Microsoft Power BI offers advanced data visualization and analytics tools that you can use with your BigCommerce data.

To use Microsoft Power BI with BigCommerce, first add your BigCommerce data to Google BigQuery using our built-in integration and then send your store’s data into Microsoft Power BI for analysis.

 

Using a Mac? Microsoft Power BI is not well suited for companies that need to create custom reports on an Apple computer. We recommend using Tableau or Google Looker Studio if your business falls into this situation.

 

How It Works

There are a variety of ways you can send your store's data into Microsoft Power BI for analysis. We recommend leveraging a data warehouse as an intermediary and offer a native integration to Google BigQuery, which can be used as a data warehouse.

  • First, add your BigCommerce data to Google BigQuery using our native integration. See Setting Up Google BigQuery for a detailed walkthrough.
  • Next, connect to Microsoft Power BI to Google BigQuery. See Microsoft's support article for instructions.
  • Once connected, you can use your new BigCommerce data source in Microsoft Power BI to create reports. See below for some example reports to help you get started.
 

Example Reports

BigCommerce, partnered with Silk Software, has created some initial Microsoft Power BI reports to help get you started – simply download the .pbit template file and follow the setup instructions listed below. After you sync these reports with your data, you can fully customize them to meet your unique business needs.

Example Reports Include:

  • Product revenue by category
  • Cost of goods sold & profit
  • Revenue by city

View the Microsoft Power BI Example Reports

For additional support with creating custom Microsoft Power BI reports, you can contact our agency partner Silk Software, who offer dedicated services for BigCommerce merchants using Microsoft Power BI.

Setup Instructions

  • Ensure that your BigCommerce store is integrated with Google BigQuery (detailed above) and that the Microsoft Power BI Desktop application is installed on your computer.
  • Download and open the report template file.
     
  • Enter your Google BigQuery Project Name and Dataset Name when prompted.
    Popup to input Google BigQuery Project and Dataset names
  • If Power BI Desktop is not already connected to your Google account, you will be prompted to sign in and grant the required permissions.
  • Let the queries refresh to see your BigCommerce store data in action.

BigCommerce Product Revenue by Category Report

This report allows you to see product line item revenue by product category, with the ability to filter by date range and order status.

BigCommerce Product Revenue by Category example report

 

BigCommerce Cost of Google Sold (COGS) Report

This report allows you to see your product line item revenue broken down by cost and profit and includes information on your profit margins. It helps you to see which products are driving the largest amount of revenue. The cost data is based on the cost field in the product Add/Edit screen in your BigCommerce control panel. Once you set up this report, the updated data will be reflected in your Google BigQuery account the next day.

BigCommerce Cost of Goods Sold (COGS) Example Report

 

BigCommerce Revenue by City Report

This report allows you to see which cities across the world your shoppers are purchasing from, based on the billing address they entered during checkout.

BigCommerce Revenue by City Example Report

 

FAQ

Does BigCommerce offer any pre-built Microsoft Power BI dashboards and reports?

Yes, BigCommerce currently offers three pre-built Microsoft Power BI report templates. You can find the download and setup instructions here. If you are interested in tailoring these reports for your business or creating new custom Microsoft Power BI reports, let us know by submitting a custom report request via Silk Software.

Can I use Microsoft Power BI if I'm using a Mac?

Microsoft Power BI Desktop is used to create reports and visualizations and is not available for Mac. For Mac users, we recommend using Tableau or Google Looker Studio.