After working for Trump’s campaign, British data firm eyes n

Re: After working for Trump’s campaign, British data firm ey

Postby admin » Wed Mar 28, 2018 4:04 pm

Inside the Clinton Campaign's TV Data Strategy
by Kate Kaye
Published on February 02, 2017

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Cardboard cutouts of Barack Obama, Donald Trump and Hillary Clinton stand inside a store at Union Station in Washington, D.C., on Jan. 18. Credit: David Paul Morris/Bloomberg

Call it Monday morning quarterbacking or 20-20 hindsight: Political practitioners and technologists on the left still are grasping for clues about which Clinton campaign decisions might have contributed to President Donald Trump's win. Many wonder whether their own skills might have boosted her to a win in November. One of them is Carol Davidsen, a key developer of technology used for Barack Obama's groundbreaking 2012 TV ad system, which was known as The Optimizer. She laments the campaign's decision not to use a new ComScore TV analytics platform she helped build for 2016.

"It's frustrating when you build something that is available to both sides, and the side you personally support doesn't use it," said Ms. Davidsen.


The Clinton camp's decision not to work with the company, however, reflects the rapid changes that have taken place in the TV data world since 2012. Those changes enabled the campaign to build a system in-house that it says gave them a more refined and comprehensive view of the data than previously available. Among many questions surrounding the campaign, it's now fair to ask whether that decision was the right move.

According to people familiar with the Clinton campaign who spoke to Ad Age under condition of anonymity, the campaign built its own internal TV buying data system and assembled a collective of analytics, data and tech specialists it called its optimization team, people who worked directly with those making TV buying decisions. The technology they built ingested raw TV data from multiple sources. That approach was more cost-efficient, they said, and gave them greater control and transparency.

Before the primaries, the campaign evaluated TV data sources and platforms, and asked, "Is there a way to be closer to the data itself than in 2012?" said a Clinton campaign source.

TV Data Explosion

The Clinton camp got its TV data -- information that helped determine what key voter groups watch -- from a variety of sources. Providers that it could have tapped include TV data compilers such as FourthWall Media and pay-TV operators such as Tivo, Cox Communications and the collaboration between Dish and DirecTV/AT&T called D2.

"We've got the explosion of talent combined with increased availability of sources," said a political TV analytics consultant who was not affiliated with ComScore or the Clinton campaign. "Innovation is taking place at the nine- and 12-month level, not the four-year level," he said, noting that there are more companies providing TV data and services, and more data analysts who emerged from 2012 and now have advanced significantly in terms of programming language capabilities and skills with TV data tools.

"It tells you that the economics have changed fundamentally," the consultant said.

In other words, all signs point to even more dissemination of TV data, analytics technologies and practitioners in 2018.

The Clinton camp relied on one of its vendors to make its TV data purchases, so those expenditures do not appear in the campaign's Federal Election Commission reports. Though it's not clear which company or companies working with the campaign made the data buys, its television buying firm GMMB received $236 million from the Clinton campaign between August 2015 and October 2016 for media buys, consulting and ad production services, according to FEC reports. Digital ad firm Bully Pulpit Interactive took in $17 million between May 2015 and October 2016.

As the Clinton camp assembled its TV optimization technology and staff of data analysts, Ms. Davidsen, VP of political technology at Comscore, and her colleagues were working to finalize a platform that could be tailored for large political campaigns like a presidential race, something much more advanced than what she and the Obama team built in-house. The result was a robust, customizable TV data platform that incorporated household level data for set-top box TV ad targeting, according to Ms. Davidsen. But by the time the ComScore system was ready for primetime, around the summer of 2016, the Clinton camp was already too far ahead with their own solution.

Ms. Davidsen played a key role in developing what came to be known as the Optimizer for the Obama 2012 campaign; the TV ad planning and buying platform used TV viewing data to inform ad buys to reach targeted voter groups in cost-effective inventory such as niche cable TV. The system relied mainly on data from Rentrak, the company Ms. Davidsen joined in 2015 which was acquired later that year by Comscore. In 2012, the relationship between Rentrak and the Obama campaign was so secretive that the TV data firm codenamed the project Eeyore, after the forlorn donkey in Winnie-the-Pooh stories.

Political Campaign as Data Processor

While a platform like ComScore's recommends which programs are optimal for targeting specific voter groups, the Clinton camp wanted more transparency into the reasoning behind the recommendations, transparency that would come by gathering and analyzing the raw data itself. The information would show that a specific TV device ID -- which could be matched to the campaign's data on key voter targets -- was tuned to a particular channel at a given time. The campaign would need to match that data to other sources showing what actual program was on the air at that time. All that data would be combined to determine the optimal TV buys to reach desired voter groups.

But raw set-top box data is not pretty. Picture rows and rows and columns and columns of unstructured, non-standardized data clutter. Each data set would need to be scrubbed of extraneous information, and put in an organized format that could be read by the platform ingesting it.

"It was odd to me, the choice for a campaign to start becoming a set-top box processing company," said Ms. Davidsen, adding, "I don't believe raw viewership data can ethically only be made available to one side. You just hope the side you personally support uses that data more effectively."

Specialists in the Clinton campaign's analytics, data and tech teams were tasked with making sense of the data mess, processing it, studying and cleaning it, and creating the algorithms used to determine which programs were being viewed by the voter segments the campaign wanted to reach. The platform showed campaign results and incorporated that information back in, hence, optimizing.

While raw TV data is unwieldy, it has its benefits. Arguably, the Clinton campaign was able to be more flexible in how it viewed the data. So, rather than using a system that only told them the "what" to buy, the campaign developed a visualization tool that surfaced the "why," something one Clinton camp source called a big jump forward from past campaign cycles. This came in handy especially down the stretch when convincing decision makers that, for example, another $100,000 was needed to aim TV ads at particular voters in a key geographic area.

The visual interface featured tables and interactive graphs allowing the optimization team to view explanations for why certain TV buys were recommended, and exposing additional notes on what was not being purchased, to help the campaign identify potential buying options it was missing.

That's where the legitimacy of the data models and the voter scores -- the numbers reflecting the campaign's perception of voters and each voter segment, their likelihood to support Ms. Clinton, and their likelihood to go to the polls -- is of utmost importance. If the expectations of how voters felt about the candidate and how their attitudes morphed throughout the campaign were improperly calibrated, the data machine would continue to hum along, but the end product may not be an accurate representation of voter reality.

The Clinton camp was criticized after the election for not placing enough emphasis on advertising in states such as Wisconsin and Michigan, where President Trump won by slim margins -- in Michigan by only around 10,000 votes and Wisconsin by 22,000. However, while the TV optimization platform was used to determine what TV inventory to purchase to efficiently reach voter targets, the campaign used its polling and field operations data system to determine whether Ms. Clinton needed to invest more in a given state.

Podesta Emails and the High Cost of Data

Cambridge Analytica, one of many data firms that assisted in the Trump campaign, did use the ComScore system in 2016, though it's not clear whether it was employed for the Trump campaign. As reported in December by Ad Age, the majority of the Trump campaign's TV buys were informed by Deep Root Analytics, a Republican TV data firm contracted by the Republican National Committee.

Clinton campaign sources and others familiar with Comscore's pricing say the products the company was offering for 2016 were far more expensive than other approaches, and much more than similar offerings in 2012.

One of the communiques exposed in the hack of Clinton Campaign Chairman John Podesta's emails alludes to the campaign's thought process on TV analytics and pricing as far back as May 2015. Elan Kriegel, Clinton campaign director of analytics, wrote to Mr. Podesta and Campaign Manager Robby Mook at that time, noting that in the past he had worked with data from Dish showing what TV programs voter targets over-indexed on viewing. He added, "Right now we buy this data through a third party vendor (Rentrak), though the price they are quoting for 2016 is quite steep."

Ms. Davidsen said that ComScore negotiated on price and variations of the platform with the Clinton camp, which did eventually test it in the summer of 2016. The campaign decided against using ComScore after that.

Ms. Davidsen kept a close eye on the campaign's TV buys anyway. She said, based on the ComScore information she had access to, that the Clinton camp was under-delivering in TV when it came to reaching likely Democratic voters at standard frequency levels (typically 12 to 16 ads per week). And she feared that the campaign was too reliant on addressable advertising, which delivers ads only to specific voters, and because of its narrow targeting, can drastically limit the amount of times an ad will run.

Addressable TV advertising allowed the Clinton campaign to deliver specific ads to persuadable Hispanic or African-American voters, for example. However, campaign sources said addressable accounted for only around 4% of the overall media budget, and therefore made up a relatively small portion of the TV budget. In fact, they say that closer to the election they were investing more in national ad buys in order to ensure exposure to certain voters, sometimes at a lower cost. For example, the campaign may have made a national buy with TBS to ensure its ads showed up during "Full Frontal with Samantha Bee" -- appointment TV with some left-leaning voters.


The campaign sources also said they were more focused than during previous election cycles on communicating with voter audiences in a more holistic manner -- what corporate marketers would call omni-channel marketing. So, for instance, if certain voter groups were not watching TV much, the campaign would emphasize digital advertising, social media or direct mail to reach them.

The people familiar with the Clinton campaign said they were confident in the analytics platform that they built to inform their TV buying and targeting. However, for campaign observers and experts like Ms. Davidsen, there remain many unanswered questions regarding things like the validity of the voter data models it built and how the campaign selected which ad creative to deliver to which voters.

So, for now, just like the opaque data platform the Clinton camp aimed to avoid, those answers remain locked inside a proverbial black box.

Kate Kaye covers the data industry for Advertising Age and is the main contributor to the Ad Age DataWorks section. Before joining Ad Age in November 2012, Kate worked as a writer and reporter covering the digital marketing industry since 2000, focusing on beats including data-driven targeting, privacy, and government regulation. Kate helped cultivate the online political campaign beat, and in 2009 wrote "Campaign '08 A Turning Point for Digital Media," a book about the digital media efforts of the 2008 presidential campaigns. Before joining Ad Age, Kate was managing editor of ClickZ News, where she worked for nearly 7 years.
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Re: After working for Trump’s campaign, British data firm ey

Postby admin » Wed Mar 28, 2018 4:10 pm

How Trump defeated Clinton using analytics
Columnist Rob Enderle writes that by following the three rules of analytics Trump won the election.
by Rob Enderle
CIO
November 11, 2016 4:00 AM PT

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What was both fascinating and sad for me watching the election results on Tuesday was how badly the news services predicted the outcome. Virtually every one had predicted a Clinton victory, which likely contributed to her loss, most wanted her to win, and virtually every one was wrong. The analytics run by the Clinton camp largely seemed to drive her to an anti-Trump message and misspend what was a vastly larger budget than Trump had. Meanwhile, Trump used analytics at the end to both better position his limited budget, time and message -- and won.

The irony here is during the last two elections Obama outperformed his Republican rivals using analytics and Trump, who largely ran despite his party, seemed to learn that lesson better than Clinton did.

This points to the biggest problem with those who use analytics, assuring the data source.

Let me take you through what happened and I’ll end with the three rules of analytics.

The known problems with the data source

Going into this election we knew that there had been a major shift in how people communicated. Particularly with the growing power class of millennials. They had largely switched to mobile phone use and away from landlines and, due to caller ID, were more likely not to answer even if they were called on their mobile phone. In fact, a massive number of folks likely had this ability to dodge calls creating a huge potential gap in the sampling methodology, which should have significantly increased the confidence intervals. Rather than plus or minus 4 percent or 5 percent these things could have had ranges of 15 percent or more.

As the campaigns matured Trump supporters were vilified by the media and the Clinton camp, and at one point she called them deplorable. This was not a wise strategy because instead of forcing them to switch sides it apparently fueled their feelings of being attacked and cheated and that drove them to the polls in impressive numbers. But the bigger problem for analysts is it made them not want to respond, or if they did respond, not respond truthfully. This introduced massive pro-Clinton bias and should have invalidated the related studies.

As an analyst, a big part of the job is identifying and mitigating bias otherwise you are driving the people who pay you to make bad decisions and, given the outcome, that would seem to be the case here.

Trump’s advantage

Unlike Clinton, however, Trump’s folks rightly identified both issues and they used a little-known analytics company called Cambridge Analytica, and another as yet undisclosed company focused on Hispanics, who came up with a very different methodology. Ten days before the election a small team rewrote the sampling methodology to eliminate both the bias and the get to the potential voters that more traditional methods were missing. This allowed them to better advise their client where to go and how to spend his limited funds.

In short, they used their realization that everyone was doing this wrong, and there had been substantial evidence of that during the primaries, to create a strategic weapon for their client and that significantly helped turn what was likely a certain loss into one of the biggest surprise victories in U.S. history.

Part of what likely worked for Trump is he didn’t want to believe the bad numbers he was seeing driving people to a better methodology. Clinton liked the numbers she was seeing so didn’t do the same. This also showcases a huge common mistake; people just don’t challenge results they like and that almost always leads to bad results.

Second example

There was a second company that popped up as a hero after the election. It was the Trafalgar Group out of Atlanta. This company particularly looked at the problem with Trump supporters being undercounted and came up with a creative way to mitigate the problem and their results were unusually accurate even though their methodology was challenged by the better-known and better-funded firms that got this wrong.

What is both fascinating and annoying, as I’ve been there myself, is that to cover up their own incompetence firms like this will say things like “they got it right but for the wrong reasons” or complaining about crappy data completely forgetting that the “got it right” part is actually the most important and excuses don’t win. Some of these folks need to review the difference between winners and losers and come to the conclusion that being expert at excuses isn’t a formula for continued success.

