Get notified immediately
A dashboard alert and an email to the person in charge
Automatic at-risk customer detection
Know who is about to leave, while they are still here
Every response is scored against your own satisfaction thresholds. The moment a customer falls below the line, the alert lands on your dashboard, the right person gets an email, and the clock on handling time starts running.
The cost of the blind spot
The customer who leaves doesn't warn you
They answer politely, never call back, and their dissatisfaction shows up nowhere. You find out at the renewal that never comes.
5 to 25×
more expensive to acquire a new customer than to keep an existing one
80% vs 8%
of companies believe they deliver a superior experience; only 8% of their customers agree
The at-risk customer never writes to you. They answer the survey, then they disappear. Your only window to act sits between the two.
Why at-risk customers go unnoticed
A disappointed customer rarely complains. They answer politely, never call back, and their dissatisfaction shows up nowhere until they switch providers or post a review. Without a detection mechanism, you find out once the problem is already public.
What it costs you:
The signal gets lost in the volume
When dozens of responses come in every week, the comments that need action drown among the rest. With no filter and no alert, nobody knows which case to open first.
Nobody knows who should step in
Dissatisfaction that is spotted but not assigned stays unhandled. Without a clear owner and a follow-up status, two people call the same customer or, more often, nobody does.
Response time goes unmeasured
An unhappy customer called back the same day can be won back. Three days later they have moved on. Without measuring time to first contact, you can't tell whether your team reacts fast enough.
From the response to the closed case, with nobody watching the queue
What automatic detection changes:
You mark scale questions and the NPS question as satisfaction determinants. An NPS of 7 or more, or a scale score of 6 out of 10 or more, marks the customer as satisfied. Below that they tip into the at-risk group, regardless of survey wording or language.
The alert is added to the dashboard and the owner gets an email with a direct link to the response. Automatic sentiment analysis also classifies written comments as positive, negative, mixed, or neutral, so delicate cases surface faster.
Four statuses frame the follow-up: to handle, assigned, customer contacted, done. You assign an owner, the team adds internal notes, and time to first contact is calculated on its own in business hours.
Response received
InputKit applies your thresholds and fires the alert
Know who is at risk while the customer can still be won back.
Customers retained+24%
G★★★★★4.9· 486 cases tracked
GWON BACK
Case closed
★★★★★
“They called me before I even had to complain. That's a first for me.”
What early detection gives you
Set your own thresholds
You decide which answers flag a customer as at risk
Know what to handle first
A dedicated filter for dissatisfied customers, no digging required
Assign an owner
Every case has an owner and a follow-up status
Measure your response time
Time to first contact is calculated automatically
Before, we might have blamed the salesperson too quickly. Now, we better understand the source of the dissatisfaction. We've implemented clear employee tracking, appreciated by the team, and faster, more professional review management.
Mario Gilbert
General Manager, Lallier Honda
Quebec City, Quebec
Ready to spot at-risk customers while there is still time?
In 15 minutes we'll walk you through the whole path: your satisfaction thresholds, the alert that reaches the right owner, and the board that tracks every case to closure.