What the numbers actually look like
Three businesses, three different problems, and the arithmetic behind each one.
These are models built from published benchmarks. Each scenario uses the same calculation we run in a Profit Recovery Report. We’d rather show you the method with numbers you can check than a testimonial you can’t.
The phone is the problem
Scenario oneA home services company doing about $2.1M a year. Three service vehicles, an office manager who also handles scheduling, and an owner who still runs most of the quotes. Plenty of demand — they spend on advertising and the phone rings.
Thirty days of call records
- Inbound calls
- 287
- Answered during hours
- 201
- Rang out after hours
- 61
- Missed during the day
- 25
- Never reached anyone
- 86
What that means
Thirty percent of the people who called this business never spoke to it. The advertising is working. The answering isn’t.
- No coverage after 5pm or on weekends, when 71% of the missed calls landed
- Voicemail existed but was checked the next morning, if at all
- No record of a missed call ever being returned
86
Calls a month that reached nobody
26
Recovered at a 30% response-and-book rate
$41K
Monthly revenue at their close rate and average job
Modeled at a $4,800 average job, a 33% close rate on booked appointments, and 30% of missed calls recovered. At a 20% recovery rate the same calculation gives $27K a month; at 40%, $54K. No new advertising spend — this is entirely demand the business had already paid to create.
Two years of quotes nobody went back to
Scenario twoA specialty trade contractor at roughly $3.4M, most of it service and maintenance work with quoted projects on top. Two estimators, a real CRM, good reputation, healthy pipeline. The phone gets answered. The problem is what happens after the quote goes out and the customer doesn’t call back.
Quotes, trailing 24 months
- Quotes sent
- 418
- Won
- 121
- Declined outright
- 54
- Never got an answer
- 243
- Value quoted and never answered
- $3.1M
What that means
A 29% win rate, which the owner believed was closer to 45%. More than half of every quote written simply went quiet, and nothing happened after that.
- Follow-up was one email, sent by whichever estimator remembered
- No sequence, no reminder, no second attempt after week one
- The oldest unanswered quotes were still valid work the customer needed
243
Quotes sitting unanswered in the system
7
Jobs recovered from a first campaign at 3%
$89K
Revenue from one pass through an existing list
Modeled at a $12,700 average job and a 3% reactivation rate, which is conservative for a list of people who requested a quote. At 2% the same list produces 5 jobs and $64K; at 5%, 12 jobs and $152K. The list regenerates continuously — every month adds more.
Losing on speed, not on price
Scenario threeA smaller operation at around $900K. Owner plus two, no office staff, everything runs through one mobile number. Leads come from search and referral. The owner’s read was that they were being undercut on price.
Time from inquiry to first contact
- Within 5 minutes
- 9%
- Within an hour
- 23%
- Same day
- 44%
- Next day or later
- 24%
- Median response time
- 4h 40m
What that means
They weren’t losing on price. They were losing to whoever called back first, and then hearing about price as the reason.
- Web form submissions went to an inbox checked in the evening
- Calls during a job went unanswered and unreturned
- Quoted jobs won at a healthy rate — the leak was before the quote
4h 40m
Median response, down to under a minute automated
+38%
More inquiries converting to a booked appointment
$127K
Additional annual revenue at their existing win rate
Modeled on published speed-to-lead research showing sharply higher contact and qualification rates when first response happens within five minutes rather than hours, applied to their existing lead volume and win rate. At a 20% improvement the same model gives $67K; at 50%, $167K.
How we build the real version
Yours won’t use benchmarks. It uses your numbers.
Your export, not our estimate
Quotes sent and won, average job value, and dates come straight out of your system. If the number is smaller than these, we tell you that.
Ranges, never a single figure
Every projection is shown at a low, likely, and high recovery rate, with the assumptions on the page. You can argue with them, which is the point.
Jobs before dollars
Revenue is easy to inflate. We show what it means in work you’d actually take on, then apply your margin to get to what you keep.
Find out what’s sitting in your system
A short call, then a report built from your own numbers. Yours to keep either way.
Book a call