3 rules of analytics

This all comes down to three rules for any kind of analysis.

First, you have to assure your data source. If you don’t have a strong sampling methodology you won’t have accurate results and you’d likely be better off not making the effort than in giving decision-makers bad advice.

Second, you have to identify and eliminate bias. Bias will invalidate the result and if you can’t eliminate it, once again, you’ll give decision-makers bad advice.

And finally, decision-makers have to learn to challenge the analysis, especially when it tells them what they want to hear, because you don’t get off the hook when you royally screw up by blaming the analysts. Yes, you can fire them but you’ll likely follow them out the door.

So, assure the data, identify and mitigate the bias, and always challenge the analysis to assure the advice you do get leads to a positive outcome.

Rob Enderle is president and principal analyst of the Enderle Group. Previously, he was the Senior Research Fellow for Forrester Research and the Giga Information Group. Prior to that he worked for IBM and held positions in Internal Audit, Competitive Analysis, Marketing, Finance and Security. Currently, Enderle writes on emerging technology, security and Linux for a variety of publications and appears on national news TV shows that include CNBC, FOX, Bloomberg and NPR.
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Re: After working for Trump’s campaign, British data firm ey

Postby admin » Wed Mar 28, 2018 4:16 pm

Clinton wins, how analytics cost Trump the election
Columnist Rob Enderle takes a look into the future, a future in which Hilary Clinton became president and Donald Trump didn’t. It all came down to analytics.
by Rob Enderle
CIO
July 22, 2016 9:45 AM PT

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During the last presidential election Barack Obama’s IT team shouldn’t have outperformed Romney’s team as massively as it did. At the heart of the Romney loss were three, as Donald Trump would say, huge errors.

The first mistake was using analytics services that didn’t understand elections, the second was using multiple services that didn’t coordinate with each other and the third was not questioning the data because it told them what they wanted to hear. This last has been a recurring cause of project and even company failure. The last mistake is not only being repeated by Trump, but he appears to be overt about it.

It would seem ironic that after giving Romney so much grief for losing, Trump is setting things up so that Romney will be able to say, after Trump loses the election, that at least he didn’t lose THAT badly. Clearly that is the outcome Ted Cruz just bet his political career on.

Trump don’t need no stinking analytics

When you read this coverage out of AdWeek that is the conclusion you walk away with, but I think it speaks to a far more common problem. When numbers agree with an executive’s view, they like them and when they don’t, there must be something wrong with the numbers. Don’t get me wrong, given the problems we’ve had with analytics that could well be the case. I recently reported on a KPMG report that basically said the majority of CEOs didn’t trust their numbers, which suggests Trump is in good company but it is still a stupid conclusion. The right path is to either better understand the numbers and/or make sure you can trust them.

Romney vs. Obama

What seems strange to me about this is here you had a guy who runs big businesses and a guy who was basically a teacher with slight political experience, and it was the teacher who used analytics better. Obama had a better team, made far better use of the systems it put in, were far more cost effective, and the results assured Obama’s second term.

Romney, however, was convinced he was going to win because the numbers told him what he wanted to hear. As a result, his team pulled back, thinking its candidate would coast to a win. So, in this case, Obama trusted his numbers, they were right, and in executing against them he won. Romney also trusted his numbers, but they were wrong, and he lost. So answer should be to ensure that the numbers, the analytics, are accurate not distrust the numbers.

Focus groups

I agree with Trump and Steve Jobs in the opinion that focus groups are crap when it comes to predicting things. The reason is they are way too easily manipulated, there is no good way to place them in the future so their decisions in the group mirror what they will actually do, and, because they are so compelling, people tend to believe what the focus group says.

I’ll give you an example. Years ago I was in a focus group for Chrysler and they showed me what I thought was a wonderful car. All of us said we’d buy it in a minute, so they put the car into production. However, in the 18 months between when the car was shown to us and when it became available, there were better cars that came from competing firms so my position, and everyone else's, changed. The car ended up not selling well.

This doesn’t mean focus groups aren’t useful. They are best used when trying to understand why someone did something. They are largely worthless in terms of predicting something. For instance, on the Brexit vote, focus groups likely would have showcased that people voted for it to show displeasure with the government not because they really wanted the exit. That would tell you the underlying problem to fix was the “pissed off at the government” part not exiting the EU.

Why Trump lost

While Clinton’s use of analytics clearly isn’t at Obama’s level, it is well above Trump’s. Partly, you can see this in regards to how much better she has been at collecting donations. She also seems to pivot better on issues as they become important for resonance. However, the lack of excitement in her campaign and the email thing still make this a race for now. The number both camps should be watching more closely is propensity to vote because this is partially what bit Romney in the butt last cycle.

But the lesson I want to leave you with is that numbers make for better decisions and, if you can’t trust them, fix the trust part -- don’t just toss out the entire concept of analytics as a key decision-making tool. If your brakes didn’t work, you wouldn’t stop using brakes, you’d get them fixed. Brakes can save your life, analytics can save your job, or in this case from being made fun of because you did worse than the guy you’ve been calling a choke artist.

Rob Enderle is president and principal analyst of the Enderle Group. Previously, he was the Senior Research Fellow for Forrester Research and the Giga Information Group. Prior to that he worked for IBM and held positions in Internal Audit, Competitive Analysis, Marketing, Finance and Security. Currently, Enderle writes on emerging technology, security and Linux for a variety of publications and appears on national news TV shows that include CNBC, FOX, Bloomberg and NPR.
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Re: After working for Trump’s campaign, British data firm ey

Postby admin » Wed Mar 28, 2018 4:24 pm

The Trump train wreck fueled by confirmation bias
Donald Trump doesn’t believe in hard facts, writes Rob Enderle. Trump is essentially the living definition of confirmation bias, which is a company killer and will likely be the downfall of Trump.
by Rob Enderle
CIO
August 5, 2016 7:54 AM PT

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You have to admit that watching Donald Trump run for president is funny in an incredibly painful way. During the primaries he seemed to be Teflon. I think we can now attribute his win to the fact that no one really took him seriously until it was too late, or as a result of using a strategy that worked for Pat Buchanan and Howard Stern.

Now in the general election it seems he has turned to glue and nearly everything he has done since has caused his poll numbers to go down. I think this is largely because he simply doesn’t believe in hard facts. He admittedly lives on Twitter and appears to not only take what he agrees with as fact, but to pretty much ignore all forms of independent data speaking out against both focus groups and analytics.

I think we can learn from his train wreck because while Trump may seem extreme, his blinders are so common we have a name for them: Confirmation bias.

Confirmation bias is when someone forms an opinion and then will accept only information that agrees with it discounting or ignoring everything else. The biggest example to date was likely the WMD belief that started the Iraq War. There were none.

How IBM almost went under

Decades ago while in IBM I was, along with a considerable number of others, very frustrated because it seemed obvious that IBM was on a managed path to failure yet the top executives seemed completely ignorant of the problem. I cornered IBM’s head of marketing and he spoke to me as if I was a small child explaining that IBM sold the equivalent of air and that customers had no choice but to buy what was sold. Thinking back, it strikes me that if this were the case what did we actually need a CMO for? Who needs to advertise air?

John Akers, who not only was a well-regarded and incredibly smart CEO, was then blindsided by the firm’s slide and remains the only IBM CEO ever fired. I later interviewed one of his aids to discover that over the years the office of the CEO had become effectively surrounded by information translators who told the CEO what he wanted to hear and effectively covered up any problems. Granted there were organizations like internal audit that reported through this barrier, but I know that those that found problems aggressively were discounted in favor of teams that reported favorable results.

Few words have consistently buzzed around the digital age like “omnichannel” — in response to increasing customer expectations for a seamless purchase journey, in an effort to deliver better...

Even in competitive analysis, where I also served, there were teams that reported accurately the problems with products and teams that reported that IBM’s products were unbeatable. In looking at the performance of our team against the other, we were defunded, and the business the other team supported went from 95 percent market share to 35 percent market. Now, to be clear, both businesses failed. Our information was disregarded resulting in failure and the other team’s information was false resulting in failure.

I recall being told that the executives were going to do what they wanted to regardless and failure wasn’t my responsibility, therefore, the smart analyst reported what the client wanted to hear not what they needed to know. While this still seems insane to me and I disregarded it at the time, in hindsight it was actually very good career advice, but an incredibly horrible way to run companies.

Analyst infamy

The second time I ran head-on into that buzz saw, apparently I’m a slow learner, was when I left IBM and became an analyst. I took over an operating system service that was on life support. Because I’d helped run a team that had tried to spin out the IBM software division I had massive amounts of market information which indicated that virtually every OS but one was vulnerable. The report not only made me famous, it had CEOs lining up to fire me. It was kind of a race to see if I, or Dataquest’s CEO, would be fired first. To suggest she was not happy would be an understatement.

I remember one call in particular with IBM regarding OS/2 where I suggested that the AR manager give the IBM management team a heads up that I was going to issue the report. Her response was that I was a nobody and no one would care what my report had to say. The next day it was front page news worldwide and repeating what she said later that day would trigger any number of profanity filters.

Now this time it worked out far better for me than it did for the CEOs or division heads who came after me as virtually all lost their jobs. However, had they put the effort into understanding and fixing the underlying problem rather than killing the messenger, me, we would have all won.

Confirmation bias the company killer

What my lessons showcased over and over again is that confirmation bias is a company killer and it can affect any of us. In my own case it happened when I was buying a motorcycle many years ago. I was convinced I knew all I needed to know about buying a Honda GL1100 and I found a really good deal. I didn’t do a lot of checking because it was such a good deal that I figured I could fix anything that was wrong with the bike and still have a decent profit. Only problem is the seller lied about the age of the motorcycle, something I’d never even considered. Had I simply done what any smart buyer had done and had the bike looked at by a shop, this would have become instantly obvious and I would have saved days in small claims court trying somewhat unsuccessfully (the seller would change jobs every time I garnished his wages) to get my money back. Not to mention I looked like an idiot in court when I explained how I was tricked, and my wife tends to remind me of this mistake any time we get into an argument about buying anything.

Given my background I should have been immune to confirmation bias, but I wasn’t and trust me, you aren’t either.

Confirmation bias made and killed Trump presidency

If you think about it, the Republican contenders that he beat constantly seemed to believe Trump wasn’t a threat until he became unstoppable. This was their own confirmation bias in play and even though early on it was clear he was appealing to a critical number of supporters they never fielded an appropriate response.

The Democrats on the other hand, even though they are having a massive number of issues themselves mostly with email, appear to have landed a killing blow right at the start of the election because Trump wasn’t paying attention to any voice but his own. In a way this means that it is very likely confirmation bias both created the Trump candidacy and eliminated any chance of a Trump presidency.


I think Trump is an extreme case because he so aggressively avoids information that it is like watching a blind bull in a china shop. Now I’ll leave you with a personal admission. I haven’t yet figured out a way to fix this. To date I’ve tried to fix this from inside firms where I worked and then with a number of clients and most efforts have failed. I’ve tried to convince friends and family, but once set on a path most don’t budge. The fact that whistle blowers exist and generally get shot is proof that fighting confirmation bias can be as deadly to your career as having it. Or, more bluntly, overcoming confirmation bias in yourself is hard, overcoming it in someone else is often impossible and potentially suicidal.

However, if you have ever successfully overcome this with someone else I’d like to hear your story, and I’ll bet Trump’s staff would appreciate it as well. Apparently they’ve gone from being concerned to becoming suicidal or more likely just given up, and sadly this last one is generally the smart move.

Avoid people who only praise or only criticize you, seek out dissenting opinions from well-founded people, and constantly challenge your own unchanging beliefs, at least consider you could be wrong, and put in place reasonable contingency plans. And if you find yourself working in a company that is lead by confirmation bias, leave, you’ll be more successful someplace else.

Rob Enderle is president and principal analyst of the Enderle Group. Previously, he was the Senior Research Fellow for Forrester Research and the Giga Information Group. Prior to that he worked for IBM and held positions in Internal Audit, Competitive Analysis, Marketing, Finance and Security. Currently, Enderle writes on emerging technology, security and Linux for a variety of publications and appears on national news TV shows that include CNBC, FOX, Bloomberg and NPR.
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Re: After working for Trump’s campaign, British data firm ey

Postby admin » Wed Mar 28, 2018 4:35 pm

Hillary Clinton’s ‘Invisible Guiding Hand’: Meet the little-known statistician behind the Democratic nominee's most important strategic decisions.
by Shane Goldmacher
September 07, 2016

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BROOKLYN, N.Y. — There are only a handful of corner offices inside Hillary Clinton’s campaign headquarters, and they are mostly occupied by familiar names: campaign manager Robby Mook, campaign chairman John Podesta, and Huma Abedin, her ubiquitous confidante.

Then there is Elan Kriegel.

Overlooking downtown Brooklyn in two directions, Kriegel’s skyline view is the backdrop for what is on the windows themselves: erasable marker scribblings reminiscent of A Beautiful Mind that amount to some of the earliest drafts of the computer algorithms that underlie nearly all of the Clinton campaign’s most important strategic decisions.

What cities Clinton campaigns in and what states she competes in, when she emails supporters and how those emails are crafted, what doors volunteers knock on and what phone numbers they dial, who gets Facebook ads and who gets printed mailers — all those and more have Kriegel’s coding fingerprints on them.

