Data shadow
Data shadow
Data shadow definition
Data shadow is an accumulation of digital footprints that you leave by interacting with online platforms, services, and content. The process of preparing someone’s data shadow involves several key steps that are needed to capture, store, and use this data.
See also: digital footprint, digital identity, digital information
Here’s how data shadows work:
- Data generation. Every time you use digital services — whether it’s browsing the internet, buying something, using social media, or even moving around with a GPS-enabled device — you generate data.
- Data collection. Many companies, including social media platforms, e-commerce websites, and internet service providers, collect this data. They use cookies, account information, and other tracking methods to gather detailed records of activities and preferences — even the most minuscule data is included.
- Analysis and profiling. This step transforms raw data into meaningful insights. Data brokers or the companies themselves use advanced algorithms and tools to analyze the aggregated data and create user profiles. These profiles include a wide range of information about an individual, like their political views, shopping habits, or what kind of movies they like — the goal is to identify patterns, preferences, and potential future behaviors.
- Application. The insights derived from data shadows are applied in various ways. Advertisers use them to target ads more effectively, retailers to tailor product recommendations, and content providers to customize what content they show to each user. Beyond commercial use, these profiles can also be used to help the government make informed decisions related to urban planning, public health, and more.