What is inferred segmentation and how is it calculated?

Inferred segmentation places subscribers into groups based on observed behavior rather than stated attributes. You don't know their job title, but you infer they're in marketing because they click on marketing content.

The calculation typically uses pattern matching:

Content affinity. Track which topics generate engagement. After enough clicks on certain categories, assign an interest tag. Someone who clicks on five articles about automation is probably interested in automation.

Engagement scoring. Weight different actions by significance. Opening is worth 1 point, clicking is worth 3, purchasing is worth 10. Total scores determine engagement tiers.

Recency weighting. Recent behavior matters more than old behavior. A click yesterday is more relevant than a click six months ago. Decay functions reduce the influence of stale signals.

Threshold rules. Define what it takes to qualify. \"Interested in topic X\" might require three clicks in 90 days. \"Highly engaged\" might require a score above 50.

Inferred segments are powerful but require maintenance. Review the rules periodically. Test whether inferred segments actually perform differently. Validate that your inference logic produces meaningful distinctions.