To understand Kriegel’s role is to understand how Clinton has run her campaign — precise and efficient, meticulous and effective, and, yes, at times more mathematical than inspirational. Top Clinton advisers say almost no major decision is made in Brooklyn without first consulting Kriegel. He was one of her first hires and is among her highest-paid, and yet he remains virtually unknown outside the cloistered community of political number-crunchers. “I can’t think of anybody who has as much impact as Elan who has as little name recognition with the national press,” said Stu Trevelyan, CEO of NGP VAN, which manages the voter file used by every major Democratic campaign, and who has worked with Kriegel for years.

Kriegel’s anodyne title is Clinton’s director of analytics, but it’s a job that makes him, and his team of more than 60 mathematicians and analysts, something of the central nervous system for the campaign: charged with sensing, even predicting, the first tinglings of electoral trouble and then sending instructions to everyone on how to respond.

When Clinton operatives talk about their “data-based” campaign, it’s invariably Kriegel’s data, and perhaps more importantly his models interpreting that data, they are talking about. It was an algorithm from Kriegel’s shop — unreported until now — that determined, after the opening states, where almost every dollar of Clinton’s more than $60 million in television ads was spent during the primary.

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Elan Kriegel, Clinton’s director of analytics, who builds statistical models for the campaign, “modeling” an ugly Christmas sweater for her online store. | Hillary Clinton campaign

The tool bypassed the expertise and instincts of her traditional media buyers by calculating the “cost per flippable delegate,” in the words of one senior Clinton official, and then spat out what states, television markets, networks and shows to buy. Obama veterans were wowed by its advancement; internally, some Clintonites saw it as their secret weapon in building an insurmountable delegate lead over Bernie Sanders.

Now, with Donald Trump investing virtually nothing in data analytics during the primary and little since, Kriegel’s work isn’t just powering Clinton’s campaign, it is providing her a crucial tactical advantage in the campaign’s final stretch. It’s one of the reasons her team is confident that, even if the race tightens as November approaches, they hold a distinctive edge. As millions of phone calls are made, doors knocked and ads aired in the next nine weeks, it is far likelier the Democratic voter contacts will reach the best and most receptive audiences than the Republican ones.

I can’t think of anybody who has as much impact as Elan who has as little name recognition with the national press.”


Zac Moffatt, who served as Mitt Romney’s digital director in 2012, was already worried about this back during the Republican primaries. In an interview then, Moffatt feared that whoever emerged as the GOP nominee would be perilously handicapped when it came to data analytics just as Romney had been compared to President Barack Obama who, like Clinton, had honed an analytics operation more than a year in advance.

“If you’re not prepared for it, you can’t catch up,” Moffatt said. “You can’t have a baby in 3 months, that’s just the reality of life. I tried.”

Some Republicans aren’t just nervous about losing to Clinton in November. They’re alarmed at the possibility of falling multiple cycles, even a generation, behind in creating a culture of data-intensive campaigns. Romney hardly had an autonomous analytics department. Trump has called data “overrated.” Kriegel, meanwhile, is incubating the next generation of Democratic talent — his team rivaled the size of Trump’s entire headquarters operation for much of the primary — the no-name analysts of 2016 who will emerge as the key players in 2018 and 2020.

The specifics of the Clinton campaign’s analytics work, such as the large-scale, academic-style experiments the department has run, are closely guarded for fear of giving away any advantage to the GOP. Kriegel himself declined to comment for this story. But Mook, the campaign manager, spoke glowingly of Kriegel and expansively of his influence.

“His hand has guided almost every aspect of what we do,” Mook said.

***

Staff in Clinton’s analytics department sit under a sign that hangs from the ceiling with the words “statistically significant” printed on it. And overnight, in some of the few hours that headquarters isn’t whirring with activity, the team’s computers run 400,000 simulations of the fall campaign in what amounts to a massive stress-test of the possibilities on Nov. 8. That way, in morning calls with senior staff, Kriegel can deliver any key findings.

One Democratic strategist, an Obama veteran with knowledge of the Clinton campaign, marveled at Kriegel’s sway in Brooklyn. “I have never seen a campaign that’s more driven by the analytics,” the strategist said. It’s not as if Kriegel’s data has ever turned around Clinton’s campaign plane; it’s that her plane almost never takes off without Kriegel’s data charting its path in the first place.

“From our schedule to our voter contact to where our organizers spend their time, almost everyone here interacts with his work and their work is influenced by his insights,” Mook said, calling Kriegel’s analyses the campaign’s “invisible guiding hand.”

And yet Kriegel remains so unknown, even in this most heavily scrutinized of campaigns, that of the millions of tweets sent about the presidential race, his full name “Elan Kriegel” hasn’t been tweeted once in 2016. (His handle was tagged about a half-dozen times.)

The last time anyone tweeted Kriegel’s name was October 2015, when Patrick Ruffini, a Republican digital strategist sifting through the campaign’s financials noticed that Clinton’s “highest paid staffer appears to be Elan Kriegel, their director of Analytics.” (That’s not quite right, as of today. One person on payroll has been paid more since the inception of the campaign, though plenty of consultants have billed far more.)

From our schedule to our voter contact to where our organizers spend their time, almost everyone here interacts with his work and their work is influenced by his insights.”


Kriegel’s pay and corner office — he’s actually in the spot Mook occupied before the campaign expanded over the summer — are only symbols of his stature. His real influence is rooted in his closeness to Mook, the penny-pinching campaign chief who turns to Kriegel for cost-cutting efficiencies on nearly everything. The two worked together closely on Terry McAuliffe’s 2013 Virginia governor’s race, and when Mook was tapped as Clinton’s campaign manager, Kriegel was among his first hires — “in the single digits, absolutely,” Mook said.

Marlon Marshall, Clinton’s director of state campaigns and political engagement, called Kriegel “one of the smartest guys I’ve ever met” but said that his success is because he makes data actionable by answering the question that senior staff always has: “How do we implement [it] in our programs?”

“He understands how to translate analytics and what he’s seeing from a data standpoint into reality,” Marshall said.

Inside the Clinton campaign, though, Kriegel’s powerful role has been a source of some nervous friction. Clinton has commissioned numerous experiments to score the effectiveness and cost efficiency of different methods of voter outreach — TV, radio, directmail, online display ads, Web videos, phone calls, etc. While the existence of the studies is more widely known in her orbit, the findings are a tightly kept secret — and threaten to wreak havoc on various vendors’ businesses and paydays in the final months.

“Elan has really been one of the people creating a culture of testing in Democratic politics,” said Trevelyan. “This was a field long dominated by a few media consultants’ guts.”

Among the pioneering areas Kriegel’s analytics team has studied, according to people familiar with the operation, is gauging not just whom to talk to, how to talk to them and what to say — but when to say it. Is the best time to contact a voter, say, 90 days before the election? 60 days? One week? The night before? It is a question Obama’s team realized was crucial to mobilizing voters in 2012 but had never been truly analyzed. With a full calendar of competitive primaries, Kriegel and his team had plenty of chances to run rigorous, control-group experiments to ferret out answers to such questions earlier this year.

“I was just in a meeting with him the other day,” Mook said, “And I was saying to him I need you to come back and tell me — we were talking about Ohio — I need you to come back and tell me, based on the information we have about voting patterns in Ohio, what are the things that my program can affect that will matter most.”

Mook called Kriegel’s studies “groundbreaking work … to help us understand what channels are most efficient at motivating, persuading different voters.”

Four years ago, Kriegel similarly won the trust of Obama’s top brass as the battleground states analytics director in The Cave, the much-heralded Obama 2012 data war room. “We didn’t make a single decision about battleground state strategy without first talking to Elan about his numbers,” said Jeremy Bird, then Obama’s national field director and now a Clinton consultant.

“And he was never wrong,” Bird added. “That’s pretty remarkable.”

One episode, in particular, stood out. Bird said he knew they were going to beat Mitt Romney early on election night 2012 when he looked at the early vote in a key Florida county and cross-checked it with Kriegel’s predictive model.

“It was,” Bird recalled, “the exact same number.”


***

In 2016, no analytics advancement has proved more significant, financially, than the TV tool created for the primaries. “TV constitutes two-thirds to three-quarters of the budget,” said David Nickerson, a professor at Temple University who worked with Kriegel doing analytics for Obama in 2012 and Clinton in 2016. “Anything that improves that efficiency is going to save the campaign a lot of money.” Senior Clinton officials outlined for POLITICO how the algorithm worked:

First, the campaign ranked every congressional district by the probability that campaigning there could “flip” a delegate into Clinton’s column. Because every district has a different number of delegates allocated proportionally (in Ohio, for instance, 12 districts had 4 delegates each while one had 17), this involved polling and modeling Clinton’s expected support level, gauging the persuadability of voters in a particular area and then seeing how close Clinton was to a threshold that would tip another delegate in her direction. (At the most basic level, for instance, districts with an even number of delegates, say 4, are far less favorable terrain, as she and Bernie Sanders were likely split them 2-2 unless one of them achieved 75 percent of the vote.)

That so-called “flippability score” was then layered atop which media markets covered which seats. If a media market touched multiple districts with high “flippability” scores, it shot up the rankings. Then the algorithm took in pricing information, and what television programs it predicted the most “flippable” voters would be watching, to determine what to buy.

Elan has really been one of the people creating a culture of testing in Democratic politics. This was a field long dominated by a few media consultants’ guts.”


If that all sounds simple enough, it’s not. Every TV market reaches a different number of voters in a different number of districts, with her support in each a different estimated distance from a delegate threshold. Calculating where dollars would go furthest, per delegate, was an incredible statistical undertaking that was months in the making.

In the end, whatever the algorithms spat out, the campaign pretty much bought. “We relied almost entirely on them,” Mook said.

So in states that Clinton won lopsidedly, Kriegel’s algorithm still had them spending big.

The breakdown of the buy in Texas, powered by Kriegel’s modeling, shows how Clinton’s TV ads budget hunted for delegates, not votes. Texas is the rare state that used state legislative districts to award delegates, and Clinton spent $1.2 million on broadcast and cable ads even as she won the state by 32 percentage points. Sanders spent $0. She spent more on ads in tiny Brownsville ($127,000) and Waco ($142,000), ranked as the 86th and 87th largest media markets in the country, as she did in Houston ($105,000), the 10th largest, according to ad data provided by a media tracker.

It paid off: In Texas alone, Clinton netted 72 delegates more than Sanders — a margin that more than offset all the Sanders’ primary and caucus wins through March 1.

***

Ten years ago, the idea that Kriegel would be a senior Clinton adviser would have seemed unthinkable. Yes, he was studying Clinton’s public movements closely then. But that was only because his first job in politics was as a producer for Bill O’Reilly, the conservative Fox News host and Clinton antagonist.

Lore is that one of Kriegel’s final acts for O’Reilly was helping prepare for his last sit-down with Clinton, in 2008. In fact, this summer, when Clinton called in to O’Reilly’s show after the terror attack in Nice, France, it was in part because Kriegel had previously laid some of the introductory groundwork between the show’s staff and Clinton’s communications shop, including communications director Jennifer Palmieri, according to three people familiar with his role. O’Reilly declined to comment for this article.

Kriegel left O’Reilly’s show to go back to school for a statistics degree and ended up at the Democratic National Committee by the 2010 cycle, and then on Obama’s 2012 campaign.

After the reelection, much of the public plaudits for Obama’s data operation went to Kriegel’s talented boss, Dan Wagner, Obama’s chief analytics officer. According to four associates of Wagner and Kriegel, Google’s Eric Schmidt, who visited the Obama headquarters often and was impressed by the analytics shop, invested an 8-figure sum into what would become Civis Analytics, with Wagner given an ownership stake and named a founder. Wagner and Kriegel, who was also offered equity in the company, parted ways over financial and other differences, these people said. Wagner did not respond to requests for comment. Kriegel, along with several Obama and Democratic Party data operatives, went on to form a firm of their own, BlueLabs.

Kriegel built Clinton’s analytics team by pulling people from BlueLabs (Pedro Suarez, the analyst who helped create the TV ad-buying tool), past campaigns (2012 reelection veteran Matt Dover) and the private sector (Nell Thomas, a top deputy, previously ran analytics for Etsy).


Trump, who infamously called campaign data “overrated” back in May, has recently hired Cambridge Analytica, which did analytics work for Ted Cruz’s campaign in the primary. But the continual staff turnover has stymied the Republican National Committee’s ability to infuse its own data program, which it has invested in heavily over the past four years, into Trump’s decisions, according to people familiar with the efforts. Each successive political director, RNC liaison and campaign manager has had to be sold anew on the program’s benefits, and the candidate himself has not embraced its value. As Trump has stumped in far-afield states like Mississippi, Washington and Texas, Republicans have implored his team to incorporate some data inputs to something as fundamental as the candidate’s schedule.

If you’re not prepared for it, you can’t catch up,” Moffatt said. “You can’t have a baby in 3 months, that’s just the reality of life. I tried.”

Ruffini, the GOP strategist who flagged Kriegel’s pay last fall, said the concern is that Republicans are going to lag further behind the Democrats after 2016. “It’s now going from one cycle behind to two cycles,” he said. “The maturity in the system is when the deputies get hired to be the directors,” Ruffini said, just as Kriegel was elevated. The problem is that Trump has neither directors nor deputies.

In Brooklyn, meanwhile, Kriegel continues to toil away. Colleagues said it’s not clear when he last took a vacation, let alone time off. So when he turned 35 earlier this summer, his team brought the beach to him, plastering his office with streamers and beach balls. Suddenly, the algorithmic scribblings on the windows shared space with tropical fish.

As Mook wrapped up his interview, he made sure to stress that, “You don’t win campaigns because of data. You run your campaign more efficiently and effectively with the data.” Clinton, he said, “has to get out there every day and make her case.”

