Case study
Recovering Booked Revenue at a PE-Backed Plumbing Platform
A three-location plumbing platform was winning demand and losing too much of it before it booked. Rebuilding the layer between the call and the dispatched job recovered about $39K a month, close to $470K a year.
An anonymized client case.
The situation
A private-equity-backed plumbing business with three locations was getting strong inbound demand and losing too much of it before it became a booked, dispatched job. Growth was coming from spend; conversion wasn't keeping pace.
The diagnosis
Demand was fine. The leak sat in the operating layer between the customer and the booked job. The online booking path added friction, intake and follow-up ran differently at each of the three locations, and calls were slipping through at peak and after hours.
What I did
- Closed the after-hours gap. Missed and after-hours calls now get an instant text-back that routes to online booking, capturing demand that used to go to voicemail.
- Redesigned the online booking flow so the demand that starts a booking finishes it.
- One intake and follow-up model across all three locations. Every site runs the same steps from first call to booked job.
- Set up an IVR, a phone menu that catches overflow calls and routes them fast.
The result
Roughly 120 additional booked jobs a month: about $39,000 in booked revenue a month, close to $470K a year. Total bookings rose across channels; the recovered jobs were new demand, not phone volume shifted to the web.
What I bought versus what I figured out
The fixes themselves were commodity: a text-back tool, a booking-flow rebuild, an IVR, one intake standard. Any platform can buy that stack in a week; most already have, and most see nothing for it. I ranked the leaks in dollars before spending on any of it.
How I measured it
I counted booked jobs. The roughly 120 additional jobs a month comes from the platform's booking counts before and after the rebuild, and total bookings rose across channels, which rules out phone volume shifting to the web. The dollar figures come from that job count at the platform's average ticket, about $39,000 a month and close to $470K a year, rather than from a separately measured revenue line.
A walkthrough of the anonymized before-and-after data is available on request.
When this applies
If demand is growing faster than you can book it, if a newly acquired location isn't converting like the others, or if calls and follow-up are leaking jobs across brands, that's the engagement.