The Edge: 5 Ways Big Tech Companies Have Used Data to Transform Their Business
“Big Tech” are the Tech Giants, also known as the Big Five. They are Alphabet (Google), Amazon, Apple, Meta (formerly Facebook), and Microsoft. These are the dominant companies in search, online advertising, e-commerce, social media, computer software, artificial intelligence (AI), cloud services, and more. The companies are all “unicorns,” having market capitalizations of over $1 trillion up to $3 trillion.
Jaron Lanier, an early advocate and inventor of virtual reality, says, “If an online service is free, you can bet it is feeding a scheme that makes money by subconsciously manipulating people.” They achieve this manipulation by collecting and mining data with the help of artificial intelligence and then make money selling the results to the highest bidder.
Here are five ways that Big Tech uses data to transform their business.
1. Algorithms
Big Tech created complex algorithms called “algos,” for short. An algo is a program that optimizes for a specific function, such as relevance or engagement. Using algos made these companies billions in profits.
Goggle’s algos are so powerful that they can predict a user’s behavior before the user thinks about the idea. Not only does Google know you better than your mother does, the algos know you better than you know yourself.
Meta has some algos that optimize for engagement. They learned that social media posts, which provoke outrage, attract more attention. This phenomenon is why negative information, even if untrue, spreads so quickly. Using this method is how the company keeps users engaged.
2. Big Data Mining
People using web content create a dataset of user information everywhere they go online. There is also mobile-phone tracking data showing where a person went, even if their phone is off. These two datasets can be combined and mined for insights.
Did you know that there are thousands of dataset repositories on the web? Scientists, researchers, students, or anyone interested in data mining can search for datasets using the Google tool.
Big Data mining looks for trends and gives insight into patterns that are not obvious and may be counter-intuitive. All Big Tech companies have massive data mining programs in progress and use many datasets to train AI.
3. Artificial Intelligence
Alphabet, through Google AI, is making such rapid advancements with artificial intelligence that it recently sparked a controversy about whether AI is sentient or not. One software engineer claimed that the AI was demonstrating self-awareness. Google promptly fired him for publicly making these claims and leaking confidential information.
Perhaps we can forgive him if he became confused between AI and human responses. The AI running behind the scenes for the Google Assistant, which you activate by saying, “Hey Google,” feels very humanlike at times. The huge amount of data collected by Google allows it to train the AI to simulate human responses, which are uncannily similar to what a real human person sounds like.
4. In-App Purchases
If you download an app from the Apple App store that contains in-app purchases, you may use the app for free. However, some users will make an in-app purchase. This purchase may be a digital collectible, premium feature, or game enhancement.
This strategy turns a free app into a revenue generator. Did you know that Apple takes a 15% to 30% cut of the sales? Elon Musk says that is ten times too high. Providing the App Store to let people download apps makes billions for Apple. More importantly, the data collected from app use is extremely valuable and allows Apple to track individuals across multiple devices.
5. Privacy Moats
Apple thwarted Meta by cutting off access to iPhone user data by using the trend toward privacy concerns as an excuse. In May 2021, Apple added the App Tracking Transparency feature to the iPhone, allowing users to opt-out of advertising tracking.
Before this change, advertisers could track iPhone users across applications. Now, users can turn off this ability. They did this in droves.
Meta complained that the new policy cost them $10 billion in annual revenues. Moreover, the user data is still available to Apple, just not to others. Apple is expanding its mobile advertising efforts, which may partially explain this policy change.
Under the guise of protecting users’ privacy, Apple created a privacy moat. Apple retains its exclusive access to iPhone user data, giving Apple a significant competitive advantage.