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What is Salesforce Data Cloud (with use cases)?

·7 mins

Salesforce Data Cloud helps companies unify customer data from various sources, gain insights into customer behavior, and deliver personalized experiences across channels.

With Data Cloud, companies can create a single view of each customer by connecting data from CRM systems, email platforms, loyalty programs, and more. Think of it as CDP (Customer Data Platform) on steroids that includes a lot more capabilities.

The recent announcements in Dreamforce 2023 have made it clear that Data Cloud is the future foundation for data in Salesforce. It will power the the system of record for customer data that will in turn power all the customer engagement systems in the Salesforce ecosystem.

What is Salesforce Data Cloud? #

Salesforce Data Cloud is a cloud-based platform that helps companies manage customer data at scale. It ingests data from multiple sources, matches customer records, maintains accuracy through continuous data quality checks, and makes the unified customer profiles available for marketing and analytics use cases. It cleans, matches, and enriches data to maintain accuracy. Data Cloud also enables real-time segmentation and activation to optimize customer engagement.

Key capabilities include:

  • Connecting data from CRM systems, web/mobile apps, email platforms, loyalty programs, etc.
  • Resolving customer profile across data sources through probabilistic matching
  • Maintaining accurate customer profiles with continuous data quality checks
  • Building unified customer profiles with analytical attributes appended
  • Segmenting customers and activating campaigns in real-time based on user behavior

Features of Data Cloud #

Some key features of Salesforce Data Cloud include:

  • Pre-built connectors to import data from popular sources like CRM, email, mobile apps, etc.
  • Identity resolution to accurately match customer records across sources.
  • Data quality tools to identify anomalies, fill gaps, and maintain accuracy.
  • Analytics to gain insights from customer data.
  • AI since there cannot be any product without mentioning AI these days.
  • Audience segmentation to define targeted groups based on attributes.
  • Integration with marketing clouds to activate campaigns.
  • Privacy compliance tools to honor data regulations.
  • APIs and SDKs to build custom integrations.

Data Cloud may soon extend into -

  • Being a unified data source that provides all goodness of data marts but being accessible in real-time for any customer data use cases (& beyond?)
  • Provide industry models OOB
  • Account-focused models and enriched B2B/B2C models that increasingly cover more MDM areas
  • Increasingly powerful AI capabilities.. since there cannot be any product without mentioning AI these days (did I say that already?)

A Bit of History of Data Cloud #

Salesforce entered the CDP space with its acquisition of Krux in 2016. Krux’s data management platform and analytics capabilities formed the foundation for Salesforce Data Cloud.

In 2019, Salesforce acquired Datorama, an AI-powered marketing analytics platform. Datorama’s capabilities were integrated into Data Cloud to provide marketing insights.

Data Cloud is an amalgamation of products with foundation in what was previously known as Salesforce Audiences 360 and, later, Customer Data Platform. It was rebranded as Data Cloud in 2021 to reflect its broader capabilities. And yes, it was known as Genie for about a month circa Dreamforce 2022.

How Data Cloud Works? #

At a high level, Salesforce Data Cloud works in four stages:

1. Connect all your data #

Data Cloud provides pre-built connectors and APIs to bring in customer data from various sources like:

  • CRM systems
  • Email platforms
  • Mobile and web apps
  • Customer service systems
  • Loyalty programs
  • POS systems
  • Offline data

The connected data serves as the raw material for creating unified customer profiles.

2. Harmonize your data #

Once data from different sources is ingested, Data Cloud resolves customer identities across these sources. This identity resolution is done through probabilistic matching algorithms.

Data Cloud also cleans, standardizes, and enriches incoming data. Any anomalies in data are identified and resolved to maintain accuracy.

3. Engage your data to put it to work for you #

The harmonized data is made available to different systems for customer engagement use cases through APIs.

You can leverage Data Cloud data for:

  • Building unified customer profiles
  • Performing analytics to gain insights
  • Creating targeted audience segments
  • Personalizing experiences in real-time
  • Orchestrating campaigns across channels
  • Measuring marketing performance

4. Create a better experience #

By tapping into accurate, unified customer data, companies can gain a holistic understanding of each customer and create consistent, relevant experiences across touchpoints.

