Do you share too much information about yourself? In all likelihood, you are unaware of how much sharing you are actually doing. When was the last time you fully read a digital information agreement before clicking your consent, all in a rush to get to whatever you want to get to? Maybe you did read the agreement, but are you getting a fair trade—your data for whatever (hopefully free) service you’re getting in return? Chances are that by now, someone out there knows more about you than you know about yourself.
“Breaks my life up into fractions of seconds and randomly stores them in the records of everyone else. But if you try to find that split second of me, it would go by without you knowing. You have to have the algorithm to put my entire life back together.” —The Girl, Anon, Netflix, 2018
Years ago, we went online and “visited” the State Library of New South Wales in Sydney. And like visionary Stew Brand, author of the Whole Earth Catalog, advocated, perusing all of that great information was free. But as Steve Wozniak, Apple co-founder, advocated, it was also expensive. We did have to give them “a little bit of our information” so we could spend hours in the library coming and going at will and staying as long as we wanted… for free.
We are pretty certain you know what Facebook’s Mark Zuckerberg said in 2010 when he launched his social network back at Harvard. When he was asked why people would give him all their personal information, he flippantly said, “I don’t know why, they trust me.”Of course, he walked back the statement of a cocky 19-year-old and made a savvy move—he changed the company name to Meta.
But Facebook, Google, Yahoo, Pinterest, Instagram, YouTube, Twitter (X), TikTok, and the thousands of other social media sites around the globe follow the same free/expensive business philosophy: use it for free, and we’ll make it up on the back end. It’s not that service providers didn’t advise users that they were going to gather some of their user/use information and that it might be used. After all, it was clearly spelled out somewhere in the long, ambiguous, boring, confusing user agreement that went on for page after 2-point-type page that was made even longer by the inclusion of a prenup agreement in the case you ever decided to leave them. Okay, we’re kidding about the prenup, but you can never tell.
People are so anxious to be connected to the online sources they use regularly that they agree with the ambiguous service agreements without even reading them. They can’t be that bad, can they? Well, how would you know? According to Security.org, only about 11% of people read digital user agreements, terms of service, and privacy policies, while 16% search and read key parts. However, 37% skim them, and a staggering 35% don’t read the documents at all.
For more than 30 years, the “free for some of your information” relationship worked well for consumers, services, and marketers. No one was “abused,” and advertising was the lifeblood of the Internet and social media services. Folks increasingly took advantage of the search, social networking, news/information/entertainment services without charge, in return for allowing the services to use some of their personal data.
But as with any good thing, services and marketers got better and more creative to the point that up until about 2019, people could be tracked from site to site thanks to “cookies”—unique bits of compute code that were unique identifiers of a consumer as he/she moved from one site to another, thus allowing the personal data to enable services to target you with relevant marketing messages.
It became so good—for marketers—that it totally changed the advertising industry to the detriment of newspapers, magazines, and even television ad sales. Companies were able to efficiently and effectively splash their ads across websites with promotions that would be tailored to a person’s specific interests. Digital advertising was so good that it was most recently a $350 billion industry, with prospects of getting even bigger and more efficient/effective as data was compiled, massaged, parsed, used, and abused.
Yeah, personal data got to be too personal, too used, so governments stepped in to draw a set of hard lines in the sand as to what was a matter of good practice and what was overreaching. The EU got really tough with services, apps, and advertisers with their privacy law—GDPR (General Data Protection Regulation)—and to no one’s surprise, personal data and ad sellers thought they were being picked on and would go broke without using all of that rich, beautiful personal data.
After all, with AI just entering the scene, folks envisioned all of that universe of data being even better to mine and pay for all those “free” services.
Okay, everyone but Apple, because in Tim Cook’s words, the company treated users’ most personal data as stuff that deserved, needed to be protected. To emphasize how committed the firm was, Cook went into gory details on how services/advertisers made money based on folks’ likes/dislikes, friends/families, relationships/conversations, and bits of information/data that became valuable when they were put together with other information and traded/sold. Tim may have gone “a little overboard,” but his words struck just the right notes with EU officials and the billions of Apple device users, and potential users, worldwide.
Of course, not to be outdone, California jumped on the privacy bandwagon and rolled out its own Consumer Privacy Act.
