---
title: "Amazon Selling Partner"
slug: "amazon-selling-partner"
description: "Access all Amazon Selling Partner metrics via Dataddo and automate your data extraction. Create your data pipeline in just a few steps. Get started now!"
updated: 2026-07-09T08:20:32Z
published: 2026-07-09T08:20:32Z
canonical: "docs.dataddo.com/amazon-selling-partner"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dataddo.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Amazon Selling Partner

**Amazon Selling Partner** is a platform for selling products on Amazon's marketplace. It provides tools to list products, manage inventory, and fulfill orders. Businesses use it to reach Amazon's customers.

Refer to our website for [the list of metrics and attributes available in Dataddo](https://www.dataddo.com/connector/amazon_selling_partner).

Refer to Amazon's official documentation to see [all available endpoints from the Amazon Selling API](https://developer-docs.amazon.com/sp-api/docs/sp-api-models).

## Authentication Methods

Amazon Selling Partner supports more than one way to connect. Pick one when you create the authorizer in Dataddo:

- **Amazon Selling Partner** - sign in with Amazon Selling Partner and approve access (recommended).
- **Amazon Selling Partner Custom** - use your own app credentials. This is for advanced setups.

## Authorize Connection to Amazon Selling Partner

To authorize this service, use **OAuth 2.0** to share specific data with Dataddo while keeping usernames, passwords, and other information private.

1. On the **Authorizers** page, click on [Authorize New Service](https://app.dataddo.com/service/new) and select your service.
2. Follow the on-screen prompts to grant Dataddo the necessary permissions to **access and retrieve** your data.
3. **[Optional]** Once your ***authorizer*** is created, click on it to **change the label** for easier identification.

Ensure that the account you're granting access to holds at least **admin-level permissions**. If necessary, assign a team member with the required permissions with the [authorizer role](https://docs.dataddo.com/docs/user-roles#authorizer) to authenticate the service for you.

For more information, see our article on [***authorizers***](https://docs.dataddo.com/docs/authorized-services).

## Data Coverage

Amazon Selling Partner exposes the following datasets. Each dataset maps to a table you can extract. The example fields are just a sample. Each dataset returns more columns.

| Dataset | Description | Example fields | Date range |
| --- | --- | --- | --- |
| Catalog | Provides programmatic access to information about items in the Amazon catalog. | Marketplace Id, Adult Product, Asin, Autographed, Brand, Browse Classification Classification Id (+16 more) | No |
| FBA Inventory | Retrieve information about inventory in Amazon's fulfillment network. | Asin, Condition, Fn Sku, Inventory Details Fulfillable Quantity, Inventory Details Future Supply Quantity Future Supply Buyable Quantity, Inventory Details Future Supply Quantity Reserved Future Supply Quantity (+21 more) | No |
| Financial Refunded Events | Returns financial events for the specified data range. | Amazon Order Id, Market Place Name, Posted Date, Seller Order Id, Shipment Item Adjustment List Item Charge Adjustment List Charge Amount Currency Amount, Shipment Item Adjustment List Item Charge Adjustment List Charge Amount Currency Code (+11 more) | Yes |
| Order Financial Breakdown | Returns detailed financial breakdown for each order | Amazon Order ID, Item Charge List, Item Fee list, Marketplace Name, Posted Date, Promotion List (+1 more) | Yes |
| Order Items | Returns detailed order item information for the order indicated by the specified order ID. | Asin, Amazon Order ID, Buyer Customized URL, Buyer Gift Message Text, Buyer Gift Wrap Level, Buyer Gift Wrap Price Amount (+27 more) | Yes |
| Orders | CRM accounts data | Amazon Order ID, Buyer Business Address, Buyer Info Buyer County, Buyer Info Buyer Email, Buyer Info Buyer Name, Buyer Info Purchase Order Number (+61 more) | Yes |
| Reports | Retrieve reports that selling partners can use to manage their businesses | dynamic (from your account) | Yes |
| Sales | Retrieve information about sales performance. | Average Unit Price Amount, Average Unit Price Currency Code, Interval, Order Count, Order Item Count, Total Sales Amount (+2 more) | Yes |

