1
00:00:00,000 --> 00:00:02,000
You

2
00:00:31,000 --> 00:00:47,000
As the general election campaign begins the candidates for governor looked to define one another that includes Tom Tiffany attacking David Crowley on data centers. This is inside Wisconsin politics.

3
00:00:48,000 --> 00:00:56,000
I'm Sean Johnson here with my colleagues Anya Van Wechtendank and Zach Schultz.

4
00:00:56,000 --> 00:00:57,000
Hello.

5
00:00:57,000 --> 00:01:16,000
So it feels like ads are just always running in Wisconsin, swing state Wisconsin, where every election is so important. But Anya, I wonder if there is an argument to be made that the ads that are running right now are potentially very critical to the outcome of a race like the one we have for governor.

6
00:01:16,000 --> 00:01:28,000
I mean, right. This is sort of the pivot point. We are going from primary to general and especially in this particular instance where we had such a kind of crazy democratic primary. There's now two very clear candidates that are going to be on the ballot.

7
00:01:28,000 --> 00:01:35,000
And so they are trying to define themselves and they're trying to define one another. And so right now I think with all of that momentum kind of coming out of the primary week.

8
00:01:35,000 --> 00:01:45,000
Now is the time that they have to turn to the entire state, not just their party base and say this is who I am. But more importantly, perhaps this is who that other guy is. And here's why you don't want to vote for him.

9
00:01:45,000 --> 00:01:55,000
Do you want to define or be defined, Zach? And it strikes me that these two candidates in particular are maybe especially vulnerable to that because they're not that well known.

10
00:01:55,000 --> 00:02:02,000
They're not that well statewide. And this is really their opportunity to decide on what territory the election will be fought.

11
00:02:02,000 --> 00:02:14,000
Will it be about, for Tom Tiffany, his greatest fears, this is an election on his connections to Donald Trump and the national economy and affordability or abortion or any of those topics that he really doesn't want to talk about.

12
00:02:14,000 --> 00:02:23,000
And probably it's absolutely, he doesn't want to have to talk about crime rates or doesn't want to talk about to some of the executive decisions he's made in Milwaukee or some of the history of that county.

13
00:02:23,000 --> 00:02:30,000
And especially where he is on data centers. This is one of those pivot points that Tom Tiffany is trying to say, let's put the race in that category.

14
00:02:30,000 --> 00:02:39,000
Because I think that's an area that people want to talk about. And I think I can make it more favorable to myself, especially in the sense that he's not well defined in that area.

15
00:02:39,000 --> 00:02:46,000
Just as we were talking about, he's trying to create the definition of where does Tom Tiffany stand on data centers because it's not super clear.

16
00:02:46,000 --> 00:02:55,000
Yeah. I mean, with the caveat that we don't know how it's going to work and neither does the Tiffany campaign, as far as wedge issues go, it's fairly clever.

17
00:02:55,000 --> 00:03:01,000
This is a relatively new issue to politics. So it's not defined in the way that some other issues are.

18
00:03:01,000 --> 00:03:04,000
You don't know exactly where the interest groups stand with the parties.

19
00:03:04,000 --> 00:03:12,000
So Anya, how is that playing out in this attack from Tom Tiffany? How is he going after David Crowley trying to frame him?

20
00:03:12,000 --> 00:03:20,000
Yeah, I mean, he's trying to use his initials against him. He's calling him data center David Crowley, DC, DC, as a way of trying to kind of tie him to this.

21
00:03:20,000 --> 00:03:30,000
And the way he's doing it is in a slightly convoluted way by saying that because David Crowley hasn't pledged to kind of roll back these specific tax incentives that that makes him more pro data center.

22
00:03:30,000 --> 00:03:38,000
David Crowley is also kind of trying to split the difference a little bit and say, well, I support local control, so communities that don't want it don't have to have it.

23
00:03:38,000 --> 00:03:43,000
I would want, you know, sort of tight controls and regulations and this kind of thing.

