Score whether new customers feel taken care of.
“Is our onboarding actually any good, or do customers just happen to stick around?”
Grades the first 90 days on the moments that make someone feel expected, not just whether they activated, and names the exact spot the welcome goes cold.
What this skill does
Grades the experience a new customer actually has, not just whether a checkbox got ticked. Most onboarding scoring measures activation: did they log in, did they finish setup. This scores the feeling: were they expected, were they guided, did anyone notice when they went quiet. It walks the first 90 days moment by moment, scores each one, and hands back the specific places the welcome went cold and what to do about it. In commoditized software the experience is the moat, so this measures the moat.
Inputs
- Works today with: a walk-through of your onboarding, the emails, the setup steps, the human touches, the first 90 days as a customer experiences them. Paste it and go.
- More powerful connected to a product-analytics tool: it sees where real customers stall versus where the playbook assumes they sail through.
- Sharper with a CRM or CS tool: it reads the human touches that actually happened, the calls, the check-ins, the silences.
- Sharper with support or survey data: it hears the friction in the customer's own words.
How it works
- 1Score the moments, not the checkboxes
Walk the first 90 days as the customer lives it: the welcome, the kickoff, the first real value, the habit forming, the first check-in. Each moment gets a score on two axes: did it happen, and did it feel like someone was expecting them. A completed setup with no human warmth scores lower than it looks.
- 2Find where the welcome goes cold
Name the exact moment the attention drops off. For most teams it is right after setup: the sale got all the energy, activation got a sequence, and then the customer is alone. That cold spot is where early churn is born, and it has a location you can point to.
- 3Grade the human touches
Automation onboards; people make customers feel chosen. Score where a human actually shows up versus where the customer is handed to a drip. A high-value customer getting a templated welcome is a scored miss, not a nice-to-have.
- 4Catch the silent stall
Score whether anyone notices when a new customer goes quiet. The worst onboarding failure is invisible: they stopped, and no one reached out, because no signal was wired to a human. If the stall is silent, that is the finding.
- 5Turn the score into fixes
Every low-scoring moment ends in a specific move: the touch to add, the signal to wire, the human to insert. Not "improve onboarding." The exact cold spot and the exact fix.
Output format
ONBOARDING AUDIT · [your product] · first 90 days
Moment Happened Felt intentional Score
Welcome yes templated 2/5
Kickoff call yes warm, tailored 5/5
First value partial no guidance 2/5
Habit forming no - 1/5
Day-30 check-in no - 0/5
COLD SPOT: right after first value. The kickoff is great, then the
customer is alone. No habit nudge, no Day-30 human touch.
SILENT STALL: not caught. No signal wired to a human when a new
account goes quiet in week 3.
FIXES:
1. Wire a week-3 inactivity signal to the CSM, not a drip.
2. Add a habit nudge tied to the aha moment, day 7 to 14.
3. Make the Day-30 check-in a human note, not an NPS survey.
Onboarding experience score: 2.0 / 5 (strong start, cold finish)
Tips
- Every graded moment scores both dimensions: did it happen, and did it feel intentional.
- The cold spot is named with a location, never "onboarding could be better."
- Human touches are scored separately from automation, never blended into one number.
- The silent-stall check is explicit: is a quiet customer noticed, yes or no.
- Every low score ends in a specific fix, never a generic recommendation.
Score your goodbye: bridge, or bridge burned.
What happens when a customer leaves?
Win a churned customer back by re-onboarding, not discounting.
Which lost customers can we actually win back?