The usual age and location stuff feels pretty surface level at this point.
What segments have you found that actually drive different user behavior? Thinking more about how people use apps or what triggers them to upgrade rather than just who they are on paper.
Session frequency tells you more than you’d think.
We split users into binge users (long sessions, less frequent) and snackers (short but daily). Completely different conversion paths.
Binge users upgraded when we hit them during their active sessions. Snackers needed push notifications and gradual feature unlocks.
Also worth looking at abandonment patterns. Users who quit at onboarding vs those who drop off after using the app for weeks need totally different retention tactics.
The week-long users usually come back if you give them a reason.
Support ticket volume segments work better than most expect.
Segmenting users by their acquisition source is key. Organic users often show different behaviors compared to those from paid ads.
Additionally, it’s effective to separate quick upgraders from those who take longer. Quick upgraders react well to urgency, while slower ones may need more social proof.
Daily users and weekly users have distinct needs too, which influences their willingness to pay.
Focus on feature engagement. Users who interact with your core feature in the first few days convert at four times the rate of others. Those who only browse need a different approach.
Segment by problem urgency too. Users tackling immediate issues will pay more, while those exploring respond well to trials and educational materials.
In the end, behavior is more important than demographics.
Time of day usage patterns work well. Morning users vs evening users want different features usually.