Online Tracking

Product Manager, Eliza Crawford (2020) informs us that the reason data is collected on you across the Internet is to learn how you behave when you visit a website. This is to “gain insights about how … customers use” websites “to provide a personalised online experience, and to monetise the user by showing them targeted adverts.”

Explaining why online tracking occurs, Crawford (2020) says:

• “When you search for a restaurant on Google and the service provides you with a list of restaurants in your local area, it’s because the search engine knows where you are based.”
• “When an e-commerce store shows you a list of recommended products, it knows what you like because it has tracked items you looked at or bought previously.” 

Pat Walshe (Privacy Matters) reminds us that behavioural data may include:

• your web browsing data – the websites you visit, the date and time you visit, the country you visited from (inferred from your IP address - a unique string of characters that identifies each device connecting to the internet and that is automatically sent when you visit a website). Also consider that when you leave a website, they’ll be able to tell which site you are visiting next and the next website you visit may be able to tell which website you came from. All of this would be considered web browsing behavioural data.
• ‘clickstream behaviour’ – data about an individual’s interactions on a website, that can include what they click and scroll and tap on a touch screen
•  ‘search engines’ such as Google that may collect and use information about what you search for, what results you click on, your IP address, and that may use a unique cookie identifier to track you.
• location – the location and type of place you visit (supermarket, casino, place of worship, hospital), or where you used an app, the dates and times, route travelled, the frequency of a visit or the routes you travel. Location data can be very revealing and behavioural in nature. 
• purchase history – this can include types of subscriptions (trade union membership, gym, newspapers etc), hotel or restaurant reservations that may have been made across search, maps, smart assistants or directly from retailers or third party services etc.
• payment or ‘transactional’ data – payments that reveal who/what organisation you paid (which can reveal the type of organisation - medical clinic, pharmacy, alcohol provider; food retailer, bookseller etc) and how much and when and how often. Tap and go card payments are a good example – think of that coffee you purchase at the start of a journey, the place, date and time you paid for it, and then payments you make later in the day with the same card.
• streaming media – “you are what you stream” and “They know what You Watched Last Night”.  Streaming media generates a lot of behavioural data about:
• o      the date and time you accessed a streaming music, audio or TV/movie service and non-precise location (country level or region      level) you accessed it from
• o which profile accessed and used the service (a name + category e.g. child)
  
• o the category of music, audio book, TV/movie (e.g. political horror, adult)
  
• o searches for content
  
• o whether you paused a song or movie and for how long (including the date(s) and time(s))
  
• o whether you skipped/abandoned a song or a TV episode movie audio track
  
• o whether you shared content and who with and your interactions with others within the service
  
• o whether you rated a song, TV show or movie
  
• o playlists or ‘watch’ lists you create
  
• o the device used to access the service and IP address and device identifiers
  

• Activity/Health data – data about your use of activity apps such as cycling, running, walking or data about your health such as that obtained via dietary or fertility apps. This data can be very revealing and may often be connected with your location for example.
• Social media graph – data revealing interconnected social relationships between people and their nature and patterns of communications

A study by Ghostery (2017) “revealed that trackers that collect data on internet users’ online behavior are present on at least 79 percent of websites (unique domains) globally. Web tracking has become so pervasive that approximately ten percent of websites send the data they’ve collected to ten or more different companies (unique tracker domains). In terms of web traffic, 15 percent of all page loads on the internet are monitored by ten or more trackers. According to the study, tracking scripts from Google (60.3 percent of page loads) and Facebook (27.1 percent) are the most prevalent”.