24
00:03:43,000 --> 00:03:52,000
But the other kind of interesting piece of how Tom Tiffany is handling this, so I went yesterday to an endorsement announcement for these environmental groups that are now backing David Crowley.

25
00:03:52,000 --> 00:03:56,000
And of course, environmental concerns are very tied up in people's concerns over data centers.

26
00:03:56,000 --> 00:04:10,000
And part of the way that Tom Tiffany is now framing it is that data centers are taking away farmland and also because there's a push from Democrats to have a sustainable energy be sort of the backbone of data centers.

27
00:04:10,000 --> 00:04:18,000
He's also now kind of using it as a one, two, three punch of they're trying to take farmland, not just to create data centers, but also to create wind farms and solar farms.

28
00:04:18,000 --> 00:04:25,000
And so he can kind of package it together and all these things that will speak to Republican voters, Democrats obviously like solar, like wind farms.

29
00:04:25,000 --> 00:04:29,000
And so they'll have more of their work cut out for them to kind of distinguish those issues.

30
00:04:29,000 --> 00:04:33,000
Yeah, Zach, I was just seeing some social media appearances from Tom Tiffany.

31
00:04:33,000 --> 00:04:38,000
He was at an event and he's kind of framing it as data centers versus farmland.

32
00:04:38,000 --> 00:04:42,000
It's maybe like a pretty transparent appeal to rural voters in that instance.

33
00:04:42,000 --> 00:04:47,000
It's doing so many things at the same time because it is about his base and rural farmland.

34
00:04:47,000 --> 00:05:01,000
One of his earliest ads months ago talked about how prevent foreign countries from coming in and buying up our farmland, which is an issue that does concern people that are worried about the rising cost of just trying to rent out a field to put crops in the ground.

35
00:05:01,000 --> 00:05:06,000
As we've seen with all the international tariffs affecting soybean and corn farmers, they're looking for someone to blame.

36
00:05:06,000 --> 00:05:10,000
And if some of the cognitive dissonance with them is they don't want to blame Donald Trump.

37
00:05:10,000 --> 00:05:13,000
I've interviewed them and they don't really want to blame him and his decision.

38
00:05:13,000 --> 00:05:16,000
So if they, Tom Tiffany says, well, it's not his fault.

39
00:05:16,000 --> 00:05:17,000
It's over here.

40
00:05:17,000 --> 00:05:19,000
This is who you blame for your rising costs.

41
00:05:19,000 --> 00:05:24,000
Well, they're more than happy to follow along if they're in that inclination to begin with.

42
00:05:24,000 --> 00:05:25,000
So it's definitely a way to do that.

43
00:05:25,000 --> 00:05:34,000
But what's another element that's fascinating is he's really trying to split off those Hong voters from David Crowley and split the left.

44
00:05:34,000 --> 00:05:39,000
Because we've seen elections where the far left and progressive left have sat out.

45
00:05:39,000 --> 00:05:43,000
Maybe not in huge numbers, but enough numbers were potentially it does swing an election.

46
00:05:43,000 --> 00:05:44,000
We saw that with Hillary Clinton.

47
00:05:44,000 --> 00:05:46,000
We saw that with Kamala Harris.

48
00:05:46,000 --> 00:05:49,000
And they're trying to repeat that pattern with David Crowley.

49
00:05:49,000 --> 00:05:58,000
If they can paint him as more moderate, more corporate and less true far left, then some of those voters may go third party or just set out together.

50
00:05:58,000 --> 00:06:03,000
And that's one of the concerns is he has to watch his flank, even though he won by being in the center.

51
00:06:03,000 --> 00:06:13,000
Certainly an open question for me, especially because you at least get the impression that a lot of Hong voters are maybe not a politics first kind of voter.

52
00:06:13,000 --> 00:06:18,000
They came to her because she spoke to them in different ways, more of a movement candidate.

