From six manual steps to zero — a fully automated customer lifecycle for a fast-growing SaaS platform.
Where things stood before we started
BayX helps independent auto repair shops manage their entire operation — bookings, invoicing, and customer communications — from a single platform. As the team grew, the gap between product capability and internal operations widened. Every new trial customer triggered a six-step manual sequence. Churn was noticed only after the fact. Reports were assembled by hand.
Trial onboarding required six manual touchpoints per new account
No system to detect disengaged or at-risk trial users before they churned
Customer success ran on spreadsheets and calendar reminders
Weekly ops reporting took 3+ hours to compile every Monday morning
The automation systems we delivered
Customer Lifecycle Automation Engine
Every new trial triggers a structured onboarding sequence — welcome, activation nudge, milestone check-in, and handoff to paid — with zero manual input from the team.
Behavioural Trial Conversion System
Usage signals are monitored in real time. When a trial user stalls before the activation milestone, a targeted recovery sequence fires automatically via email and in-app.
Churn Early-Warning Agent
A six-signal health model runs daily across all active accounts. At-risk accounts are flagged the same day and routed to the correct CS rep with context and suggested action.
Automated Operations Dashboard
Trial conversion, churn rate, activation completion, and revenue data pulled from across the stack — compiled automatically and delivered to the team every Monday morning.
Support Triage Pipeline
Inbound support requests are categorised, prioritised, and routed to the right team member based on account tier and issue type — without a human in the loop.
Measured results after deployment
“We used to spend half our week managing the logistics of growth — onboarding emails, trial nudges, churn flags, weekly reports. Nuevexa eliminated all of it. Now we work on growth. The difference is hard to overstate.”