The "what's the return on investment of an AI receptionist?" question is one a garage door shop owner can answer with a calculator and ten minutes. You already have most of the inputs: average ticket, close rate on answered calls, and some sense of how many calls you're not getting to. The math isn't subtle. What's subtle is resisting the urge to inflate the assumptions until the answer feels good.
This page walks the math for a realistic two-truck shop, runs the same math at lower and higher volumes, and lays out the soft returns that don't fit on a spreadsheet but still matter.
Before any ROI calculation, gather these from your own shop. Estimates work, but numbers pulled from your phone logs and invoices work better.
For the broader case for why missed calls cost what they cost, see how much missed calls cost contractors: the real math. For the breakdown of the average garage door repair job, see what's the average garage door repair job worth?.
This is a planning example with reasonable planning numbers. Replace each input with your own.
Shop profile: - Two trucks, mixed residential work, steady call volume with seasonal spikes - Average ticket: $425 (blended across spring jobs, openers, and routine repairs) - Close rate on answered calls: 45% - Current missed calls: about 5 per week (260 per year, or roughly 22 per month), mostly during jobs, at lunch, and after hours - Reasonable conversion on missed calls if they had been answered: 40% (lower than the answered-call close rate, because some missed calls are non-buyers)
Without any change, those missed calls represent:
With Ava installed at $297/month, the realistic capture rate on the same missed-call pool:
Net monthly impact:
ROI multiple: $2,635 in added revenue against $297 in cost = 8.9× revenue-to-cost. After subtracting the cost, the shop nets 7.9× the cost in revenue.
These are example numbers. Pull your own. Most shops that run this calculation honestly end up somewhere between 3× and 15× revenue-to-cost on a flat-rate AI receptionist, depending on call volume and missed-call rate.
For a tighter look at a specific conservative scenario, see the ROI when you miss five calls a week.
Two reasons. First, the example counts only the immediate booked job. A booked spring repair leads to a maintenance call next year, a new opener when the old one finally dies, and a neighbor referral the next time a door breaks. The lifetime value of one captured garage door customer is meaningfully higher than the first ticket. For a closer look at that math, see the lifetime value of a garage door customer.
Second, the example assumes 40% conversion on the missed-call pool — lower than the 45% the shop sees on calls it currently answers. The honest reason: some missed calls really are non-buyers, and pretending otherwise is how ROI calculations lose credibility. The actual capture rate depends on the call mix. Trapped-car calls, broken-spring calls, and door-stuck-open calls convert at a high rate. Open-ended quote requests convert lower. The example splits the difference.
If you want to rerun the math with a more aggressive conversion assumption — say 55% on the missed-call pool — the numbers get bigger, fast. Just know that 55% is an upper bound, not a planning figure.
Not every shop misses five calls a week. A one-truck operation with lower volume still runs the same math, just at a smaller scale.
Lower-volume example: - One truck, smaller radius - Average ticket: $375 - Close rate on answered calls: 40% - Missed calls: about 2 per week (roughly 8 per month) - Reasonable conversion on missed calls: 35%
Smaller shops can still clear the bar, but the cushion is thinner. A shop that misses one or two calls a month may not pencil out against a flat monthly fee; in that case, the math favors a per-call plan. See the is an AI receptionist worth it? page for the break-even test.
A busy three- or four-truck shop with strong marketing spend sees the ROI shift in a different direction.
Higher-volume example: - Four trucks, broad service area, heavy marketing - Average ticket: $475 - Close rate on answered calls: 50% - Missed calls: about 15 per week (roughly 65 per month) - Reasonable conversion on missed calls: 40%
Busy shops are where the math stops being arguable. The flat fee stays $297; the captured revenue scales with call volume. For a higher-volume shop, the ROI multiple is in the tens, not single digits.
Some returns are real and don't fit a calculation:
These don't show up on an ROI line item, but they show up in how the shop runs. For a longer look at the soft side, see the soft ROI: time, sanity, and evenings back.
The honest test of any AI receptionist ROI claim is what shows up on your books after 30, 60, and 90 days. Track:
The first month is the proof. The guarantee Ava ships with — 30-day "First 10 Leads On Us" money-back guarantee — is the test in writing: if the first 10 leads don't show up, the money comes back. That's a measurable promise, not a marketing claim.
Three traps to avoid when running the calculation:
For a longer look at what's real and what's hype in this category, see the broader ai receptionist cost: what you'll actually pay page.
The ROI of an AI receptionist for a garage door shop is rarely subtle. The shop is missing calls; the AI answers them, captures the details, and books the window; the booked jobs show up on the calendar; the revenue shows up on the books. The cost is a fixed $297 a month. The math pencils out at any volume above a couple of missed calls a week, and it pencils out fast at typical shop volumes.
Run the calculation with your own numbers. Use 35%–45% conversion on the missed-call pool, your own average ticket, and the actual missed-call count from your phone logs. If the result is positive by even a small margin, the question isn't whether to install — it's how soon.
The first month is $97. The guarantee covers the first 10 leads. There's no reason to run the math on paper when you can run it for real.
Call the live demo and have Ava call you now — hear exactly what your customers will hear when they call your shop.