One definition, everywhere
Which order states count as revenue is configured once and applied by every screen and every export.
Statistics
Numbers you can actually quote
Revenue, best sellers, conversion, retention, seasonality, promotions, catalogue hygiene and where orders are stuck — computed once, so two screens never disagree about the same month.
Orders, 30 days
0
+9%
Average order
0
+3%
Repeat customers
0
+2pp
It tells you what it excluded
If cancelled orders were dropped from a figure, the figure says so — a zero that hides three cancelled orders is not an answer.
Comparable cohorts
Retention says how long each cohort has had to come back, so a recent month does not read as a collapse.
Including the awkward questions
Who writes the most offers and who converts them. Which vouchers cost the most. Which products have no image, no EAN or have not sold in a year. The reports people avoid building because they are tedious.
- Per-salesperson offer and conversion figures
- Catalogue hygiene, with the product list behind each count
- Seasonality across years, month by month
| Product | Units | Orders | Revenue |
|---|---|---|---|
| Colier argint Delicate 20 Pearls | 40 | 39 | 8,605.67 |
| Sterling Silver Bracelet Summer | 56 | 55 | 7,367.92 |
| Cercei argint Double Glow gold | 28 | 28 | 6,370.10 |
Eleven views, one definition of a sale
- Revenue and orders per day, over any period
- Best sellers by revenue or by units sold
- Where orders sit by status, and how long they have been there
- Quote conversion: written, accepted, and what that was worth
- Per-salesperson figures — offers written and offers won
- Monthly cohorts: do customers come back, and how long each cohort has had
- Seasonality across years, month by month
- Which vouchers were used and what they gave away
- Catalogue hygiene: no image, no EAN, thin description, nothing sold in a year
- Profit with a cost-coverage figure, so you know how much is measured
- Customer segments by lifetime value and order count
- Everything exportable as a spreadsheet
In practice
The Monday meeting, answered before it starts
Four questions that used to take an afternoon and a spreadsheet.
- How did last week go, day by day, against the week before.
- What sold most — and separately, what made the most margin.
- How many offers we wrote, how many landed, and who wrote them.
- What is stuck: orders sitting in a status longer than they should.
| Person | Written | Accepted | Value |
|---|---|---|---|
| Dana | 24 | 11 | 18,420.00 |
| Tudor | 19 | 9 | 14,905.50 |
| Elena | 12 | 7 | 9,110.20 |
Questions about this
Why do your numbers differ from PrestaShop’s?
Usually because of which order states count as revenue. That is configured once here and applied everywhere, and every figure says what it excluded.
Can I get this into a spreadsheet?
Any list can be exported as a CSV, and the export says plainly when it is a partial one rather than the whole set.
Is the profit figure trustworthy?
It is as trustworthy as your cost data, and it says so: every profit view reports what share of revenue had a real cost behind it rather than an assumed margin.
See it against your own catalogue
Tell us about your shop and we will set up an instance for you. You will be looking at your own products, not a demo dataset.
Request access
No card. No obligation.