Data Cloud makes the customer data readily available for powering these use cases.

Use Cases for Data Cloud #

Here are some examples of how Data Cloud enables better customer experiences across industries:

Financial Services #

Banks can unify data from core banking systems, credit card programs, insurance policies, and online/mobile apps to get a 360° customer view. This powers use cases like:

  • Personalized product recommendations
  • Cross-sell and upsell opportunities
  • Customer loyalty programs
  • Targeted campaigns across channels
  • Fraud prevention

Healthcare and Life Sciences #

Healthcare providers can consolidate patient data from various hospitals, clinics, wearables, and more. This enables:

  • Complete patient profiles for improved care
  • Better appointment reminders and engagement
  • Personalized recommendations for health programs
  • Optimized clinical trials targeting

For pharma companies, Data Cloud can power compliant, multichannel patient marketing campaigns.

Retail and Consumer Goods #

Retailers can ingest point-of-sale, ecommerce, CRM, and third-party data to understand customer behavior. This facilitates:

  • Building shopper profiles across channels
  • Personalized promotions and recommendations
  • Optimized product assortments
  • Customer retention programs

Media and Communications #

Media companies can create unified profiles of customers engaging across web, mobile, OTT streaming, and other properties. This allows:

  • Personalized content recommendations
  • Customized subscriptions and billing
  • Targeted promotions and advertisements
  • Measurement of engagement across properties

How to Use Salesforce Data Cloud? #

Here are some tips for getting started with Data Cloud:

Interacting with Data Cloud data #

Once Data Cloud has unified your customer data, you can interact with it through:

  • APIs to access profile and segment data for customer engagement systems.

  • The Audience Studio UI to build segments, activate campaigns, and analyze performance.

  • Analytics to run queries, generate insights, and create dashboards.

Leveraging Platform capabilities #

The Customer 360 Platform provides a suite of products to drive different use cases that easily extend Data Cloud:

  • Use Journey Builder to orchestrate personalized cross-channel campaigns.
  • Leverage Commerce Cloud to optimize customer engagement post-purchase.
  • Use Interaction Studio to design omni-channel customer journeys.
  • Harness Einstein Analytics for deeper insights
  • Look forward to run AI/ML models on your data with Einstein1 / or whatever it is known as at the time of you reading this

Sending Data Cloud Data back to the transactional database #

You can also feed insights from Data Cloud back to your transactional systems to enrich customer records. For example, use web behavioral segments to update CRM profiles. The sync with platforms like Sales Cloud and Service Cloud is bi-directional, and you can expect the same seamless behaviour across the ecosystem.

What’s new and innovative here? #

Salesforce Data Cloud provides an end-to-end CDP++. It not only focuses on building unified profiles but also powers customer engagement across the journey. Key differentiators at the time of writing include:

  • Leveraging AI/ML for matching, data quality, insights
  • Real-time customer segmentation and activation
  • Rich analytics for harnessing data
  • Seamless integration with broader Customer 360 platform
  • Cloud-native and scalable architecture

While you see Data Cloud being used in the context of Marketing Cloud in the past, it is projected as the the catch-all system that unifies data across salesforce ecosystem and beyond in the future.

Should I jump to the Data Cloud bandwagon, or wait? #

Well, it depends.

If you are a Salesforce customer, you may already be using Data Cloud in some form or find immediate use cases for integration / consolidation / profiling. Salesforce announced Free Data Cloud licenses for Enterprise Edition and above.

  • 250k credits
  • 1 admin, limited “consumer” users
  • 2 Tableau creator licenses

See details here.

The consumption based model and free credits are a good way to start small, explore use cases and expand use cases. No need to talk to Account Executives, Sales people, or to a dozen consultants.

So, why would one want to wait?

  • Well, I would take Dreamforce announcements with a pinch of salt
  • The product is still evolving and there may be gaps in functionality / marketing messages vs reality
  • Use cases may be hard to identify with overlapping functions across salesforce products

Learn More about Data Cloud #

Here are some resources to learn more about Dataforce Data Cloud: