What types of data are used for segmentation?
Still have a question, spotted an error, or have a better explanation or a source we should cite?
Most segmentation strategies draw from some combination of six data types, each offering different signal quality and collection complexity.
Behavioral data: what subscribers actually do. Opens, clicks, purchases, site visits, feature usage. This is the most reliable signal because it's observed, not claimed. Someone who clicks your pricing page three times is telling you something demographic data can't. Behavioral data powers engagement segmentation and intent scoring.
Transactional data: purchase history, order value, product categories, subscription tier. Drives lifecycle segments (first-time buyer, repeat customer, lapsed buyer) and product recommendation personalization.
Demographic data: age, location, gender, job title. Easy to collect at signup; quick to decay in accuracy. Most actionable for localization, regional compliance, and time zone targeting.
Preference data: what subscribers explicitly say they want. Topic preferences, frequency, product interests. High quality when collected; requires a preference center to gather systematically.
Lifecycle data: how long someone has been a subscriber, where they are in the customer journey. Drives messaging tone and appropriate offers. A new subscriber gets different content than a 2-year loyal customer.
Psychographic data: values, interests, inferred motivations. Harder to collect directly; usually inferred from behavioral patterns over time. Less common except in consumer brands with rich data.
The most practical starting point: behavioral and transactional data. These are already in your ESP or CRM, they reflect real actions, and they're what most lifecycle segmentation runs on. Clean data is the prerequisite for any of this to work. Garbage in, garbage segments out.
Contributors
Who worked on this answer
Every name links to their profile. Every company links to their site. Real people, real accountability.
