Two companies. Same revenue. Same tech count. One owner clears $180K more per year. The difference is eight miles.
You’re looking at two HVAC companies side by side. Both run $2.4M in revenue. Both have six trucks. Both have solid Google reviews and a clean P&L. You’d pay the same multiple for either one.
But Company A’s techs average 5.1 calls per day. Company B’s techs average 3.6.
The difference isn’t talent, training, or motivation. It’s geography. Company A’s customers are clustered inside an 8-mile radius. Company B’s are scattered across 30 miles of suburban sprawl. Company A’s techs drive 12 minutes between calls. Company B’s techs drive 42 minutes. That gap — 30 minutes per call, multiplied across every tech, every day, every year — is worth north of $400K in annual revenue that Company B is leaving on the road.
You will not find this in a Quality of Earnings report. The QoE tells you what happened. Route density tells you why — and whether it can change.
What Route Density Actually Is (and What It Isn’t)
Route density is not the size of your customer list. A company with 8,000 customers spread across three counties has worse route density than a company with 2,200 customers inside two ZIP codes.
Route density measures the average distance and drive time between consecutively dispatched service calls on the same truck, on the same day.
Three components define it:
- Geographic concentration — Where do the customers physically sit? Are they clustered or scattered?
- Dispatch proximity — When a tech finishes one call, how far is the next? This is where the dispatcher either compounds the geography or makes it worse.
- Service area shape — A company serving a long, narrow corridor (highway towns) has different density math than one serving a compact metro pocket.
A large customer base in a tight area is the dream. A small customer base in a tight area is fixable through marketing. A large customer base across a wide territory is the trap — it looks great on paper and bleeds money in windshield time.
This connects directly to the customer concentration risk analysis every buyer should run — but where concentration looks at who the customers are, density looks at where they are.
The Math That Makes It Material
Here’s why this matters more than most metrics on a broker’s teaser.
The average HVAC technician spends 27% of their working day driving. Not diagnosing. Not repairing. Not selling maintenance agreements. Driving.
That’s roughly 2.2 hours of an 8-hour day with the wheels turning and the meter off.
Top-performing companies — the ones private equity keeps buying — have pushed that down to 15–18%. Their techs complete 5.2 calls per day against the industry average of 3.8. The difference is 1.4 extra revenue-generating stops every single day.
Run the numbers on that gap:
- 1.4 additional calls/day at a $150 average residential ticket
- 250 working days/year
- = $52,500 in additional revenue per technician per year
For a six-truck operation, that’s $315,000 in annual revenue that a route-dense company captures and a sprawling one doesn’t. And because the marginal cost of that extra call is almost zero — the tech is already on the clock, the truck is already running — nearly all of it falls to the bottom line.
Industry data from ACCA (Air Conditioning Contractors of America) puts revenue per technician benchmarks at $150K–$250K/year. The companies at the top of that range aren’t running better techs. They’re running tighter routes.
The structural ceiling is real. A tech who averages 45–90 minutes of unnecessary drive time per day — and the data says most do — physically cannot complete more than 3.5 calls. It doesn’t matter how fast they work on-site. The windshield is the bottleneck.
How to Run the Diagnostic Before You Sign the LOI
You don’t need the seller’s cooperation for most of this. You need their customer database — which you’ll get during initial diligence — and about two hours with a spreadsheet.
Step 1: Export and Map the Customer Base
Pull every active customer (service visit in the last 24 months) with their address. Plot them. Google My Maps works fine. You’re looking for visual clustering.
What you want to see: a heatmap with a hot center and defined edges. What you don’t want to see: a shotgun blast.
