HomeCasa Monthly business report: from numbers to a clear narrative
Turn the month's metrics into a report people read in five minutes: executive summary, results vs target, confirmed causes vs hypotheses, risks and next month's priorities. Designed for ChatGPT, Claude, Gemini and Microsoft Copilot. It includes 5 customizable variables and you can copy it for free in one click.
Intermediate · Text · Pending editorial review
Prompt
Act as a business analyst who writes monthly reports so leadership understands what happened, why, and what to do next, without dressing up the data.
Data:
- Company or team: {{company}}
- Report month: {{month}}
- Metrics (this month, last month, same month last year if available, and target): {{metrics}}
- Relevant events this month (campaigns, price changes, incidents, seasonality): {{events}}
- Audience: {{audience}}
If the target or comparison period is missing for any metric, ask me or mark it [FILL IN].
Deliverables:
1. An executive summary of 3-5 bullets: the most important point first, with numbers.
2. A results table against target and prior period, with absolute and percentage change and a status flag (on track, at risk, behind).
3. An explanation of the meaningful changes that clearly separates confirmed facts (backed by the data or events I gave you) from hypotheses, marked [HYPOTHESIS: verify with…].
4. Wins, problems and risks for next month.
5. Priorities and specific asks (decisions, resources or support needed).
6. A one-paragraph short version to send by email or chat.
7. Two or three recommended charts to go with the report.
Constraints:
- Do not invent causes, numbers or comparisons that are not in the data.
- Neutral, professional tone: neither triumphant nor alarmist.
- Round consistently and state the units.
Format: headings, one table and short sentences; the executive summary must stand on its own.How to use it
Paste the metrics exported from your reporting tool along with the month's events. Review the flagged hypotheses before sending and replace them with confirmed causes once you have them.
Usage example
Company: online travel agency · Month: October 2026 · Metrics: bookings 1,240 (Sept 1,410, target 1,300), revenue $455,000 · Events: end of season, website down two days · Audience: leadership.
Sample output
Executive summary (October 2026)
- Revenue: $455,000, 4.2% below target ($475,000) and 11.8% lower than September.
- Bookings: 1,240, 4.6% below target (1,300) and 12.1% lower than last month.
- Average revenue per booking is flat (~$367): the drop is volume, not price.
- Cancellation rate rose to 6.1% (+0.7 pp).
- Context: end of the summer season, website down for 2 days, fall getaways campaign live from the 15th.
Results
| Metric | October | Sept. | Change | Target | vs target | Status |
|---|---|---|---|---|---|---|
| Bookings | 1,240 | 1,410 | −170 (−12.1%) | 1,300 | −4.6% | At risk |
| Revenue | $455,000 | $516,000 | −$61,000 (−11.8%) | $475,000 | −4.2% | At risk |
| Cancellation rate | 6.1% | 5.4% | +0.7 pp | [FILL IN] | — | Watch |
What explains the changes
- Fact: the website was down for 2 days.
- [HYPOTHESIS: verify with daily bookings] Part of the shortfall falls on those 2 days; quantifying it would separate the technical impact from seasonality.
- [HYPOTHESIS: verify against last year] The end of summer usually lowers October demand; October 2025 data is needed to confirm.
- [HYPOTHESIS: verify by campaign] The fall campaign has only half a month of data.
Short version
October closed at $455,000 (−4.2% vs target) on 1,240 bookings. Average booking value held steady, so the drop is volume. Next: measure the impact of the 2-day outage and look into rising cancellations. …
Key facts
- Category
- Data management · Reports
- Output type
- Text
- Level
- Intermediate
- Designed for
- ChatGPT, Claude, Gemini and Microsoft Copilot
- Verified in
- Pending editorial verification
- Variables
- Company or team, Report month, Metrics, Relevant events and Audience
- Language
- English
- Price
- Free, no sign-up
- Updated
- Nov 7, 2026
Frequently asked questions
Why separate facts from hypotheses?
Because a report that presents guesses as causes can lead to bad decisions. Flagging hypotheses shows what needs checking before anyone acts.
Can I reuse it every month?
Yes. Keeping the same structure makes months easy to compare. Save your filled-in prompt and change only the data and events.
What is this prompt for?
Turn the month's metrics into a report people read in five minutes: executive summary, results vs target, confirmed causes vs hypotheses, risks and next month's priorities.
Which AI tools does it work with?
It is designed for ChatGPT, Claude, Gemini and Microsoft Copilot. We have not verified it in these tools yet, so results may vary between them.
How do I customize the prompt?
Click “Customize” and fill in the variables (Company or team, Report month, Metrics, Relevant events and Audience). The text updates instantly and you can then copy it in one click. Values are stored only in your browser.
Do I need experience to use it?
It is intermediate: it helps to know the topic so you can provide good context and review the result critically.
Is this prompt free?
Yes. Every HomeCasa Prompts prompt is free, with no sign-up or subscription. You can also use them in professional projects.
Can I trust the AI output?
Treat it as a high-quality draft: always check data, figures and important claims before publishing or making decisions.