Marketing Cloud Intelligence (formerly known as Datorama) is a powerful marketing analytics platform. Most Salesforce Marketers know the platform’s “Lite” version, which is included in the Marketing Cloud Engagement license, under the name “Marketing Cloud Intelligence Reports”. However, this merely scratches the surface of what Marketing Cloud Intelligence has to offer.
As a standalone solution, Marketing Cloud Intelligence is one of the most extensible, flexible, and intelligent (it’s in the name) marketing analytics platforms out there. It is also best at combining data from online and offline media with Salesforce products. In this guide, we’ll cover how you can leverage the three features I mentioned to ingest data from various sources.
Extensibility: Connect to External Data Sources
Marketing Cloud Intelligence relies on three main options for data connections: API Connect, TotalConnect, and LiteConnect.
As a user, you will likely use all three methods side-by-side. Which one to choose depends on the data source and business use case in question. All options have their uses, benefits, and limitations, which we will go through in detail now.
APIConnect: Connect Directly to the Source
API connect is the method of using a connector to connect an external data source to Marketing Cloud Intelligence. The connector mediates data directly between the data source and the Marketing Cloud Intelligence API, meaning that no csv exports or SFTP transfers are needed.
When it comes to connecting a data source to Marketing Cloud Intelligence, a connector should always be the first point of call. It is by far the most secure and easiest way available for users to manage data connections.
Connectors are relatively simple to set up; you need admin permissions in Marketing Cloud Intelligence, and valid user credentials to the external platform you want to connect to.
There are two kinds of connectors available:
- Native connectors: Declarative solutions built upon the Marketing Cloud Intelligence infrastructure that come with predefined dimensions and measurements.
- Custom connectors: Require manual setup using external code but offer more flexibility for data being streamed in.
At the time of writing, Marketing Cloud Intelligence boasts a whopping 174 pre-built API connectors to different social media, marketing automation, ad platforms, and more.
Here are a few popular API connectors available in Marketing Cloud Intelligence:
- Demand-Side Platforms (DSPs): e.g. Adform, Amazon DSP, Criteo, Google Display and Video 360, MediaMath.
- eCommerce Platforms: e.g. Amazon Seller, Salesforce B2C Commerce Cloud, Salesforce Order Management System (OMS).
- Marketing Automation Platforms: e.g. HubSpot, Mailchimp, Marketo.
- Paid Search: e.g. Bing Ads, Google Ads, Yahoo Gemini, Youtube Ads.
- Paid Social: e.g. Facebook Ads, Instagram Ads, LinkedIn Ads, Pinterest Ads, Tiktok Ads.
- Social Listening: e.g. Brandwatch, Crimson Hexagon, Netbase, Radarly, Sprout Social.
- Web Analytics: e.g. Adobe Analytics, Google Analytics.
And of course, you have access to the following connectors to Salesforce Marketing Cloud suite of products:
- Marketing Cloud Account Engagement (Pardot)
- Marketing Cloud Advertising (Advertising Studio)
- Marketing Cloud Engagement (i.e. Marketing Cloud Email and Mobile Studios)
- Marketing Cloud Personalization (Interaction Studio)
TotalConnect: Include File-Based Data in the Data Model
Even with the cornucopia of connectors out there, there are situations where a more flexible data connection option is needed, for example:
- There simply isn’t an API connector available for the data source you require.
- The API connectors available may not have the particular fields, parameters, or granularity you require.
Then, TotalConnect is the option to go for, allowing you to import data stored in a flat file (e.g. csv, xlsx, html, or pdf format) and automatically map its data to the Marketing Cloud Intelligence data model.
To use TotalConnect, you need to first make the data accessible to Marketing Cloud Intelligence. The following methods can be used:
- Direct upload: Manually upload files.
- Email: Schedule file exports to a dedicated Marketing Cloud Intelligence email address.
- Import: Choose one of the available technical vendors to import data.
- FTP: Use an external SFTP or FTPS service to send files to Marketing Cloud Intelligence.
LiteConnect: Import a File (and Keep Data Separated)
Sometimes, you just need to bring in data “as is”. For those ad hoc data needs, you want to use LiteConnect.
With this method, you can stream in data to Marketing Cloud Intelligence for simple visualizations without having to consider potential impacts to the overall data model. This is useful for testing purposes or when creating a proof of concept.
With LiteConnect, you can add dimensions and measurements to the data stream using formulae, as you can with TotalConnect. The main difference is that the resulting data stream will be separate from other data, and cannot be used in dashboard widgets combining data from several sources.
Bonus: Granular Data Center
The Granular Data Center (formerly Datorama Data Lake), is an enterprise solution for ingesting huge volumes of raw data, without having to compromise system performance or data granularity.
As a premium solution, it comes with a price tag. However, Granular Data Center may be the solution for you if you plan to include a data source spanning millions or billions of data rows, since the cost is not row-based but data usage based.
Flexibility: Map, Harmonize, and Classify Data
Marketing Cloud Intelligence has a highly flexible data model to suit the particular needs of your business.
