Which Types of Jobs Should I Chase, and Which Should I Stop Taking?

Revenue per job is the wrong ranking

A $450 move-out clean looks better than a $200 recurring visit until you count the hours, the supplies, the higher refund risk, and the fact that the move-out customer is leaving town. In my own data, move-out customers are inherently one-off, which is exactly why I exclude them when I measure one-time to recurring conversion. A job type's value is its margin per hour times what it leads to afterward.

How to run the analysis

• Group completed jobs by type (recurring, deep clean, move-out, add-ons) over at least three months.
• Compute gross profit per job: collected revenue minus payout for that job.
• Divide by actual hours, not estimated hours. Underestimated duration is where "good" job types quietly go bad.
• Trace refunds and redos to job type. A category with a 5% refund rate needs its margin haircut by more than 5%, because a redo also burns a slot you could have sold.
• Tag what each job led to: recurring conversion, referral, or nothing. That's the LTV column, and it changes the ranking.

The decision rule

• High margin per hour, leads to recurring: chase. Point marketing spend here.
• Thin margin, leads to recurring: keep, treat as paid customer acquisition.
• High ticket, low margin per hour, leads nowhere: raise the price or stop. This is usually the category owners defend hardest, because the invoice looks good.
• High refund rate whatever the margin: fix the process or drop the category.

Why this needs two systems

Your booking platform knows job type and revenue. Payouts, refunds, and true costs live in payroll and your payment processor. The join is where the answer is, which is why most owners rank job types by ticket size, the one number they can see, and quietly subsidize their worst category for years. The same join, run against my own 920 cleans, is what produced the margin numbers in the benchmark report.