53
00:06:18,000 --> 00:06:23,000
She would not want to identify with Donald Trump, but a movement candidate in that way.

54
00:06:23,000 --> 00:06:26,000
You get different people into the political arena.

55
00:06:26,000 --> 00:06:34,000
And one question that I think some of them had during the primary was, why don't more Democrats just say what Francesca Hong is saying?

56
00:06:34,000 --> 00:06:36,000
We're going to have more Torrey on data centers.

57
00:06:36,000 --> 00:06:37,000
I like the sounds of that.

58
00:06:37,000 --> 00:06:41,000
Why wouldn't David Crowley just say, hey, let's put the brakes on these.

59
00:06:41,000 --> 00:06:45,000
And this data center issue is all taking care of for me politically.

60
00:06:45,000 --> 00:06:48,000
Well, politically speaking, data centers are not popular.

61
00:06:48,000 --> 00:06:52,000
The vast majority of voters, Democrats and Republicans don't support data centers.

62
00:06:52,000 --> 00:06:55,000
They certainly don't support them sort of coming into their own communities.

63
00:06:55,000 --> 00:07:02,000
But there is a real kind of question around the types of jobs that they can bring in, the kind of economic development possibilities there.

64
00:07:02,000 --> 00:07:17,000
And so I think as a politician, you don't necessarily want to say, categorically, I will not support a thing that could be a driver of economic growth, especially in some of these kind of hard hit places in Wisconsin that are kind of hurting for economic opportunities.

65
00:07:17,000 --> 00:07:27,000
One other piece of this too is that a lot of the data center, a lot of the unions that back David Crowley are involved in data center construction.

66
00:07:27,000 --> 00:07:35,000
And so one of the things that he has said is that, again, if a local community wants a data center, one of the things that he would want to see is that it has to be union built.

67
00:07:35,000 --> 00:07:37,000
That gets you union support.

68
00:07:37,000 --> 00:07:42,000
And unions are a pretty big part of how the Democratic Party defines itself as being a party of the unions.

69
00:07:42,000 --> 00:07:47,000
And unions are a pretty big part of how Republicans have started to kind of make huge inroads with working people.

70
00:07:47,000 --> 00:07:51,000
So the union question, I think, is an untapped and unanswered one so far.

71
00:07:51,000 --> 00:08:01,000
And it seems like he's also raised sort of just the practical arguments during the primary campaign that, look, putting a moratorium on these things is not going to change the ones that are already in the works.

72
00:08:01,000 --> 00:08:08,000
That there's a lot of data centers that are happening or in development now that a moratorium just won't solve.

73
00:08:08,000 --> 00:08:16,000
So how are we seeing David Crowley and his allies, I guess you'd say, go after Tom Tiffany in this early stage.

74
00:08:16,000 --> 00:08:21,000
Or how is he presenting himself as a candidate for governor on TV airwaves?

75
00:08:21,000 --> 00:08:25,000
Well, Tom Tiffany is splitting the baby. He's doing a little bit of both.

76
00:08:25,000 --> 00:08:31,000
He's still continuing his I'm and every man who thinks of your rural farmland and your local schools.

77
00:08:31,000 --> 00:08:34,000
He's still running some of those positive ads to try and define himself.

78
00:08:34,000 --> 00:08:43,000
That was one of his goals and one of the freedoms he had of not having a primary is he could spend millions of dollars trying to create a brand for himself as a Wisconsin guy.

79
00:08:43,000 --> 00:08:50,000
Because his brand as a DC congressman is frankly toxic in the national political environment round.

80
00:08:50,000 --> 00:08:54,000
No one wants to say, I'm deeply connected to Donald Trump in Washington, DC.

81
00:08:54,000 --> 00:08:57,000
No one from either party really likes that at this very moment.

82
00:08:57,000 --> 00:09:00,000
So he has to build a brand of being from Wisconsin.

83
00:09:00,000 --> 00:09:03,000
And he's got enough roots to be able to do it. And he's got the support to do it.

