Illustrative example · fictitious data
01
Online clothing store
- Business
- Fashion e-commerce · 2 people · ~3,000 orders a year
- Data
- One Excel file with 14 months of orders
- Service
- Diagnosis & roadmap
- Timeframe
- 10 business days
The question
They had every sale in a spreadsheet but could not answer basic questions: when do we sell more, which garments actually move, and in which sizes?
What we analysed
We cleaned and grouped 14 months of orders by product, size, day, month and returns, and compared each season with the previous one.
What we found
64%
of revenue came from 18% of the catalogue. Half of the products sold fewer than five units in a year.
9 days
earlier than the rest, sizes M and L of the best-sellers ran out — right in the strongest weeks.
21%
of jeans orders were returned, mostly for size. The size guide did not match the supplier’s measurements.
What we delivered
- A plain-language report, with each finding explained in money
- A monthly dashboard in Google Sheets: sales, sizes and returns
- A 30-60-90 day action plan, ordered by priority
- A presentation session with the owners