What Your "Successful" Users Actually Do Differently
Successful users: those who retain, convert, and drive revenue: don't behave like everyone else. They complete specific actions sooner, use specific features more, and follow a different path. US teams that compare successful vs. unsuccessful users discover the behavior pattern that predicts success, and optimize for it.**
You have users who stick around. Users who convert. Users who upgrade and refer. You call them "successful" or "power users." But do you know what they do differently?
Most teams don't. They assume. They have personas. They have intuition. But they've never run the analysis: compare successful users to everyone else. What actions do they take? What's the sequence? What's the timing?
The answer is usually simple. And actionable. Successful users do something specific in the first 24-72 hours that others don't. Once you see it, you can guide everyone toward it.
The Analysis
Define "Successful"
Pick one (or combine):
- Retained: Still active after 30/60/90 days
- Converted: Became paying customers
- High-LTV: Drive the most revenue
- Power users: Highest engagement, most features used
Create a segment. These are your "successful" users.
Define "Everyone Else"
The rest. Or a comparison group: churned users, non-converters, low-LTV users.
Compare Behavior
For each group, ask:
- What events did they complete in the first 24 hours? 7 days? 30 days?
- What's the sequence? Did they do A before B?
- What's the timing? Did they hit the activation event faster?
- Which features did they use that others didn't?
The differences are your optimization targets.
Common Patterns
Pattern 1: Time to First Value
Successful users hit the activation event faster. Maybe in <1 hour vs. 3+ days for everyone else. Implication: Speed to value matters. Optimize onboarding for speed.
Pattern 2: The Critical Action
Successful users complete Action X in the first week. Others don't. Action X might be:
- Connecting a data source
- Creating a project
- Inviting a teammate
- Using a specific feature
Implication: Action X is the gate. Make it obvious. Guide users to it. Measure it.
Pattern 3: The Feature Combo
Successful users use Feature A + Feature B. They don't use one without the other. The combo creates stickiness. Implication: Bundle these in onboarding. Design for the combo.
Pattern 4: The Sequence
Successful users do A → B → C. Others do A → (stop) or A → C (skip B). The sequence matters. Implication: Guide users through the sequence. Don't let them skip B.
How to Run the Analysis
Event-Level Comparison
Export (or view) event streams for successful vs. unsuccessful users. Compare:
- Event types
- Event frequency
- Event timing
- Event sequences
SingleAnalytics lets you build segments from events and properties. Compare retained vs. churned. Compare converters vs. non-converters. See what they did differently.
Funnel Comparison
Build a funnel. Filter by "successful" vs. "everyone else." See where the paths diverge. The step where successful users convert and others drop off is your leverage point.
Cohort + Behavior
Segment retention by behavior. "Users who did X in Week 1" vs. "Users who didn't." The retention gap tells you how much that action matters.
Real Impact
A US project management tool compared power users (3+ projects, active 90 days) to everyone else. They found: power users had created their first project within 2 hours of signup. Everyone else took 3+ days, or never did. "Create first project in <2 hours" was the predictor.
They redesigned onboarding around that goal. Empty states. Push notifications. "Create your first project" as the hero CTA. Activation (first project in <24h) went from 28% to 52%. Retention improved. One behavior. One fix. Massive impact.
Ready to find what your successful users do differently? Compare segments with SingleAnalytics and optimize for the behavior that predicts success.