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Structured Data

Structured data is data that is predefined, meaning each of the data points have assigned fields in a spreadsheet, table, or database. Typical examples of fields would be someone’s name, address, phone number, income, transaction history, hobbies, etc. For data to be structured, at some point someone like an enterprise architect will create a data model to determine which types of data go into what fields.

What are the Benefits of Structured Data?

Structured data is the end goal for all data. The more structured it is, the more valuable and useful it is to different people and applications. Structured data can be easily input from a data entry perspective, can be searched against more effectively, and can be changed and integrated with other data where fields can be mapped to like fields.

How Do Customer Data Platforms (CDPs) Use Structured Data?

CDPs are ideal platforms for structured data, as they can use that data to create unified profiles for individual customers. Enterprises can use those unified profiles as a single source of truth to market and sell against. CDPs take in all forms of structured data, from demographic to firmographic, and from behavioral to transactional.

What are the Different Types of Structured Data?

Demographic Data

Demographic data is data related to personal and geographic attributes, like:

  • Age
  • Current Location
  • Email
  • Mailing Address
  • Name
  • Telephone number

Firmographic Data

Firmographic data is data related to companies. Firmographic data is helpful for account-based marketing (ABM) campaigns, and includes data like:

  • Company Address
  • Company Name
  • Industry
  • Number of Employees
  • Revenue

Behavioral Data

Behavioral data is data related to deeper insights into your customers. This allows brands to do more effective audience segmentation and targeting.

  • Email Open Rates
  • Product and Service Usage Patterns
  • Purchase Patterns
  • Social Media Engagement
  • Videos and Content Consumed
  • Web Activity history

Transactional Data

Transactional data is related to how a customer transacts with your business, and includes insights like:

  • Credit Card Payments
  • Insurance Claims
  • Invoices
  • Purchase Orders
  • Sales Orders
  • Shipping Documents
Amy Onorato
Amy Onorato
Amy Onorato is the Managing Editor of CDP.com and Senior Content Marketing Manager at Treasure Data. Prior editorial and creative roles include journalism, content marketing and content strategy for CBSNewYork, Newsday, DMN, and Publicis Sapient.

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