
Donald J. Trump’s $30M Testing Team - vdOlvWffCy
https://medium.com/@babyak/donald-j-trumps-30m-testing-team-e1a9d542039e#.lex06vf4n
======
tokenizer
Interesting stuff, I checked the website out and was impressed by the design.

I'm not too familiar with analytics and marketing, but I did like how the
contribution and web store mechanics were set up.

That all said, I'm curious how much revenue you can attribute to optimization
versus just general interest when it came to people wanting to donate, or buy
a MAGA hat.

What I mean is, how much money could have been generated, without utilizing
optimization tools such as the ones you used from Adobe, and by adding
"Official" to everything.

Not trying to demoralize them, I'm just curious if they could separate that
revenue, and point to a portion of it that directly came from optimization.

~~~
kordless
> Not trying to demoralize them

My observation indicates nobody is saying otherwise, which would normally beg
the question "why are you saying this?" if someone didn't know any better. In
this case, however, I think why you are saying it is actually based on inverse
trust hacking.

Personally, I don't care about hearing about how using anti-trust got another
anti-trust implementation success. Anti-trust doesn't scale, and the gains to
be had by anti-trust imply suffering for many and only a small chance of
reduced suffering for the wielder of it.

HN: This story represents blame and anti-trust. Report it least it spread
further.

------
btown
It's easy to underestimate the level of data-driven thinking that the Trump
campaign brought to bear. Some important reading for those interested:

[https://motherboard.vice.com/en_us/article/how-our-likes-
hel...](https://motherboard.vice.com/en_us/article/how-our-likes-helped-trump-
win)

[https://www.bloomberg.com/news/articles/2016-10-27/inside-
th...](https://www.bloomberg.com/news/articles/2016-10-27/inside-the-trump-
bunker-with-12-days-to-go)

> First, Cambridge Analytica [a company that was founded in Steve Bannon's
> office and counts him as a board member] buys personal data from a range of
> different sources, like land registries, automotive data, shopping data,
> bonus cards, club memberships, what magazines you read, what churches you
> attend. Nix displays the logos of globally active data brokers like Acxiom
> and Experian—in the US, almost all personal data is for sale. For example,
> if you want to know where Jewish women live, you can simply buy this
> information, phone numbers included. Now Cambridge Analytica aggregates this
> data with the electoral rolls of the Republican party and online data and
> calculates a Big Five personality profile. Digital footprints suddenly
> become real people with fears, needs, interests, and residential
> addresses... Cambridge Analytica also uses, Nix told us, "surveys on social
> media" and Facebook data.

> The embedded Cambridge Analytica team, apparently only a dozen people,
> received $100,000 from Trump in July, $250,000 in August, and $5 million in
> September. According to Nix, the company earned over $15 million overall.
> (The company is incorporated in the US, where laws regarding the release of
> personal data are more lax than in European Union countries. Whereas
> European privacy laws require a person to "opt in" to a release of data,
> those in the US permit data to be released unless a user "opts out.")

> In the Miami district of Little Haiti, for instance, Trump’s campaign
> provided inhabitants with news about the failure of the Clinton Foundation
> following the earthquake in Haiti, in order to keep them from voting for
> Hillary Clinton. This was one of the goals: to keep potential Clinton voters
> (which include wavering left-wingers, African-Americans, and young women)
> away from the ballot box, to “suppress” their vote, as one senior campaign
> official told Bloomberg in the weeks before the election. These “dark
> posts”—sponsored news-feed-style ads in Facebook timelines that can only be
> seen by users with specific profiles—included videos aimed at African-
> Americans in which Hillary Clinton refers to black men as predators, for
> example.

(Though, with a grain of salt, it's hard to tell which ad campaigns were
optimized by CamAnalytica vs. other data scientists on the team:
[https://twitter.com/GaryCoby/status/825454953560936451](https://twitter.com/GaryCoby/status/825454953560936451)
... but the type of thinking is the same.)

Regardless of your political leanings, it's clear that the arms race in data
for politics has reached a new level. If a party (or niche therein), whose
views you fundamentally oppose, builds a data science team, are you morally
obligated to try to counteract their efforts by helping to build even better
targeting for the candidates and views you support? That statement, it would
seem, goes both ways.

~~~
ceejayoz
> Cambridge Analytica also uses, Nix told us, "surveys on social media" and
> Facebook data.

I've always suspected those "connect your Facebook to find your future
soulmate" things that are rampant were something along those lines.