## How Data Extraction Works

What each extraction pulls depends only on whether a dataset supports a date range (see the Date range column above):

- **Date range supported (Yes):** the source reads a relative window (for example "last 7 days"), and that window slides forward with the current date. Every run re-reads the window, so a range of "1 day ago" always pulls the previous day (D-1). Each run replaces the window's data rather than adding older history. To load records from before the window, run a full data re-sync with a wider range. See [Data Backfilling](/docs/data-backfilling).
- **No date range (No):** every run pulls all currently available data.

Set the relative date range when you create the source.

## Metadata Columns

When you create a source, you can add these Dataddo metadata columns to the extracted data:

- **dataddo_hash** - a fingerprint built from each record's key fields. It works as a natural key, so it is ideal for upserts (updating existing rows in your destination instead of creating duplicates).
- **dataddo_extraction_timestamp** - the date and time the row was extracted. Use it to track how records change over time, for example to build slowly changing dimensions.

## How to Create an Amazon Selling Partner Data Source

Creating a data source takes you through six steps, shown in the progress bar at the top of the wizard. Each step is explained below.

**1. Pick the connector**

On the **Sources** page, click **Create Source**, then select the connector from the catalog. Use the search bar or the category tabs if you do not see it right away. You can rename the source at any time using the pencil icon next to its name.

**2. Select the dataset**

A dataset defines the shape of your data: which fields you get and how they relate. Select the dataset you want; you can still fine-tune the exact fields later.

- Each dataset has a short description of what it contains. Use the search box to find a dataset, attribute, or metric by name.
- The panel on the right previews the selected dataset's fields. For each field you can see its **data type**, whether it holds **sensitive** data (personal fields such as name or email are flagged), and which **other datasets it links to**, so you can see how the datasets relate.

**3. Choose the account**

This step selects what Dataddo reads from.

- **Authorizer:** Select an account you have already authorized from the drop-down. If you have none yet, choose **Add new account** and follow the prompts. If no authorizer is selected, Dataddo asks you to authorize before you continue.
- **What to extract from:** Select the exact entity you want to pull data from. Depending on the service this may be labelled an account, property, profile, workspace, or similar, sometimes with a sub-level to choose as well.
- **Multiple accounts:** To pull the same data from every entity you can access, turn on **Automatically collect data from all ...**. This is multi-account extraction. Leave it off to choose them by hand.

**4. Refine the attributes and metrics**

The dataset already sets the structure. Here you fine-tune it: tick or untick the specific attributes and metrics you want to keep, and use the search box to find a field quickly. Click **Test on Sample Data** at any point to preview the result before you continue.

**5. Add metadata columns (optional)**

Two optional columns help your destination handle the data.

- **Dataddo Hash (Include Row Hash):** a fingerprint built from the columns you pick. It works as a natural key, so your destination can deduplicate rows and run upserts instead of creating duplicates. Turn it on, then select the columns that uniquely identify a row.
- **Dataddo Extraction Timestamp:** the time each row was extracted. Use it to watermark the data, for example to build slowly changing dimensions or to track when a value last changed.

**6. Set the schedule**

Decide how often Dataddo runs the extraction.

- **Frequency:** how often the pipeline runs, for example daily. Click **Show advanced settings** to also set the exact hour and minute (UTC).
- **Date range:** the relative window each run extracts, for example "Yesterday". The window moves forward on every run.
- **Historical data:** a new source starts from the current window. To load older data, run a [full data re-sync](https://docs.dataddo.com/docs/data-backfilling) after the source is created.
- **Allow Empty Data Extractions:** when on, a run that returns no data records zero rows instead of failing. Turn it on if the source can legitimately have periods with no data.