But for just about everything else, there is Elan Kriegel. And, by the time the campaign’s over, some people outside of headquarters might even know his name.
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Re: After working for Trump’s campaign, British data firm ey

Postby admin » Wed Mar 28, 2018 4:45 pm

How Clinton lost Michigan — and blew the election
Across battlegrounds, Democrats blame HQ’s stubborn commitment to a one-size-fits-all strategy.
by Edward-Isaac Dovere
12/14/2016 05:08 AM EST

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Everybody could see Hillary Clinton was cooked in Iowa. So when, a week-and-a-half out, the Service Employees International Union started hearing anxiety out of Michigan, union officials decided to reroute their volunteers, giving a desperate team on the ground around Detroit some hope.

They started prepping meals and organizing hotel rooms.

SEIU — which had wanted to go to Michigan from the beginning, but been ordered not to — dialed Clinton’s top campaign aides to tell them about the new plan. According to several people familiar with the call, Brooklyn was furious.

Turn that bus around, the Clinton team ordered SEIU. Those volunteers needed to stay in Iowa to fool Donald Trump into competing there, not drive to Michigan, where the Democrat’s models projected a 5-point win through the morning of Election Day.

Michigan organizers were shocked. It was the latest case of Brooklyn ignoring on-the-ground intel and pleas for help in a race that they felt slipping away at the end.


“They believed they were more experienced, which they were. They believed they were smarter, which they weren’t,” said Donnie Fowler, who was consulting for the Democratic National Committee during the final months of the campaign. “They believed they had better information, which they didn’t.”

Flip Michigan and leave the rest of the map, and Trump is still president-elect. But to people who worked in that state and others, how Clinton won the popular vote by 2.8 million votes and lost by 100,000 in states that could have made her president has everything to do with what happened in Michigan. Trump won the state despite getting 30,000 fewer votes than George W. Bush did when he lost it in 2004.

Politico spoke to a dozen officials working on or with Clinton’s Michigan campaign, and more than a dozen scattered among other battleground states, her Brooklyn headquarters and in Washington who describe an ongoing fight about campaign tactics, an inability to get top leadership to change course.

Then again, according to senior people in Brooklyn, Clinton campaign manager Robby Mook never heard any of those complaints directly from anyone on his state teams before Election Day.

In results that narrow, Clinton’s loss could be attributed to any number of factors — FBI Director Jim Comey’s letter shifting late deciders, the lack of a compelling economic message, the apparent Russian hacking. But heartbroken and frustrated in-state battleground operatives worry that a lesson being missed is a simple one: Get the basics of campaigning right.

Clinton never even stopped by a United Auto Workers union hall in Michigan, though a person involved with the campaign noted bitterly that the UAW flaked on GOTV commitments in the final days, and that AFSCME never even made any, despite months of appeals.

The anecdotes are different but the narrative is the same across battlegrounds, where Democratic operatives lament a one-size-fits-all approach drawn entirely from pre-selected data — operatives spit out “the model, the model,” as they complain about it — guiding Mook’s decisions on field, television, everything else. That’s the same data operation, of course, that predicted Clinton would win the Iowa caucuses by 6 percentage points (she scraped by with two-tenths of a point), and that predicted she’d beat Bernie Sanders in Michigan (he won by 1.5 points).

“I’ve never seen a campaign like this,” said Virgie Rollins, a Democratic National Committee member and longtime political hand in Michigan who described months of failed attempts to get attention to the collapse she was watching unfold in slow-motion among women and African-American millennials.

Rollins, the chair emeritus of the Michigan Democratic Women’s Caucus, said requests into Brooklyn for surrogates to come talk to her group were never answered. When they held their events anyway, she said, they also got no response to requests for a little money to help cover costs.


Rollins doesn’t need a recount to understand why Clinton lost the state.

“When you don’t reach out to community folk and reach out to precinct campaigns and district organizations that know where the votes are, then you’re going to have problems,” she said.

The enthusiasm gap

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Hillary Clinton speaks at the Service Employees International Union (SEIU) 2016 International Convention on May 23 in Detroit, Michigan. | Getty

From the day Clinton released her launch video, the campaign knew she’d struggle with enthusiasm. Yet they didn’t do many of the things voters are used to seeing to give a sense of momentum, insisting that votes didn’t come from campaign literature, door knocking, commitment to vote cards or the standard program of sending absentee ballot applications to likely voters rather than just appealing to the people once they’d already ordered the ballots.

“It was very surgical and corporate. They had their model, this is how they’re going to do it. Their thing was, ‘We don’t have to leave [literature] at the doors, everyone knows who Hillary Clinton is,’” said one person involved in the Michigan campaign. “But in terms of activists, it seems different, it’s maybe they don’t care about us.”

Michigan operatives relay stories like one about an older woman in Flint who showed up at a Clinton campaign office, asking for a lawn sign and offering to canvass, being told these were not “scientifically” significant ways of increasing the vote, and leaving, never to return. A crew of building trade workers showed up at another office looking to canvass, but, confused after being told there was no literature to hand out like in most campaigns, also left and never looked back.

“There’s this illusion that the Clinton campaign had a ground game. The deal is that the Clinton campaign could have had a ground game,” said a former Obama operative in Michigan. “They had people in the states who were willing to do stuff. But they didn’t provide people anything to do until GOTV.”

The only metric that people involved in the operations say they ever heard headquarters interested in was how many volunteer shifts had been signed up — though the volunteers were never given the now-standard handheld devices to input the responses they got in the field, and Brooklyn mandated that they not worry about data entry. Operatives watched packets of real-time voter information piled up in bins at the coordinated campaign headquarters. The sheets were updated only when they got ripped, or soaked with coffee. Existing packets with notes from the volunteers, including highlighting how much Trump inclination there was among some of the white male union members the Clinton campaign was sure would be with her, were tossed in the garbage.

The Brooklyn command believed that television and limited direct mail and digital efforts were the only way to win over voters, people familiar with the thinking at headquarters said. Guided by polls that showed the Midwestern states safer, the campaign spent, according to one internal estimate, about 3 percent as much in Michigan and Wisconsin as it spent in Florida, Ohio and North Carolina. Most voters in Michigan didn’t see a television ad until the final week.

Most importantly, multiple operatives said, the Clinton campaign dismissed what’s known as in-person “persuasion” — no one was knocking on doors trying to drum up support for the Democratic nominee, which also meant no one was hearing directly from voters aside from voters they’d already assumed were likely Clinton voters, no one tracking how feelings about the race and the candidates were evolving. This left no information to check the polling models against — which might have, for example, showed the campaign that some of the white male union members they had expected to be likely Clinton voters actually veering toward Trump — and no early warning system that the race was turning against them in ways that their daily tracking polls weren’t picking up.


People involved in the Michigan campaign still can’t understand why Brooklyn stayed so sure of the numbers in a state that it also had projected Clinton would win in the primary.

“Especially given what happened in the primary,” said Michigan Democratic Party chairman Brandon Dillon. “We knew that there was going to have to be more attention.”

With Clinton’s team ignoring or rejecting requests, Democratic operatives in Michigan and other battleground states might have turned to the DNC. But they couldn’t; they weren’t allowed to ask for help.

State officials were banned from speaking directly to anyone at the DNC in Washington. (“Welcome to DNC HQ,” read a blue and white sign behind the reception desk in Brooklyn that appeared after the ouster of Debbie Wasserman Schultz just before the July convention).

A presidential campaign taking over the party committee post-convention is standard, but what happened in 2016 was more intense than veterans remember. People at the DNC and in battleground states speak of angry, bitter calls that came in from Brooklyn whenever they caught wind of contact between them, adamant that only the campaign’s top brass could approve spending or tactical decisions.

“Don’t touch them. Stay away,” one person on the other end of the call remembered Clinton campaign states director Marlon Marshall saying after hearing about a rogue conversation between a battleground operative and an official at the DNC. “You can’t be calling those people and making them think something is coming when nothing is.

Mook himself made a number of those calls.

To Brooklyn, this was the only way to shut down what they perceived early as an effort to undermine the campaign’s planning, DNC officials playing good cop as they made promises they couldn’t keep to friends in the states, took credit for moves Clinton’s staff already were making, or looked to dig up trouble to use against them later

Shunning help from outside

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Supporters hold signs at a campaign rally for Hillary Clinton in Detroit, Michigan on Nov. 4. | AP Photo

Brooklyn’s theory from the start was that 2016 was going to be a purely base turnout election. Efforts were focused on voter registration and then, in the final weeks, turning out voters identified as Clinton’s, without confirmation that they were.

Marshall, at Mook’s direction, had designed a plan that until the final weeks was built around holding Pennsylvania and winning just one more state — electoral math that would have denied Trump the presidency on the reasonable assumption Michigan and Wisconsin were Clinton’s.

There was a logic guided by data, they say.

“We have built an operation and we run an operation as if this is going to be a close race,” Marshall said in an interview with Politico in early October. “We have not seen an organization in many states on the Trump side that reflects that.”

In Michigan, Brooklyn tracked 211 staff compared with 58 for Barack Obama in 2012. A source there said the field plan called for an additional 70 staffers, but deferred to the local team instead on using the $1.4 million allotment for a limited paid canvass.

But enough tremors were reaching Brooklyn by late October that veterans of previous campaigns were brought on to help oversee a stabilization — despite tension that dated back to many at the firm never wanting Mook to be campaign manager in the first place.

A battle against Mook’s direction took hold, with multiple people plotting ricochets, complaining to people like Chief Administrative Officer Charlie Baker and longtime Clinton confidante Minyon Moore in the hopes of getting the campaign manager overruled.

Michigan was the only presidential battleground that didn’t have an active Senate race, and that cost the state money from Brooklyn. Waving off complaints during a visit to Michigan a few weeks out, Marshall explained to the room that Clinton was going to clobber Trump in the final debate and they were talking about moving money into Senate seats. And by the time they arrived in Las Vegas for that third debate, Clinton’s top aides were boasting about how they were about to expand the lead and pull marginal Senate candidates over the line to give her a governing majority.

In Michigan, they raised more than $700,000 to cover costs, mostly from in-state donors. Though the campaign said every check was signed off on in Brooklyn, Fowler said the DNC approved a $50,000 rogue transfer — let the Clinton campaign complain to him after Election Day, he told them.

“You’re in a state, your job is to win the battleground state, not to have complete fealty to the national campaign headquarters, especially if the national campaign headquarters is not listening,” Fowler explained.

Among the other workarounds claimed was one from interim DNC chair Donna Brazile, who was persuading the Democratic Senatorial Campaign Committee and Democratic Congressional Campaign Committee to hold the $5 million transferred to them from the Clinton campaign and to wait to spend it buying airtime for minority voter turnout in the final week they otherwise wouldn’t have been able to fund.

But there also were millions approved for transfer from Clinton’s campaign for use by the DNC — which, under a plan devised by Brazile to drum up urban turnout out of fear that Trump would win the popular vote while losing the electoral vote, got dumped into Chicago and New Orleans, far from anywhere that would have made a difference in the election.

Nor did Brooklyn ask for help from some people who’d been expecting the call. Sanders threw himself into campaign appearances for Clinton throughout the fall, but familiar sources say the campaign never asked the Vermont senator’s campaign aides for help thinking through Michigan, Wisconsin or anywhere else where he had run strong. It was already November when the campaign finally reached out to the White House to get President Barack Obama into Michigan, a state that he’d worked hard and won by large margins in 2008 and 2012. On the Monday before Election Day, Obama added a stop in Ann Arbor, but that final weekend, the president had played golf on Saturday and made one stop in Orlando on Sunday, not having been asked to do anything else. Michigan senior adviser Steve Neuman had been asking for months to get Obama and the first lady on the ground there. People who asked for Vice President Joe Biden to come in were told that top Clinton aides weren’t clearing those trips.

“We worked collaboratively with Brooklyn throughout and made a robust investment in Michigan, and we were obviously disappointed that we came up short. Everybody was,” Neuman said.

‘Not the right plan’

Top aides in Brooklyn write off complaints from battleground state operatives as Monday morning quarterbacking by people who wouldn’t have had much of a case if Clinton had won. They continue to blame the loss on FBI Director James Comey, saying he shifted late deciders, not any tactical failures.

“Now of course, in hindsight, there are any number of steps that we could have taken that may have made the difference in a state as closely decided as Michigan, but the consistent theme across all the battleground states was that we saw our numbers drop in the final week after Jim Comey sent his shocking letter to Congress,” said former Clinton spokesman Brian Fallon.

When top aides to the Trump campaign mapped out the best-case scenarios for election night, they always fell short of 270, and Michigan was always the state that they couldn’t see a way through.

Trump’s last stop of the election was a massive rally in Michigan that went on past midnight, his campaign homing in on Trump’s chances there largely from nervousness it sensed coming out of Brooklyn.

Walking out at the end, Trump turned to his running mate, Mike Pence, almost confused: “This doesn’t feel like second place,” he said, according to a person familiar with the conversation.


Democrats felt it too. Rep. Debbie Dingell, who complained throughout the campaign about the lack of urgency and support, has told people since the election that Hillary and Bill Clinton both said in their final appearances in the state that they felt something was off.

On the morning of Election Day, internal Clinton campaign numbers had her winning Michigan by 5 points. By 1 p.m., an aide on the ground called headquarters; the voter turnout tracking system they’d built themselves in defiance of orders — Brooklyn had told operatives in the state they didn’t care about those numbers, and specifically told them not to use any resources to get them — showed urban precincts down 25 percent. Maybe they should get worried, the Michigan operatives said.

Nope, they were told. She was going to win by 5. All Brooklyn’s data said so.

