How are Companies Using Your Data?

In the digital era, we have so many apps and services at our fingertips that we can use for free at any time.

But are these services really free?

The answer is simple. There is no such thing as a free service.

We used to think that the only way to pay for something was by using actual money in exchange for a service or product. In the digital world though, the most common currency has become our own private information. Companies offer us services in exchange for some piece of our personal data so they can build detailed profiles of our online behavior, our interests, and search history they will further sell to advertising companies.

There are more reasons behind data collection, and we'll go through them in this article.

Big companies collect a vast amount of different types of data. This collected data includes name, phone number, email address, locations, birth date, age, gender, devices used, operating system, language, internet provider, friend connections, profile information, uploaded media, likes, shares, browsing history, types of purchases, buying activity.

You can learn more about all the data companies collect from our previous article:

If you read the Terms of Services of the services you're using you'll notice they stat data collection as the purpose of giving them information to improve customer experience.

Each customer is different and has its own wants, needs, and preferences. So, as a company or retailer, it's hard to please all your customers by using the same overall strategy. And now it's more important than ever to keep up with what customers want because customers have become more demanding and quickly switch services if they are not pleased with the user experience.

Consumer data provides companies with a better understanding of how to meet their customers' demands. By analyzing people's behavior, feedback, and reviews, companies have enough information to modify their presence, products, and services to suit their customers' demands.

Marketers report improved success in terms of engagement, revenue, and conversion when turning to personalized apps or websites that recognize the preferences and interests of the users. Take Netflix or Amazon as an example. Their platforms are personalized and unique in terms of the content they recommend based on a specific user's interests and browsing history. And for personalization to work, companies need to collect as much data as possible about the users' behavior.

Retailers don't only track the amount of money you spent on their products, but they also keep information on the specific products you purchased. This information is further sold to advertising companies.

Having this data provides advertising companies with the opportunity to target specific people with ads of specific products based on their purchase history.

For example, let's say you're lactose intolerant. It will be inefficient and a waste of resources for a company to hit you with ads promoting diary products because there' no chance they'll get your attention. But because they have information about your past purchases, they know to show you ads of lactose-free products so you're more inclined to click and make a purchase.

This data about consumers' purchase history combined with data about their browsing history make for a really powerful tool for advertisers. They know exactly what consumers want and need. And using advanced technology to analyze all the data, allows them to even predict customers' future needs.

We are heading towards a world were advertisers know, even better than ourselves, what and when we need specific products and services.

When we make online purchases, we share lots of intimate details about our buying habits with the vendors. These consumption patterns can give away a lot more information than you might think. Sometimes it can even get creepy.

A great example of how properly analyzing data can give really accurate insights about customers' lifestyle comes from Target, that figured out how to tell if women are pregnant, sometimes even before they did.

For every customer, Target assigns an ID number that contains their credit card, name, email address, and stores every purchase and additional information bought from other sources. Analyzing the purchase history of the women known to have been pregnant, they figured out there is a buying pattern each of them follows. They identified 25 products that, when analyzed together, they can predict if a woman is pregnant, and even the due date or the sex of the baby. They use this prediction to send out coupons related to specific stages of pregnancy so they convert the women into loyal customers.

It is mindblowing how much information you can learn just by paying attention to people's online activity and analyzing the data. Especially when it comes to the activity that becomes public on social networks. There are companies that keep an eye out for every piece of content posted on social networks so they can alert corporations if critical information pops up. This way, those corporations can react fast to the breaking news, staying steps ahead.

For example, Datamir is a real-time discovery solution that provides assets for corporate security, finance, news, and the public sector. It uses machine learning to determine the significance of the information obtained from the public.

How does this work in practice?

Think about Twitter. There are over 500 million tweets shared daily on the platform. Datamir monitors all the tweets in real-time and uses algorithms to sort them based on different variables such as user reputation, importance, and patterns. If a piece of information is shared by multiple users, Datamir will alert the clients that some breaking news might arise.

There's no news that most companies conduct a bit of Google search before hiring someone so they can get a feel of the person before making a decision. HR also creates profiles of the employees so they can analyze work performance.

What you might not know is that there are companies specialized in analyzing employees based on way more metrics than the in-house HR department does.

For example, Evolv is a big data company focusing on finding solutions to enhance workplace performance. One application of their product is to use data to understand who the employees are, how to make them more effective, and to predict their future performance in the workplace or how long they are likely to stay in their jobs. For this analysis, they use different kinds of metrics from employees' criminal records to seemingly trivial details such as their web browser preference. You read that right! They learned that employees who change the default browser to a nonstandard browser such as Chrome or Firefox perform better than those who use standard browsers such as Safari or IE.

Every time you connect to the internet, some type of data starts being shared with companies. There are ways in which big companies can follow you online everywhere you go and gather all the information about your online behavior so they can build a detailed profile of your digital footprint.

We went over how companies collect data and which are the top big data companies in our previous article: