Onboarding Funnel Drop-off Simulator

Cohort & Friction

Concurrent users 200

UX friction ×1.00

Just-in-time permission ask One-tap social login

Live Funnel

Empirical conversion

–

Theoretical conversion

–

Biggest bottleneck

–

Stage	Pass	Reach

How it works

An onboarding funnel is a chain of independent gates. If p_i is the probability a user clears gate i, the fraction of the original cohort still active after n gates is a simple product:

R(n) = (1 - p_drop,1) × (1 - p_drop,2) × … × (1 - p_drop,n)

Because the terms multiply, a single bad gate — usually the permission request — dominates the final activation rate far more than its own drop percentage suggests. This simulator assigns every visible "user" instance a random outcome at each gate the moment it is spawned (a Bernoulli trial with the gate's current drop probability), then animates it either continuing down the corridor or peeling off and falling away.

Concurrent users — how many instanced particles are alive in the corridor at once (visual density, not a probability).
UX friction — scales every gate's base drop probability up or down, modelling a generally rougher or smoother flow.
Just-in-time permission ask — halves the drop rate at the Permission Request gate (asking for camera/location access only when the feature is used, not upfront, is the single highest-leverage fix in real mobile funnels).
One-tap social login — halves the drop rate at Account Setup by removing manual form fields.

The "Empirical conversion" readout is a rolling average of the last 400 completed journeys through the live particle system; "Theoretical" is the exact closed-form product above. Watch them converge — that gap is exactly the sampling noise a real analytics dashboard has to average away.

Active user Dropped off Activated

⚠ Couldn't load the 3D engineThree.js failed to load from the CDN. Check your connection and reload.