The Garage Door Company That Tracked Proposal-to-Signed by Tech and Cut Sales Cycle in Half

A $6M residential garage door company in the Southeast had a problem that did not look like a problem. Call volume was up 14% year over year. Their booking rate sat at a healthy 71%. But their signed-job revenue barely moved.

The owner kept blaming ad spend. His ops manager kept blaming lead quality. Neither of them was looking at the right data.

When they finally pulled proposal-to-signed ratios by technician, one tech was closing 58% of proposals written. Two others were closing 22%. Same trucks, same territory, same price book. The bottleneck was not leads. It was what happened in the customer's driveway.

The proposal pile that never moved

The first thing they found was that 184 written proposals from the last 90 days had no follow-up activity logged. Zero calls, zero texts, zero emails. The office assumed techs were following up. The techs assumed the office was.

Tommy Mello's A1 Garage Door books 89% of inbound calls compared to a 42% industry average according to ServiceTitan's case study. But A1's advantage starts at the phone and keeps going. Every unsold estimate gets tagged and worked through a sequenced follow-up, not left to die in a spreadsheet.

The Southeast operator had none of that. Proposals written on-site dropped into a ServiceTitan view nobody owned.

Text Sully: "Show me every proposal written in the last 90 days with no follow-up contact attempt logged."

What the per-tech close rates actually showed

Once they sorted proposal-to-signed by technician, the spread was ugly. Technician A closed 58% of proposals. Technicians B and C hovered around 22%. Technician D was at 31%, but his average ticket was the highest in the shop.

Technician A was not writing more proposals. He was writing fewer, but he was writing them for the right jobs. His conversion-weighted revenue per dispatch was 2.3x the shop average.

This is the pattern the 2025 Garage Door Marketers industry report describes across mid-market operators. The top quartile of techs is not closing because they are better talkers. They are closing because they diagnose a scope the homeowner can actually say yes to on the spot, then present it the same day.

Text Sully: "What is my proposal-to-signed ratio for each tech in the last 60 days, sorted by conversion-weighted revenue per dispatch?"

The same-day estimate the office was accidentally delaying

Their workflow had techs write proposals on-site, sync to the office, and wait for a CSR to send the PDF to the customer. Average delay from write to send was 4.2 hours.

On hot jobs, that 4.2 hours was the gap where the homeowner called a second company and took a same-day appointment.

ServiceTitan's multi-option estimate builder exists specifically to close this gap. Techs build the proposal on-site, the customer signs on the tablet, done. Contractors using tiered good-better-best estimates see a 15% to 25% increase in average ticket per ServiceTitan's own data.

The operator's fix was structural, not training. They pulled the office out of the send flow. Techs sent proposals from the truck, with the customer still in the driveway.

The follow-up sequence nobody was running

For proposals that did not close on-site, the shop had no systematic follow-up. A1 Garage Door runs a 30-day sequence of automated emails and texts on every unsold quote, plus a manual call at day 3 and day 14.

The Southeast shop turned on a 7-touch sequence over 21 days. The first 30 days produced 22 additional signed jobs out of 180 unsold proposals, a 12% recovery rate on revenue that had previously been written off.

On a $1,100 average ticket, that was $24,200 in recovered revenue in one month from proposals already written.

Text Sully: "List unsold proposals older than 7 days that have had no outbound contact, sorted by estimated value."

The one tech whose tickets were too small

Technician B had a 22% close rate but an average ticket 40% below the shop average. On the surface he looked like a poor closer. Under the surface, he was a scope compressor.

When a homeowner needed springs, he quoted springs. When they needed a full opener upgrade he could have bundled, he quoted springs. He was closing the easy yes and walking away from $600 to $1,400 of obvious add-on work per job.

Tiered estimates fix this mechanically. When the proposal is good-better-best, the tech is not making the upsell decision, the homeowner is. A 2024 ServiceTitan study across 200 garage door shops found multi-option presentation lifted tickets on repair-plus-install mixes even when close rate stayed flat.

Text Sully: "Show me techs whose average ticket is more than 20% below shop average, with their repair vs. install mix."

The sales cycle that was actually two cycles

When they mapped proposal-to-signed time by job type, they found two different businesses inside the same shop. Repair proposals signed same-day 78% of the time. Install proposals took 11 days on average.

The shop was running both through the same workflow. Repair leads got the full 30-day nurture sequence they did not need. Install leads got the same sequence designed for urgent buyers, and it was not converting discretionary homeowners who wanted to see the product and think.

Splitting the two sequences cut the install sales cycle from 11 days to 6 days. The repair cycle stayed at same-day, but the office stopped sending 14-day follow-up texts to customers whose garage door had already been fixed three weeks earlier.

The fix sounds trivial. The data to notice it was not.

The top tech who was also the top trainer

Once the owner saw the 58% closer clearly, he stopped treating him as an outlier and started treating him as the template. Technician A rode along with each of the 22% closers for two full days, then they rode along with him for two full days.

Eight weeks later, the two lowest closers were at 34% and 37%. Still below the top tech, but the shop-wide proposal-to-signed ratio moved from 38% to 46%.

John Wilson of The Wilson Companies made a similar move on his plumbing team, noting on Owned and Operated that "the only way to grow a business is with more leads, and the only way to service those leads is with more people." But the same math applies in reverse: the fastest way to scale without more leads is to lift the bottom techs to the average.

What the sales cycle looked like after 90 days

Ninety days in, the numbers had moved. Shop-wide proposal-to-signed was at 46%, up from 38%. Average sales cycle on install jobs was 6 days, down from 11. Monthly recovered revenue from unsold proposal follow-up was averaging $21,000.

More importantly, the ops manager stopped blaming lead quality. The owner stopped blaming ad spend. Both of them started looking at per-tech data every Monday.

The whole exercise cost them zero dollars in new software. They already owned the data. They had never looked at it by technician before.

What this means for your shop

You are probably sitting on the same data right now and not looking at it. Most garage door shops under $10M look at close rate as a shop-wide number. That number hides everything.

Pull proposal-to-signed by technician. Pull average ticket by technician. Pull follow-up activity by proposal. The three numbers together tell you whether your bottleneck is training, pricing, or process. It is almost never marketing.

Sully runs these queries against your ServiceTitan or Workiz data in chat, which matters if your ops manager is a field person who does not live in reports. Ask the question in the truck, get the answer before the next dispatch.

For more on where AI fits into garage door operations, see our guide to AI agents for garage door companies, the build vs. buy decision for AI dispatchers, and the AI quoting and estimating playbook.

Sources

• ServiceTitan: Maximize Your Leads with Tommy Mello
• ServiceTitan: How to Price Garage Door Jobs 2026
• ServiceTitan: Technician Close Rate by Job Type Report Guide
• 2025 Garage Door Industry Market Report
• Owned and Operated: Legends of Tommy Mello's $200M Business
• Medium: From Garage Doors to $220M a Year, Tommy Mello Blueprint