner to let

381
00:21:12,560 --> 00:21:15,720
Speaker 1: you quote vote with your wallet, and you can learn

382
00:21:15,760 --> 00:21:19,200
Speaker 1: about a products history, make a purchase decision, and then

383
00:21:19,280 --> 00:21:22,680
Speaker 1: also communicate your decision to the company, tell them why

384
00:21:22,840 --> 00:21:25,800
Speaker 1: you are or are not buying a product. And there's

385
00:21:25,880 --> 00:21:29,880
Speaker 1: also the Bipartisan app, which is a very clever name

386
00:21:30,080 --> 00:21:34,560
Speaker 1: buy partisan um that also lets you scan a products

387
00:21:34,600 --> 00:21:36,800
Speaker 1: bar code, and in this case you can see the

388
00:21:36,800 --> 00:21:42,160
Speaker 1: political contributions of the company, CEO, board of directors, um

389
00:21:42,200 --> 00:21:45,600
Speaker 1: even their employees. So it seems like never before have

390
00:21:45,880 --> 00:21:50,640
Speaker 1: we had the intense level of transparency that allows us

391
00:21:50,680 --> 00:21:54,840
Speaker 1: to sort of get all this information about politics and

392
00:21:54,840 --> 00:21:57,200
Speaker 1: and sort of these divisive issues that we've talked about

393
00:21:57,240 --> 00:22:00,280
Speaker 1: before making a purchasing decision. I mean, how does that

394
00:22:00,520 --> 00:22:02,960
Speaker 1: play into all of this. It's really hard to find

395
00:22:03,240 --> 00:22:06,600
Speaker 1: an issue that's not politicized, and there are a lot

396
00:22:06,600 --> 00:22:11,000
Speaker 1: more opportunities now. Well, yes, so the opportunities is one.

397
00:22:11,200 --> 00:22:14,120
Speaker 1: The second thing is that the instance that you mentioned,

398
00:22:14,160 --> 00:22:16,560
Speaker 1: the Chick fil a instance that started this whole thing, right,

399
00:22:16,600 --> 00:22:19,400
Speaker 1: that that happened through the media. People for the most part,

400
00:22:19,440 --> 00:22:21,680
Speaker 1: became aware of it through the media. So as we've

401
00:22:21,720 --> 00:22:25,600
Speaker 1: been talking here, we've been talking mainly about consumers reacting

402
00:22:25,640 --> 00:22:28,359
Speaker 1: to things that they see in the media. What these

403
00:22:28,400 --> 00:22:32,159
Speaker 1: applications are doing is they're they're actually allowing consumers to

404
00:22:32,200 --> 00:22:35,320
Speaker 1: initiate this process right on a one on one basis,

405
00:22:35,320 --> 00:22:38,400
Speaker 1: with any brand that they want um. And so, yeah,

406
00:22:38,480 --> 00:22:41,280
Speaker 1: we think that the scope of the implications for the

407
00:22:41,320 --> 00:22:45,080
Speaker 1: results that we found this bi valent right, small positive,

408
00:22:45,080 --> 00:22:47,800
Speaker 1: big negative effect. We think that the scope is just

409
00:22:47,880 --> 00:22:51,280
Speaker 1: made substantially larger by the technology and the access that

410
00:22:51,320 --> 00:22:53,960
Speaker 1: people have to this information. That it doesn't have to

411
00:22:54,000 --> 00:22:55,719
Speaker 1: be anything that's in the news at all, or that

412
00:22:56,040 --> 00:22:59,280
Speaker 1: or that anybody else really cares about. If I care

413
00:22:59,280 --> 00:23:03,040
Speaker 1: about it, I can bring my concerns to bear on

414
00:23:03,200 --> 00:23:07,040
Speaker 1: this particular decision and my attitudes towards this particular brand.

415
00:23:07,560 --> 00:23:10,040
Speaker 1: With the aid of these technologies, yeah, we think, we

416
00:23:10,119 --> 00:23:14,560
Speaker 1: think that that the general phenomenon will translate to situations

417
00:23:14,560 --> 00:23:18,040
Speaker 1: that have nothing to do with with any media broadcasting

418
00:23:18,119 --> 00:23:21,760
Speaker 1: anything about the stance that's adopted. Thank you guys so much,

419
00:23:21,840 --> 00:23:24,080
Speaker 1: Kurt and Chris for joining us, and thanks to you

420
00:23:24,119 --> 00:23:27,080
Speaker 1: all for listening to Bloomberg Benchmark. We will be back

421
00:23:27,119 --> 00:23:29,119
Speaker 1: next week and until then you can find us on

422
00:23:29,160 --> 00:23:31,919
Speaker 1: the Bloomberg terminal and Bloomberg dot com, as well as

423
00:23:31,920 --> 00:23:35,679
Speaker 1: on iTunes, Pocketcast, Stitchard, and a few other places. And

424
00:23:35,760 --> 00:23:38,000
Speaker 1: while you're there, please take a minute to rate and

425
00:23:38,040 --> 00:23:40,560
Speaker 1: review the show so more listeners can find us, and

426
00:23:40,880 --> 00:23:42,960
Speaker 1: please let us know what you thought of the show.

427
00:23:43,240 --> 00:23:45,560
Speaker 1: You can talk to and follow me on Twitter at

428
00:23:45,840 --> 00:23:50,000
Speaker 1: Tori Stillwell, and you can look up our guests research

429
00:23:50,119 --> 00:23:54,119
Speaker 1: at Consumer Research dot Georgetown dot du if you're interested

430
00:23:54,160 --> 00:23:56,680
Speaker 1: in learning more, and if you can think of any

431
00:23:56,720 --> 00:23:59,440
Speaker 1: examples of brands taking political stances that we miss, please

432
00:23:59,480 --> 00:24:01,520
Speaker 1: feel free to let us know and we'll see you

433
00:24:01,600 --> 00:24:08,239
Speaker 1: next week. M m hm