By Greg Allan, tradesman and creator of Data First Coaching
Why can a cleaning business look profitable but the bank account says otherwise?
A cleaning business running commercial contracts, bond cleans, carpet and upholstery work and insurance restoration jobs under one combined set of books can show a healthy gross profit margin on the profit and loss while the owner still feels short every month. The P&L adds every job type together, so a thin margin on one service and a strong margin on another cancel each other out and hide where the money actually goes.
A recurring commercial clean with a steady roster and predictable chemical use behaves nothing like a water damage callout with hired drying equipment, or a bond clean that ran two extra labour hours because the tenant left the oven and carpets in a state nobody quoted for. When those costs land in the same bucket as everything else, the owner cannot see which service is carrying the business and which is being carried.
Why do bond cleans, commercial contracts and restoration jobs need their own numbers?
Each job type carries a different mix of labour, chemicals and equipment, so lumping them together under one overall gross profit margin hides which service is actually paying the wages. A quiet fortnight on commercial contracts, a run of difficult end of lease cleans needing extra labour, or a mould job that needs specialist chemicals and equipment the business does not use every week, each shows up as a dent in overall profit rather than a flag against the job type that caused it.
Strata and commercial clients often pay to a schedule, insurers on restoration work can be slow to settle, and a bond clean is usually paid on completion. A business can be doing good work and still feel the cash gap when one of those payment patterns stalls, and without the numbers split by job type there is no way to tell whether that gap is timing or a genuinely thin margin on one side of the business.
What should a cleaning business coach look at before anything else?
A cleaning business coach worth paying should start by asking to see your own job and finance data split by service, not by asking you to describe the business from memory in a first session. Data first coaching means the conversation starts from what your numbers already show, so the time goes on fixing the real gap rather than retelling a story that is out of date within weeks.
This is also where AI agents start to matter. An AI agent is software that does a job the way you would, with your prices, wording and rules, and a cleaning business can use one to tie labour, chemicals and equipment back to the job type they actually belong to as the cost is entered, instead of sorting it out at the end of the month when the trail has gone cold. A second AI agent can sit on the insurer side of restoration work, keeping track of what has been claimed and what is still owed, so a slow payer does not quietly become a write-off.
What should you ask a cleaning business coach before you sign up?
Ask whether the coach has run a trade business themselves, whether they start from your own job and finance data or a template, and whether every problem they raise gets answered with “hire someone” rather than a look at what is actually going wrong. A coach who has only studied businesses from the outside tends to reach for general advice that would read the same for a cleaner, a sparky or a landscaper.
Greg Allan, who coaches cleaning business owners this way, built his own trade business before coaching anyone else's, which is one way to tell the difference between a coach who has run jobs and crews and one who has only read about them. Warning signs worth watching for: a salesperson leads the first call instead of a conversation about your numbers, the advice is the same worksheet handed to every business regardless of trade, and nobody asks to see your actual gross profit margin by job type before telling you what is wrong.
What changes when a cleaning business finally sees all its numbers in one place?
Picture a multi-service cleaning business whose first attempt at an in-house dashboard for commercial contracts, bond cleans and restoration work turned clunky fast. Two people were building separate sections that never quite lined up, the screen took an age to load, and within a season it had stopped updating altogether, so nobody trusted it enough to open it before a quote.
When it was rebuilt, all the job and finance data sat in one clean central place, and the screen simply pulled fresh numbers each time it opened rather than storing a stale copy. AI agents were set up to check the work at each stage of the build, so a figure that looked wrong got flagged before it ever reached the owner's screen. The picture is not a result, it is what becomes possible once the data has somewhere proper to live.
How does Data First Coaching approach this?
Data First Coaching, created by Greg Allan, starts with the owner's own job and finance data through the Trade Business Intelligence, not with a round of questions about how the business runs. For a cleaning business carrying commercial contracts, bond cleans, carpet and upholstery work and restoration jobs side by side, that means looking at gross profit margin by service first, because a healthy overall number can be hiding a service that loses money every time it runs.
The Trade Business Intelligence reads that data alongside ten years of coaching trade businesses, and it is powered by every member, so what one cleaning business learns about tracking restoration costs or insurer payment patterns sharpens the picture for every other member. The how, the systems and the builds, are worked through inside the Academy, with members, and the Academy is for owners who are open minded, innovative and willing to share what they find.