84
00:09:03,000 --> 00:09:09,000
And he's got the money to do it. And at the same time, he's starting to run his negative ads going after David Crowley in all these areas.

85
00:09:09,000 --> 00:09:20,000
Crowley on the flip side is and his allies we've seen from the Democratic Governors Association are doing everything we expected to have happen, which is linking Tiffany to Trump and international and national politics.

86
00:09:20,000 --> 00:09:26,000
Because that is their route right now is to try and connect those dots for voters who may not understand that.

87
00:09:27,000 --> 00:09:30,000
Because that is not a winning formula for Tom Tiffany going into the fall.

88
00:09:30,000 --> 00:09:32,000
Voters are thinking of those two together.

89
00:09:32,000 --> 00:09:36,000
And we are now seeing it was more than a week after the primary.

90
00:09:36,000 --> 00:09:39,000
David Crowley running his first ad where it's kind of biographical.

91
00:09:39,000 --> 00:09:49,000
The Democratic Governors Association ads were out right away after the primary and kind of seemed to fill that crucial period when you want to be grabbing people's attention.

92
00:09:50,000 --> 00:09:57,000
What does it take for one side to win this definition war on you and Zach?

93
00:09:57,000 --> 00:10:01,000
I mean, it's kind of an open question, but maybe it's a simple answer.

94
00:10:01,000 --> 00:10:06,000
I actually, well, I think it's sort of a simple answer in that the question is like nobody knows.

95
00:10:06,000 --> 00:10:07,000
Sure.

96
00:10:07,000 --> 00:10:18,000
Every sort of, you know, political advertising expert I've ever spoken to has said, you know, nobody knows why people choose Colgate over crust or crust over Colgate, but people spend billions of dollars to make sure that you pick one of those.

97
00:10:18,000 --> 00:10:20,000
And it's sort of the same with when you're voting.

98
00:10:20,000 --> 00:10:23,000
And so I think, you know, we're seeing the negative ads.

99
00:10:23,000 --> 00:10:24,000
We're seeing the positive ads.

100
00:10:24,000 --> 00:10:43,000
Like, we're seeing just kind of a lot of different types of messaging get thrown out there because what resonates with like a young, annoyed, you know, Hong voter who isn't quite sure about Crowley isn't going to be the same thing that resonates such as sort of like your moderate person who hasn't really been paying attention maybe didn't vote in the primary, but it's going to vote in the general.

101
00:10:43,000 --> 00:10:51,000
And in any election where the difference might be 20,000 votes as we often see in these general elections, you kind of need to get a little bit of each of those types of people.

102
00:10:51,000 --> 00:10:56,000
So Sean, we've seen throughout history that there's a phrase that this time of year talks about you.

103
00:10:56,000 --> 00:10:59,000
You can't win the election now, but you can lose it.

104
00:10:59,000 --> 00:11:06,000
So in your mind, what is the losing move from either one of these candidates of what could they do to really put themselves in a hole going into the fall?

105
00:11:06,000 --> 00:11:09,000
You know, one way would it do it would just be to disappear.

106
00:11:09,000 --> 00:11:19,000
You know, if David Crowley had no money or his allies had no money and just been off the air for a couple of weeks, that's dangerous territory.

107
00:11:19,000 --> 00:11:23,000
You know, you don't have somebody to answer the Tiffany attacks.

108
00:11:23,000 --> 00:11:25,000
You get in real trouble that way.

109
00:11:25,000 --> 00:11:29,000
And so I think the one thing you do is you just keep hitting those ads.

110
00:11:29,000 --> 00:11:34,000
The Colgate and Crest ads as she would characterize them.

111
00:11:34,000 --> 00:11:36,000
So that's one thing that we've seen from them.

112
00:11:36,000 --> 00:11:48,000
I think for Tiffany, it's also though kind of a critical period because when the thought was this was going to be a Tiffany versus Hong race, which was conventional wisdom, you know, a couple of weeks ago.