In at least one of the war rooms in New York, they’d already started celebratory drinking by the afternoon, according to a person there. Elsewhere, calls quietly went out that day to tell key people to get ready to be asked about joining transition teams.

But an hour-and-a-half after polls closed, Clinton aides began making rushed calls, redrawing paths to 270 through the single electoral vote in Maine and Nebraska. Still assuming wins in Wisconsin and Pennsylvania, Michigan suddenly looked like the state that was going to decide the presidency.

They scrambled a call with campaign attorney Marc Elias, prepping for a recount in a vote that oddly looked like it would be a narrower win than they had ever prepared for. An hour later, after they hung up, they realized it was over. They could tell by the numbers they were seeing — not the numbers being spewed from their own internal analytics team, but the numbers sitting at the bottom of the TV tuned to CNN. With the recount frozen, Clinton lost Michigan by 10,704 votes.


“I think it’s true, they executed well. I think it’s true that the plan was accomplished,” said a former labor leader in the state. “But the plan was not the right plan.”
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Re: After working for Trump’s campaign, British data firm ey

Postby admin » Wed Mar 28, 2018 4:57 pm

Democrats to Clinton: The DNC's data was fine -- you just used it wrong
by Eric Bradner
CNN
Updated 4:06 PM ET, Fri June 2, 2017

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Washington (CNN) Democratic data gurus are lashing out at Hillary Clinton after she complained publicly that her campaign was hamstrung by a party that had out-of-date information on individual voters.

Clinton said Wednesday in an interview with Recode's Kara Swisher that once she became the Democratic nominee, she inherited "nothing." The Democratic National Committee's data, she said, "was mediocre to poor, nonexistent, wrong. I had to inject money into it."

Her comments drew swift rebuttals from some Democratic operatives who built, or worked with, that data.

Andrew Therriault, the former DNC director of data science, lashed out in two since-deleted tweets, calling Clinton's comments "f---ing bull----."


"I hope you understand the good you did despite that nonsense," he said in a message directed to DNC data staffers.

David Radloff, the co-founder of the Democratic data and analytics firm Clarity Campaign Labs, tweeted:
"Used DNC data on numerous campaigns this year, well managed, efficient, accurate. Real question is who's feeding Clinton bad info and why??"


John Hagner, a partner at Clarity, added: "I worked with DNC data every day last cycle, on winning Gov races. It was accurate and up-to-date and I'm grateful for their hard work."

Many Democrats noted that Clinton -- just like her opponent Bernie Sanders -- had access to the DNC's data from the outset of her campaign. Therefore, they said, if there was trouble with the data, her staff would have known long before she won the Democratic presidential nomination.

Tom Bonier, the chief executive officer of TargetSmart, a Democratic voter-targeting firm, said in using the DNC's data, the Clinton campaign was "absolutely standing on the shoulders of the Obama data juggernaut. There's just no question."

"I can tell you, having worked with the DNC from the outside over that time period, the DNC not only maintained what was built as part of the Obama 2008 and 2012 campaigns, but they built upon it," he said. "And that meant more staff and that meant better data. They built an in-house analytics team, which they had not had in the past. And they were constantly adding data to the file."

Bonier added: "You can argue about whether or not they were behind Republicans. ... But it's absurd to suggest that any Democratic candidate who was using the DNC data in 2016 was inheriting nothing, as Secretary Clinton said. What they were inheriting was the best data operation the Democratic Party has ever seen."


So what went wrong?

Several Democrats pointed to the Clinton campaign's use of the data in making decisions about which voters to target, where to send the candidate and where to devote its advertising dollars.

That element of the campaign -- analytics -- is built on top of the party-provided data.

Speculating about why Clinton might have complained about the DNC's data, Bonier said: "The modeling's built on data, right, so maybe it's a stone's throw from there where you don't want to blame your own staff who build the models, who told you, you don't need to go to Wisconsin ... so you go a little bit further upstream and say it was the data that that was built upon."

Still, there were elements of Clinton's argument that are difficult to dispute.

Much of her criticism of the DNC was an implicit shot at former President Barack Obama, who many Democrats have complained kept his own campaign's data and analytics housed separately and allowed the party's infrastructure to lapse under former chairwoman Debbie Wasserman Schultz's leadership.

The Republican National Committee made improving its data and analytics a priority between 2012 and 2016, erasing the advantage Obama had in previous elections.

Clinton also cited the Trump campaign's use of the controversial GOP firm Cambridge Analytica, which boasts of "psychographic" profiles of voters based heavily on Facebook information.

Clinton's campaign did not hire a similar outside data firm, but she said Cambridge Analytica helped Trump.

"You can believe the hype on how great they were or the hype on how they weren't, but the fact is, they added something," she said.


Tom Perez, the new Democratic National Committee chairman, also complained about the party's data operation in his campaign for the job over the winter. However, when asked on CNN's "Erin Burnett Outfront" on Thursday about Clinton's remarks, Perez said, "There are a lot of reasons for not winning that election."

"We're totally focused on the future of the DNC," he told Burnett. "We're totally focused on building an infrastructure for success."

OutFrontCNN

@OutFrontCNN
.@HillaryClinton used the words "mediocre" and "poor" in describing the @DNC. @ErinBurnett asked @TomPerez to react
5:10 PM - Jun 1, 2017


"We have to up our game at the DNC," he added, noting the organization is "getting back to basics" by investing in organizing, training of candidates and technology.

DNC spokesman Michael Tyler said the party is in the process of overhauling its data and technological operations.

"Tom has said before that the DNC was not firing on all cylinders and that's why he did a top to bottom review that included technology. The DNC is now undergoing an organizational restructuring that will include a new chief technology officer, who will do an in-depth analysis and maintain the party's analytics infrastructure needs," Tyler said in a statement.

"Tom is already deeply engaged with the outpouring of support from Democrats across the country, from Silicon Valley to suburban Georgia, who want to help improve the data and tech, get it in the hands of more organizers everywhere, and build the grass-roots funding stream required to support those efforts."

Clinton's allies say her joint fundraising efforts helped improve the DNC's positioning.

"She was intent on leaving the party in the black," a Clinton associate said Thursday.

Despite her loss, the associate said, she was pleased to leave the party without a debt "and she turned over her email list and her data, something that Bernie Sanders did not do and has not done. Because we've got to have this in one place so people can utilize it."

CNN's Saba Hamedy contributed to this report.
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Re: After working for Trump’s campaign, British data firm ey

Postby admin » Wed Mar 28, 2018 5:51 pm

Target Audience Analysis
by Cdr (Rtd.) Dr Steve Tatham Ph.D.
Royal Navy
StratCom and TAA Subject Matter Expert
StratCom Centre of Excellence
The Three Swords Magazine
28/2015

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THERE EXISTS NO UNIVERSAL COMMUNICATION MODEL APPLICABLE TO ALL GROUPS AND CULTURES. ALL COMMUNICATION EFFORTS MUST BE TAILORED TO THE LOCAL DYNAMICS AND WITH RESPECT TO THE BEHAVIOURS ONE IS SEEKING TO CHANGE.

THERE is a great (and true) story about the inventor of the jet aircraft engine, Englishman Frank Whittle. Whittle, a Royal Air Force officer, took his first design for a jet engine to the British Government in 1929. It was turned down for funding on the grounds of impracticality (displaying the same longterm strategic vision that the British Admiralty showed in 1901, when they turned down a design for submarines, proclaiming them "underwater, underhand and damned un-English"). Thankfully, Whittle persevered, and in 1930, he patented the design himself, having sunk all his personal funds into research. In 1934, with the patent up for renewal, he again applied for the British government sponsorship, and again he was declined. Luckily, he managed to raise £2,000 in private finance and continued his research. In 1937, after eight years of further research and development, he again offered the project to the British Government, which again declined to assist him. It was only in 1939 that a single government official, at personal risk to his career and reputation, backed Whittle's invention and lobbied in the corridors of Whitehall for its funding. The result of all of this procrastination was that the British jet aircraft only finally entered operational service at the end of the Second World War but rather scarily, and very nearly, did not enter at all.

All very interesting but, so what? Well, one could just as equally apply this story to the tortuous journey that NATO and western Strategic Communications (StratCom) have taken over the last few years. Like Whittle's jet engine, the huge number of naysayers has nearly drowned the concept, which I think is incredible, considering its highly effective use by Russia in Crimea, and Da'esh (I refuse to call such murderous criminals "Islamic State") — in Iraq and Syria, not to mention its hugely ineffective use by NATO in Afghanistan, and the wider, so-called Global War on Terror.

But, StratCom has languished for some time now. In the United States, the term was even abandoned, albeit unilaterally, by George Little, then Acting Assistant Secretary of Defense for Public Affairs, who banned the term, proclaiming it has: "added a layer of staffing and planning that blurred roles and functions of traditional staff elements and resulted in confusion and inefficiencies."

Indeed, one of the problems for StratCom is that it has not really worked very well. NATO is currently undertaking a full review of ISAF's StratCom efforts in Afghanistan, which may well conclude that NATO (and western StratCom) were unhealthily wedded to advertising and marketing techniques (and companies) that costed a fortune and delivered, as the U.S. Government Audit Office (GAO) has observed, almost nothing of worth — aside from big profits for their shareholders.

As early as 2012, the U.S. GAO had concluded that: "the [U.S. StratCom] programs are inadequately tracked, their impact unclear, and the military doesn't know if it is targeting the right foreign audiences." What is needed now is a "divorce" and at last this is happening in the newly established Centre of Excellence (CoE) for Strategic Communications in Riga, Latvia, where the vision and focus are very much on the "audience" and its actual behaviour, not on the synchronisation across varied themes and perceptions. By courtesy of a CAD $1-million donation to the StratCom CoE, the Centre will soon be an accredited training facility using Behavioural Dynamics Institute's "Target Audience Analysis Methodology" through a Train the Trainer Programme — a purposebuilt NATO course developed and delivered by the Strategic Communications Laboratories Group (SCL) and Information Operations Training and Advisory Services Global (IOTAGlobal) of London, UK.

Verified and validated by government scientific organizations globally, and coincidentally cited as best practice by the U.S. GAO, the TAA programme will be delivered by the UK company SCL, who have spent over $40 million and 25 years, developing this group behaviour prediction tool. In June and July of this year, upwards of 20 students from across the NATO Alliance will begin an eight-week training programme in Riga; Lesson 1, Day 1, Week 1 will explain to the assorted PsyOpers, StratComers and Intelligence Analysts from across the NATO Alliance why attitudes are such poor precursors to behaviours and why trying to make the audience "love us" ("us" may be substituted by ISAF, KFOR, U.S., UK or NATO, etc.) using mass advertising techniques is destined to fail.


Image

AT THE heart of TAA is the ability to empirically diagnose the exact groupings that exist within target populations. Knowing these groupings allows them to be ranked and the ranking depends upon the degree of influence they may have in either promoting or mitigating constructive behaviour. The methodology involves the comprehensive study of a social group of people. It examines this group of people across a host of psycho-social research parameters, and it does so in order to determine how best to change that group's behaviour.

Crucially, it goes much further than opinion polling, which can only examine attitudes. TAA is the decision-maker's tool, which will explain and forecast behaviour — and make scientifically justifiable recommendations to implement programmes to change problematic behaviours. Indeed, it is not simply research for the sake of greater understanding, but TAA achieves many of the crucial tasks that the planners require. Indeed, when undertaken properly, TAA employs innovative and rigorous primary research, drawing together qualitative, quantitative and other methods. This data is then triangulated with extensive expert elicitation and secondary research. It builds up a detailed understanding of current behaviour, values, attitudes, beliefs and norms, and examines everything from whether a group feels in control of its life, to who they respect, and what radio stations they listen to. TAA can be undertaken covertly. Audience groups are not necessarily aware that they are the research subjects and government's role and/or third parties can be invisible. In short, it is a tried, tested and proven methodology.

IF THERE is one lesson that Afghanistan must drum into everyone in the NATO community it is that understanding the audience is not a "nice to have" but an imperative pre-requisite for success.
Matt Cavanagh was a special adviser to the UK Labour Party. In an article for the RUSI journal, he writes: "No one inside the British [government] system knew much about the insurgency, the opium trade, or the local politics and tribal dynamics — or, just as importantly, how these different elements fitted into each other. Planners and policy makers [in 2006] did not know much about the human or even physical geography of Helmand."

The Pentagon's paper Five Lessons We Should Have Learned In Afghanistan notes: "what deploying soldiers really need to learn is how and why Afghans do certain things," whilst retired British Army Captain Dr Mike Martin wrote in his book An Intimate War: An Oral History Of The Helmand Conflict 1978- 2012, that "We [UK] often made the conflict worse, rather than better. This was usually as a result of the Helmandis' manipulating our ignorance (...) outsiders have most often misunderstood the struggle in Helmand."

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YOUNG UNMARRIED MALES PARAMETERS
STRATCOM "If there is one lesson that Afghanistan must drum into everyone in the NATO community it is that understanding the audience is not a nice to have but an imperative pre-requisite for success."


TAA, therefore, aims to fill this Population Intelligence gap by constructing a robust profile of the audience and how it can be influenced by an appropriately conceived and deployed message campaign. One key feature of this approach is that messages are developed in a bottom-up fashion, with them being constructed from a process of measurement and research, and subsequently derived from reliable knowledge of the audience. This is a significant change from the way the big PR and marketing companies work, in that their approach is a creative one and based on sending pre-determined messages in volume to mass audiences in the hope that they will resonate with some portions of that audience. This, of course, fits with the traditional way that the military conducts its business, where themes and messaging are crafted centrally and distributed downwards to theatre troops.

