This page provides you with instructions on how to extract data from Salesforce Marketing Cloud Email Studio and analyze it in Power BI. (If the mechanics of extracting data from Salesforce Marketing Cloud Email Studio 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 Salesforce Marketing Cloud?
Salesforce Marketing Cloud is a marketing automation platform for B2B and B2C marketing. Salesforce Marketing Cloud Email Studio (known as ExactTarget before the company that created it was purchased by Salesforce in 2013) lets businesses create scalable data-based email marketing campaigns. The data it tracks (e.g. open and bounce rates) can be accessed by other parts of the Marketing Cloud platform, which also comprises social media marketing, digital advertising, and mobile messaging components.
What is Power BI?
Power BI is Microsoft’s business intelligence offering. It's a powerful platform that includes capabilities for data modeling, visualization, dashboarding, and collaboration. Many enterprises that use Microsoft's other products can get easy access to Power BI and choose it for its convenience, security, and power.
With high-value use cases across analysts, IT, business users, and developers, Power BI offers a comprehensive set of functionality that has consistently landed Microsoft in Gartner's "Leaders" quadrant for Business Intelligence.
Getting data out of Salesforce Marketing Cloud
Marketing Cloud offers two APIs:
- A REST API that exposes access to a range of Marketing Cloud capabilities
- A SOAP API that provides access to most email functionality, including tracking, subscribers and lists, automations, and content
The SOAP API uses SOAP envelopes to pass SOAP data. A call to retrieve all messages sent since the last batch might look like this.
<Envelope xmlns="http://schemas.xmlsoap.org/soap/envelope/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <Header> <Security xmlns="https://www.marketingcloud.com/"> <fueloauth>YOUR_ACCESS_TOKEN</fueloauth> </Security> </Header> <Body> <RetrieveRequestMsg xmlns="http://exacttarget.com/wsdl/partnerAPI"> <RetrieveRequest> <ObjectType>SentEvent</ObjectType> <Properties>SubscriberKey</Properties> <Properties>EventDate</Properties> <QueryAllAccounts>false</QueryAllAccounts> <Filter xsi:type="SimpleFilterPart"> <Property>SendID</Property> <SimpleOperator>equals</SimpleOperator> <Value>12345</Value> </Filter> <RetrieveAllSinceLastBatch>true</RetrieveAllSinceLastBatch> </RetrieveRequest> </RetrieveRequestMsg> </Body> </Envelope>
Sample Salesforce Marketing Cloud Email Studio data
The Email Studio API returns information in a SOAP envelope. You have to parse all the attributes before loading the data into your data warehouse. Here's an example of what some of the data for that call to retrieve all messages might look like.
<soap:Envelope xmlns:soap="http://schemas.xmlsoap.org/soap/envelope/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:wsa="http://schemas.xmlsoap.org/ws/2004/08/addressing" xmlns:wsse="http://docs.oasis-open.org/wss/2004/01/oasis-200401-wss-wssecurity-secext-1.0.xsd" xmlns:wsu="http://docs.oasis-open.org/wss/2004/01/oasis-200401-wss-wssecurity-utility-1.0.xsd"> <soap:Header> <wsa:Action>RetrieveResponse</wsa:Action> <wsa:MessageID>urn:uuid:cdb7b621-8341-4a35-840d-c4ec56fb8a6d</wsa:MessageID> <wsa:RelatesTo>urn:uuid:e6a83541-3ae7-412d-9412-d40ee321c4aa</wsa:RelatesTo> <wsa:To>http://schemas.xmlsoap.org/ws/2004/08/addressing/role/anonymous</wsa:To> </soap:Header> <soap:Body> <RetrieveResponseMsg xmlns="http://exacttarget.com/wsdl/partnerAPI"> <OverallStatus>OK</OverallStatus> <RequestID>cefcfd29-d44f-4bbd-9188-e2bd51e2de5f</RequestID> <Results xsi:type="SentEvent"> <PartnerKey xsi:nil="true"/> <ObjectID xsi:nil="true"/> <SubscriberKey>email@example.com</SubscriberKey> <EventDate>2017-03-26T10:02:01.987</EventDate> </Results> <Results xsi:type="SentEvent"> <PartnerKey xsi:nil="true"/> <ObjectID xsi:nil="true"/> <SubscriberKey>firstname.lastname@example.org</SubscriberKey> <EventDate>2014-03-26T10:02:01.987</EventDate> </Results> <Results xsi:type="SentEvent"> <PartnerKey xsi:nil="true"/> <ObjectID xsi:nil="true"/> <SubscriberKey>email@example.com</SubscriberKey> <EventDate>2017-03-26T10:02:01.987</EventDate> </Results> </RetrieveResponseMsg> </soap:Body> </soap:Envelope>
Preparing Salesforce Marketing Studio Data
If you don't already have a data structure in which to store the data you retrieve, you'll have to create a schema for your data tables. Then, for each value in the response, you'll need to identify a predefined datatype (INTEGER, DATETIME, etc.) and build a table that can receive them. Salesforce's documentation should tell you what fields are provided by each endpoint, along with their corresponding datatypes.
