A two-city junk-removal company, 60 days
Average job value up 26% across 31 jobs. Google reviews from 29 to 54. What was built, what it cost in software (nothing), and what didn't work.
1. Problem
Good work, priced by feel
An owner-operated junk-removal company in Houston, expanding to a second city, was getting plenty of jobs through referrals and neighborhood groups. Every quote was a judgment call. Tracking lived in a spreadsheet nobody looked at twice. The website was a site-builder placeholder tagged noindex, so a customer who Googled the company by name landed on a competitor.
Nothing was broken in a way the owner could see. The business was simply monetizing its demand inconsistently, and no one could tell which jobs, sources, or cities were actually profitable.
2. Evidence
The baseline, from the owner's own job log
| Metric | Before |
|---|---|
| Average job value | $212 |
| Minimum job price | $85 |
| Jobs under $150 | about 25% |
| Google reviews | 29 |
| Pricing method | judgment, no formula |
| Tracking | a spreadsheet |
| Website | placeholder, noindex |
The $212 average is a logged figure from the pre-pilot job log, not a recollection. That makes the comparison logged-to-logged.
3. Requirement
Raise average job value without losing volume
Success was defined as stronger unit economics, not more revenue and not more jobs. A month with fewer jobs and higher contribution per job would count as a win. Secondary requirement: make profitability visible by job, by lead source, and by city, so future decisions stop being guesses.
4. Reality test
The smallest systems that would work
Thirteen ideas were on the table at the start. Four survived the question "what decision will this support?"
| Element | As-is | To-be | Action taken |
|---|---|---|---|
| Pricing | Judgment call per job | Repeatable formula | Rate card with a $99 floor and three-option quotes (curbside, full-service, full trailer) |
| Tracking | Spreadsheet, rarely used | Job-level economics | Job log capturing value, costs, time, access, and source; live dashboard of $/hour and profit by source and city |
| Reviews | Ad hoc | Systematic ask | Review request built into job close-out, tracked against a redesigned metric |
| Web presence | Placeholder, noindex | Indexable, local | Static site: brand home plus a page per city, local-business schema, pricing published |
Everything ran on tools the business already had. Recurring software cost: zero. The binding constraint was named on day one: adoption. A rate card the owner doesn't quote from is a PDF, not a system.
5. Change
What moved, and what didn't
| Metric | Before | After | Note |
|---|---|---|---|
| Average job value | $212 | $268 | +26%, n=31 |
| Google reviews | 29 | 54 | 5.0 rating, two cities (29 to 46 in the first, 0 to 8 in the second) |
| Google-sourced jobs | none tracked | $550 avg | first month after the site launched |
| Effective rate | unknown | $135/hr | revenue per labor hour, from the job log |
Method: 12 of 31 jobs entered retrospectively from records; baseline from the business's pre-pilot job log. Numbers as of September 2026. The second city is still ramping.
What didn't work: the review-ask rate stalled around 60 to 70% until the metric was redesigned to track asks per closed job instead of reviews per week. Job volume dropped when ownership changed mid-pilot, which is why the result is stated as average job value and not revenue.
What I'd do differently
Start the job log on day one instead of reconstructing 12 jobs from records later. Retrospective entry is defensible, and it's stated above, but a clean logged-from-the-start series would have made the before-and-after stronger and saved a week. And I'd set the adoption check-in weekly from the first week, not the third. Systems fail on the people side long before they fail on the tech side.
Why this matters for a med spa
Different business, same shape. A spa's version of judgment pricing is judgment follow-up: whoever remembers, whenever they have a minute. The fix is the same three steps, diagnose with real numbers, install the smallest system, measure. See the method or book a call.