In a previous article I stated that the real value of data is not the information you type in your profile, but what happens when the company combines multiple data sources.
Sometimes these data sources stem from your interaction with for example a free app. So has Niantic Inc. from the app Pokémon Go, your profile and all the information it gathers while you play. For example, GPS data, Wi-Fi networks you encounter, how long you play and how often.
At the same time, you are not the only person providing data. Your information is compared to the data of all the other people using the app. Pokémon Go still has 65 million active users every month. By analysing data from millions of users, companies can predict what you’re going to do next.
This is not limited to spending patterns based on current buying behaviour. Companies predict changes in spending caused by life events like a move, marriage or pregnancy.
This sounds complex, but let me give an example.
Target started sending prenatal brochures to a family in America when they suspected the daughter might be pregnant. The father was furious, but the daughter later confessed according to a New York Times article. Mr Andrew Pole, Senior Manager at Target, is cited in the article explaining how Target identified 25 products that together indicate the likelihood of a pregnancy and the probable due date.
Target is not the only company analysing us in detail. We are all part of the largest psychological test in the history of mankind, as stated in an edition of VPRO Tegenlicht. Every online action, like, post or search is tracked and recorded. Additionally, a lot of company websites conduct split testing to identify factors that increase sales.
The chances are that every time you go online you are part of a psychological experiment without noticing it, giving permission or knowing what your data will be used for and by whom.
That Big Data enables psychological testing, is usually overlooked by people. Big Data is not just about analysing clicks; it actually predicts life events that impact your spending pattern like a pregnancy. This allows companies to offer the right products at the right time.
Big Data is extremely effective in predicting human behaviour because of the sheer size of data points. The data of everyone on the Internet can be used to make a model. More data means better predictions and increased sales.
Sending a brochure is a relative innocent example of what companies can do with predictive analysis. Unless you haven’t shared the happy news with your spouse yet, are a minor or suffered sexual assault that caused the pregnancy. Then it’s extremely hurtful to receive baby flyers and coupons.
It is even more destructive when the company uses data for other, more impactful decisions like who to offer health care coverage to (and who not).
Especially in the USA where digital privacy laws are not as strict as in Europe, you can buy lists of people according to race, ethnicity, and sexual orientation. It is even possible to buy a list of rape sufferers according to Executive Director Ms Pam Dixon from World Privacy Forum in an edition of ZEMBLA. The price for a name of a rape sufferer? 7.9 cents on the dollar according to Ms Dixon.
Who sells this kind of information for crying out loud?!
So-called data brokers buy and sell lists of personal information from all over the world. That means that any company that has members or gathers email addresses can monetize this kind of data by selling it to a data broker.
Essentially any company with a website could also be in the business of selling data. Many privacy policies include the right to gather, sell or share some information with third parties.
Eventually, data sales become more profitable than other products or services of the company. You might think a company mainly sells dog food, real estate or protein bars, but the main source of revenue can actually come from aggregating, combining and selling user data.
So as developments in big data allow for more accurate predictions, personal information becomes more valuable. It won’t be long before ordinary small and medium companies recognize this potential and you are recorded and tested everywhere you go.
This post was first published on Steemit in August 2017.