Painting Business Profit Calculator – Model a Lean $1.7M Company

Your Numbers

Appointments per year

The benchmark estimator ran ~600 (about 2.4 per working day).

Close rate

Average job value

Gross margin

Revenue left after paying crews and materials.

Fixed overhead per month ($)

Marketing, software, insurance, vehicles.

Estimator salary per year ($)

VA cost per month ($)

Live Results

Annual revenue

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Gross profit

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Net profit

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Net margin

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Jobs booked / yr

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Jobs / week

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Estimator appts / working day

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Revenue to Net Profit

Benchmark: you vs the lean $1.7M model

Benchmark: 600 appointments, 42% close, $6,750 average job, 45% gross margin, $9k/mo overhead, $90k estimator, $1.5k/mo VA.

Scenario compare

Current

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Lean Model

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Estimator capacity and close rate FAQ

Is 600 appointments a year realistic for one estimator?

Yes. 600 appointments across roughly 250 working days is about 2.4 per day. With tight territory routing and a VA handling scheduling, many residential estimators run 2 to 3 daily.

What close rate should a painting company target?

Residential repaint companies commonly close 35 to 50 percent of qualified in-home estimates. Below 30 percent usually signals pricing, lead quality, or follow-up problems rather than an estimating problem.

How does the lean model stay profitable with no salespeople?

Marketing generates booked appointments, one estimator converts them, subcontracted crews carry production, and a VA runs scheduling and admin. Fixed costs stay small, so gross profit falls almost straight to the bottom line.

Painting revenue, gross margin and fixed costs

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Read the explanation

The saved source fixture says six thousand seven hundred fifty average job value, but the native range control has a hundred-dollar step. The browser rounds that value to six thousand eight hundred. At six hundred appointments and forty-two-percent closing, expected jobs are two hundred fifty-two. Actual initial revenue is therefore one million seven hundred thirteen thousand six hundred, while the raw JavaScript benchmark built directly from the fixture is one million seven hundred one thousand. Bars compare these amounts at point zero zero zero three pixels per dollar. This illustrates why reading a fixture constant alone does not prove the actual page result. These are authored estimates, not verified company results. At the native six-thousand-eight-hundred job value, modeled revenue one million seven hundred thirteen thousand six hundred times forty-five-percent gross margin gives seven hundred seventy-one thousand one hundred twenty. Fixed expenses sum nine thousand monthly overhead and fifteen hundred monthly assistant cost, multiply by twelve and add ninety thousand annual salary, totaling two hundred sixteen thousand. Net becomes five hundred fifty-five thousand one hundred twenty. Bars compare gross and net at point zero zero zero six pixels per dollar. The model does not validate category completeness, taxes, crew costs, materials or capacity. The benchmark remains based on the raw fixture and therefore differs from the page actual default controls. The appointments slider cannot go below one hundred. Native Home therefore selects one hundred rather than zero. Expected jobs become forty-two and revenue is two hundred eighty-five thousand six hundred. Gross profit is one hundred twenty-eight thousand five hundred twenty; subtracting unchanged fixed costs gives negative eighty-seven thousand four hundred eighty. Bars show revenue and the loss magnitude at point zero zero zero six pixels per absolute dollar, with labels distinguishing the sign. The source metric text animates for finite elapsed time, so native verification waits until its actual final values appear. The program assumes fifty weeks and two hundred fifty working days for workload summaries. It does not establish real business viability.