Click **Save**. Your data source is ready.

### Dataset-Specific Fields

Some Amazon Selling Partner datasets need extra fields. You select or fill them in on the **Metrics and Attributes** step. This applies to these datasets:

* Catalog
* Report
* Sales

#### **Catalog Dataset**
Fill in the **keywords** (separated by commas, e.g., `electronics,clothes,furniture`) and **select your metrics and attributes**. Keep in mind that metrics and attributes depend on the selected dataset.

:::(Info) (**DATADDO TIP**)
**Keywords** let you search for **a group of products**. Precise identifiers like ASIN, UPC, or EAN point to a single item. A keyword works more like a search you would type on the Amazon website. For example, use:
*     **Brand names** like "Apple" or "Samsung"
*     **Product categories** like "coffee makers"
*     **Descriptive phrases** like "cordless vacuum cleaner"
:::

#### **Report Dataset**
Select the **Report type** to choose which business data to extract. Amazon offers many report types. Each one holds different data, such as:

* **Sales and Traffic Reports**: Data on sales volume, order details, and page views.
* **FBA Inventory Reports**: Information about your products in Amazon's fulfillment centers.
* **Settlement Reports**: A breakdown of your financial transactions. This covers sales, fees, and payments.
* **FBA Returns Reports**: Information on customer returns and the state of the returned products.
* **Pricing Reports**: Data about a product's current price and competing offers.

For more information, see [Amazon's official documentationl](https://developer-docs.amazon.com/sp-api/docs/report-type-values).

#### **Sales Dataset**
Select your **Time period breakdown** to set how the data is grouped. Supported options are:

* **Hour**: Groups data by hour. This gives the most detailed view.
* **Day**: Groups data by day. This is useful to track daily performance.
* **Week**: Rolls up data into a weekly summary. This is good for short-term trends.
* **Month**: Sums up data by month. This is ideal for monthly reports and comparisons.
* **Year**: Groups data by year. This is used for long-term trends and yearly reviews.
* **Total**: Gives a single grand total for the whole time period, with no breakdown.

A daily breakdown gives a detailed view. A monthly or yearly breakdown is better for long-term trends.
* * *

## Troubleshooting

### Data Preview Unavailable
No data preview when you click on **Test Data** might be caused by an issue with your ***source*** configuration. The most common causes are:

* **Date range**: Try a smaller date range. You can load the rest of your data afterward via [manual data load](https://docs.dataddo.com/docs/data-backfilling).
* **Insufficient permissions**: Please make sure your authorized account has at least admin-level permissions.

 

### Missing Amazon Selling Partner Reports Data
Do you need data from your Amazon Selling Partner reports? Then you need a custom ***data source***. Reach out to us at support@dataddo.com and we will create the custom ***source*** for you.

### `Orders` Dataset Exception
This field from the `Orders` dataset is available **only** to the Brazilian marketplace:

* `SellerDisplayName`

 

## Related Articles
Now that you have successfully created a ***data source***, see how you can connect your data to a dashboarding app or a data storage.

**Sending Data to Dashboarding Apps**
* [Simple Data Integration to Dashboards](https://docs.dataddo.com/docs/simple-data-integration-to-dashboards)
* [Data Backfilling to Dashboarding Apps](https://docs.dataddo.com/docs/data-backfilling-to-dashboarding-apps)

**Sending Data to Data Storages**
* [Batch Ingestion to Data Warehouses](https://docs.dataddo.com/docs/ingestion-to-data-warehouses)
* [Data Backfilling to Storages](https://docs.dataddo.com/docs/data-backfilling-to-storages)

**Other Resources**
* [Troubleshooting](https://docs.dataddo.com/docs/troubleshooting)
* [Extraction Logs](https://docs.dataddo.com/docs/extraction-logs)
* [Data Duplication](https://docs.dataddo.com/docs/data-duplication)