Bronto to Google Data Studio

This page provides you with instructions on how to extract data from Bronto and analyze it in Google Data Studio. (If the mechanics of extracting data from Bronto seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)

What is Bronto?

Oracle Bronto is an ecommerce email marketing platform. It integrates ecommerce and point-of-sale data with operational platforms, enabling brands to maximize the value of customer data and deliver relevant, personal messages.

What is Google Data Studio?

Google Data Studio is a simple dashboard and reporting tool. It's free and easy to use, but it lacks the sophisticated features of higher-end reporting software. Many of the connectors it supports are for Google products, but third parties have written partner connectors to a wide variety of data sources. Its drag-and-drop report editor lets users create about 15 types of charts.

Getting data out of Bronto

You can use Bronto's API to get Bronto data into your data warehouse. The API was originally designed using the SOAP API protocol, but a new REST API lets you access and work with product and order data.

Bronto's API offers numerous endpoints that can provide information on orders, products, and campaigns. Using methods outlined in the API documentation, you can retrieve the data you need. For example, to get a list of all transactions for a given order object, you could GET /orders/{orderId}.

Sample Bronto data

The Bronto REST API returns JSON-formatted data. Here's an example of the kind of response you might see when querying an objects endpoint.

{
    emailAddress:validly formatted email address
    contactId:string
    orderDate:ISO-8601 datetime
    status:PENDING | PROCESSED
    hasTracking:boolean
    trackingCookieName:string
    trackingCookieValue:string
    deliveryId:string
    customerOrderId:string
    discountAmount:number
    grandTotal:number
    lineItems:[
      {
        name:string
        other:string
        sku:string
        category:string
        imageUrl:string
        productUrl:string
        quantity:number
        salePrice:number
        totalPrice:number
        unitPrice:number
        description:string
        position:number
      }
    ]
    originIp:IPv4 or IPv6 address
    messageId:string
    originUserAgent:string
    shippingAmount:number
    shippingDate:ISO-8601 datetime
    shippingDetails:string
    shippingTrackingUrl:string
    subtotal:number
    taxAmount:number
    cartId:UUID
    createdDate:ISO-8601 datetime
    updatedDate:ISO-8601 datetime
    currency:ISO-4217 currency code
    states: {
      processed:boolean
      shipped:boolean
    }
    orderId:UUID
}

Loading data into Google Data Studio

Google Data Studio uses what it calls "connectors" to gain access to data. Data Studio comes bundled with 17 connectors, mostly to pull in data from other Google products. It also supports connectors to MySQL and PostgreSQL databases, and offers 200 connectors to other data sources built and supported by partners.

Using data in Google Data Studio

Google Data Studio provides a graphical canvas onto which users drag and drop datasets. Users can set dimensions and metrics, specify sorting and filtering, and tailor the way reports and charts are displayed.

Keeping Bronto data up to date

Now what? You've built a script that pulls data from Bronto and loads it into your data warehouse, but what happens tomorrow when you have new transactions?

The key is to build your script in such a way that it can identify incremental updates to your data. Thankfully, Bronto's API results include fields like createdDate that allow you to identify records that are new since your last update (or since the newest record you've copied). Once you've take new data into account, you can set your script up as a cron job or continuous loop to keep pulling down new data as it appears.

From Bronto to your data warehouse: An easier solution

As mentioned earlier, the best practice for analyzing Bronto data in Google Data Studio is to store that data inside a data warehousing platform alongside data from your other databases and third-party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites Bronto to Redshift, Bronto to BigQuery, Bronto to Azure SQL Data Warehouse, Bronto to PostgreSQL, Bronto to Panoply, and Bronto to Snowflake.

Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data automatically, making it easy to integrate Bronto with Google Data Studio. With just a few clicks, Stitch starts extracting your Bronto data, structuring it in a way that's optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Google Data Studio.