Experience from over 20 years of conflict communications tells me that Whitehall and Washington political messages are often a diluted and distant memory by the time they reach the tactical level, and they may actually have no relevance at ground level anyway. The huge amounts of data that are captured during this process can be daunting for policy-makers and strategists. This is why SCL's Gaby Van den Berg and Tom Wein have created a "dashboard" that quickly presents the information in a manageable format.

An early design example is illustrated: The picture above shows the various behavioural parameters associated with a real key target audience study — in this case "Young Unmarried Males", aged 18-24. The group was identified in the early stages of the TAA methodology as being the most influential from many identified groups in the area being studied. The black columns are key Behavioural Change Research Parameters, to their right you can see the various data points within those parameters and then a scoring system to assess their relevance to group behaviour. Finally, the white boxes to their right will form a basic traffic light system indicating how a particular course of action may or may not resonate with that audience. However, because this data is taken from a real life project some redaction has been made for operational security.

The picture below models the effect of an influence intervention — in this case the traffic lights quickly show that the large injection of money into the problem would resonate badly on the behavioural research parameters for the target group. Thus, using this model potential strategy can be modeled to a very high degree of accuracy.

It should therefore be clear why the empirical TAA approach is far more effective than simple marketing approaches, or even cultural understanding. There exists no universal communication model applicable to all groups and cultures. All communication efforts must be tailored to the local dynamics, and with respect to the behaviours one is seeking to change. Because audiences are multi-faceted and cannot be grouped as a population, influencing the differing component groups of a society requires precisely targeted methods and approaches: One message — no matter how culturally relevant — does not fit all. Working out who to influence, why, how, when, and whether it is possible, constitutes the first steps of TAA. Often, it will be necessary to influence one group in order to influence another. Above all else, the process of influencing is not necessarily to make a particular group like "us" or "our" ideas — although this is always an extra "bonus."

There are some further issues with TAA that merit consideration. If we think of TAA as the process of identifying the "right" audience, we must also be mindful that there are other audiences also present. We might think of them in four groups, and the messages that we deploy may well cast a shadow upon them. They are:

— The target audience;
— A group who may react positively to the messaging applied to the target;
— A group who may react negatively to the messaging applied to the target; and,

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YOUNG UNMARRIED MALES PARAMETERS FINANCIAL AID

THERE HAS BEEN A GRADUAL REALIZATION THAT TAA IS A KEY COMPONENT IN FUTURE OPERATIONS.


There has been a gradual realization that TAA is a key component in future operations, and commercial companies are increasingly making claim to these skills. To understand TAA capabilities better, one of my final tasks in the UK Ministry of Defence last year was to define three tiers of TAA capability: Tiers 1, 2 and 3, which are presented briefly below:

Tier 3 TAA is the least detailed TAA and is almost exclusively secondary research. This is typical remote, open source analysis of target groups, but these analyses are done in the language of the analyst as opposed to that of the target group. This may be an internet-based research project on a specific group — for example, Alawites in Syria or the Kurds in Iraq. Invariably, it will try to find third party studies, perhaps academic or NGO, and aggregate the information for military usage. Although this is invariably open source, it may also involve classified intelligence. The UK has defined output of Tier 3 TAA as assumed information.

Tier 2 TAA is any primary research involving actual contact with the audiences of interest but, critically, it does not follow any specific scientifically verified deductive methodology. It may be conducted in-country or remotely and is largely attitudinally-based. The output of Tier 2 TAA is information recorded from interactions with target audiences. An example of Tier 2 TAA is a patrol report or a shura, where soldiers ask locals what they think is going on and what actions might positively change attitudes and behaviours. A refined variation might be Cultural Advisors (CULAD) on patrol. This type of TAA is typically undertaken by coalition PsyOps forces and it may with time become quite detailed. It provides another layer of data over and above that of Tier 3.

By far the most useful TAA, however, is Tier 1. This is a multi-source, scientifically verified, diagnostic methodology undertaken in-country and in host language, and it is used to identify specific motivations for behaviour. The output of Tier 1 TAA is information deduced from methodically gathered data, which is tested against a scientifically derived hypothesis.

So, for nearly eight weeks this summer, students from across NATO will study at the Latvian Defence Academy and learn how to undertake Tier 1 TAA, and with those skills return back to their respective commands and HQs with the mission of improving organic StratCom capabilities. Leon Wieseltier, American writer, critic, philosopher and magazine editor once wrote that "The doctrine of 'exit strategy' fundamentally misunderstands the nature of war and the nature of historical action. The knowledge of the end is not given to us at the beginning." But, perhaps, better armed with science-based TAA in the future, maybe that knowledge will be with us at the start, not just at the end like the jet engine, and our joint communication efforts will then be truly strategic.

Dr Steve Tatham is the contracted Subject Matter Expert for StratCom and TAA at the NATO CoE for Strategic Communications in Riga. He served for 26 years in the UK Armed Forces, commanding the UK PsyOps Group on operations and, in his last appointment, as the Special Project's Officer in the MoD's Military Strategic Effects Department. Dr Tatham holds a Ph.D. in "Strategic Communication in Conflict" and, with Generals Andrew Mackay and Stanley McChrystal, he is the author of "Behavioural Conflict", the seminal text book on how to conduct information operations in conflict.

Anyone wishing further guidance on TAA is invited to contact the author by email on: steve.tatham@iota-global.com
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Re: After working for Trump’s campaign, British data firm ey

Postby admin » Wed Mar 28, 2018 8:26 pm

The Cambridge Analytica Files
‘I made Steve Bannon’s psychological warfare tool’: meet the data war whistleblower
by Carole Cadwalladr
Sun 18 Mar 2018 05.44 EDT First published on Sat 17 Mar 2018 14.00 EDT

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He was the gay Canadian vegan ... diagnosed with ADHD and dyslexia....At six, while at school, Wylie was abused by a mentally unstable person. The school tried to cover it up, blaming his parents, and a long court battle followed. Wylie’s childhood and school career never recovered....His career trajectory has been, like most aspects of his life so far, extraordinary, preposterous, implausible .... He left school at 16 without a single qualification. Yet at 17, he was working in the office of the leader of the Canadian opposition; at 18, he went to learn all things data from Obama’s national director of targeting, which he then introduced to Canada for the Liberal party. At 19, he taught himself to code, and in 2010, age 20, he came to London to study law at the London School of Economics ... Another Lib Dem connection introduced Wylie to a company called SCL Group ....Alexander Nix, then CEO of SCL Elections, made Wylie an offer he couldn’t resist....The job was research director across the SCL group, a private contractor that has both defence and elections operations. Its defence arm was a contractor to the UK’s Ministry of Defence and the US’s Department of Defense ... the British government has paid SCL to conduct counter-extremism operations in the Middle East, and the US Department of Defense has contracted it to work in Afghanistan.... "It’s like dirty MI6 because you’re not constrained"....A few months later, in autumn 2013, Wylie met Steve Bannon ...It was Bannon who took this idea to the Mercers....Nix and Wylie flew to New York to meet the Mercers ...I come to think of his pink hair as a false-flag operation ... Cambridge Analytica is Chris’s Frankenstein. He created it. It’s his data Frankenmonster. And now he’s trying to put it right.

-- The Cambridge Analytica Files, by Carole Cadwalladr


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For more than a year we’ve been investigating Cambridge Analytica and its links to the Brexit Leave campaign in the UK and Team Trump in the US presidential election. Now, 28-year-old Christopher Wylie goes on the record to discuss his role in hijacking the profiles of millions of Facebook users in order to target the US electorate

The first time I met Christopher Wylie, he didn’t yet have pink hair. That comes later. As does his mission to rewind time. To put the genie back in the bottle.

By the time I met him in person, I’d already been talking to him on a daily basis for hours at a time. On the phone, he was clever, funny, bitchy, profound, intellectually ravenous, compelling. A master storyteller. A politicker. A data science nerd.

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Cambridge Analytica whistleblower: 'We spent $1m harvesting millions of Facebook profiles' – video

Two months later, when he arrived in London from Canada, he was all those things in the flesh. And yet the flesh was impossibly young. He was 27 then (he’s 28 now), a fact that has always seemed glaringly at odds with what he has done. He may have played a pivotal role in the momentous political upheavals of 2016. At the very least, he played a consequential role. At 24, he came up with an idea that led to the foundation of a company called Cambridge Analytica, a data analytics firm that went on to claim a major role in the Leave campaign for Britain’s EU membership referendum, and later became a key figure in digital operations during Donald Trump’s election campaign.

Or, as Wylie describes it, he was the gay Canadian vegan who somehow ended up creating “Steve Bannon’s psychological warfare mindfuck tool”.

In 2014, Steve Bannon – then executive chairman of the “alt-right” news network Breitbart – was Wylie’s boss. And Robert Mercer, the secretive US hedge-fund billionaire and Republican donor, was Cambridge Analytica’s investor. And the idea they bought into was to bring big data and social media to an established military methodology – “information operations” – then turn it on the US electorate.

It was Wylie who came up with that idea and oversaw its realisation.
And it was Wylie who, last spring, became my source. In May 2017, I wrote an article headlined “The great British Brexit robbery”, which set out a skein of threads that linked Brexit to Trump to Russia. Wylie was one of a handful of individuals who provided the evidence behind it. I found him, via another Cambridge Analytica ex-employee, lying low in Canada: guilty, brooding, indignant, confused. “I haven’t talked about this to anyone,” he said at the time. And then he couldn’t stop talking.

By that time, Steve Bannon had become Trump’s chief strategist. Cambridge Analytica’s parent company, SCL, had won contracts with the US State Department and was pitching to the Pentagon, and Wylie was genuinely freaked out. “It’s insane,” he told me one night. “The company has created psychological profiles of 230 million Americans. And now they want to work with the Pentagon? It’s like Nixon on steroids.”

As part of its outreach to U.S. officials, SCL is touting more than 20 years of experience in shaping voter perceptions and advising militaries and governments around the world on how to conduct effective psychological operations....

Alexander Nix, a senior SCL executive who has overseen its U.S. expansion, confirmed the recent outreach to federal agencies and acknowledged that the company was stepping up its efforts to secure U.S. government business. He said that the push is an extension of the work the company has done as a subcontractor on a variety of government projects during the last 14 years — and that SCL would have sought the new work no matter who had won the election.

“We’re clearly seeking to augment our existing client services and products with some of the new technologies we’ve been developing in our other sectors, such as the political field,” he said in a phone interview. “But this is not a radical shake-up or anything new.”

“I’d like to think that regardless of the outcome of the election, we’d be working in this space,” Nix added and said he has not communicated with Bannon about the company’s work. “We’ve survived different administrations from left and right of the aisle, with different policy agendas.”...

SCL’s main offering, first developed by its affiliated London think tank in 1989, involves gathering vast quantities of data about an audience’s values, attitudes and beliefs, identifying groups of “persuadables” and then targeting them with tailored messages. SCL began testing the technique on health and development campaigns in Britain in the early 1990s, then branched out into international political consulting and later defense contracting....

SCL, which says it has worked in 100 countries, offers military clients techniques in “soft power.” Nix described it as a modern-day upgrade of early efforts to win over a foreign population by dropping propaganda leaflets from the air.

In a 2015 article for a NATO publication, Steve Tatham, a British military psyops expert who leads SCL’s defense business outside of the United States, explained that one of the benefits of using the company’s techniques is that it “can be undertaken covertly.”

“Audience groups are not necessarily aware that they are the research subjects and government’s role and/or third parties can be invisible,” he wrote.

In the United States, the company’s efforts to win new government contracts are being led by Josh Weerasinghe, a former vice president of global market development at defense giant BAE Systems who previously worked with Flynn at the Office of the Director of National Intelligence. Flynn served as an adviser to SCL on its efforts to expand its contracting work, according to two people familiar with his role....

“We have been doing this for nearly 30 years,” he said. “I suppose if it didn’t work, we wouldn’t still be in business and we wouldn’t still be growing.”

-- After working for Trump’s campaign, British data firm eyes new U.S. government contracts, by Matea Gold and Frances Stead Sellers


He ended up showing me a tranche of documents that laid out the secret workings behind Cambridge Analytica. And in the months following publication of my article in May, it was revealed that the company had “reached out” to WikiLeaks to help distribute Hillary Clinton’s stolen emails in 2016. And then we watched as it became a subject of special counsel Robert Mueller’s investigation into possible Russian collusion in the US election.

The Observer also received the first of three letters from Cambridge Analytica threatening to sue Guardian News and Media for defamation. We are still only just starting to understand the maelstrom of forces that came together to create the conditions for what Mueller confirmed last month was “information warfare”. But Wylie offers a unique, worm’s-eye view of the events of 2016. Of how Facebook was hijacked, repurposed to become a theatre of war: how it became a launchpad for what seems to be an extraordinary attack on the US’s democratic process.

As early as 2012, the U.S. GAO had concluded that: "the [U.S. StratCom] programs are inadequately tracked, their impact unclear, and the military doesn't know if it is targeting the right foreign audiences." What is needed now is a "divorce" and at last this is happening in the newly established Centre of Excellence (CoE) for Strategic Communications in Riga, Latvia, where the vision and focus are very much on the "audience" and its actual behaviour, not on the synchronisation across varied themes and perceptions. By courtesy of a CAD $1-million donation to the StratCom CoE, the Centre will soon be an accredited training facility using Behavioural Dynamics Institute's "Target Audience Analysis Methodology" through a Train the Trainer Programme — a purposebuilt NATO course developed and delivered by the Strategic Communications Laboratories Group (SCL) and Information Operations Training and Advisory Services Global (IOTAGlobal) of London, UK.