113
00:11:48,000 --> 00:11:52,000
You had Republican donors around the country saying, sign me up.

114
00:11:52,000 --> 00:11:54,000
I want to put money into that race.

115
00:11:54,000 --> 00:11:56,000
I want to fight back Democratic socialism.

116
00:11:56,000 --> 00:12:02,000
And I want a potential win in a swing state in a year when Republicans could have losses all over the place.

117
00:12:02,000 --> 00:12:07,000
I think the conventional wisdom right now is still that this is Wisconsin.

118
00:12:07,000 --> 00:12:09,000
Everything's 50-50 here.

119
00:12:09,000 --> 00:12:10,000
It's a race for governor.

120
00:12:10,000 --> 00:12:13,000
And so, yeah, it's winnable for Tom Tiffany.

121
00:12:13,000 --> 00:12:21,000
But he needs to maintain that perception that he can win this race because once that perception goes the way the money is going to go with it.

122
00:12:22,000 --> 00:12:24,000
I got a more important question.

123
00:12:24,000 --> 00:12:27,000
What do we think about the way these ads look?

124
00:12:27,000 --> 00:12:32,000
How are the candidates portrayed in them when they talk about data center David Crowley?

125
00:12:32,000 --> 00:12:36,000
You know, the visuals are very striking in that ad.

126
00:12:36,000 --> 00:12:37,000
Yeah.

127
00:12:37,000 --> 00:12:50,000
And I mean, especially compared to, again, those sort of pro-Tom Tiffany ads, which are all like sunshine and backyards and pancakes and his latest kind of, you know, defining himself ad is him saying, like, I'll teach your kids to read.

128
00:12:50,000 --> 00:12:55,000
And I'll put money in your pocket and a third promise that was quite pissy and I am not remembering right now.

129
00:12:55,000 --> 00:13:00,000
As compared to the kind of doom and gloom of this person's going to come in and build data centers and steal your farm.

130
00:13:00,000 --> 00:13:03,000
And so it really is like these tonal differences.

131
00:13:03,000 --> 00:13:09,000
And as you kind of go between them, it really is like even just a color difference of sort of black and white versus technicolor.

132
00:13:09,000 --> 00:13:14,000
Yeah, I mean, the Crowley thing reminds me, okay, Anya, this is a very old reference.

133
00:13:14,000 --> 00:13:31,000
But Max Headroom, the, you know, kind of apocalyptic doom and gloom vision of the 1980s of our future where they got kind of this like kind of digital background and then there's David Crowley talking up on stage.

134
00:13:31,000 --> 00:13:33,000
He was at a journal center forum.

135
00:13:33,000 --> 00:13:36,000
You know, they obviously doctored the background to make it look a little techno.

136
00:13:36,000 --> 00:13:40,000
Zach, you remember that obviously you had the same exact thought when you watched that.

137
00:13:40,000 --> 00:13:42,000
I think of Max Headroom all the time.

138
00:13:42,000 --> 00:13:44,000
He would be a podcaster today.

139
00:13:44,000 --> 00:13:45,000
He won't be a television anchor.

140
00:13:45,000 --> 00:13:47,000
I think he was new medium.

141
00:13:47,000 --> 00:13:48,000
Sure.

142
00:13:48,000 --> 00:13:51,000
Yeah, we just hadn't figured out where his role was in the world.

143
00:13:51,000 --> 00:13:53,000
Yeah, that's a Google reference for all the kids.

144
00:13:53,000 --> 00:13:54,000
Google it.

145
00:13:54,000 --> 00:13:55,000
Max Headroom.

146
00:13:55,000 --> 00:13:56,000
Yeah.

147
00:13:56,000 --> 00:13:57,000
I will also Google that.

148
00:13:57,000 --> 00:13:58,000
Yeah.

149
00:13:58,000 --> 00:14:00,000
Old man memories here.

150
00:14:00,000 --> 00:14:04,000
The Democratic ads attacking Crowley, though, to me, it's funny.

