Seller Tools

Export Amazon Orders to Spreadsheet

Last updated -

May 28, 2026

Article Summary

✅ Exporting Amazon orders to a spreadsheet is useful only when the order rows stay current enough to support SKU, revenue, refund, and fulfillment decisions.

‍

✅ Amazon order exports can include fields such as order-id, purchase-date, sku, quantity-purchased, item-price, ship-state, and sales-channel, depending on the report type.

‍

✅ Gorilla ROI pulls Amazon order data into Google Sheets so your team can work from structured order rows instead of rebuilding CSV exports.

‍

There was a time where I wasted too much effort to export Amazon orders into my spreadsheets and other multichannel fulfillment software.

Twelve years of selling on Amazon means twelve years of seeing the same order export problem.

You log into Seller Central, request an order report, download the CSV, open it in Google Sheets, paste the rows, adjust a few columns... before you even start work and you are already tired.

That works for a one-time check.

It gets messy when your team has to repeat the same process every Monday, compare SKU movement, check order status, track marketplace sales, and trust that nobody pasted the wrong range.

The export is only the first step. The real question is whether your order spreadsheet can be trusted after someone else touches it.

The export button is not the bottleneck

The export itself takes about five minutes once you know where to go. The steps are annoying.

The common process is:

Open Seller Central
Go to order reports
Pick the report type and date range
Download the CSV
Open it in Google Sheets or Excel
Paste or import the rows into your working sheet

That sounds simple because it is simple for one file.

The weak point is repeatability. A CSV is a snapshot. It shows what Amazon reported when you pulled it. Order status, cancellation status, fulfillment status, and updated timestamps can change later.

That is where your spreadsheet starts getting stale.

If your team uses the sheet for order analysis, stale order data can lead to bad SKU counts, missed cancellations, duplicated rows, and a false sense that the sheet is current.

The 30-Day PII Cutoff

One thing most sellers don't catch until they actually need it: per Amazon's Data Protection Policy, buyer name, email, and shipping address are redacted from order records 30 days after shipment. The fields come back blank. No tool gets around this, including Gorilla ROI.

If you ever need buyer contact details for a dispute or return on an older order, pull it from Seller Central directly while the window is still open.

The Fields That Actually Matter

The order report has a lot of columns. These are the ones that do real work in a live sheet.

| Field | What it does | |---------------------|---------------------------------------------------------------------------------------------------| | amazon-order-id | The join key for everything. Links this order to returns, refunds, and shipment records. | | purchase-date | What your SUMIFS runs on for daily, weekly, and monthly revenue slices. | | last-updated-date | Shows status changes after the original pull. A static CSV does not have this. | | order-status | Pending / Unshipped / Shipped / Canceled. FBM teams need this live to know what to pack today. | | fulfillment-channel | AFN means Amazon ships it (FBA). MFN means you ship it. Splits the two without a second report. | | sku | Your join key to inventory and COGS tabs. A trailing space here breaks every downstream formula. | | asin | Amazon's product ID. Useful when multiple SKUs share a parent ASIN. | | quantity-purchased | Units per line item. Feeds your daily units-sold and reorder velocity calculations. | | item-price | Revenue for the line item. Verify which additional fields your specific report pull includes. |

FBA fees and referral fees are not in this report. It's in the Settlement Report. You join them to order data using amazon-order-id. For a full map of which Amazon reports feed which sheet tabs, see the Amazon data to Google Sheets guide.

With this info, here's a good way to structure spreadsheets from your exports. Do not build analysis tabs until these fields are clean in the raw order tab.

| Field | Spreadsheet job | Mistake it prevents | |---|---|---| | Order ID | Main order key for lookup and deduping | Counting the same order twice | | Purchase Date | Groups orders by day, week, or month | Mixing old orders into current order analysis | | Last Update Date | Shows when the order row changed | Missing status changes after the first pull | | Order Status | Separates shipped, unshipped, pending, and canceled orders | Treating canceled orders as active sales | | Fulfillment Channel | Separates FBA and FBM orders | Mixing two fulfillment paths in one number | | Marketplace | Keeps marketplaces separated | Blending regions or currencies | | ASIN | Connects the order row to the Amazon listing | Losing product-level context | | SKU | Connects the order row to your internal product system | Breaking joins to product or cost tabs | | Quantity Ordered | Counts ordered units | Using order count when you need unit count | | Quantity Shipped | Shows shipped units | Assuming every ordered unit shipped | | Item Price | Captures item revenue | Treating units sold as revenue | | Shipping State | Supports state-level order analysis | Losing regional order patterns |

Build the order spreadsheet in layers

Keep imported order data separate from formulas and analysis tabs.

This is the clean structure I would use:

| Tab | What belongs there | Rule | |---|---|---| | ORDERS_RAW | Order ID, Purchase Date, Last Update Date, Order Status, Fulfillment Channel, Marketplace, ASIN, SKU, Quantity Ordered, Quantity Shipped, Item Price, Shipping State | No formulas and no manual edits | | ORDER_CALCS | Clean dates, SKU grouping, duplicate checks, status filters, helper columns | Formulas live here | | SKU_ORDER_ANALYSIS | SKU, order count, units ordered, units shipped, item revenue, marketplace split | This is the manager-facing analysis tab | | ORDER_AUDIT | Duplicate Order ID checks, blank SKU checks, blank price checks, old refresh checks | Trust check before anyone uses the analysis |

This keeps the sheet simple.