Verified and validated by government scientific organizations globally, and coincidentally cited as best practice by the U.S. GAO, the TAA programme will be delivered by the UK company SCL, who have spent over $40 million and 25 years, developing this group behaviour prediction tool. In June and July of this year, upwards of 20 students from across the NATO Alliance will begin an eight-week training programme in Riga; Lesson 1, Day 1, Week 1 will explain to the assorted PsyOpers, StratComers and Intelligence Analysts from across the NATO Alliance why attitudes are such poor precursors to behaviours and why trying to make the audience "love us" ("us" may be substituted by ISAF, KFOR, U.S., UK or NATO, etc.) using mass advertising techniques is destined to fail.

AT THE heart of TAA is the ability to empirically diagnose the exact groupings that exist within target populations. Knowing these groupings allows them to be ranked and the ranking depends upon the degree of influence they may have in either promoting or mitigating constructive behaviour. The methodology involves the comprehensive study of a social group of people. It examines this group of people across a host of psycho-social research parameters, and it does so in order to determine how best to change that group's behaviour.

Crucially, it goes much further than opinion polling, which can only examine attitudes. TAA is the decision-maker's tool, which will explain and forecast behaviour — and make scientifically justifiable recommendations to implement programmes to change problematic behaviours. Indeed, it is not simply research for the sake of greater understanding, but TAA achieves many of the crucial tasks that the planners require. Indeed, when undertaken properly, TAA employs innovative and rigorous primary research, drawing together qualitative, quantitative and other methods. This data is then triangulated with extensive expert elicitation and secondary research. It builds up a detailed understanding of current behaviour, values, attitudes, beliefs and norms, and examines everything from whether a group feels in control of its life, to who they respect, and what radio stations they listen to. TAA can be undertaken covertly. Audience groups are not necessarily aware that they are the research subjects and government's role and/or third parties can be invisible. In short, it is a tried, tested and proven methodology.

IF THERE is one lesson that Afghanistan must drum into everyone in the NATO community it is that understanding the audience is not a "nice to have" but an imperative pre-requisite for success.

-- Target Audience Analysis, by Cdr (Rtd.) Dr Steve Tatham Ph.D., Royal Navy, StratCom and TAA Subject Matter Expert


Wylie oversaw what may have been the first critical breach. Aged 24, while studying for a PhD in fashion trend forecasting, he came up with a plan to harvest the Facebook profiles of millions of people in the US, and to use their private and personal information to create sophisticated psychological and political profiles. And then target them with political ads designed to work on their particular psychological makeup.

“We ‘broke’ Facebook,” he says.

And he did it on behalf of his new boss, Steve Bannon.

“Is it fair to say you ‘hacked’ Facebook?” I ask him one night.

He hesitates. “I’ll point out that I assumed it was entirely legal and above board.”

Last month, Facebook’s UK director of policy, Simon Milner, told British MPs on a select committee inquiry into fake news, chaired by Conservative MP Damian Collins, that Cambridge Analytica did not have Facebook data. The official Hansard extract reads:

Christian Matheson (MP for Chester): “Have you ever passed any user information over to Cambridge Analytica or any of its associated companies?”

Simon Milner: “No.”

Matheson: “But they do hold a large chunk of Facebook’s user data, don’t they?”

Milner: “No. They may have lots of data, but it will not be Facebook user data. It may be data about people who are on Facebook that they have gathered themselves, but it is not data that we have provided.”

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Alexander Nix, Cambridge Analytica CEO. Photograph: The Washington Post/Getty Images

Two weeks later, on 27 February, as part of the same parliamentary inquiry, Rebecca Pow, MP for Taunton Deane, asked Cambridge Analytica’s CEO, Alexander Nix: “Does any of the data come from Facebook?” Nix replied: “We do not work with Facebook data and we do not have Facebook data.”

And through it all, Wylie and I, plus a handful of editors and a small, international group of academics and researchers, have known that – at least in 2014 – that certainly wasn’t the case, because Wylie has the paper trail. In our first phone call, he told me he had the receipts, invoices, emails, legal letters – records that showed how, between June and August 2014, the profiles of more than 50 million Facebook users had been harvested. Most damning of all, he had a letter from Facebook’s own lawyers admitting that Cambridge Analytica had acquired the data illegitimately.

Going public involves an enormous amount of risk. Wylie is breaking a non-disclosure agreement and risks being sued. He is breaking the confidence of Steve Bannon and Robert Mercer.

It’s taken a rollercoaster of a year to help get Wylie to a place where it’s possible for him to finally come forward. A year in which Cambridge Analytica has been the subject of investigations on both sides of the Atlantic – Robert Mueller’s in the US, and separate inquiries by the Electoral Commission and the Information Commissioner’s Office in the UK, both triggered in February 2017, after the Observer’s first article in this investigation.

It has been a year, too, in which Wylie has been trying his best to rewind – to undo events that he set in motion. Earlier this month, he submitted a dossier of evidence to the Information Commissioner’s Office and the National Crime Agency’s cybercrime unit. He is now in a position to go on the record: the data nerd who came in from the cold.

There are many points where this story could begin. One is in 2012, when Wylie was 21 and working for the Liberal Democrats in the UK, then in government as junior coalition partners. His career trajectory has been, like most aspects of his life so far, extraordinary, preposterous, implausible.

Wylie grew up in British Columbia and as a teenager he was diagnosed with ADHD and dyslexia. He left school at 16 without a single qualification. Yet at 17, he was working in the office of the leader of the Canadian opposition; at 18, he went to learn all things data from Obama’s national director of targeting, which he then introduced to Canada for the Liberal party. At 19, he taught himself to code, and in 2010, age 20, he came to London to study law at the London School of Economics.

“Politics is like the mob, though,” he says. “You never really leave. I got a call from the Lib Dems. They wanted to upgrade their databases and voter targeting. So, I combined working for them with studying for my degree.”


Politics is also where he feels most comfortable. He hated school, but as an intern in the Canadian parliament he discovered a world where he could talk to adults and they would listen. He was the kid who did the internet stuff and within a year he was working for the leader of the opposition.

It showed these odd patterns. People who liked 'I hate Israel' on Facebook also tended to like KitKats


“He’s one of the brightest people you will ever meet,” a senior politician who’s known Wylie since he was 20 told me. “Sometimes that’s a blessing and sometimes a curse.”

Meanwhile, at Cambridge University’s Psychometrics Centre, two psychologists, Michal Kosinski and David Stillwell, were experimenting with a way of studying personality – by quantifying it.

Starting in 2007, Stillwell, while a student, had devised various apps for Facebook, one of which, a personality quiz called myPersonality, had gone viral. Users were scored on “big five” personality traits – Openness, Conscientiousness, Extroversion, Agreeableness and Neuroticism – and in exchange, 40% of them consented to give him access to their Facebook profiles. Suddenly, there was a way of measuring personality traits across the population and correlating scores against Facebook “likes” across millions of people.


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Examples, above and below, of the visual messages trialled by GSR’s online profiling test. Respondents were asked: How important should this message be to all Americans?

The research was original, groundbreaking and had obvious possibilities. “They had a lot of approaches from the security services,” a member of the centre told me. “There was one called You Are What You Like and it was demonstrated to the intelligence services. And it showed these odd patterns; that, for example, people who liked ‘I hate Israel’ on Facebook also tended to like Nike shoes and KitKats.

“There are agencies that fund research on behalf of the intelligence services. And they were all over this research. That one was nicknamed Operation KitKat.”

The defence and military establishment were the first to see the potential of the research. Boeing, a major US defence contractor, funded Kosinski’s PhD and Darpa, the US government’s secretive Defense Advanced Research Projects Agency, is cited in at least two academic papers supporting Kosinski’s work.


But when, in 2013, the first major paper was published, others saw this potential too, including Wylie. He had finished his degree and had started his PhD in fashion forecasting, and was thinking about the Lib Dems. It is fair to say that he didn’t have a clue what he was walking into.

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An example of the visual messages trialled by GSR’s online profiling test. Respondents were asked: How important should this message be to all Americans?

“I wanted to know why the Lib Dems sucked at winning elections when they used to run the country up to the end of the 19th century,” Wylie explains. “And I began looking at consumer and demographic data to see what united Lib Dem voters, because apart from bits of Wales and the Shetlands it’s weird, disparate regions. And what I found is there were no strong correlations. There was no signal in the data.

“And then I came across a paper about how personality traits could be a precursor to political behaviour, and it suddenly made sense. Liberalism is correlated with high openness and low conscientiousness, and when you think of Lib Dems they’re absent-minded professors and hippies. They’re the early adopters… they’re highly open to new ideas. And it just clicked all of a sudden.”

Here was a way for the party to identify potential new voters. The only problem was that the Lib Dems weren’t interested.

“I did this presentation at which I told them they would lose half their 57 seats, and they were like: ‘Why are you so pessimistic?’ They actually lost all but eight of their seats, FYI.”

Another Lib Dem connection introduced Wylie to a company called SCL Group, one of whose subsidiaries, SCL Elections, would go on to create Cambridge Analytica (an incorporated venture between SCL Elections and Robert Mercer, funded by the latter). For all intents and purposes, SCL/Cambridge Analytica are one and the same.

Alexander Nix, then CEO of SCL Elections, made Wylie an offer he couldn’t resist. “He said: ‘We’ll give you total freedom. Experiment. Come and test out all your crazy ideas.’”

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An example of the visual messages trialled by GSR’s online profiling test. Respondents were asked: How important should this message be to all Americans?

In the history of bad ideas, this turned out to be one of the worst. The job was research director across the SCL group, a private contractor that has both defence and elections operations. Its defence arm was a contractor to the UK’s Ministry of Defence and the US’s Department of Defense, among others. Its expertise was in “psychological operations” – or psyops – changing people’s minds not through persuasion but through “informational dominance”, a set of techniques that includes rumour, disinformation and fake news.

SCL Elections had used a similar suite of tools in more than 200 elections around the world
, mostly in undeveloped democracies that Wylie would come to realise were unequipped to defend themselves.

Wylie holds a British Tier 1 Exceptional Talent visa – a UK work visa given to just 200 people a year. He was working inside government (with the Lib Dems) as a political strategist with advanced data science skills. But no one, least of all him, could have predicted what came next. When he turned up at SCL’s offices in Mayfair, he had no clue that he was walking into the middle of a nexus of defence and intelligence projects, private contractors and cutting-edge cyberweaponry.

“The thing I think about all the time is, what if I’d taken a job at Deloitte instead? They offered me one. I just think if I’d taken literally any other job, Cambridge Analytica wouldn’t exist. You have no idea how much I brood on this.”

A few months later, in autumn 2013, Wylie met Steve Bannon. At the time, he was editor-in-chief of Breitbart, which he had brought to Britain to support his friend Nigel Farage in his mission to take Britain out of the European Union.

What was he like?

“Smart,” says Wylie. “Interesting. Really interested in ideas. He’s the only straight man I’ve ever talked to about intersectional feminist theory. He saw its relevance straightaway to the oppressions that conservative, young white men feel.”

Wylie meeting Bannon was the moment petrol was poured on a flickering flame. Wylie lives for ideas. He speaks 19 to the dozen for hours at a time. He had a theory to prove. And at the time, this was a purely intellectual problem. Politics was like fashion, he told Bannon.

If you do not respect the agency of people, anything you do after that point is not conducive to democracy
-- Christopher Wylie


“[Bannon] got it immediately. He believes in the whole Andrew Breitbart doctrine that politics is downstream from culture, so to change politics you need to change culture. And fashion trends are a useful proxy for that. Trump is like a pair of Uggs, or Crocs, basically. So how do you get from people thinking ‘Ugh. Totally ugly’ to the moment when everyone is wearing them? That was the inflection point he was looking for.”

But Wylie wasn’t just talking about fashion. He had recently been exposed to a new discipline: “information operations”, which ranks alongside land, sea, air and space in the US military’s doctrine of the “five-dimensional battle space”. His brief ranged across the SCL Group – the British government has paid SCL to conduct counter-extremism operations in the Middle East, and the US Department of Defense has contracted it to work in Afghanistan.

I tell him that another former employee described the firm as “MI6 for hire”, and I’d never quite understood it.

“It’s like dirty MI6 because you’re not constrained. There’s no having to go to a judge to apply for permission. It’s normal for a ‘market research company’ to amass data on domestic populations. And if you’re working in some country and there’s an auxiliary benefit to a current client with aligned interests, well that’s just a bonus.”

When I ask how Bannon even found SCL, Wylie tells me what sounds like a tall tale, though it’s one he can back up with an email about how Mark Block, a veteran Republican strategist, happened to sit next to a cyberwarfare expert for the US air force on a plane. “And the cyberwarfare guy is like, ‘Oh, you should meet SCL. They do cyberwarfare for elections.’”

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Steve Bannon: ‘He loved the gays,’ says Wylie. ‘He saw us as early adopters.’ Photograph: Tony Gentile/Reuters

It was Bannon who took this idea to the Mercers: Robert Mercer – the co-CEO of the hedge fund Renaissance Technologies, who used his billions to pursue a rightwing agenda, donating to Republican causes and supporting Republican candidates – and his daughter Rebekah.

Nix and Wylie flew to New York to meet the Mercers in Rebekah’s Manhattan apartment.

“She loved me. She was like, ‘Oh we need more of your type on our side!’”

Your type?

