Spreadsheet analysed successfully.

File: monthly_sales.xlsx
Sheet: Monthly Sales
Period: January 2025 to June 2026
Rows analysed: 18

Columns detected:
Month, Leads, Customers, Revenue, Marketing Spend, Refunds, Net Revenue, Conversion Rate

Data:
2025-01 | 210 leads | 24 customers | 7,200 revenue | 1,200 marketing | 180 refunds | 7,020 net revenue | 11.43% conversion
2025-02 | 225 | 27 | 8,100 | 1,250 | 220 | 7,880 | 12.00%
2025-03 | 240 | 30 | 9,000 | 1,300 | 160 | 8,840 | 12.50%
2025-04 | 235 | 28 | 8,400 | 1,350 | 240 | 8,160 | 11.91%
2025-05 | 255 | 33 | 9,900 | 1,400 | 190 | 9,710 | 12.94%
2025-06 | 270 | 36 | 10,800 | 1,450 | 210 | 10,590 | 13.33%
2025-07 | 280 | 35 | 10,500 | 1,500 | 250 | 10,250 | 12.50%
2025-08 | 360 | 30 | 9,000 | 2,600 | 340 | 8,660 | 8.33%
2025-09 | 295 | 39 | 11,700 | 1,550 | 200 | 11,500 | 13.22%
2025-10 | 310 | 42 | 12,600 | 1,600 | 230 | 12,370 | 13.55%
2025-11 | 325 | 45 | 13,500 | 1,700 | 260 | 13,240 | 13.85%
2025-12 | 390 | 58 | 18,000 | 2,200 | 310 | 17,690 | 14.87%
2026-01 | 300 | 40 | 12,000 | 1,650 | 280 | 11,720 | 13.33%
2026-02 | 315 | 43 | 12,900 | 1,700 | 240 | 12,660 | 13.65%
2026-03 | 335 | 47 | 14,100 | 1,750 | 210 | 13,890 | 14.03%
2026-04 | 350 | 50 | 15,000 | 1,800 | 260 | 14,740 | 14.29%
2026-05 | 370 | 54 | 16,200 | 1,900 | 230 | 15,970 | 14.59%
2026-06 | 395 | 59 | 17,700 | 2,000 | 270 | 17,430 | 14.94%

Calculated summary:
Total revenue: 216,600
Total net revenue: 212,320
Average monthly revenue: 12,033.33
Average monthly net revenue: 11,795.56
Total customers: 720
Average conversion rate: 13.07%

Notable findings:
- Revenue, customer numbers, and conversion rates generally increased over time.
- December 2025 had the highest net revenue at 17,690.
- June 2026 had the highest conversion rate at 14.94%.
- August 2025 is a clear outlier. Marketing spend increased to 2,600, but conversion fell to 8.33%, the lowest rate in the spreadsheet.
- Net revenue increased from 7,020 in January 2025 to 17,430 in June 2026.

Summary  
This chapter covers how to parse and process CSV and spreadsheet data in code to group records, compute aggregates and metrics, detect patterns and outliers, and generate actionable insights.  

General domain of usage  
Business financial performance analysis

Claude is also very useful for understanding data. You can hand it files full of numbers and it can extract insights, run calculations, and help you make sense of what's actually going on.

### Why This Matters

With just a couple of prompts, Marcus was able to analyse **eighteen months of data** and uncover **real, actionable insights**. He didn't need to build formulas, create pivot tables, or spend hours exploring the spreadsheet manually.

At its core, data analysis is often about **spotting patterns**, **finding outliers**, and **answering specific questions**. You don't necessarily need advanced technical skills. What matters most is asking a clear question.

Claude can work directly with **spreadsheets**, **CSV files**, **tables**, and **pasted data**, helping you identify trends, anomalies, and opportunities that might otherwise go unnoticed.

> ### Task
>
> - Find a spreadsheet you've been meaning to review, such as your **spending**, **time tracking**, **sales pipeline**, or **work hours**. Upload it to Claude and ask a specific question about it.
>   - **Which category did I spend the most on?**
>   - **What trends can you find in my work hours?**
>   - **Which sales opportunities should I prioritize?**

Learn how to get the most out of Claude for work, study, and everyday tasks. This course covers everything from writing better prompts and analysing documents to using advanced features such as Projects, Artifacts, Memory, Skills, and Connectors. You'll also explore how Claude integrates with tools like Chrome, Slack, Excel, PowerPoint, and mobile devices. By the end of the course, you'll be able to use Claude confidently to save time, improve productivity, and solve real-world problems more effectively.

Learn the fundamentals of Claude, including account setup, the interface, plans, and core capabilities.