151
00:14:04,000 --> 00:14:07,000
They have to portray the Tom Tiffany that you know.

152
00:14:07,000 --> 00:14:26,000
And so the Tom Tiffany that they put up on the screen is the Tom Tiffany from these ads where he's like, you know, I'm Mr. Wisconsin and I'm having pancakes and, you know, attending a dam, you name it.

153
00:14:26,000 --> 00:14:35,000
One of them, they do have his bolo tie look, which is interesting because he brought that out early in the campaign to get a little of the rural roots element.

154
00:14:35,000 --> 00:14:38,000
But then he went away from it as his ads got more polished.

155
00:14:38,000 --> 00:14:45,000
But one of those attack ads has Tom in the bolo tie, which is an interesting look because what is it trying to say?

156
00:14:45,000 --> 00:14:47,000
I mean, is that Wisconsin look?

157
00:14:47,000 --> 00:14:48,000
Is that a rural look?

158
00:14:48,000 --> 00:14:49,000
Is that a rustic look?

159
00:14:49,000 --> 00:14:52,000
And it's just when they pick those things, it's fun to pick them apart.

160
00:14:52,000 --> 00:14:55,000
If you're really bored and you like to watch campaign commercials.

161
00:14:55,000 --> 00:14:56,000
I do.

162
00:14:56,000 --> 00:14:57,000
Who doesn't?

163
00:14:57,000 --> 00:14:58,000
Come on.

164
00:14:58,000 --> 00:15:04,000
Then I think that is one thing to decide is how do they decide what makes this candidate look most ridiculous and not appealing to the average voter?

165
00:15:04,000 --> 00:15:06,000
Versus how do they portray themselves?

166
00:15:06,000 --> 00:15:08,000
What kind of lighting and how are they dressed?

167
00:15:08,000 --> 00:15:11,000
And I think Tiffany's wearing a car heart jacket in one of them.

168
00:15:11,000 --> 00:15:13,000
He's, of course, he's got his rural connections.

169
00:15:13,000 --> 00:15:18,000
Well, and I think that actually raises an interesting point, which is that normal people don't watch these political ads.

170
00:15:18,000 --> 00:15:24,000
And actually what happens is like one pops up and people change the channel or they try to get out of that YouTube page or whatever.

171
00:15:24,000 --> 00:15:28,000
And so you need kind of all of those frames, all of those images to say something.

172
00:15:28,000 --> 00:15:33,000
So another thing that you see a lot in these Tom Tiffany attack ads is him next to Donald Trump.

173
00:15:33,000 --> 00:15:36,000
Because like, that's the only thing that you see for one split second.

174
00:15:36,000 --> 00:15:38,000
It's putting those two people together in your mind.

175
00:15:38,000 --> 00:15:40,000
And that is a win for Democrats.

176
00:15:40,000 --> 00:15:41,000
Yeah.

177
00:15:41,000 --> 00:15:42,000
Yeah.

178
00:15:42,000 --> 00:15:43,000
That's unmistakable.

179
00:15:43,000 --> 00:15:46,000
They always try to try the extreme, um, MAGA, Tom Tiffany, Donald Trump.

180
00:15:46,000 --> 00:15:49,000
Uh, those are, that's like low hanging fruit for Democrats this time.

181
00:15:49,000 --> 00:15:59,000
And as clever as the data center ads are for Tom Tiffany, it might be the Democrats just need to hit those go to points over and over again in this midterm election.

182
00:16:00,000 --> 00:16:02,000
I have another follow up question for both of you.

183
00:16:02,000 --> 00:16:07,000
And that is how long will Francesca Hong continue to define this election when she's not in it?

184
00:16:07,000 --> 00:16:09,000
She set the standard in the Democratic primary.

185
00:16:09,000 --> 00:16:10,000
She was the conversation.

186
00:16:10,000 --> 00:16:14,000
And now it's her position on data centers that is still defining this race.