Complicating things is the fact that the records retrieved from the source may not always be "flat" – some of the objects may actually be lists. This means you'll likely have to create additional tables to capture the unpredictable cardinality in each record.
Loading data into Power BI
You can analyze any data in Power BI, as long as that data exists in a data warehouse that's connected to your Power BI account. The most common data warehouses include Amazon Redshift, Google BigQuery, and Snowflake. Microsoft also has its own data warehousing platform called Azure SQL Data Warehouse.
Connecting these data warehouses to Power BI is relatively simple. The Get Data menu in the Power BI interface allows you to import data from a number of sources, including static files and data warehouses. You'll find each of the warehouses mentioned above among the options in the Database list. The Power BI documentation provides more details on each.
Analyzing data in Power BI
In Power BI, each table in the data warehouse you connect is known as a dataset, and the analyses conducted on these datasets are known as reports. To create a report, use Power BI’s report editor, a visual interface for building and editing reports.
The report editor guides you through several selections in the course of building a report: the visualization type, fields being used in the report, filters being applied, any formatting you wish to apply, and additional analytics you may wish to layer onto your report, such as trendlines or averages. You can explore all of the features related to analyzing and tracking data in the Power BI documentation.
Once you've created a report, Power BI lets you share it with report "consumers" in your organization.
Keeping Salesforce Marketing Cloud data up to date
At this point you've coded up a script or written a program to get the data you want and successfully moved it into your data warehouse. But how will you load new or updated data? It's not a good idea to replicate all of your data each time you have updated records. That process would be painfully slow and resource-intensive.
Instead, identify key fields that your script can use to bookmark its progression through the data and use to pick up where it left off as it looks for updated data. Auto-incrementing fields such as updated_at or created_at work best for this. When you've built in this functionality, you can set up your script as a cron job or continuous loop to get new data as it appears in Email Studio.
And remember, as with any code, once you write it, you have to maintain it. If Salesforce modifies its API, or the API sends a field with a datatype your code doesn't recognize, you may have to modify the script. If your users want slightly different information, you definitely will have to.
From Salesforce Marketing Cloud Email Studio to your data warehouse: An easier solution
As mentioned earlier, the best practice for analyzing Salesforce Marketing Cloud Email Studio data in Power BI 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 Salesforce Marketing Cloud Email Studio to Redshift, Salesforce Marketing Cloud Email Studio to BigQuery, Salesforce Marketing Cloud Email Studio to Azure SQL Data Warehouse, Salesforce Marketing Cloud Email Studio to PostgreSQL, Salesforce Marketing Cloud Email Studio to Panoply, and Salesforce Marketing Cloud Email Studio to Snowflake.
Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data from Salesforce Marketing Cloud Email Studio to Power BI automatically. With just a few clicks, Stitch starts extracting your Salesforce Marketing Cloud Email Studio data via the API, 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 Power BI.