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VervoxAI
Mobile TradesIllustrative scenario

Perth mobile mechanic stops overbooking across the metro

Roadside Ready WA · Perth, WA

Illustrative only. These are illustrative scenarios modelled on typical AU SMB workloads, not specific Vervox customers. Names, suburbs, and metrics are representative composites. Real testimonials will replace each entry as launched accounts opt in to share their results.

96%On-time arrivalsUp from 71%
2.3 hrs / driver / dayTime savedLess driving, more working
+40%Jobs per weekSame fleet, same hours
0Schedule conflictsIn first 60 days post-launch

The Challenge

Roadside Ready WA runs a five-van mobile servicing team across greater Perth — from Fremantle in the south to Joondalup in the north, plus the eastern hills. Their customer is the small business fleet: tradies, sales reps, nurses, ridesharers who can't spare a whole morning to bring a van in.

Their biggest constraint was the drive. The founder was also the dispatcher, mentally juggling traffic, suburb distances, and parts-collection detours to build each driver's day. Two pains showed up repeatedly:

  • Over-booking — "sometime between 8 and 12" windows that slipped to 1pm after the morning job ran over, bleeding customer trust.
  • Under-booking — conservative two-hour gaps between jobs "just in case", leaving drivers idle for an hour between gigs.

The Solution

The team turned on Vervox Smart Booking with home-visit routing. Key setup:

  1. Defined service coverage by suburb list (110 suburbs across Perth metro).
  2. Set each driver as a provider, with their own home base (not the workshop — their home suburb) and hours.
  3. Enabled per-suburb travel estimates, so slots offered reflect real drive times between jobs.
  4. Padded a 15-minute buffer on every service for parts retrieval and customer handover.
  5. Connected Google Calendar per-driver — the AI respects personal appointments drivers add themselves.

The AI now asks every caller "what suburb are you in?" before offering slots, and picks the driver whose previous job is closest. Drivers see tomorrow's route the night before, sorted by proximity, with each job's actual 30-minute window.

The Results

In the first 60 days:

  • On-time arrivals climbed to 96% — up from 71%. 30-minute customer windows actually stick, because the AI never builds a tighter day than the drives allow.
  • Each driver saves ~2.3 hours a day — less sitting in traffic between far-apart jobs, more billable work. Effectively a third of each driver's day recovered.
  • Jobs booked per week rose 40% — same fleet, same roster, smarter routing.
  • Zero schedule conflicts in the first 60 days — the travel-aware logic means no two jobs overlap in practice, even at the 30-minute-window level.

The added throughput meaningfully outpaces the monthly subscription cost — a typical van-day fills with billable jobs that previously would have been quoted but never booked, and the travel-aware add-on pays for itself within the first week.

What an operations lead might say: 'We used to give customers a sometime-between-8-and-12 window because nobody could work out the driving in their head. The AI does the maths in real time — every customer gets a 30-minute window that actually sticks.'

Composite scenarioOperations lead, AU mobile-trades business

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