We mapped the operating challenge
Quote requests, job details, booking changes, and customer follow-up were arriving while the team was travelling or on site.
Trades case study
Quote requests, booking changes, and customer follow-up were arriving while the team was travelling or on site. This case study shows how enquiry capture and approval-led reminders reduced after-hours admin.
The business received job enquiries, quote requests, booking changes, site details, customer questions, and follow-up tasks while the team was travelling or delivering work.
The team needed faster response and better follow-up, but could not risk wrong promises about pricing, availability, materials, or job complexity.
After the starting point was clear, we moved through four practical steps: mapping the challenge, defining where AI could safely help, putting the workflow in place, and setting the handoffs and review points that kept judgement with the team.
Quote requests, job details, booking changes, and customer follow-up were arriving while the team was travelling or on site.
Enquiry capture, quote follow-up, and booking reminders could move without waiting for the owner, while pricing, diagnosis, and availability needed trade review.
We set up enquiry capture, quote triage, follow-up reminders, booking tasks, and customer update paths tied to staff approval.
Before the workflow was treated as live, we set the ownership, handoff rules, and review points for sensitive requests. Routine work could move faster, while judgement stayed with the team.
The change showed up in the day-to-day work: fewer things slipping through, cleaner handoffs, and clearer ownership for the team.
You do not need to know the right solution yet. Share what is slowing the team down and we will help shape the next move.