A 6-truck HVAC shop stops losing summer emergency calls
A 6-truck HVAC shop stops losing summer emergency calls
Modelled on a shop taking 400 inbound calls a month in peak season, missing roughly a quarter of them, with an average ticket of $480.
The starting situation
Dispatch answers while the phones are quiet, but from 7am to 11am in a heat wave every tech is on a roof and the office line rings out. Callers do not leave voicemail during an emergency — they dial the next result on Google. Nobody in the shop knows how many jobs walked, because a missed call leaves no record anywhere except the carrier log.
What was installed
- AI Missed-Call Text-Back wired to the main business line through the existing phone provider
- Three-question qualifier: system type, symptom, and whether the unit is fully down
- Booking link that writes straight into the dispatch calendar with a 2-hour arrival window
- Weekly recovery report listing every missed call, the reply sent, and whether it booked
Before and after
| Measure | Before | After |
|---|---|---|
| Inbound calls / month | 400 | 400 |
| Calls missed | ~100 | ~100 |
| Missed calls that got a reply within 60s | 0 | 100 |
| Missed calls recovered to a booked job | ~5 (callbacks) | ~22 |
| Average ticket | $480 | $480 |
The arithmetic
- 100 missed calls × 22% recovery rate = 22 recovered jobs per month.
- 22 jobs − 5 that manual callbacks were already saving = 17 incremental jobs.
- 17 × $480 average ticket = about $8,160 of recovered monthly revenue.
- Running cost: the $59 system, one-time, plus roughly $15/month of SMS spend.
First recovered job pays for the system several times over — day one, in practice.
Verdict: Missed-call text-back is the highest-leverage first install for any trade with a phone-driven pipeline, because it monetises demand you already paid to generate.
What to install to reproduce this
This build runs on AI Missed-Call Text-Back, bundled inside the HVAC package.
- · AI Missed-Call Text-Back wired to the main business line through the existing phone provider
- · Three-question qualifier: system type, symptom, and whether the unit is fully down
- · Booking link that writes straight into the dispatch calendar with a 2-hour arrival window
- · Weekly recovery report listing every missed call, the reply sent, and whether it booked
Related pages
More build math
Key terms on this page
- Lead qualification
Lead qualification is the process of asking a new enquiry a short set of questions — job type, location, timeline, and budget range — to decide whether it is worth a sales conversation and how urgently to route it.
- Speed to lead
Speed to lead is the elapsed time between a prospect making contact and your business making a real, personalised first response.
- SMS lead responder
An SMS lead responder is an automation that sends a personalised text message to every new enquiry within seconds, then continues a short qualifying conversation over text until the lead books or opts out.
- Missed-call text-back
Missed-call text-back is an automation that detects an unanswered inbound call and immediately sends the caller a text apologising, naming your business, and offering to book or answer questions.
- Payback period
Payback period is how long a system takes to generate enough additional gross profit to cover what it cost to buy and install.
- AI appointment setter
An AI appointment setter is an automation that takes a qualified lead through to a confirmed calendar slot over text, chat, or voice, including reminders and rescheduling.
How the numbers on this page are measured
Every metric quoted for this modelled build has a stated definition, a formula, and an assumption you can test against your own books. Last reviewed 2026-08-05.
| Metric | Definition | How it's calculated | Assumption |
|---|---|---|---|
| Missed-call recovery rate | The share of unanswered inbound calls that are converted into a booked job through an automated text-back conversation. | booked_jobs_from_missed_calls ÷ total_missed_calls, per calendar month. | Requires a phone system that reports missed calls with caller ID, and a jurisdiction where transactional SMS reply to an inbound caller is permitted. |
| Speed to lead | The elapsed time between a prospect raising their hand (form, call, DM) and the first substantive reply reaching them. | first_reply_timestamp − inbound_timestamp, measured per lead and reported as a median. | An automated reply counts only if it asks a qualifying question or offers a booking action — an autoresponder that says 'we got your message' is not a reply. |
| Cost per booked job | All-in monthly cost of the system divided by the jobs it books. | (system_cost + tool_subscriptions) ÷ booked_jobs_attributable_to_the_system. | Only jobs where the system made first contact are attributed; jobs from referral or repeat customers are excluded. |
Sources
- The Short Life of Online Sales LeadsHarvard Business Review, 2011Response time is the dominant variable in inbound lead conversion; contact odds fall sharply after the first hour.
- Lead Response Management studyMIT / InsideSales, 2007Contacting a web lead within five minutes materially increases qualification rates versus contacting after 30 minutes.
- Local Consumer Review SurveyBrightLocal, 2024Most consumers read reviews before choosing a local service business, and review recency affects trust.
- Local Search Ranking FactorsWhitespark, 2023Review quantity, recency, and response behaviour are recognised local-pack ranking signals.
- Small business phone and messaging behaviour researchGoogle / Ipsos small business studies, 2019Calls are a primary conversion path for local service searches, so unanswered calls are lost revenue rather than deferred revenue.
- Business texting engagement benchmarksTwilio Messaging research, 2023SMS is opened and replied to faster than email for time-sensitive service conversations.
What this is — and isn't
Figures on this page are modelled, not audited client results. Inputs (call volume, ticket size, close rate) are stated next to every number so you can substitute your own. We do not publish named-client outcomes, aggregate ratings, or testimonials we cannot evidence.
Full modelling rules, attribution rules, and the correction policy are on our methodology page.
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