Model how a funnel change shifts activation, drop-off, and trust before release.
Test onboarding, checkout, and activation changes against synthetic users and see where they drop, which lever lifts conversion, and the step to fix first before release.
OVERVIEW
Most users who leave your funnel never tell you why. They hit a step that asks too much, lose trust, or simply stall, and you are left reading drop-off numbers without the cause behind them. Changing the flow blind can close one leak and open another.
Polyhyle lets you walk synthetic users through the funnel before you ship a change. Each one tells you where they would abandon, the friction that caused it, and the single fix that would keep them moving. You see how the population flows step by step, which step leaks the most, and which lever lifts conversion, so you fix the right thing first.
INSIDE Polyhyle
Funnel changes
Remove one onboarding step and introduce a proof checkpoint before users reach the first simulation.
01
Map the funnel and the changes
List the steps, from landing to payment, and the levers or variations you want to test on them.
02
Walk each user through
Every synthetic user moves step by step and names where they would abandon, the friction that causes it, and the single change that would keep them going.
03
See where the population leaks
Answers aggregate into step-by-step flow, who enters and who remains, and a ranked list of friction points by frequency and severity.
04
Find the step to fix first
Get the predicted biggest drop-off step and the expected uplift of each lever, before you ship the change.
Polyhyle.app/simulations/funnel-changes
SIMULATION DETAIL
Funnel changes
Remove one onboarding step and introduce a proof checkpoint before users reach the first simulation.
Running
Biggest drop
Sign up
End conversion
12%
Conversion lift
+3.4%
World inputs
Current funnel steps, friction points, and completion assumptions
New flow variants, trust cues, and time-to-value constraints
Segments by urgency, technical confidence, and switching cost
Simulated outcome
Ship the shorter flow for experienced teams, keep guided proof for first-time users, and measure trust recovery before removing the checkpoint globally.
Ship the shorter flow for experienced teams, keep guided proof for first-time users, and measure trust recovery before removing the checkpoint globally.
WHY SIMULATE THIS
The usual way to fix a funnel is to ship a change and read the new drop-off, then ship another and read again. Each round needs real traffic and time, and a change that fixes one step can quietly hurt another you were not watching.
Simulating it first shows the leak and its cause before you touch production. You learn which step to fix and which lever actually lifts conversion in one pass, so you ship the change that works instead of iterating on live users.