Get to Know the Cloud Information Model

Learning Objectives

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

  • Describe data model challenges.
  • Recognize Cloud Information Model terminology.
  • Explain how Salesforce is using the Cloud Information Model.

Cloud Information Model

Successful missions often have hi-tech gadgets and technical support running in the background. For Customer 360 products to manage and organize large amounts of data, we have support behind the scenes, too. We use the Cloud Information Model (commonly known as CIM). The CIM is a schema (or model) used to communicate between connected data sources with different data structures and formats. It uses APIs (a developer tool that allows for systems to talk to each other) and other mappings to connect applications and data.

It’s helpful to understand how and why the CIM came to be. Salesforce and other large companies (including AWS, IBM, and Google) collaborated to create an open source data model that standardizes data formatting across applications. Basically, it provides a way to make integration seamless and scalable regardless of what cloud platform you are using. This also reduces the barriers to cross-product integration. Standardization is important for a couple of reasons.

Data Models

In search of connected experiences and digital transformation, many companies adopt multiple systems. Remember our NTO example with team members using data from lots of different sources? That’s pretty typical. The larger the company, the more systems they work with. And each system comes with a unique data model. This makes it challenging for users to unify data across departments and systems. Companies often solve this issue by asking developers or consultants to create custom code and solutions to connect the dots. And the result is best stated on the CIM homepage: “Instead of accelerating digital transformation, this process slows innovation and leads to brittle integrations.”

Database Structure

Enterprise data is rarely standardized. The data is instead heavily customized for specific business requirements—and can even be found in its raw form with unlimited decimals or lengths. This can be messy, but it gets messier. Data can also be classified as structured or unstructured (meaning with or without a formal data model). And there are many variety of different types of databases that store data, from relational databases that use Structured Query Language (SQL) to ones that don't, called NoSQL databases. (For reference, Marketing Cloud stores data using a relational database structure.) Many organizations today store their data in a variety of databases. Having different types of data is fine, as long as it is easily retrievable—which isn’t always the case.



Learn more about data systems in the Trailhead module Strategies for Big Data Architecture.

A Marketer’s Guide to the CIM

As a marketer, you know that data is what drives your business and personalized experiences for your customers. While you don’t need to be an expert on the CIM (or data models, in general), it’s helpful to know how it impacts your work. Think of how a customer record is stored in a retail point of sale (POS) system and how that same customer is identified in Marketing Cloud. A POS might store a customer as a random number based on the time of the sale (like 1145). Marketing Cloud stores that same customer using a subscriber key (like Susan1145). So how can you integrate systems that have different ways of identifying the same customer, along with different data formats?

The CIM solves this by creating standardized data models that can be used in common scenarios based on subject areas (like sales orders). This creates a standard way for platforms using the CIM model to map to each other, making data mapping easier. If data mapping is easier, identifying the same customer in multiple systems becomes easier.

CIM Terminology

To create a standard model across systems, the CIM created a common language to use across platforms. Let’s go over the basic components of the CIM.

CIM components depicted as nested content boxes in order of hierarchy: subject area, entity groups, entities, and attributes.

Subject Area

A subject area is a business concept identified by the CIM, for example, Sales Order. Each subject area contains one or more entity groups.

Entity Group

An entity group is a logical grouping of related entities within a subject area, for example, Retail Sales. Each entity group contains one or more entities.


A unique object that an organization collects information about, such as Retail Customers. An entity is like a Marketing Cloud data extension (which is a standard database table).  


An attribute is a unique characteristic of an entity, for example, a customer’s First Name. This is similar to a data extension field in Marketing Cloud.

Salesforce, the CIM, and You

Why embrace the CIM? The CIM helps us bring together customer data across various Salesforce apps, as well as outside sources. Using the CIM, data models become usable across a variety of platforms. It allows us to deliver a truly self-service data management platform, for even the most complex data pipelines. 

For marketers, the CIM is used in Customer 360 Audiences to make data modeling marketer-friendly using pre-built models based on common marketing use cases. These crafted data models for things like general customer engagement or tracking customer loyalty are called data bundles. While we won’t dive into specific information about data bundles in this module, the thing to know is that data bundles help you standardize your data without extensive manipulation or a PhD in data science.



If the pre-built data use cases or standard options don’t work for your business, you also have the ability to customize your own data models.

Marketing Cloud Contact Model

Implementing Customer 360 Audiences won’t impact your current contact model in Marketing Cloud Contact Builder. Your contact model in Marketing Cloud is just one piece of the data model puzzle. It’s the job of Customer 360 Audiences to integrate and work across multiple channels and clouds. That being said, in the next unit, we cover some prep work you can do to prepare for Customer 360 Audiences.



Want more info about data strategy? Check out the Trailhead module Customer-Centric Data Strategies to learn more customer data considerations.

Now you have an overview of the products and how the data is managed behind the scenes, let's take a closer look at Customer 360 Audiences.


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