What types of data do companies use about me?

Understand Data About You

Data can be grouped in two categories, core data and derived or modeled data.

‘Core’ data is gathered and purchased by Acxiom from multiple sources and represents demographic data about you and/or your household; what your household buys and how often; and what your household’s interests are. These are the ‘core’ data elements because Acxiom has not applied any analytics to them.

Core data can come from many sources, such as when people sign up for services, buy tickets for a sporting event, donate to a charity or purchase a new vehicle. The companies that share their data for marketing purposes will let you know this in their privacy policy and give you a chance to opt-out.

Modeled Insights

Derived or modeled insights are different from core data in a number of ways. Companies like Acxiom make assumptions and predictions about people based on analytical processing that uses the core data. Derived and modeled insights are used to determine a person’s likelihood to perform an action, to exhibit a behavior or to purchase a product, and when that might occur. Examples include the likelihood to go to a professional soccer match, donate to a Public Broadcasting Service (PBS) charity or buy a new vehicle after owning one for 4 years.

Derived and modeled insights are an interpretation of reality based on a single company’s extrapolation of multiple core data elements. This interpretation will change and evolve over time, as a person’s core data changes. It is used to try to reach consumers when core data doesn’t directly identify their marketing interests. Derived and modeled insights are used the same way as core data in marketing campaigns – to shape offers and provide consumers with a more relevant and timely marketing experience.

Here is an example of how derived and modeled insights differ from core data:

Susie orders a pair of tennis shoes for herself and her toddler daughter over the Internet and general information about her purchase is shared with partners of the company she bought her shoes from. The core data that is shared is: Susie is interested in tennis shoes. She has children present in her household. She purchases via the web. She looks at advertising via the web, and she lives in the northeast.

The modeled data that may result from this purchase could be: Susie is the type of person who has the likelihood to purchase fitness equipment, gym memberships, gym clothing. She is likely to purchase products over the web.

The modeled insights predict a likelihood of a certain action or characteristic, based on common known data characteristics. As you can see, modeled insights represent best estimates or predictions based on the core data. Marketers may use those characteristics to identify an audience for athletic shoes and to identify other individuals who resemble the purchaser and might also be interested in athletic shoes.

See an Example of Modeled Data About You