Clean an E-commerce Product Feed CSV Before Upload
A rejected import costs time. A short cleanup of the feed file avoids the most common errors.
Product feeds are edited by many people, so they collect problems: duplicate SKUs, trailing spaces, prices with symbols, mixed capitals and blank required fields. A marketplace or store importer often rejects the whole file for one bad row.
Start with the Data Profiler to see blanks and duplicates per column. Then use Data Transformation: trim spaces, change text case where needed, find and replace to remove currency symbols or fix a brand name, remove duplicate rows, and remove empty values. Keep SKUs and barcodes as text so leading zeros stay.
Check against the importer rules. Each platform has required columns and formats, and the tool does not know them, so read the platform guide and compare your headers. Rename columns in Data Transformation to match.
Keep the original file, compare row counts before and after, and test with a small batch first. The cleanup happens in your browser and the file is not uploaded.
Related tool pages
- Delete Columns from a CSV File: Remove one or more columns from a CSV or Excel file and download the result. Free, in your browser, and your file is never uploaded.
- Reorder Columns in a CSV File: Drag columns into a new order, or send a column to the start or the end, in a CSV or Excel file. Free, in your browser, nothing is uploaded.
- Remove Empty Rows and Columns from CSV: Remove rows with empty cells, rows that are completely empty, or columns with no values from a CSV or Excel file. Free, in your browser.
- Find and Replace in a CSV File: Find and replace text in a column of a CSV or Excel file, then download the result. Free, in your browser, and nothing is uploaded.
- Change Date Format in a CSV File: Change the date format of a column in a CSV or Excel file, for example 09/03/2026 to 2026-03-09, or get only the year or month. Free, in your browser.
- Convert Excel Date Numbers to Dates: Turn Excel date numbers such as 46090 and unix timestamps into readable dates in a CSV or Excel file. Free, and your file stays in your browser.
How to use the Data Transformation: step by step
- Profile the feed in the Data Profiler.
- Open Data Transformation and add trim, replace and duplicate steps.
- Rename columns to match the importer.
- Download the file and test a small batch first.
When to use the Data Transformation
- Fix a catalogue before a marketplace upload
- Remove duplicate SKUs
- Clean prices and brand names
- Standardise column names
Example
Input: plans.csv + customers.csv, key = id
Output: id, first_name, plan, amount
Frequently asked questions
Which transformations are available?
Join with a second file (inner, left, right, full), trim spaces, concatenate columns, change case, find and replace, split a column, rename, remove columns, reorder columns, remove empty rows or columns, filter rows, remove duplicates, sort and fill empty cells.
Can I run several steps?
Yes. Steps run from top to bottom and each one sees the result of the one before. You can reorder or remove them.
Can I join two files or combine columns?
Yes. Data Transformation lets you join two CSV or Excel files on a key (inner, left, right or full), and trim spaces, concatenate columns, change case, find and replace, split, rename, filter, sort, remove duplicates and fill empty cells. You choose the steps, check the result and download it. Your files stay in your browser.
Can I change the date format of a column?
Yes. Add a Change date format step, pick the column and the new format, such as 2026-03-09, 09/03/2026 or March 9, 2026. It reads many layouts, Excel date numbers and unix timestamps, and can also give only the year, month, weekday or quarter. If 03/04/2026 is unclear, you choose day first or month first.
Tip: Keep SKUs and barcodes as text so codes such as 000123 keep their zeros.