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Use TotalConnect

Learning Objectives

After completing this unit, you’ll be able to:

  • Identify when to use TotalConnect to upload data in Marketing Cloud Intelligence.
  • Set up a TotalConnect data stream.
  • Map the data in your data stream and validate your mapping.

What Is TotalConnect?

TotalConnect is used for customized data upload, especially when there isn’t an API that can be used to get certain data into Marketing Cloud Intelligence. The process of creating a TotalConnect data stream starts with uploading a sample file of the data. This way, Marketing Cloud Intelligence can identify the appropriate data stream type according to the data model. Then, the platform is able to map the source fields to the corresponding Marketing Cloud Intelligence fields. 

Data can be ingested in a TotalConnect data stream either manually or automatically. To automate data feeds, the TotalConnect data stream can receive scheduled email reports or SFTP uploads. TotalConnect can also retrieve data from a technical vendor. You can configure your import to retrieve data at any specific frequency using a variety of methods, including external databases, HTTP requests, Google BigQuery, Python, and AWS-S3 to name a few. 

In this unit, we cover how to connect your data using TotalConnect. Check out this video to see the steps in action.

Set Up Your TotalConnect Data Stream

Once you select TotalConnect in Marketing Cloud Intelligence, you can either upload your first data file or choose to import data from a technical vendor. 

TotalConnect file upload screen and technical vendor list.

You can upload your file by using Drag & Drop or clicking Browse to select a file. You can upload any type of data file.

Once a file is loaded, the Preview (1) window appears. This is where you can see how Marketing Cloud Intelligence reads your source data, including the fields (2) and their types. A field can be a date, text, or number, and you can change a field’s type if needed. 

TotalConnect Preview window with Preview, source fields and Next button highlighted.

Once you click Next (3), Marketing Cloud Intelligence will analyze your source data and automatically select the relevant data stream type for you. The data stream type determines the dimensions and measurements that will be available for mapping, according to Marketing Cloud Intelligence’s data model. 

Map Your Data

Once you upload a file, you can map the data. Mapping means connecting the source fields in your uploaded file to the corresponding Marketing Cloud Intelligence fields. At this point you can manually apply the mapping yourself, but in most cases Marketing Cloud Intelligence automatically maps the source fields to the corresponding Marketing Cloud Intelligence fields using machine learning algorithms. If you think the automatic mapping is incorrect, simply unmap any incorrect connection and remap as needed. Let’s take a look at the Mapping screen.

Mapping screen showing different areas numbered.

  • In the External data (1) sidebar, you can find the source fields, as they were brought in from your files. You can filter between viewing Mapped and Unmapped fields.
  • Under the selected data stream type (2), you can see the Data Model fields from Marketing Cloud Intelligence grouped by Entity type, for example Campaign or Media Buy entity.
  • Within Mapped (3) you can see the connections between your source data fields and Marketing Cloud Intelligence data fields, and you can even create new connections. You can customize a mapped data field by clicking on it (4), and you can change the display name, or even add or edit a formula.

Marketing Cloud Intelligence maps the fields that are identified, but there may be unidentified fields that you require. If you need to map an unmapped field, simply select the unmapped field (from the External Data sidebar) and then select the relevant unmapped Data model field (under the data stream type) and click Apply. In this example the source field Campaign Category was mapped to the Marketing Cloud Intelligence field Campaign Category simply by dragging and dropping.

The unmapped field, Campaign Category, being mapped to the unmapped data model field Campaign category.

If you would like to unmap a field that has already been mapped, simply click in the middle of the connection in order to unmap it. 

A mapped field connection is shown with the Unmap option highlighted

Validate Your Mapped Data

When you finish mapping your data, you can use the Validate (1) feature to ensure there aren’t any errors or irregularities with your mapping. If Marketing Cloud Intelligence identifies any errors, you will automatically see which field needs to be edited and what steps you can take (2) to correct the issue. 

Validate button and a mapping validation message are highlighted.

After you edit the mapping, click Validate again to ensure all errors have been fixed.

Preview Your Data Before Upload

Before creating your TotalConnect data stream, you can use the Preview (1) button to see a preview of your mapped data (2). You can also see the date range (3) of the file you uploaded to verify that it’s correct.

Data Preview showing, Preview button, mapped data, date range and Create button highlighted.

Click Create (4) to create your data stream and upload the data. It’s recommended that you validate your data using a pivot table to ensure the data is correctly mapped and aggregated.

Once you finish this process, a new data stream is created in the Data Streams List. To help you identify the source of the data stream, the Source column appears as TotalConnect. 

Data Streams List with newly created data stream highlighted.

Next Up

In this unit, you learned how to upload data with TotalConnect—a great option when your data is stored at a source with no API Connector, yet you need the data to be ingested with a regular and automated data feed. Join us in the next unit to learn another way to upload your data in Marketing Cloud Intelligence: using LiteConnect.

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