Data modeling is made convenient by providing marketers with 19 reusable templates for different data source types, e.g. online advertising, eCommerce, social listening, and web analytics. Data modeling doesn’t stop with you bringing data in – you can re-map, supplement, harmonize, and classify data as needed.
Adjust Your Data Mapping
Data Mapping Visualizer is the tool you need to get a clean overview of your data, useful for:
- Understanding how external data maps to your data model.
- Which external data feeds into a selected data model field.
You can understand how external data maps to your data model by selecting a data stream, and examining the columns in the external data. Clicking or hovering over a column will highlight the data model field it maps to.
For which external data feeds into a selected data model field, hover over a data model field, and toggle the “+” button that appears.
For a deeper view of your data mapping, it’s best to go to the “Data Mapping” section that displays your data mapping in a tabular format. I find it easier to simply export this view, and work on it in Excel.
If you discover that you need to re-map, un-map, or supplement your data in some way, you should head over to the “Data Streams List” and select the data stream you want to alter.
Re-mapping or un-mapping is simple to do technically: select the data stream, go to the “Map to Model” screen, and click the blue dot in the middle of the screen where your chosen source data and data model field intersect.
- Re-mapping: You may need to re-map fields as your data model develops, or if you simply made a mistake in your earlier mapping attempt.
- Un-mapping: Useful for managing data row usage by reducing granularity. For example, going from city-level data to regions, or switching from daily to weekly data can significantly reduce the number of data rows brought in.
Note: Changes to data mappings only affect future data data imports. If you wish to alter historical data, you will need to rerun past imports of the data stream. In this case, do account for the risk of data loss by creating backups of the current data stored in Marketing Cloud Intelligence.
Harmonize and Classify Your Data
Having a shared naming convention across platforms is key for achieving analytics success. But why is that?
With Marketing Cloud Intelligence, you can parse the naming convention – a long string of text with descriptions, dates, codes and delimiters – into separate fields. In other words, you don’t need to rely on what information is available to you through pre-built connectors if you can include what’s required in the campaign name itself.
For instance, a campaign called “2024_01_23_EMEA_Facebook_Retargeting_300x250_18-25” contains a wealth of information, including date, area, medium, objective, placement size, and age group. With a naming convention and pattern in place, you can capture these insights into data model fields automatically. Cool, right?
Patterns allow you to gather harmonized dimensions from your landing pages, campaign names, and media buys. You can go beyond that by adding classification rules onto those harmonized dimensions. For instance, you can group countries to continents with the use of an Excel file. Or, you could upload a product catalog that classifies individual SKUs under product categories.
With classification rules, you only need to include the most specific level insights in the campaign name (e.g. you only need the country, not the continent), saving valuable real estate (i.e. characters) when setting up ad campaigns or building landing pages.
Intelligence: Let AI Do the Work for You
So far, we’ve covered features that are more or less standard fair when it comes to marketing analytics. The game-changer that Marketing Cloud Intelligence brings to the table is predictive AI.
Marketing data is highly granular, complex, and messy. Making sense of this data is a task perfectly suited for AI. Marketing Cloud Intelligence’s AI functionalities enable you to:
- Identify and map your data streams correctly.
- Spot emerging trends.
- Detect areas for improvement.
- Optimize campaign performance.
Untangle Messy Marketing Data
One cool aspect of TotalConnect is that when adding or editing a data stream, a predictive AI model runs in the background trying to match the columns in the source data with commonly used data source types.
The AI model then sets up a preliminary mapping of the data, which you can fully adjust to fit your needs. This saves an incredible amount of time that you’d otherwise have to spend on manual work, and also mitigates the risk of human error.
Uncover Insights With Einstein Bots
Turning data into actionable insights takes up valuable time and becomes exceedingly difficult as your data sources abound. Luckily, Einstein Bots are here to help. They are AI-driven solutions that you configure in the system to provide automated insights whenever something interesting occurs in the data. There are two types of insights Einstein Bots provide:
- Performance changes: e.g. the number of conversions is down from the previous month, or the cost of impressions has gone up.
- Change drivers: e.g. number of conversions is up from previous month, and this could be due to increase in site traffic by x%.
AI features into Einstein Bots in two ways. Firstly, when setting up the bot, you’ll already notice that it suggests key dimensions to give insights on. Secondly, it uses machine learning to look at possible causes for increases or decreases in your target metric.
Once new insights become available, the Einstein Bot can be set to send an email notification to relevant persons in your organization. This way, you can react quickly to early warning signs, or you can notify sales if there’s a campaign performing outstandingly well. Either way, Einstein Bots provides a valuable tool to stay on top of your insights and uncover value from them.
Summary
Marketing Cloud Intelligence (Datorama) is one of the most extensible, flexible, and intelligent marketing analytics platforms out there – combining data from online and offline media with Salesforce products. Hopefully now you understand how you can ingest data from various sources into Marketing Cloud Intelligence.
