What types of data are used for segmentation?

Segmentation data falls into several categories, each revealing different aspects of your subscribers.

Demographic data describes who someone is: age, gender, location, job title, company size. It's relatively stable and often collected at signup.

Behavioral data describes what someone does: email opens and clicks, website visits, purchases, app usage, support interactions. It changes constantly and requires ongoing tracking.

Transactional data captures purchase history: what they bought, when, how much, how often. For e-commerce, this is often the most valuable segmentation source.

Engagement data measures interaction with your emails specifically: open rates, click patterns, recency of activity, response to different content types.

Preference data reflects stated interests: topics they selected, frequency preferences, communication channels they prefer. This is explicit rather than inferred.

Lifecycle data tracks where someone is in their relationship with you: new subscriber, first-time buyer, repeat customer, at-risk, churned.

The richest segmentation combines multiple types. Behavioral signals show intent. Demographics provide context. Transactions prove value. Together they paint a complete picture.