While apps and companies lobbied heavily against the restrictions, Google could read the writing on the wall and said they were going to give up using third-party cookies to give people greater control over which parts of their data was available for companies to use.
Surprise, the digital advertising industry didn’t collapse, and creative marketers found new, better ways to reach their prospective customers. Oh yeah, and even government agencies found more productive ways to find out more about you than you know about you….
But in the content creation/distribution industry, it was Netflix that quietly led the movement, and almost no one noticed. Probably because they kept their data to themselves. Back in the early days, Netflix Co-founder Reed Hastings and his team quietly kept track of which movie/show DVDs folks liked, which ones were rising, and which ones were fading. And they juggled their inventory accordingly.
As the Internet got more robust and their distribution algorithms got better, Hastings’ folks said let’s bypass the post office and go direct to the consumer. Studios and networks laughed and said sure, we’ll license you our content and you can be another revenue stream for us. Hastings added a former video store employee to his team, Ted Sarandos, who also had a lot of connections in , and love for, the Hollywood scene. The two, and others, along with their growing data library of folks’ likes/dislikes were used to invest in stuff they were pretty certain people would sign up to watch.
As the organization grew to nearly 250 million subscribers worldwide and inched toward ultimate profitability, studios/nets decided that the envelope pushers may be on to something, and if they can do it, the creatives could do it—and better.
Using increasingly advanced generative AI tools to determine what folks around the globe would like and would be willing to pay to see, they got into the side of the business Sarandos really liked: the creative side. The frustrating thing, though, for rating services, studios/nets, and yes, creatives, is that they wouldn’t share much of the viewer information, so they had a tough time figuring out what their formulas were for adding/dropping shows and how much and how many folks really paid to watch.
Hastings and Sarandos admitted that about half of their audience was getting a free ride by borrowing user keys, but they wrote that off as a marketing expense until they decided enough was enough and freeloaders had to pay their own way before they’d share any more information. Studios/nets and Wall Street were sure (again) that this would crush Netflix, but the crafty techie/creatives came up with another wrinkle, tiered pricing, and something Hastings wasn’t fond of in the early days… a cheap ad-supported offering.
Yeah, they lost a few “viewers,” but by “swearing” they’d keep ads to a minimum (3-4 minutes vs. networks’ 20 minutes of ads per hour), their AI data had proven that most folks (those who mattered) would go with the flow.
As soon as the studios/nets solve all of their other balance sheet problems, they’ll probably follow suit, but… first things first. Besides, they were anxious to learn more about how and why Netflix was doing so well.
In a move to greater transparency, Netflix released more of their subscriber/viewer data, and the content producers/distributors got busy trying to figure out how they did what they do so well. But it was the industry’s talent hustlers who dug deeply into the data because they were certain they—okay, their clients—weren’t being paid everything that was due. (Remember Tom Cruise’s iconic phrase in Jerry Maguire? Show me the money!) But as someone said, “The data is good,” and things have been worked out for all concerned, and creatives are learning how to work out better contracts that don’t count on huge, long backend payments.
The proactive tech folks (Google, Apple, Amazon, Netflix) got out front of the data collection/usage regulation changes, especially with their use of GenAI tools; but, it hasn’t been easy. To learn—and to be effective—AI requires a tremendous amount of personal profile and activity data, and left unchecked/monitored, it functions a lot like some people in an all-you-can-eat buffet with a seemingly insatiable appetite.
But the smart organizations have found that less can be more as long as it’s the right data.
The great thing—for those of us who think ads are a good thing—is that these streaming and social services will help their advertisers be more efficient and more effective, and will help keep subscribers and users happy and connected. After all, not all advertising, even targeted ads, is created equal.
AI is good at gathering information about what you want and don’t want. However, really understanding the why is, for the foreseeable future, beyond the grasp of the technology because, ultimately, the decision is logical but based on illogical/emotional reasons. At times, even the customer doesn’t realize why he/she “wants/needs” the product/service, and both sides need the cold/calculated guidance of AI to bring the two parties together.
Of course, some folks are like The Girl in Anon when she said, “It’s not that I have something to hide. I have nothing I want you to see.”
If she really means what she said, she probably watches content from folks who keep her data close to home and use it to develop even more creative stuff to keep connected with them, rather than giving it to some aging college kid who is intent on building an ultra-private compound on Maui. It probably won’t be much, but it’ll be the best secure private location your data can buy.