CSV Drag-and-Drop Mapper

Source headers are dragged onto target fields; the tool auto-matches by normalized name, and the output reorders and renames columns to the target layout.

Nadia is a marketing operations analyst migrating a Shopify customer export into her CRM. The export and the CRM use completely different column names and order.

1. Export:Her file has headers name, email, phone, product, qty and total_price across 1,204 rows; the CRM import expects full_name, email_address, phone_number, product_name, quantity and price.
2. Auto-match:She drops the file in; the tool parses all rows and auto-maps all 6 of 6 columns — email and phone by normalized name, qty by the abbreviation rule (qty → quantity), and total_price by substring match (total_price contains price).
3. Verify:She glances at the mapping chips — every source column shows its target, and the live preview already shows the columns in the CRM's expected order. No manual fixes needed.
4. Reuse:She saves the mapping as Shopify-to-CRM and applies it to next week's export with a single click — no re-dragging.