How Bezos built his data machine

The next challenge was to decide what to sell beyond books.

They picked CDs and DVDs. Over the years, electronics, toys and clothing followed, as did overseas expansion.

And all this time, Amazon was building a battalion of data-mining experts.

Artificial intelligence expert Andreas Weigend was one of the first.

Before joining, he had published more than 100 scientific articles, co-founded one of the first music recommendation systems, and worked on an application to analyse online trades in real-time.

Amazon made him its first chief scientist.

“I had weekly meetings… with people, whoever wanted to stop by, where we just looked at clickstream histories in the evening, with beer and pizza, to wrap our brains around why would people actually do this, why on Earth would they click here,” he remembers.

Clickstreams are the digital breadcrumb trail which Amazon follows to see which sites users come from, how they travel through its own pages and where they go to next.

(Amazon’s response to my data request didn’t contain my own clickstream history, although the firm has provided such records to others in the past. A spokesman could not explain why.)

A savvy ad-tech specialist was among Weigend’s recruits.

David Selinger quickly climbed the ranks to lead the new Customer Behavior Research unit.

Bezos and Selenger sitting on Weigend's bed: "I don’t know how that picture happened, I know that picture is in my bedroom in my bed at my home and nobody really is clear how Jeff Bezos got in my bed"

Bezos and Selenger sitting on Weigend's bed: "I don’t know how that picture happened, I know that picture is in my bedroom in my bed at my home and nobody really is clear how Jeff Bezos got in my bed"

“Our job was to build a customer-based dataset and then prove that there were opportunities, kind of fissures of gold,” Selinger says.

Once a week they too delved into individuals' behaviour.

“We had to make it actionable,” Selinger continues.

“So to do that, we would project on the wall this view [of a] single customer and try to understand who she was.

“What was unique about the internet and Amazon at the time was that we were able to take each individual customer and then change the experience.”

Their work gave rise to personalisation and targeted recommendations, such as a customised front page for each user, and tailored emails in their inboxes.

“I was shocked to see how predictable people are,” says Dr Weigend.

“We didn’t think of it as exploiting, we thought about helping people make better decisions.”

Weigend and Selinger moved on, but Amazon continued to hire talent to find innovative ways to turn data into dollars.

Among them was ex-banker James Thomson.

“I had worked for other companies where there was a so-called data warehouse,” says the former Amazon Services business chief.

“But Amazon’s is literally the largest.

“Amazon knows not just your preferences but the million other preferences of customers that look a lot like you.

“So Amazon can basically anticipate what you’re going to need next - size up the inventory of which brands they are going to need in three to six months when you are ready to ‘unexpectedly’ buy those products.”

It used to be exotic to talk of “big data”. These days the buzz phrase is “artificial intelligence”.

However you frame it, Amazon leads the way in finding patterns in the noise of customer behaviour.

But while this fuels its profits, it has also prompted concerns about the elevated positions Bezos and his deputies enjoy as a result.

“We find ourselves being shot backward into a kind of feudal pattern where it was an elite, a priesthood, that had all the knowledge and all the rest of the people just kind of groped around in the dark,” says Shoshana Zuboff, a Harvard professor and author of The Age of Surveillance Capitalism.

“This narrow priesthood of data scientists and their bosses sits at the pinnacle of a new society.

“They are not beholden to us as customers, because in the surveillance capital model we are not customers, we are sources of raw material.”

from Hacker News https://ift.tt/2SWuiFi