“The gays. She loved the gays. So did Steve [Bannon]. He saw us as early adopters. He figured, if you can get the gays on board, everyone else will follow. It’s why he was so into the whole Milo [Yiannopoulos] thing.”

Robert Mercer was a pioneer in AI and machine translation. He helped invent algorithmic trading – which replaced hedge fund managers with computer programs – and he listened to Wylie’s pitch. It was for a new kind of political message-targeting based on an influential and groundbreaking 2014 paper researched at Cambridge’s Psychometrics Centre, called: “Computer-based personality judgments are more accurate than those made by humans”.

“In politics, the money man is usually the dumbest person in the room. Whereas it’s the opposite way around with Mercer,” says Wylie. “He said very little, but he really listened. He wanted to understand the science. And he wanted proof that it worked.”

And to do that, Wylie needed data.

How Cambridge Analytica acquired the data has been the subject of internal reviews at Cambridge University, of many news articles and much speculation and rumour.

When Nix was interviewed by MPs last month, Damian Collins asked him:

“Does any of your data come from Global Science Research company?”

Nix: “GSR?”

Collins: “Yes.”

Nix: “We had a relationship with GSR. They did some research for us back in 2014. That research proved to be fruitless and so the answer is no.”

Collins: “They have not supplied you with data or information?”

Nix: “No.”

Collins: “Your datasets are not based on information you have received from them?”

Nix: “No.”

Collins: “At all?”

Nix: “At all.”

The problem with Nix’s response to Collins is that Wylie has a copy of an executed contract, dated 4 June 2014, which confirms that SCL, the parent company of Cambridge Analytica, entered into a commercial arrangement with a company called Global Science Research (GSR), owned by Cambridge-based academic Aleksandr Kogan, specifically premised on the harvesting and processing of Facebook data, so that it could be matched to personality traits and voter rolls.

He has receipts showing that Cambridge Analytica spent $7m to amass this data, about $1m of it with GSR. He has the bank records and wire transfers. Emails reveal Wylie first negotiated with Michal Kosinski, one of the co-authors of the original myPersonality research paper, to use the myPersonality database. But when negotiations broke down, another psychologist, Aleksandr Kogan, offered a solution that many of his colleagues considered unethical. He offered to replicate Kosinski and Stillwell’s research and cut them out of the deal. For Wylie it seemed a perfect solution. “Kosinski was asking for $500,000 for the IP but Kogan said he could replicate it and just harvest his own set of data.”
(Kosinski says the fee was to fund further research.)

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An unethical solution? Dr Aleksandr Kogan Photograph: alex kogan

Kogan then set up GSR to do the work, and proposed to Wylie they use the data to set up an interdisciplinary institute working across the social sciences. “What happened to that idea,” I ask Wylie. “It never happened. I don’t know why. That’s one of the things that upsets me the most.”

It was Bannon’s interest in culture as war that ignited Wylie’s intellectual concept. But it was Robert Mercer’s millions that created a firestorm. Kogan was able to throw money at the hard problem of acquiring personal data: he advertised for people who were willing to be paid to take a personality quiz on Amazon’s Mechanical Turk and Qualtrics. At the end of which Kogan’s app, called thisismydigitallife, gave him permission to access their Facebook profiles. And not just theirs, but their friends’ too. On average, each “seeder” – the people who had taken the personality test, around 320,000 in total – unwittingly gave access to at least 160 other people’s profiles, none of whom would have known or had reason to suspect.

What the email correspondence between Cambridge Analytica employees and Kogan shows is that Kogan had collected millions of profiles in a matter of weeks. But neither Wylie nor anyone else at Cambridge Analytica had checked that it was legal. It certainly wasn’t authorised. Kogan did have permission to pull Facebook data, but for academic purposes only. What’s more, under British data protection laws, it’s illegal for personal data to be sold to a third party without consent.

“Facebook could see it was happening,” says Wylie. “Their security protocols were triggered because Kogan’s apps were pulling this enormous amount of data, but apparently Kogan told them it was for academic use. So they were like, ‘Fine’.”

Kogan maintains that everything he did was legal and he had a “close working relationship” with Facebook, which had granted him permission for his apps.


Cambridge Analytica had its data. This was the foundation of everything it did next – how it extracted psychological insights from the “seeders” and then built an algorithm to profile millions more.

For more than a year, the reporting around what Cambridge Analytica did or didn’t do for Trump has revolved around the question of “psychographics”, but Wylie points out: “Everything was built on the back of that data. The models, the algorithm. Everything. Why wouldn’t you use it in your biggest campaign ever?”

In December 2015, the Guardian’s Harry Davies published the first report about Cambridge Analytica acquiring Facebook data and using it to support Ted Cruz in his campaign to be the US Republican candidate. But it wasn’t until many months later that Facebook took action. And then, all they did was write a letter. In August 2016, shortly before the US election, and two years after the breach took place, Facebook’s lawyers wrote to Wylie, who left Cambridge Analytica in 2014, and told him the data had been illicitly obtained and that “GSR was not authorised to share or sell it”. They said it must be deleted immediately.

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Christopher Wylie: ‘It’s like Nixon on steroids’

“I already had. But literally all I had to do was tick a box and sign it and send it back, and that was it,” says Wylie. “Facebook made zero effort to get the data back.”

There were multiple copies of it. It had been emailed in unencrypted files.

Cambridge Analytica rejected all allegations the Observer put to them.

Dr Kogan – who later changed his name to Dr Spectre, but has subsequently changed it back to Dr Kogan – is still a faculty member at Cambridge University, a senior research associate. But what his fellow academics didn’t know until Kogan revealed it in emails to the Observer (although Cambridge University says that Kogan told the head of the psychology department), is that he is also an associate professor at St Petersburg University. Further research revealed that he’s received grants from the Russian government to research “Stress, health and psychological well-being in social networks”. The opportunity came about on a trip to the city to visit friends and family, he said.

There are other dramatic documents in Wylie’s stash, including a pitch made by Cambridge Analytica to Lukoil, Russia’s second biggest oil producer. In an email dated 17 July 2014, about the US presidential primaries, Nix wrote to Wylie: “We have been asked to write a memo to Lukoil (the Russian oil and gas company) to explain to them how our services are going to apply to the petroleum business. Nix said that “they understand behavioural microtargeting in the context of elections” but that they were “failing to make the connection between voters and their consumers”. The work, he said, would be “shared with the CEO of the business”, a former Soviet oil minister and associate of Putin, Vagit Alekperov.

“It didn’t make any sense to me,” says Wylie. “I didn’t understand either the email or the pitch presentation we did. Why would a Russian oil company want to target information on American voters?”


Mueller’s investigation traces the first stages of the Russian operation to disrupt the 2016 US election back to 2014, when the Russian state made what appears to be its first concerted efforts to harness the power of America’s social media platforms, including Facebook. And it was in late summer of the same year that Cambridge Analytica presented the Russian oil company with an outline of its datasets, capabilities and methodology. The presentation had little to do with “consumers”. Instead, documents show it focused on election disruption techniques. The first slide illustrates how a “rumour campaign” spread fear in the 2007 Nigerian election – in which the company worked – by spreading the idea that the “election would be rigged”. The final slide, branded with Lukoil’s logo and that of SCL Group and SCL Elections, headlines its “deliverables”: “psychographic messaging”.

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Robert Mercer with his daughter Rebekah. Photograph: Sean Zanni/Getty Images

Lukoil is a private company, but its CEO, Alekperov, answers to Putin, and it’s been used as a vehicle of Russian influence in Europe and elsewhere – including in the Czech Republic, where in 2016 it was revealed that an adviser to the strongly pro-Russian Czech president was being paid by the company.

When I asked Bill Browder – an Anglo-American businessman who is leading a global campaign for a Magnitsky Act to enforce sanctions against Russian individuals – what he made of it, he said: “Everyone in Russia is subordinate to Putin. One should be highly suspicious of any Russian company pitching anything outside its normal business activities.”

Last month, Nix told MPs on the parliamentary committee investigating fake news: “We have never worked with a Russian organisation in Russia or any other company. We do not have any relationship with Russia or Russian individuals.”

There’s no evidence that Cambridge Analytica ever did any work for Lukoil. What these documents show, though, is that in 2014 one of Russia’s biggest companies was fully briefed on: Facebook, microtargeting, data, election disruption.


Cambridge Analytica is “Chris’s Frankenstein”, says a friend of his. “He created it. It’s his data Frankenmonster. And now he’s trying to put it right.”

Only once has Wylie made the case of pointing out that he was 24 at the time. But he was. He thrilled to the intellectual possibilities of it. He didn’t think of the consequences. And I wonder how much he’s processed his own role or responsibility in it. Instead, he’s determined to go on the record and undo this thing he has created.

Because the past few months have been like watching a tornado gathering force. And when Wylie turns the full force of his attention to something – his strategic brain, his attention to detail, his ability to plan 12 moves ahead – it is sometimes slightly terrifying to behold. Dealing with someone trained in information warfare has its own particular challenges, and his suite of extraordinary talents include the kind of high-level political skills that makes House of Cards look like The Great British Bake Off. And not everyone’s a fan. Any number of ex-colleagues – even the ones who love him – call him “Machiavellian”. Another described the screaming matches he and Nix would have.

“What do your parents make of your decision to come forward?” I ask him.

“They get it. My dad sent me a cartoon today, which had two characters hanging off a cliff, and the first one’s saying ‘Hang in there.’ And the other is like: ‘Fuck you.’”

Which are you?

“Probably both.”

What isn’t in doubt is what a long, fraught journey it has been to get to this stage. And how fearless he is.

After many months, I learn the terrible, dark backstory that throws some light on his determination, and which he discusses candidly. At six, while at school, Wylie was abused by a mentally unstable person. The school tried to cover it up, blaming his parents, and a long court battle followed. Wylie’s childhood and school career never recovered. His parents – his father is a doctor and his mother is a psychiatrist – were wonderful, he says. “But they knew the trajectory of people who are put in that situation, so I think it was particularly difficult for them, because they had a deeper understanding of what that does to a person long term.”

Facebook has denied and denied this. It has failed in its duties to respect the law
-- Paul-Olivier Dehaye


He says he grew up listening to psychologists discuss him in the third person, and, aged 14, he successfully sued the British Columbia Ministry of Education and forced it to change its inclusion policies around bullying. What I observe now is how much he loves the law, lawyers, precision, order. I come to think of his pink hair as a false-flag operation. What he cannot tolerate is bullying.

Is what Cambridge Analytica does akin to bullying?

“I think it’s worse than bullying,” Wylie says. “Because people don’t necessarily know it’s being done to them. At least bullying respects the agency of people because they know. So it’s worse, because if you do not respect the agency of people, anything that you’re doing after that point is not conducive to a democracy. And fundamentally, information warfare is not conducive to democracy.”

Russia, Facebook, Trump, Mercer, Bannon, Brexit. Every one of these threads runs through Cambridge Analytica. Even in the past few weeks, it seems as if the understanding of Facebook’s role has broadened and deepened. The Mueller indictments were part of that, but Paul-Olivier Dehaye – a data expert and academic based in Switzerland, who published some of the first research into Cambridge Analytica’s processes – says it’s become increasingly apparent that Facebook is “abusive by design”. If there is evidence of collusion between the Trump campaign and Russia, it will be in the platform’s data flows, he says. And Wylie’s revelations only move it on again.

“Facebook has denied and denied and denied this,” Dehaye says when told of the Observer’s new evidence. “It has misled MPs and congressional investigators and it’s failed in its duties to respect the law. It has a legal obligation to inform regulators and individuals about this data breach, and it hasn’t. It’s failed time and time again to be open and transparent.”

Facebook denies that the data transfer was a breach. In addition, a spokesperson said: “Protecting people’s information is at the heart of everything we do, and we require the same from people who operate apps on Facebook. If these reports are true, it’s a serious abuse of our rules. Both Aleksandr Kogan as well as the SCL Group and Cambridge Analytica certified to us that they destroyed the data in question.”

Millions of people’s personal information was stolen and used to target them in ways they wouldn’t have seen, and couldn’t have known about, by a mercenary outfit, Cambridge Analytica, who, Wylie says, “would work for anyone”. Who would pitch to Russian oil companies. Would they subvert elections abroad on behalf of foreign governments?

It occurs to me to ask Wylie this one night.

“Yes.”

Nato or non-Nato?

“Either. I mean they’re mercenaries. They’ll work for pretty much anyone who pays.”

It’s an incredible revelation. It also encapsulates all of the problems of outsourcing – at a global scale, with added cyberweapons. And in the middle of it all are the public – our intimate family connections, our “likes”, our crumbs of personal data, all sucked into a swirling black hole that’s expanding and growing and is now owned by a politically motivated billionaire.

The Facebook data is out in the wild. And for all Wylie’s efforts, there’s no turning the clock back.

Tamsin Shaw, a philosophy professor at New York University, and the author of a recent New York Review of Books article on cyberwar and the Silicon Valley economy, told me that she’d pointed to the possibility of private contractors obtaining cyberweapons that had at least been in part funded by US defence.

She calls Wylie’s disclosures “wild” and points out that “the whole Facebook project” has only been allowed to become as vast and powerful as it has because of the US national security establishment.

“It’s a form of very deep but soft power that’s been seen as an asset for the US. Russia has been so explicit about this, paying for the ads in roubles and so on. It’s making this point, isn’t it? That Silicon Valley is a US national security asset that they’ve turned on itself.”

Or, more simply: blowback.

• Revealed: 50m Facebook profiles harvested in major data breach
• How ‘likes’ became a political weapon

This article was amended on 18 March 2018 to clarify the full title of the British Columbia Ministry of Education
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