Step 2: Calculate ZIP-Code Concentration
Group customers by ZIP code. Then calculate what percentage of total customers sit in the top 5 ZIPs.
| Top-5 ZIP Concentration | What It Signals |
|---|---|
| 70%+ | Excellent density — this is a route-optimized business |
| 50–69% | Good density with room to tighten |
| 35–49% | Moderate sprawl — optimization possible but margins are capped |
| Below 35% | Structural sprawl — this is a different kind of acquisition |
Step 3: Pull Average Drive Time Between Dispatched Calls
If the company uses ServiceTitan, Housecall Pro, or any modern field service platform, this number exists in the dispatch reports. Ask for it. If they’re dispatching off a whiteboard and a prayer, that tells you something too. The ServiceTitan due diligence shortcut covers what to pull and how to ask for it without spooking the seller.
The benchmark: zone-based dispatching companies average 15–25 minutes between calls. Companies without it average 35–50 minutes.
Step 4: Calculate Revenue Per Road Mile
Pull total revenue. Pull total fleet miles from maintenance records or GPS logs. Divide.
This is the number nobody tracks and everybody should. More on this below.
Step 5: Cross-Reference With Technician Productivity
Take calls completed per tech per day from the dispatch data and compare to technician performance benchmarks that separate healthy operations from struggling ones. If call counts are low but on-site time is normal, drive time is the culprit.
What the Results Tell You
Route density results sort acquisition targets into three buckets. Each one means something different for your offer, your integration plan, and your upside.
Dense Cluster: The Scalable Operation
Top-5 ZIPs hold 65%+ of customers. Average inter-call drive time under 20 minutes. Techs completing 4.5+ calls/day.
This is the operation that scales. Adding a truck here means adding revenue at the same efficiency rate. Marketing dollars compound because new customers slot into existing routes. Maintenance agreement density builds on itself — a tech can run six PM visits in a day when they’re all within four miles.
You pay full price for this. Possibly a premium. The revenue per truck numbers will confirm what the map shows.
Sprawl: The Structural Ceiling
Customers spread across 20+ ZIPs with no concentration above 12% in any single code. Drive times averaging 40+ minutes. Techs stuck at 3.0–3.5 calls/day.
This business has a ceiling that isn’t talent or demand — it’s physics. The tech can’t be in two places at once, and the distance between those places eats the day.
Sprawl isn’t fatal, but it changes the math. Your working capital requirements go up because you need more trucks and more techs to service the same revenue. Your margins are structurally lower. And your growth lever isn’t marketing — it’s consolidation, buying another company whose territory fills your gaps.
Price accordingly. A sprawled $2M company is not worth what a dense $2M company is worth, even if the trailing EBITDA looks identical. The dense company has room to grow inside its footprint. The sprawled company needs capital to restructure. Your acquisition math should reflect the difference.
Semi-Dense With Gaps: The Optimization Play
A strong core cluster covering 50–60% of customers with thin coverage radiating outward. Drive times averaging 25–35 minutes. Techs at 3.8–4.2 calls/day.
This is the most interesting acquisition target for an operator-buyer. The core is solid. The gaps are identifiable. Post-close, you have a clear playbook:
- Zone the dispatch. Assign techs to geographic territories instead of dispatching by availability. This alone drops inter-call drive time by 10–15 minutes.
- Market into the gaps. Run targeted campaigns in the ZIPs adjacent to your dense core. Every new customer in a cluster ZIP is more valuable than one in a frontier ZIP because they add density to existing routes.
- Shed the frontier. Some customers aren’t worth keeping. A customer 45 minutes from your nearest cluster who calls once a year for a filter change is costing you money every time you send a truck. Refer them out or raise their rates to cover the drive.
The gap between current performance and optimized performance is your post-close value creation. Build it into your due diligence model and your pro forma — but don’t pay for it. The seller hasn’t captured that value. You shouldn’t buy it as if they did.
Three Things to Do With This Data
1. Implement Zone-Based Dispatching (Week One)
This is the single highest-ROI operational change in HVAC. Instead of dispatching the next available tech to the next incoming call, you divide your service area into zones and assign techs to their zone for the day.
The math is straightforward. Zone-based dispatching reduces average drive time from 35–50 minutes between calls to 15–25 minutes. That’s 1–2 additional calls per tech per day. At $150 average ticket, that’s $55,000–$85,000 in additional revenue per technician per year.
