# Integrate BigCommerce with Databox

BigCommerce provides businesses with a powerful eCommerce platform to manage products, orders, payments, and customers all in one place. It offers built-in tools for storefront customization, inventory management, SEO, and marketing automation — enabling merchants to scale operations, optimize online sales performance, and deliver seamless shopping experiences across channels.

## Connection

### Before you begin

### Step 1: Create an API account

You'll need a BigCommerce API account to connect BigCommerce to Databox, whether it's your [first setup](/add-a-connection) or a credential update. To create one, follow the step-by-step guide in [BigCommerce's official documentation](https://support.bigcommerce.com/s/article/Store-API-Accounts).

To ensure Databox can access your BigCommerce data, grant **Read** permissions for all relevant API resources in your API account.

### Step 2: Find your Store Hash

The Store Hash can be found in your store's URL. It appears right after `store-` in the address.

Example: `https://store-abc123.mybigcommerce.com` → here, **abc123** is the Store Hash.

### Step 3: Add a connection

Enter your **Store Hash** and **Access Token** from your BigCommerce API account to establish the connection.

connect
## ![lock](/assets/lock.2fb1bbc208afcc03d15a0a45f22bdf7f830322016e038e5721965851130807af.419bb737.svg) Datasets

The BigCommerce integration supports the creation of [datasets](/understanding-datasets), which allow you to structure and format your BigCommerce data for more flexible reporting in Databox. By organizing your data into a tabular format, datasets make it easier to filter, segment, and visualize key metrics across projects, clients, and team members.

The entity relationship diagram (ERD) below illustrates how data is organized within the BigCommerce integration, displaying the available **views** and **columns**, as well as the relationships between them (primary and foreign keys). This diagram represents the **schema**, or structure, of the data and helps you understand the underlying data model. With this context, you can create datasets using the relevant views and columns to build custom metrics tailored to your reporting needs.

## Resources

For comprehensive details on metrics, data availability, templates, specifications, usage guidelines, and other key information, refer to the resources listed below.

 

Ask Genie
Get instant answers or help with your data using the in-app AI assistant.

Talk to an expert
For customers: Get help with your setup, strategy, or making the most of Databox.

Book a demo
New to Databox? See how it works and get guidance on getting started.

Send an email
Reach out to support for help with your account, data, or technical issues.