構造化データ | 用語集

Structured Data | CDP.com Glossary Structured Data Structured data is information organized into predefined fields in databases, tables, or spreadsheets. Learn its benefits and how CDPs use it for unification. CDP.com Staff April 9, 2026 4 min read Structured data is data that is organized in a predefined format with clearly defined fields, types, and relationships, typically stored in spreadsheets, tables, or relational databases . 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 through data integration where fields can be mapped to like fields. How Do Customer Data Platforms (CDPs) Use Structured Data? Customer data platforms (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. Independent Research Evaluating CDPs? See how analysts rank the market. Forrester Wave™ Report RFP Template 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 FAQ What is the difference between structured and unstructured data? Structured data is organized into predefined fields and formats, such as rows and columns in a database or spreadsheet, making it easy to search and analyze. Unstructured data lacks a predefined schema and includes formats like images, videos, emails, and social media posts. Semi-structured data , such as JSON or XML, falls between the two with some organizational properties but no rigid schema. Why is structured data important for marketing? Structured data enables marketers to build precise customer segments, run targeted campaigns, and measure performance against clear metrics. Because it is organized into queryable fields like purchase history, demographics, and engagement scores, it can be directly used by customer data platforms and marketing automation tools with proper data governance in place. Without structured data, personalization and attribution become significantly more difficult. How is structured data used in customer data platforms? Customer data platforms ingest structured data from CRM systems, point-of-sale systems, web analytics, and other sources to build unified customer profiles. Each data point—such as a transaction amount, email address, or product preference—maps to a defined field, enabling identity resolution and audience segmentation . This structured foundation is what allows CDPs to serve as a single source of truth for marketing and customer experience. Related Terms Data Modeling — Process of defining the schemas and relationships that structure data Data Pipeline — Infrastructure that moves structured data between systems for processing Data Validation — Ensures structured data conforms to expected formats and quality rules ETL and ELT — Processes that extract, transform, and load data into structured formats Analyst Report Forrester Wave™: Customer Data Platforms, 2024 Independent evaluation of 12 vendors across 26 criteria Download free report Research Report AI Agents in the Enterprise: From Pilots to Proof 13 martech leaders & 8 real-world AI agents. By The Martech Weekly Download free report Independent Research Evaluating CDPs? See how analysts rank the market. The Forrester Wave™ evaluates CDP vendors on strategy, current offering, and market presence. B2C CDP Report B2B CDP Report Written by CDP.com Staff The CDP.com staff has collaborated to deliver the latest information and insights on the customer data platform industry. Continue Reading Glossary Ad Exchange An ad exchange is a digital marketplace where buyers and sellers come together and enter into a real-time bidding process to buy and sell ad space. Read more Glossary Affiliate Marketing Affiliate marketing is a results-driven program where businesses pay third parties for referring new customers or visitors to their online properties. Read more Glossary Agent Data Platform An agent data platform is unified data infrastructure AI agents use to read profiles, decide, act, and learn — an Agentic CDP rebuilt for agents. Read more