Most owners have the numbers: sales in the accounting tool, leads in the CRM, ad spend in Meta or Google. What they lack is an hour each month to put it together and ask "so what?".
AI is very good at that "so what". Export last month and the month before, paste them in, and get a one-page report that a busy owner or a business partner can read in two minutes.
How to use it
- Export the same few things every month: revenue by service, number of leads by source, jobs won, ad spend, and any big expenses. CSV or a copied table both work.
- Paste this month and last month (and the same month last year, if you have it).
- Ask follow-up questions after the report: "Which lead source has the best cost per job?" is where it gets useful.
monthly-report.txt
You are my business analyst. Read the data below and write a one-page monthly report I can read in two minutes. Business: [name], [what we do] Month: [month and year] What I care about most right now: [e.g. more booked jobs, better margins, which ads work] Data (this month, last month, and same month last year if available): [paste exports or tables here] Write: 1. Headline: one sentence on how the month went. 2. Key numbers: a small table with this month, last month and the change in %, for revenue, leads, jobs won, close rate, average job value, ad spend, cost per lead and cost per job (only those the data supports). 3. What happened: 3 to 5 bullet points explaining the biggest changes, pointing to the numbers behind each. 4. What to watch: anything unusual or worrying. 5. One recommendation for next month, specific and doable, with the number it should move. Rules: show your working for any calculated figure. If data is missing or unclear, say so rather than guessing. Plain English, no jargon.
Make it a habit
- Same day every month, for example the 3rd, once the books are closed.
- Track the same five numbers so trends become obvious: leads, cost per lead, jobs won, average job value, profit.
- One decision per report. Pick the single change for next month and write it at the top of the next report.
Check every number the AI quotes against your export before you act on it. AI tools can misread a column or do sums wrong; the analysis is only as good as the data.