Some Amazon analysis software require a specific format for files to be in in order to allow them to run successfully. Price Checker is different:

Price Checker supports .xls, .xlsx, .csv, and .tab (tab delimited) file formats

Column order doesn’t matter

Missing headers don’t matter

Missing check digits don’t matter

Spaces in IDs don’t matter

Mixing of IDs is fine, too

Prices can use comma or dot as decimal delimiter

Single digit currency symbols in front of prices don’t matter

The only thing we really ask is that your files contain proper columns, not ones that were created using visual formatting tricks.

Price Checker will attempt to auto-detect the type of Product ID and the cost column. If for some reason it got it wrong, you can change the column mapping before you start your run. See Run Settings

Occasionally company header and brand formatting above the data can interfere with column detection. The easiest workaround is to delete all rows above the actual product data and any blank columns to the left.

Column Hints

Price Checker will bias its selection when it sees the following non-case-sensitive keywords in column titles:

For detecting column

Header Keywords, in order of preference
These are not case-sensitive

Additional notes

Product ID

ASIN, EAN, UPC, ISBN, Keywords, SellerSKU, ID, Barcode, Bar Code

The first few values are also checked, and the most likely candidate selected (e.g. data format should be valid)

Cost

My Cost, My Price, Net Cost, Cost, Special, Sale Price, Price, Amount

Additions: ‘My’, ‘Case’, ‘Wholesale’, ‘WHSL’

The presence of any of the additions will give more weight to that candidate column

Wholesale Pack

Pack, Packaging, Case, Qty, Box

Using these as the column title or part of the column title will make it more likely that the correct column is chosen.

UPC / ID correction

Price Checker will attempt to correct Product Identifiers by automatically adding leading zeros and calculating missing check digits.

Mixed IDs

You can mix ID types within your file, as long as they are in the same column. Please note that this may have a small impact on throughput.