See Exactly
Where Users Drop Off
Visual funnel builder with per-step conversion and timing analysis
Define your key user journeys, visualize drop-off at each step, and understand exactly how long each transition takes. All analyzed within individual sessions for privacy.
Watch Users Flow Through Your Steps
Define the steps that matter, then see exactly how many sessions complete each one
Custom Step Sequences
Define any sequence of events as your funnel. Track onboarding flows, checkout processes, feature adoption paths, or any user journey.
Per-Step Drop-off
See exactly how many sessions drop off at each step. The biggest drop-offs tell you where to focus your optimization efforts.
How Long Does Each Step Take?
Understand timing between each transition. Long times often indicate friction, confusion, or complexity.
Transition Timing
Time between consecutive steps within a session
| Transition | Median | Mean | P25 (Fast) | P75 (Slow) | Sessions |
|---|---|---|---|---|---|
|
signup_started
email_entered
|
23s | 31s | 12s | 45s | 2,435 |
|
email_entered
password_set
|
47s | 68s | 28s | 112s | 1,812 |
|
password_set
signup_completed
|
8s | 11s | 4s | 15s | 1,623 |
⚠️ Insight: The email_entered → password_set transition
has a P75 of 112s - almost 2 minutes. This is where slower users are getting stuck. Consider simplifying password requirements.
Why Are Sessions Dropping Off?
Go beyond the funnel. Analyze exactly what non-completing sessions were doing before they exited.
🚪 Last Event Before Exit
Where non-completing sessions ended
Most exits happen at password-related events
⚖️ Converting vs Non-Converting
What do successful sessions do differently?
Non-converting sessions encounter password requirements 3x more
Actionable Insight
The data strongly suggests password complexity is your biggest conversion killer. Non-converting sessions are 3x more likely to see the password requirements screen. Consider simplifying your password policy or adding a password strength meter earlier in the flow.
Build Your Funnel in Seconds
Define Your Steps
Select the events that make up your funnel in order. For example: app_open → feature_viewed → purchase
See Session Flow
Watch sessions flow through your funnel. See exactly how many complete each step and where they drop off.
Analyze Timing
Understand how long each transition takes. P25 shows your fast users, P75 shows where people are struggling.
Diagnose Drop-offs
Use drop-off diagnostics to understand why sessions aren't completing. Compare converting vs non-converting behavior.
🔒 Session-Based Analysis
All funnel analysis is done within individual sessions. If a user starts the funnel in one session and completes it later, those are analyzed as separate journeys. Sessions rotate every 2 hours, and we don't track users across sessions. This approach works for 100% of your traffic with no data quality warnings.
Funnel vs. Conversion Analysis
Both are powerful—use them for different purposes
🔻 Funnel Analysis
Best for hypothesis testing
- • You define the steps you want to analyze
- • See per-step drop-off with exact percentages
- • Get timing data between steps (median, P25, P75)
- • Analyze specific flows like signup, onboarding, checkout
🎯 Conversion Analysis
Best for discovery
- • Automatic discovery of what matters
- • Find conversion boosters and blockers you didn't know about
- • See top paths that lead to conversion
- • No need to define steps upfront
Frequently Asked Questions
What is funnel analysis?
+
Funnel analysis tracks how users progress through a series of steps you define - like signup → onboarding → purchase. It shows where users drop off and how long each step takes, helping you optimize the flow.
How do I create a funnel?
+
In Respectlytics, you define funnel steps by selecting event names in order. For example: signup_started → email_entered → password_set → signup_completed. The system automatically tracks sessions through these steps.
What does step timing tell me?
+
Step timing shows how long users take between each step. We provide median, mean, P25 (25th percentile - faster users), and P75 (75th percentile - slower users) times. Long step times often indicate friction or confusion.
What are drop-off diagnostics?
+
Drop-off diagnostics analyze sessions that didn't complete the funnel, identifying their last event before exit. This tells you exactly where and why users are leaving, so you can prioritize fixes.
Is funnel analysis session-based?
+
Yes. Funnels are analyzed within individual sessions - if a user starts the funnel in one session and completes it later, those are analyzed as separate journeys. Sessions rotate every 2 hours for privacy, with no cross-session tracking.
How is this different from Conversion Analysis?
+
Conversion Analysis automatically discovers what drives conversions without you defining steps. Funnel Analysis is for when you want to analyze a specific sequence of steps you define. Both are useful - discovery vs. hypothesis testing.
Ready to Find Your Drop-off Points?
Build your first funnel and see exactly where users get stuck
Questions? Contact us