187
00:16:14,000 --> 00:16:18,000
So how much longer will we see her loom over all of this?

188
00:16:18,000 --> 00:16:24,000
Well, and, and I think probably till November, she's out there campaigning for David Crowley now, right?

189
00:16:24,000 --> 00:16:27,000
I mean, she's not just being a silent partner here.

190
00:16:27,000 --> 00:16:30,000
She's out there saying, I support David Crowley.

191
00:16:30,000 --> 00:16:31,000
You should too.

192
00:16:31,000 --> 00:16:35,000
And some of her supporters don't actually care for that either.

193
00:16:35,000 --> 00:16:38,000
You know, they're kind of going along reluctantly or not at all.

194
00:16:38,000 --> 00:16:41,000
So I mean, I think it's going to be something that's going to be going on for a while.

195
00:16:41,000 --> 00:16:42,000
Yeah.

196
00:16:42,000 --> 00:16:55,000
And I think the Democrats kind of don't win if she does not like fully kind of throw her weight behind this because if you lose the nomination by 3,500 votes as she did, like that is not a clear and decisive mandate for David Crowley.

197
00:16:55,000 --> 00:17:07,000
And particularly on this issue of data centers, which I think there is no question that she defined that question that a huge part of why she did kind of stand out was because she took the most stand out stance on that issue.

198
00:17:07,000 --> 00:17:23,000
So if she wants to kind of if Democrats want her voters to come along, it's going to need to both revolver and sort of that issue and also have her as the movement candidate, not just kind of the issues that she stood behind, but her as this very compelling figure to the 300 some odd thousand

199
00:17:23,000 --> 00:17:27,000
voted for her to kind of get on board and certainly not stay home on election day.

200
00:17:27,000 --> 00:17:37,000
Well, and I think you have to remember that those voters that did stay with her did that in the face of all the pressure in the world from ads, their own party members, a lot of their neighbors saying, are you sure about this vote?

201
00:17:37,000 --> 00:17:38,000
And they stuck with her.

202
00:17:38,000 --> 00:17:40,000
So they weren't casual hung voters.

203
00:17:40,000 --> 00:17:51,000
So where she goes through the fall could decide, well, how many of those do tag along with her and say, all right, believe in the mission, she said from the beginning, she was on board to defeat Tom Tiffany.

204
00:17:51,000 --> 00:17:58,000
And she will need to be a crucial player in this all the way through, which is fascinating to see how much impact she's had in this whole process.

205
00:17:58,000 --> 00:18:03,000
I'll tell you one other wild card that we don't know right now as we speak here today.

206
00:18:03,000 --> 00:18:04,000
We have the ads.

207
00:18:04,000 --> 00:18:05,000
We've seen them.

208
00:18:05,000 --> 00:18:10,000
We have what they say they're going to do in terms of how big the reach of the ads is are.

209
00:18:10,000 --> 00:18:14,000
We don't know how much they're going to spend on these ads.

210
00:18:14,000 --> 00:18:23,000
And sometimes just repetition and bombarding the state with money is what you need in an election like this one for governor.

211
00:18:23,000 --> 00:18:30,000
I think that will be a clue that we'll see over the coming weeks, who's really putting money in this race and who's not.

212
00:18:30,000 --> 00:18:32,000
That's all the time we have for today.

213
00:18:32,000 --> 00:18:35,000
Our colleague, Rich Kramer.

214
00:18:35,000 --> 00:18:37,000
That's all the time we have for today.

215
00:18:37,000 --> 00:18:39,000
Our colleague, Rich Kramer, will be back next week.

216
00:18:39,000 --> 00:18:41,000
This has been Inside Wisconsin Politics.

217
00:18:41,000 --> 00:18:47,000
Be sure to follow us on PBS Wisconsin.org, WPR.org, YouTube, or wherever you get your podcasts.

218
00:19:11,000 --> 00:19:16,000
Thank you.

