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The Best Way to Merge Shopify and Walmart Marketplace Data for Cost of Goods Sold Tracking
If you're doing cost of goods sold tracking by hand right now, here's the fastest path from "two exports" to "one usable sheet," and why the manual version keeps breaking.
Step by step
- Decide your target columns once. Most people settle on Date, Channel, Order ID, and Total — set that up in CSV Experts and you won't redo it.
- Import the Shopify file first. The first time you see this file shape, you map each of its columns to your target list.
- Import the Walmart Marketplace file the same way. Its columns get mapped once too — after that, every future file with this shape merges with no extra clicks.
- Check the merged totals. Dates and numbers are normalized automatically, so a European "24,00" and a US "24.00" both land as the same value.
- Export. CSV or Excel, ready for cost of goods sold tracking.
What actually goes wrong if you do this by hand
Shopify gives you a Created At timestamp that includes a timezone offset, while Walmart Marketplace gives you an Order Date column separate from the ship-by date — line those up manually across a few hundred rows and it's easy to miscount a week. On top of that, Shopify's export exports one row per line item by default, so an order with 3 products becomes 3 rows unless you export the summary report instead, and Walmart Marketplace's each order line can appear as its own row with a repeated order ID, similar to Shopify's line-item export. Individually those are minor quirks; combined into one spreadsheet by hand, they're where most reconciliation errors for cost of goods sold tracking actually come from.
Why it matters for cost of goods sold tracking
Calculating cost of goods sold across channels requires item-level data lined up the same way regardless of where it sold.
Just want the quick column-difference reference instead? See the short version.