Product teams typically create different types of user segments to understand their user base:

• Demographic segments help tailor marketing messages and localize features (e.g., European users prefer different payment methods than US users).
• Behavioral segments inform feature development (e.g., users who export data weekly need batch processing features).
• Value-based segments guide monetization strategies (e.g., teams with > 100 members need advanced admin controls).
• Technographic segments influence technical decisions (e.g., mobile-heavy users need offline capabilities).
• Engagement segments help prioritize retention efforts (e.g., users who perform > 5 core actions per week have 80% better retention).

Each segment type serves different analytical purposes, from feature prioritization to marketing campaigns. Strong segments need clear boundaries anyone can understand. Use simple rules like " active users are those who have logged in within 7 days" rather than complex formulas. Make sure the segments are mutually exclusive and include enough users to show real patterns — having too many small segments can make analysis misleading and ineffective.