We’re using AI to predict which users will churn and personalizing push notifications based on behavior patterns.
It’s effective for retention, but it’s starting to feel invasive, like we know too much about our users.
How do you find the balance between growth and privacy?
Been running campaigns for years and this hits close to home.
The creepy line is real.
Users engage better when they know what data you’re using. We started adding simple explanations in retention emails - “because you used feature X” or “based on your recent activity.”
Conversions stayed strong but complaints dropped. Transparency beats being sneaky about predictions.
I avoid behavioral triggers that feel too personal. Predicting app usage? Fine. Inferring mood or personal situations? That’s where I draw the line.
Yeah, stick to basic usage data. Skip the personal stuff - it’s more respectful and keeps users happy.
We just focus on app actions and avoid trying to guess personal details. Keep it simple.
Use data that users expect you to have from normal app usage.
Someone opens your fitness app every morning? Workout reminders make sense. But predicting their relationship status or financial stress from usage patterns? That’s weird territory.
I stick to predictions based on what they actually do in the app, not who they are as people.
Just ask users first. Most people say yes anyway.
Simple rule: don’t do stuff to users that you’d hate. Use their behavior data to actually help them. Show features they need, catch problems before they happen. But don’t make creepy personal predictions that feel invasive. Be upfront about what you’re doing and let them control it. You’ve crossed the line when users feel manipulated instead of helped. Focus on solving their problems, not exploiting how they behave.