For a six-truck shop, that’s $330K–$510K in new annual revenue with zero additional headcount. The cost to implement: a dispatcher who understands geography and a field service platform with zone assignment capability.
2. Run Strategic Gap-Fill Marketing
Once you’ve mapped the clusters and the gaps, your marketing spend gets surgical. Instead of blanketing a metro area with LSA ads, you target the ZIPs between your clusters.
Every new customer in a gap ZIP does double duty: they generate revenue and they tighten the route for every tech who drives through that area. A $200 customer acquisition cost in a gap ZIP might be worth $600 in a frontier ZIP because of what it does to the route math around it.
3. Adjust the Purchase Price for Low Density
If the diagnostic reveals structural sprawl, you have a quantifiable negotiation lever. Here’s how to frame it:
Calculate the revenue gap between current calls/tech/day and the zone-optimized benchmark. Multiply by tech count and 250 days. That’s the annual revenue the company is leaving on the table because of its geographic footprint.
The capital and operational cost to close that gap — zone software, possible dispatcher hire, 6–12 months of gap-fill marketing, potential customer attrition from frontier shedding — belongs in your working capital analysis, not absorbed into the multiple.
If the seller’s asking 3.5x SDE and the route sprawl will cost you $150K and 12 months to fix, that’s a 3.5x multiple on today’s earnings plus $150K in capital that buys you tomorrow’s earnings. Adjust the offer or reframe the deal structure.
The Metric Nobody Tracks: Revenue Per Road Mile
Every HVAC owner knows their revenue. Most know their revenue per tech. Almost none know their revenue per road mile.
Here’s how to calculate it:
Annual revenue ÷ Total annual fleet miles = Revenue per road mile
A company running $2.4M on 180,000 fleet miles generates $13.33 per mile. A company running the same $2.4M on 300,000 fleet miles generates $8.00 per mile.
Both companies look identical on a broker’s teaser. But the first company is 67% more efficient at converting miles into money. Its fuel costs are lower. Its vehicle maintenance is lower. Its techs are less fatigued. Its insurance exposure is smaller. And its owner-operator replacement cost is more predictable because the operation doesn’t depend on one person’s mental map of an impossibly large territory.
Revenue per road mile is the metric that captures everything route density implies and converts it to a single, comparable number.
Revenue Per Road Mile Benchmarks
| Revenue/Mile | Rating | Typical Profile |
|---|---|---|
| $15+ | Elite | Tight geography, zone dispatch, high ticket average |
| $10–$15 | Strong | Good density with optimized routing |
| $7–$10 | Average | Typical independent HVAC company |
| $5–$7 | Below average | Geographic sprawl or low ticket pricing |
| Below $5 | Red flag | Structural problem — the truck costs more than it earns per mile |
If you’re comparing two acquisition targets and everything else looks equal, the one with higher revenue per road mile is the better buy. Every time.
The Bottom Line
Route density is the operational metric that hides in plain sight. It doesn’t appear on a P&L. It doesn’t show up in a QoE report. No broker includes it in a teaser.
But it determines how many calls your techs can run, how much revenue each truck generates, how far your marketing dollars stretch, and whether the business can grow without proportionally growing its fleet.
Two HVAC companies with the same revenue are not the same company if one operates inside 8 miles and the other covers 30. The dense company has a wider moat, a lower cost structure, and a higher ceiling. The sprawled company has a problem that money alone doesn’t solve — because the problem is distance, and you can’t buy geography.
Run the diagnostic before you sign the LOI. Map the customers. Pull the drive times. Calculate the revenue per road mile. It takes two hours and it will tell you more about the acquisition’s real economics than a $20,000 QoE report ever will.
The best deal I ever did looked mediocre on the financials and incredible on the map. The worst deal I ever passed on looked great on the financials and terrible on the map. I got lucky on that second one — the buyer who took it spent two years trying to solve a geography problem with better techs. You can’t outrun the route.