The Field Service Revenue Leak Audit: Pull These Numbers Before You Engage Anyone
You don’t need a consultant to identify your biggest revenue leaks. Every number on this checklist is available in your FSM and call tracking system today. Pull them, compare them to the benchmarks, and you’ll know where the money is going before anyone walks in the door.
13
Metrics in This Audit
13 metrics covering field operations and back-of-house, with benchmarks for each
$1.1M+
Typical Recoverable
Typical recoverable revenue and margin on a 50-tech field service operation
2 hrs
Time to Pull
Estimated time to pull all 13 metrics from your FSM and call system
Pull each metric from your FSM (ServiceTitan, FieldEdge, or equivalent) and call tracking system for the trailing 90 days. Compare to the benchmark range provided. Flag any metric outside the benchmark as a priority investigation item — not a problem to immediately fix, but a signal that warrants a closer look before you spend money on any intervention.
Field Operations Checklist
Field Operations — 6 Metrics
Gross margin % by technician (same job type)Pull: GM% for each tech on your top 3 job types by volume, filtered to comparable job scope. Not blended GM by job type — by tech within job type.
Benchmark: Spread of less than 5 points between top and average on the same job type. More than 8 points indicates a standardization gap worth quantifying. On a 20-tech shop running 300 comparable jobs per month, an 8-point spread is typically worth $150K–$250K annually in recoverable margin.Flag if spread > 8 points
Quote variance by job typePull: Average quote value for the same job type across techs, last 90 days. Filter to comparable scope — same job category, same equipment class.
Benchmark: Less than 15% variance on comparable scope. 15–30% variance is common and addressable. Variance above 30% typically indicates inconsistent pricebook usage or option presentation, not market differences.Flag if variance > 15%
Discount and override rate by techPull: Total discount value and override count by technician, last 90 days. Sort descending by total discount value.
Benchmark: Less than 5% of jobs should have a manager-level discount or override. Top 20% of discounters typically account for 60–70% of total discount value. If one tech is responsible for more than double the team average in discount value, that's the starting point.Flag if any tech > 2x team average
Callback rate by tech and job typePull: Callback jobs as a percentage of total jobs, filtered by originating tech and job type. Requires consistent callback tagging in your FSM to be accurate.
Benchmark: Less than 2.5% overall. More than 4% on any tech or job type warrants root-cause analysis. Each callback costs $500–$800 fully loaded. A tech running 4% callbacks on 80 jobs per month is generating $1,600–$2,560 in monthly warranty cost.Flag if overall rate > 4% or any tech > 6%
Attach rate (memberships and accessories) by techPull: Membership offers made divided by eligible calls, and accessories sold divided by eligible calls, by tech. You need the offer rate, not just the conversion rate.
Benchmark: Top performers offer on 90%+ of eligible calls. Team average is often 40–60%. The gap is almost always in offer rate, not conversion rate. Techs who make the offer convert at 25–40%. Techs who don't make the offer convert at 0%.Flag if team average offer rate < 70%
New tech ramp time to team average GMPull: GM% trajectory for techs hired in the last 12 months, compared to team average at the same point in their tenure. How long does it take new hires to reach team average GM?
Benchmark: Well-structured onboarding systems get new techs to team average GM within 60–90 days. Unstructured onboarding often takes 6–12 months. At a $450 average ticket and 2-point GM gap for 6 months, each tech in extended ramp costs roughly $12,000–$18,000 in recoverable margin.Flag if > 90 days to reach team average
Back of House Checklist
Back of House — 7 Metrics
Call answer rate during business hours (peak)Pull: Total calls received vs. calls answered, filtered to business hours, last 30 days. Segment by hour of day. Exclude sub-10-second calls (likely misdials). Look at the shape, not the daily average.
Benchmark: Answer rate above 88% during business hours. Peak hours below 80% indicate a staffing or routing gap. At 1,500 monthly calls and a 17% miss rate, that's 255 calls missed at $450 average ticket — a 6-figure monthly exposure at 75% conversion.Flag if any hour < 80% answer rate
CSR booking rate by rep (first-time inbound)Pull: Bookings divided by inbound calls by CSR, filtered to first-time callers on your top 2 service categories. Requires call tracking integration with your FSM.
Benchmark: Top performers at 80–90%. Team average below 65% indicates a standard and coaching gap. A spread of more than 20 points between your best and worst CSR on the same call type requires root-cause investigation. At 100 first-time calls per week, a 20-point spread is 20 lost bookings per week.Flag if team average < 65% or spread > 20 pts
Unsold estimate follow-up ratePull: Unsold estimates from last 90 days. Percentage that received at least one follow-up attempt within 5 business days of estimate delivery.
Benchmark: Top-performing shops follow up on 90%+ of unsold estimates. Industry average is closer to 50–60%. If you're sitting on 200 unsold estimates per month with no follow-up system, and 15–25% of followed-up estimates convert, the gap is 30–50 unbookd jobs per month.Flag if follow-up rate < 75%
Unsold estimate recovery ratePull: Of estimates that did receive follow-up, the percentage that converted to booked jobs. Segment by job type and estimate value.
Benchmark: 15–25% of followed-up estimates should convert. If recovery rate is below 10%, the follow-up script or timing is the issue, not the offer rate. The call is happening but it's not converting — which is a different problem than the call not happening at all.Flag if recovery rate < 15%
Membership offer rate by CSRPull: Membership offers made divided by eligible inbound calls, by CSR. Eligible calls are service calls from non-members within your service area.
Benchmark: Offer rate above 85% on eligible calls. Conversion rate on offers actually made should be 25–40%. Low conversion rate on offers made typically means offer timing or framing is wrong. Low offer rate means the CSR isn't making the offer — which is a coaching gap, not a conversion gap.Flag if offer rate < 80%
Membership renewal ratePull: Members up for renewal in last 90 days. Percentage that renewed. Segmented by who handled the renewal outreach and by how far in advance the outreach began.
Benchmark: Well-managed renewal programs renew 70–80% of eligible members. Below 60% indicates a communication or staffing gap in the renewal process. Each membership lost is a revenue reduction of $150–$350 annually plus the LTV reduction from losing the customer relationship.Flag if renewal rate < 65%
Inbound call abandonment rate by hourPull: Calls that rang and disconnected before being answered, by hour of day. This is distinct from missed calls — abandonment specifically means the customer hung up while waiting.
Benchmark: Less than 8% overall. Peak hours above 15% abandonment indicates overflow capacity gap. High abandonment in specific hours points directly to staffing misalignment with call volume patterns. This is the most actionable metric in the back-of-house checklist.Flag if peak hour abandonment > 15%
How to Interpret What You Find
Any metric outside the benchmark range isn't a problem to immediately fix — it's a priority investigation item. The benchmark tells you there's likely a gap worth quantifying. The investigation tells you what's producing it.
The next step for each flagged metric follows a consistent pattern: pull the raw data behind the number, identify the top two to three contributors, schedule one observation session (a ride-along or call listen) on the highest-cost gap. What you observe in that session tells you more than six months of reports.
Prioritize your flagged metrics by dollar value, not severity. The metric that's farthest outside the benchmark is not necessarily the most expensive one. Multiply the gap by job volume and ticket average. Start with the highest-dollar gap, not the worst-looking ratio.
The operators who close the gap fastest don't start by buying a solution. They start by pulling the data, identifying the highest-cost gap, and watching what actually happens at the point of decision. The fix almost always follows from the observation.
If you've pulled these numbers and want a second set of eyes on what they mean, the 45-minute diagnostic is built for that. We'll show you which gaps are worth pursuing first and what closing them requires.