‍ORDERS_RAW is the source.
‍ORDER_CALCS does the work.
‍SKU_ORDER_ANALYSIS gives the team something useful.
‍ORDER_AUDIT catches mistakes before they spread.

I would rather use a plain sheet that survives six months than a beautiful sheet where imports, formulas, and manual notes all live in the same place.

Where manual order exports break

Manual exports are fine when one careful person owns the file. They break when the process depends on memory.

| Issue | What happens | Consequence | |---|---|---| | Duplicate import | The same date range gets pasted twice | Sales look higher than they were | | Missed refresh | The team uses an old file | Decisions are made from stale order rows | | Wrong date field | Purchase Date is used when Last Update Date mattered | Updated or canceled orders get missed | | Header mismatch | A formula expects one column name, but the export uses another | Lookup formulas return blanks or wrong results | | Raw tab edits | Someone fixes imported data by hand | The next import overwrites the fix | | Mixed marketplaces | Multiple marketplace rows sit in one total | Regional sales get blended together |

Here is the simple test: if the order sheet only works when the same person updates it the same way every time, the process is fragile.

That does not mean the CSV is useless. It means the CSV should not be the long-term system if your team depends on the sheet every week.

Manual CSV, custom API pull, or connected Google Sheet

There are three practical ways to get Amazon orders into a spreadsheet.

| Method | Best fit | What you still own | |---|---|---| | Manual CSV export | One-time order checks, small accounts, occasional audits | Download timing, date range, paste location, dedupe checks | | Custom SP-API pull | Internal system with developer support | API setup, authorization, report requests, field mapping, maintenance | | Connected Google Sheet | Weekly or daily order analysis by SKU, date, status, and marketplace | Sheet structure, protected tabs, analysis logic |

Use the manual CSV if you only need order data once in a while.

Use a custom API pull if you already have a developer maintaining Amazon data and your order workflow needs custom logic.

Use a connected Google Sheet when the order export has become a repeated team task.

For broader Amazon seller data beyond orders, use the Amazon seller data to Google Sheets guide.

Where Gorilla ROI fits for order data

Gorilla ROI is a Google Sheets data hub for ecommerce operations. For this article, the use case is narrow: pull Amazon order data into Sheets so your team can analyze orders without rebuilding the CSV process.

It does not remove the need for sheet structure. You still need raw tabs, formulas, checks, and analysis tabs. The value is that your team stops doing the same export work over and over.

| Manual order process | Gorilla ROI order process | |---|---| | Log into Seller Central | Open the existing Google Sheet | | Download the order CSV | Pull order fields into the same sheet structure | | Paste rows into the workbook | Keep order rows in ORDERS_RAW | | Fix formulas after column changes | Keep formulas in ORDER_CALCS | | Check for duplicate orders manually | Use ORDER_AUDIT to catch duplicate Order IDs | | Repeat the same work next week | Refresh the same order tab structure |

It does not remove the need for sheet structure. You still need raw tabs, formulas, checks, and analysis tabs. The value is that your team stops doing the same export work over and over.

When Gorilla ROI is the wrong choice for order exports

| Right for you | Wrong for you | |---|---| | Your team checks Amazon order data in Google Sheets every week | You only need one order export per month | | More than one person touches the workbook | One careful person owns the full process and does not miss pulls | | You need recurring SKU, status, marketplace, and item price analysis | You only need a one-time customer service lookup | | You want structured order rows your team can shape into reports | You want a finished screen with no spreadsheet setup |

I would not use Gorilla ROI for order exports if a monthly CSV takes 15 minutes and answers the question. Automation earns its place when the export becomes the work.

Video Tutorial on Exporting Amazon Orders to Spreadsheet

Amazon order export FAQ

How do I export Amazon orders to a spreadsheet?

You can export Amazon orders from Seller Central by requesting an order report, downloading the CSV, and opening it in Google Sheets or Excel. That works for one-time checks. Weekly order analysis needs protected raw tabs, dedupe checks, and a repeatable refresh process.

What fields should I include in an Amazon order spreadsheet?

Start with Order ID, Purchase Date, Last Update Date, Order Status, Fulfillment Channel, Marketplace, ASIN, SKU, Quantity Ordered, Quantity Shipped, Item Price, and Shipping State. Those fields give you the base for SKU, status, date, and marketplace analysis.

Can I export Amazon orders directly into Google Sheets?

Yes, but there are three practical ways to do it: manual CSV download, a custom SP-API connection, or a Google Sheets connection through Gorilla ROI. Manual downloads are fine for one-off review, while a connected sheet fits repeated order review.

Can order data connect to refunds and returns?

Yes. Use Order ID, SKU, ASIN, Purchase Date, and Quantity Ordered as the bridge between order rows and refund or return rows. For return-specific fields and reason codes, use the Amazon FBA returns in Google Sheets article.

Does the order report include advertising spend?

‍No. Advertising data is a separate report category. To calculate TACoS, pull advertising data into its own tab and join with total order revenue by SKU and date range. The Amazon advertising metrics article covers the advertising tab structure.

Does an Amazon order export include full profit data?

No. Order exports show order-level data. Full profit analysis usually needs other data sources such as fees, refunds, settlement data, and product cost. Keep this article’s workflow focused on the order rows first.

What is the safest first sheet setup?

Use ORDERS_RAW, ORDER_CALCS, SKU_ORDER_ANALYSIS, and ORDER_AUDIT. Protect the raw tab, keep formulas out of imported rows, and use Order ID as the dedupe key.