Find where users drop off
before your aha moment.
Describe your onboarding in steps. Get a drop-off risk score for each stage, the friction causing abandonment, and a prioritised fix list — specific to your product type and user goal.
No screenshots needed. Tell us your product type, target user, desired aha moment, and the steps in your onboarding — in plain English.
Claude evaluates every step against known drop-off patterns for your product type — scoring risk, estimating abandonment rate, and identifying friction points.
A risk score per stage, the specific friction causing drop-off, and a concrete fix for each — plus your overall health score and estimated time to aha moment.
Most churn is decided in the first session.
If a new user doesn't reach value before they leave, they almost never come back. Onboarding is not a feature — it's the entire product for the first 30 minutes.
Wrong sequence kills retention
Asking for a credit card before delivering value, or showing advanced features before core ones, causes 40-70% of trial users to never return. Sequence is everything.
Most teams never measure their own onboarding
Teams that build onboarding rarely go through it as a new user. They optimise for familiarity, not first-time comprehension — which are completely different experiences.
Time to aha moment predicts churn
The longer it takes a new user to reach the moment they feel the product works, the more likely they are to churn. Every unnecessary step between signup and value is a churn driver.
Friction compounds across stages
A 20% drop at stage 1 and a 30% drop at stage 3 leaves you with under 56% of your original cohort before anyone has seen the core feature. Small improvements at each stage compound.
Common questions
How does the onboarding flow grader work?
You describe your product type, target user, and onboarding steps in plain English. Claude analyses your flow against known drop-off patterns for that product and user type — scoring each stage by risk, estimating abandonment rate, and identifying the specific friction causing users to leave.
Do I need screenshots or a live product link?
No. The grader works from your plain-text description. You describe what happens at each step and the AI analyses the structure and likely friction from that description.
How accurate are the drop-off estimates?
The estimates are based on industry benchmarks for your product type. They are directional — intended to rank stages by risk and quantify likely impact — not a replacement for your actual analytics. The most valuable output is the friction identification and fix prioritisation.
What is an "aha moment" and why does it matter?
The aha moment is the first time a new user genuinely experiences the core value of your product. Research consistently shows that the faster users reach this moment, the higher their long-term retention. The grader evaluates whether your onboarding sequence efficiently delivers users there.
How many steps should I include?
Between 2 and 7 steps — each representing a distinct stage where the user has to do something or make a decision. Focus on the major gates (signup, setup, first action, first value) not every micro-interaction.
AI spots the drop-off.
We redesign the flow.
Our product designers validate every friction point against your actual user data, then deliver a redesigned onboarding flow — with clear effort vs. impact priorities so you know where to start.
No commitment · We'll scope it together