Three columns is all you need. Everything else is optional and simply unlocks more of the app.
One row per sale, or one row per product per day. Both work — the app adds up whatever it finds.
| Column | What it is | Examples of what it might be called |
|---|---|---|
| Date | When the sale happened | Date Invoice Date SalesDate trandate BEDAT |
| Product | The product name or code | Product Description Item SKU MATNR |
| Quantity | How many units sold | Quantity Qty Units Sold MENGE |
The app recognises hundreds of column names across English, German, Spanish, French and SAP field codes. If it guesses wrong, you can correct it from a dropdown — nothing needs renaming first.
Date,Product,Quantity Sold 2024-01-03,Cotton T-Shirt White,47 2024-01-03,Instant Coffee 200g,62 2024-01-04,Cotton T-Shirt White,51
| Add this | Columns needed | What it turns on |
|---|---|---|
| Stock levels | Product, quantity on hand | Reorder alerts, overstock warnings, stock turnover |
| Costs | Product, purchase price | Every figure in money rather than units, plus proper order quantities |
| Purchase orders | Supplier, order date, receiving date | Real supplier lead times and reliability, instead of an assumed number |
Drop them all in together. Each file is identified automatically — you do not need to say which is which.
Tally writes dates as DD-MM-YYYY. The app detects this and shows you what it decided — check it on the Data check tab.
If your file is over the Excel row limit of 1,048,576 it has been silently truncated. The app detects that and warns you.
MATNR, MENGE and a date fieldSAP's field codes are recognised directly — no renaming required.
| Period | What you can rely on |
|---|---|
| 2 years or more | Seasonality confirmed by repetition. Order quantities are dependable. |
| 1 year | Seasonality seen once. Reasonable, not yet confirmed. |
| 6–12 months | Rankings and cash figures are sound. Annual quantities are projected. |
| Under 6 months | Useful for spotting priorities and stuck stock. Not a basis for ordering. |
The app grades your file on exactly this and states plainly what it can and cannot support — before showing you any numbers.
| Symptom | Cause and fix |
|---|---|
| "No sales history found" | The app could not identify three required columns. Open the mapping dropdowns in the Data panel and set them by hand. |
| Dates look wrong | A file of 03/04/2024-style dates with no value above 12 is genuinely ambiguous. The app says which it assumed — override it in the Data panel if wrong. |
| Many rows skipped | Usually subtotal rows, blank lines or text such as "N/A" in the quantity column. The Data check tab itemises exactly what was dropped and why. |
| Numbers look 1000× off | A European file read as Anglo, or the reverse — 1.234 means 1,234 in one and 1.234 in the other. The Data check tab shows which was used. |
| "Model adds 0% over a simple average" | Not a fault. Your demand has no learnable pattern, and the app is telling you so instead of pretending otherwise. Use the historical average and a stock rule. |
| Large file is slow | Files over about 100 MB take a minute or two. Everything is computed on your own machine, so speed depends on it. |
Email info@quantonique.com with the column headings from your file — the first row only, never the data itself — and we will tell you how to map it.
Open the app