Back in 2009 the game “Farmville” was released on Facebook and quickly became one of the biggest games of the time. To the average player, it may have looked like the goal of Farmville was to keep your crops alive and thrive as a farmer. But that wasn’t the real goal. The goal of Farmville was to make a ton of money for Zynga (the developer). To do that, they had to get a lot of people to spend a ton of real money to buy their fake in-game cash.
And that they did.
One of the main reasons for its success was the widescale use of split testing. Split testing is essentially using focus groups to help you make decisions. While a lot of people were playing Farmville, not everyone was playing the same version of Farmville. When Zynga was creating a new feature, or otherwise modifying the game, they would create two versions. Let’s call them A and B. Some players would get version A and some would get version B.
Both versions of the new feature would be released at the same time and the developers would sit back and see which version, A or B, resulted in the most money for Zynga. They used the reaction of the players to tell them which one worked the best.
But they weren’t just shooting in the dark, because they knew a lot about their players. They knew the number of times you clicked on a certain button, how much time you spent doing a particular activity, how many (and which) of your friends were you playing with, what times of day you played and thousands of other bits and pieces of data. They would use this data to figure out the most effective way to get people to spend real money on fake things.
They didn’t need to have all the answers right away because, by watching the reactions of the players, they were able to fine-tune the feature for maximum effectiveness. Once they figured out which version worked better, they would push that version out to all the players. When they had learned from the data they had collected what motivated certain people to do certain things, they were able to better predict how to motivate them to do different things in the future.
Then they would design two versions of another new feature with the same end goal, more money for Zynga. It was one of the first marriages of Big Data and Big Media and it worked very, very well.
The result of their efforts was an addictive (we in the industry call it “habit forming”) game that used social engineering to control the real-world actions of millions of people.
Many of the same people who used social engineering to maximize revenues for their companies are still working in Big Data and Big Media. They’ve taken those lessons learned in Farmville and other similar games to new opportunities and are now compelling people to do more than just open their wallets.
Today, Facebook, Google and Twitter know more about you than you know about yourself. They know how you think, what you think and who you think of. They know what you search for, what you think about buying, what you actually do buy, what you “like” and “share”, who you block, which articles you read and how much time you spend reading them. They know who you email, who you text, who you “private message” and what you say to them.
Big Data and Big Media have melded into a single entity. They are now one and the same and they’re very good at what they do. And they’re “woke”.
And, they want others to be “woke” too.
So, they tried a bunch of things to see which would work best. They tried different versions of different types of messages and saw which ones better provided the desired results. Then, they could use the massive amount of data they’d collected to predict how someone would react to something in the future.
By watching the online reactions of people who had willfully handed over their data, they were able to figure out a lot. And they were able to use it to further their agenda. They didn’t need to have all the answers right away. By watching how people react, they were able to fine-tune their message and maximize its effectiveness. Just like Farmville.
- They figured out that using the word “baseless” works better than “unjustified”.
- They figured out how many times they needed to repeat a lie before people would start to believe it.
- They figured out that every game needs a villain, so they came up with “Orange Man Bad”.
- They figured out that calling someone a racist is worse than someone actually being a racist.
- They figured out that if they selectively edited videos to show things taken out of context, a lot of people wouldn’t care.
- They figured out the terms “systemic racism” and “white privilege” worked equally as well so they decided to use both.
- They figured out a way to get millions of mostly law-abiding citizens to turn against the police.
- They figured out how to get people to spend their hard-earned money on “BLM Bucks”.
- They figured out that “mostly-peaceful protesters” is a more socially acceptable term than “violent insurrectionist”.
- They figured out how to convince you to be deathly afraid of a disease that isn’t likely to hurt you at all.
- They figured out how to use your online activity to predict which candidate you’re likely to vote for. Then, they were able to encourage to vote only those people who were determined to be “woke”.
Most importantly they figured out that if they simply ignored something, no matter how big that something is, a lot of people are going to believe that it never existed.
To Big Media, this is all one big game. The Game of Woke. And, like Farmville, they’re using everything they know about you to change how you think and act.
However, there’s a big difference between The Game of Woke and Farmville. In Farmville, you’re the one tending to your crops, buying land and controlling your character. But, in The Game of Woke, you’re the one getting played.
