File: 'Q1-2026-revenue-by-segment.csv'\nRows: 18 · Columns: month, segment, mrr, customer_count, churn_rate\n\nFull data:\n2025-11, SMB, $42,300, 312, 4.1%\n2025-11, Mid-Market, $128,500, 87, 2.2%\n2025-11, Enterprise, $89,000, 12, 1.0%\n2025-12, SMB, $40,800, 298, 4.8%\n2025-12, Mid-Market, $134,200, 91, 2.0%\n2025-12, Enterprise, $94,500, 13, 0.8%\n2026-01, SMB, $38,100, 281, 5.4%\n2026-01, Mid-Market, $141,800, 95, 1.9%\n2026-01, Enterprise, $98,200, 14, 0.7%\n2026-02, SMB, $35,200, 263, 6.1%\n2026-02, Mid-Market, $148,900, 99, 1.7%\n2026-02, Enterprise, $108,000, 16, 0.5%\n2026-03, SMB, $33,400, 245, 6.8%\n2026-03, Mid-Market, $156,200, 104, 1.5%\n2026-03, Enterprise, $115,500, 18, 0.4%\n2026-04, SMB, $31,200, 228, 7.2%\n2026-04, Mid-Market, $164,400, 109, 1.4%\n2026-04, Enterprise, $122,800, 20, 0.3%\n\nAuto-detected: SMB MRR is declining month-over-month while Mid-Market and Enterprise are growing. Total MRR is growing despite SMB decline. SMB churn rate has nearly doubled over the period.

Summary  
This chapter covers prompt engineering techniques for interpreting structured data by using iterative prompts and context reuse to guide a model toward extracting specific, actionable insights.  

General domain of usage  
Business analytics

You can throw a CSV at Claude and get back **"MRR is up overall."** Useless. You can also get a sharp three-line read that names the segment in trouble, the month it started, and what to do about it. Same data – different system prompt.

## The Shift from Notes to Numbers

A notes-reading tool returns prose. A spreadsheet tool returns rows – but that changes the **failure mode** rather than removing it.



Ask **"summarize this spreadsheet"** and you'll get: **"Revenue grew, churn varied, customers fluctuated."** All true, all worthless. The model has to **interpret** the numbers, not echo them.



| Month | Segment | Mrr | Customer_count | Churn_rate |
|---|---|---|---|---|
| 2025-11 | SMB | $42,300 | 312 | 4.1% |
| 2025-11 | Mid-Market | $128,500 | 87 | 2.2% |
| 2025-11 | Enterprise | $89,000 | 12 | 1.0% |
| 2025-12 | SMB | $40,800 | 298 | 4.8% |
| 2025-12 | Mid-Market | $134,200 | 91 | 2.0% |
| 2025-12 | Enterprise | $94,500 | 13 | 0.8% |
| 2026-01 | SMB | $38,100 | 281 | 5.4% |
| 2026-01 | Mid-Market | $141,800 | 95 | 1.9% |
| 2026-01 | Enterprise | $98,200 | 14 | 0.7% |
| 2026-02 | SMB | $35,200 | 263 | 6.1% |
| 2026-02 | Mid-Market | $148,900 | 99 | 1.7% |
| 2026-02 | Enterprise | $108,000 | 16 | 0.5% |
| 2026-03 | SMB | $33,400 | 245 | 6.8% |
| 2026-03 | Mid-Market | $156,200 | 104 | 1.5% |
| 2026-03 | Enterprise | $115,500 | 18 | 0.4% |
| 2026-04 | SMB | $31,200 | 228 | 7.2% |
| 2026-04 | Mid-Market | $164,400 | 109 | 1.4% |
| 2026-04 | Enterprise | $122,800 | 20 | 0.3% |

Table for the Task

> ## Task
>
> You will work with the data above.
>
> Enter this prompt:
>
>><b>Analyse this revenue spreadsheet. What are the top trends I should bring to next week's leadership meeting?
>
>Then push it:
>
>
>><b>Which segment should we double down on for Q3?
>
>Each follow-up uses the same loaded data. Same numbers, different lens.

A hands-on, beginner-friendly course designed for non-technical business users to understand and leverage AI tools and concepts in their daily work. The course covers foundational AI concepts, effective communication with AI, practical use of AI-powered tools, and building simple AI assistants.

Introduction to artificial intelligence, large language models, and essential AI vocabulary for business users.

Learn how to communicate effectively with AI systems through prompt engineering and tone selection.

Explore how AI can be integrated with business tools for research, note-taking, and data analysis.

Learn the basics of agent personas and how to build and tune simple AI assistants for work.