Spaid embeds with plumbing operators running ServiceTitan or Housecall Pro, uses AI to analyze 6–12 months of dispatch outcomes, job margins, callback patterns, and CSR booking data, and deploys plumbing-specific operational intelligence that your FSM reports have never shown you.
Plumbing margin loss isn’t one problem. It’s three or four compounding failures across dispatch, execution, and job mix. Most plumbing operators can name the symptoms. Almost none have seen the dollar amount tied to each one — because the data sitting in their FSM has never been read that way.
Your best plumbing tech closes service calls at 40% GM. Your average runs 30%. The 10-point spread is visible in ServiceTitan or HCP job data — sorted by tech, by job type, by complexity. But the standard reports don’t surface it that way. By the time the P&L shows the margin compression, you’ve been running the pattern for 90 days.
8–14 point GM spread between top and bottom plumbing techs — recoverable $8K–$16K per tech per yearWrong part on a water heater replacement. Incomplete diagnosis on a drain call. Mismatched tech assigned to a commercial repiping job. Each of these callback root causes exists in your FSM job data — cross-referenced with tech, job type, part combination, and complexity. A 50-tech plumbing shop burning $18K/month on callbacks has a solvable data problem.
35% of plumbing callbacks involve a missing part or incomplete diagnosis — preventableWhen emergency call volume spikes, plumbing operators send whoever is available — not whoever is right for the job type. Callback rates climb. Pricing consistency drops. The data to prevent this builds up in the FSM year-round. Almost nobody analyzes it during steady periods to prepare for surges.
$200K–$400K/year in avoidable margin loss during emergency volume spikes for a 50-tech plumbing shopGeneric field service software tracks your plumbing jobs. Plumbing operations intelligence tells you why your margins are where they are — and what to do about it.
Shows revenue totals and job counts. Doesn’t surface GM variance by tech, callback rate by job type, or dispatch outcome patterns.
Addresses general business principles. Not built from your specific data, your job types, your service area.
Adds features inside the existing system. Doesn’t cross-reference your FSM data with call recordings or analyze 12 months of dispatch outcomes.
Adds headcount. Still requires a system to tell them what to look for, how to look for it, and what to do when they find it.
Pulls every job record, technician performance metric, and part combination from your existing FSM. No new platform. No migration.
Built from your actual plumbing job history — drain, water heater, repiping, commercial, residential. Not generic field service benchmarks.
Recommended parts list for the job type, callback risk flag, prior job history at the address, customer LTV. Delivered in the existing FSM job card.
Monitors every tech’s performance against baseline daily. Flags the patterns before they compound into a P&L problem.
Four tools. One engineer on-site. The first 30 days are diagnostic — no changes, just numbers.
AI connects to ServiceTitan, Housecall Pro, FieldEdge, or Jobber via API and reads 6–12 months of plumbing job records — drain, water heater, repiping, commercial, residential. Callback patterns by tech and job type. GM by job category. Dispatch outcomes by complexity. The full plumbing operational picture from your existing FSM data.
During the first 30 days, the Spaid engineer rides with your highest-margin plumbing techs — documents how they diagnose a drain job, what they look for on a water heater call, what they bring to a repiping job. Converts that into a repeatable briefing for every tech on every high-callback job type. Specific to your service mix, your market, your customer base.
AI surfaces recommended parts list for the specific job type and complexity, callback risk flag from historical data, and prior job history at the address — delivered in the existing FSM job card before the tech departs. Not generic checklists. Built from your plumbing callback and parts data.
AI monitors GM per job, callback rate, and quote variance for every tech daily — by job type, by complexity, by season. Flags when a tech is drifting on commercial pricing, when a job type trends high on callbacks, or when dispatch patterns are creating avoidable waste. 3–4 week lead time before monthly P&L review.
Our Full-Operation Audit (Days 1–30) maps every plumbing margin leak — tech performance, callback root causes, and dispatch patterns. If we don’t identify at least $200,000 in recoverable annual revenue, we refund Phase 1 in full. You keep all audit deliverables.
After kickoff, we ask for about 30 minutes a week of your ops leader’s time.
We’ll start with a recent export or sample job data from your FSM, show you the biggest margin gaps and callback patterns, and scope the engagement. Full access happens only if you proceed to the audit.