We can classify data in different ways. The classification of data also depends on the use case at hand.
To understand CDPs better, we need to understand the different types of data they can collect. The classification can be done in two ways: h ow the data is collected and the nature of the data collected.
Classification of Data based on how it is Collected
Customer data can be divided into three types based on the origin of the data:
- First-Party Data: First-party data refers to the data brands collect when users interact with their websites, apps, retail stores, and so on. The data is collected with consent, and user identification is possible. Most of the collected data is supplied by the user, like email IDs and phone numbers. Others are collected when users interact with the brands, like purchase history, membership details, loyalty program info, and so on. First-party data is highly reliable and accurate, and the most useful data for brands.
- Second-Party Data: Second-Party data is the data that brands collect from trusted partners. The agreement with partners can be based on a data-sharing agreement, or brands may purchase the data from a third-party partner. As the partner is a trusted one, second-party data is also accurate and reliable, but less so than first-party data. It is important to be cognizant of privacy regulations like GDPR and CCPA before you buy data from partners. Second-party data is merged with first-party data to create more accurate data models.
- Third-party Data: Third-party data is the data that brands acquire from data aggregators. Data aggregators are companies that collect data from different sources and compile them into datasets to sell to other companies. The data aggregators do not themselves interact with the customers. They maintain and build datasets. As the data is obtained from different sources, they are less reliable and accurate than first-party and second-party data. Also, one has no clue whether data regulations were followed while obtaining the data. So brands have to be careful while using third-party data. But if properly used, third-party data can be stitched together with other first-party to improve targeting. Examples of third-party data include data collected from Google advertising.
In the following table, we have summarized the differences between the three data types:
First-party Data | Second-party Data | Third-party Data |
Direct relationship with the customer | Indirect customer relationship | Indirect customer relationship |
Collected with consent | Collected with consent | Unknown if it’s collected with consent (depends on the data provider) |
Individual data | Individual data | Aggregate Data |
High accuracy and reliability | High accuracy and reliability | Low accuracy and reliability |
Not shared | Shared only with trusted partners | Shared with many companies |
Examples: Customer Email | Examples: Website Activity | Examples: Income |
– Customer email | – Website activity | – Income |
Table 2.1: Classification of Data based on how it is collected