What is the key characteristic of explicit data in a lead scoring model?

In a lead scoring model, explicit data is characterized by the demographic information that leads provide themselves. This type of data includes details such as a lead's job title, company size, industry, and other self-reported information. Such explicit data is crucial because it allows marketers to assess the potential fit of a lead based on predefined criteria relevant to their targeting and segmentation strategy.

Understanding this helps marketers prioritize leads that are more likely to convert based on specific characteristics and demographic factors. This contrasts with implicit data, which is derived from observing a lead's behavior, such as their engagement with content or interactions with the company's website. By using explicit data, marketers can create a more structured and informed lead scoring model that focuses on quality rather than just engagement metrics.