Average ticket: definition, formula, and how to track it
Average ticket is the revenue your company earns per completed job. Here is how to calculate it correctly, what moves it, who owns it, and how to watch it in real time across your HVAC, plumbing, or electrical operation.
Formula
Average ticket = total revenue ÷ number of completed jobs
Add up invoiced revenue for all completed jobs in the period, then divide by the count of those jobs. Use completed (invoiced) jobs only, not dispatched or in-progress work orders. Track it by job type to see the real story.
For multi-department operations, calculate average ticket separately for service, install, and maintenance calls so the blended number does not hide a weak segment.
What is average ticket?
Average ticket is the mean revenue per completed job across a defined period. It answers a simple question: when a tech closes a job, how much does the company earn on average? For home-service companies, it is one of the three levers on total revenue (alongside job volume and close rate), so a small move in average ticket compounds quickly.
Consider a scenario most owners recognize: a tech completes a full day of service calls and the schedule looks fine, but when the invoices close several came in at the bare-minimum repair rather than the full set of options the customer qualified for. The booking rate was 100 percent and the job count was solid; average ticket is the number that tells you what was left on the table.
How the math works
To calculate it, divide total revenue by the number of completed jobs for the period. Read it against the prior period and by technician: job volume can climb while revenue per job falls, and a small drop in average ticket multiplied across every job is a large weekly swing that a headline job count hides. On a datacube board this is Revenue per Job in Housecall Pro (total revenue divided by completed jobs) and the Opportunity Job Average on ServiceTitan's Technician Performance Report, shown as Avg Service and Avg Install.
How to calculate average ticket without distorting it
Use invoiced revenue, not estimates or proposals. Exclude cancelled jobs and warranty callbacks that generate no revenue. If your operation runs service, install, and maintenance under one roof, calculate average ticket separately for each job type before blending them, because a $12,000 install mixed with ten $300 service calls produces a blended average that tells you nothing actionable. Pair average ticket with job profitability and gross margin to know whether higher revenue per job is also higher-margin revenue.
Who owns it and how often to review it
The sales or service manager owns average ticket for the team. Individual techs own their own number, visible on a technician scorecard. Review it daily per tech on a live board for in-the-moment coaching, weekly by job type to spot a category softening, and monthly alongside revenue per technician to see whether lower average ticket is dragging total output.
Average ticket by job type: the same week, three categories
| Job type | Jobs completed | Total revenue | Average ticket | Read |
|---|---|---|---|---|
| Service / repair | 64 | $38,400 | $600 | Below goal; check option presentation |
| Install / replacement | 12 | $43,200 | $3,600 | On target; strong close on premium tier |
| Maintenance / tune-up | 44 | $9,680 | $220 | Low by design; flag if add-ons drop |
| Blended total | 120 | $91,280 | $761 | Useful for revenue math; hides the service-call gap |
What good and poor average ticket movement looks like
Targets vary by trade, market, job mix, and season. Set your baseline from your own last 90 days, not a published industry number.
- Average ticket rising while job count holds or growsTechs are presenting more options and winning at a higher price pointGood
- Current
- Target
- Average ticket flat but job mix shifting toward lower-value categoriesRevenue may hold this month but margin and growth are under pressureWatch
- Current
- Target
- Wide spread between your highest and lowest techA training and option-presentation gap, not a territory or lead-quality problemWatch
- Current
- Target
- Average ticket falling during peak seasonTechs may be rushing calls to clear the board; presentation quality drops under volumePoor
- Current
- Target
- Average ticket looks high but discounts are increasingHeadline number is inflated; net realized ticket after discounts is the real measurePoor
- Current
- Target
| Metric | Current | Target | Status |
|---|---|---|---|
| Average ticket rising while job count holds or growsTechs are presenting more options and winning at a higher price point | Good | ||
| Average ticket flat but job mix shifting toward lower-value categoriesRevenue may hold this month but margin and growth are under pressure | Watch | ||
| Wide spread between your highest and lowest techA training and option-presentation gap, not a territory or lead-quality problem | Watch | ||
| Average ticket falling during peak seasonTechs may be rushing calls to clear the board; presentation quality drops under volume | Poor | ||
| Average ticket looks high but discounts are increasingHeadline number is inflated; net realized ticket after discounts is the real measure | Poor |
Info
Coaching moment: when average ticket drops but job count holds
If your team ran the same number of jobs last week but average ticket fell, it is rarely a lead-quality issue. Nine times out of ten, techs stopped presenting full-option menus or started defaulting to the lowest-priced fix to avoid a 'no.' Pull the per-tech numbers on a live board and you will see immediately whether the drop is one person or the whole crew. That conversation happens at 10 a.m. on a Monday, not in a month-end review.
Warning
Common mistake: discounts inflate the apparent average
If your CRM records the pre-discount invoice total, your average ticket looks better than it is. A $1,200 HVAC repair discounted to $900 at the door is a $900 job for revenue purposes. Always calculate average ticket on invoiced and collected amounts, not on quoted or pre-discount figures. For teams using ServiceTitan or Housecall Pro, check which revenue field your reporting pulls from before you trust the number.
Average ticket on a live technician board
How average ticket appears in a datacube Techs board, broken out by individual and job type so a service manager can spot a training gap in the morning, not at month-end.
Figures are illustrative. Your datacube board reflects your own connected CRM, invoicing, and revenue data.
Who can move average ticket and how
| Role | Lever | Cadence |
|---|---|---|
| Field technician | Present all repair/replace options on every call; offer maintenance add-ons; avoid defaulting to the cheapest fix | Every job |
| Service manager | Review per-tech average ticket daily; run ride-alongs for techs below target; share high-ticket call recordings as training | Daily / weekly |
| Sales / install team | Improve close rate on premium-tier proposals; follow up same-day on unaccepted quotes | Per-quote |
| Owner / GM | Set job-type targets separately; review blended average weekly; ensure pricing is current and not eroded by informal discounts | Weekly / monthly |
Owner takeaway
- A $100 increase in average ticket across 500 jobs a month is $50,000 in additional monthly revenue with zero extra marketing spend.
- Never read the blended average alone. Separate service, install, and maintenance to find which category is drifting.
- A live per-tech view turns average ticket from a lagging report into a same-day coaching tool. You see the gap while the tech is still in the field.
Average ticket FAQs
See average ticket by technician, live, in your datacube
Connect your CRM or field-service platform and watch average ticket update in real time, broken out by tech and job type so your service manager can coach in the morning instead of explaining a soft month at the end of it.
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