Agentforce is going to be a major focus at Dreamforce 2024, and we’ve already seen a tremendous amount of hype and development around the artificial intelligence capabilities it provides. We have also seen a commensurate focus on Data Cloud as the tool that brings data from multiple sources to make this AI wizardry possible. But how exactly do the two work together? Is Data Cloud needed to enable Einstein? Why is there such a focus on data, anyway?

Data Cloud as the foundation for data unification

As a leader in the IBM Data Technology & Transformation practice, I’ve seen firsthand that businesses need a solid data foundation. Clean, comprehensive data is necessary to optimize the execution and reporting of their business strategy. Over the past few years, Salesforce has made heavy investments in Data Cloud. As a result, we’ve seen it move from a mid-tier customer Data Platform to the Leader position in the 2023 Gartner® Magic Quadrant™. Finally, we can say definitively that Cloudera Data Platform (CDP) is the most robust foundation as a comprehensive data solution inside the Salesforce ecosystem.

Data Cloud works to unlock trapped data by ingesting and unifying data from across the business. With over 200 native connectors—including AWS, Snowflake and IBM® Db2®—the data can be brought in and tied to the Salesforce data model. This makes it available for use in marketing campaigns, Customer 360 profiles, analytics, and advanced AI capabilities.

Simply put, the better your data, the more you can do with it. This requires a thorough analysis of the data before ingestion in Data Cloud: Do you have the data points you need for personalization? Are the different data sources using the same formats that you need for advanced analytics? Do you have enough data to train the AI models?

Remember that once the data is ingested and mapped in Data Cloud, your teams will still need to know how to use it correctly. This might mean to work with a partner in a “two in a box” structure to rapidly learn and apply those takeaways. However, it requires substantial training, change management and willingness to adopt the new tools. Documentation like a “Data Dictionary for Marketers” is indispensable so teams fully understand the data points they are using in their campaigns.

Einstein Studio provides enhanced AI tools

Once you have Data Cloud up and running, you are able to use Salesforce’s most powerful and forward-thinking AI tools in Einstein Studio.

Einstein Studio is Salesforce’s low-code platform to embed AI across its product suite, and this studio is only available within Data Cloud. Salesforce is investing heavily in its Einstein Studio roadmap, and the functions continues to improve through regular releases. As of this writing in early September 2024, Einstein Studio consists of three components:

Prompt builder

Prompt builder allows Salesforce users to create reusable AI prompts and incorporate these generative AI capabilities into any object, including contact records. These prompts trigger AI commands like record summarization, advanced analytics and recommended offers and actions.

Copilot builder

Salesforce copilots are generative AI interfaces based on natural language processing that can be used to both internally and externally to boost productivity and improve customer experiences. Copilot builder allows you to customize the default copilot functions with prompt builder functions like summarizations and AI-driven search, but it also triggers actions and updates through Apex and Flow.

Model builder

The Bring Your Own Model (BYOM) solution allows companies to use Salesforce’s standard large language models. They can also incorporate their own, including SageMaker, OpenAI or IBM Granite™, to use the best AI model for their business. In addition, Model Builder makes it possible to build a custom model based on the robust Data Cloud data.

How do you know which model returns the best results? The BYOM tool allows you to test and validate responses, and you should also check out the model comparison tool here.

Expect to see regular enhancements and new features as Salesforce continues to invest heavily in this area. I personally can’t wait to hear about what’s coming next at Dreamforce.

Salesforce AI capabilities without Data Cloud

If you are not yet using Data Cloud or haven’t ingested a critical mass of data, Salesforce still provides various AI capabilities. These are available across Sales Cloud, Service Cloud, Marketing Cloud, Commerce Cloud and Tableau. These native AI capabilities range from case and call summarization to generative AI content to product recommendations. The better the quality and cohesion of the data, the better the potential for AI outputs.

This is a powerful function, and you should definitely be taking advantage of Salesforce’s AI capabilities in the following areas:

Campaign optimization

Einstein Generative AI can create both subject lines and message copy for marketing campaigns, and Einstein Copy Insights can even analyze the proposed copy against previous campaigns to predict engagement rates. This function isn’t limited to Marketing Cloud but can also propose AI-generated copy for Sales Cloud messaging based on CRM record data.

Recommendations

Einstein Recommendations can be used across the clouds to recommend products, content and engagement strategies based on CRM records, product catalogs and previous activity. The recommendation might come in various flavors, like a next best offer product recommendation or personalized copy based on the context.

Search and self-service

Einstein Search provides personalized search results based on natural language processing of the query, previous interactions and various data points within the tool. Einstein Article Answers can promote responses from a specified knowledge to drive self-service, all built on Salesforce’s foundation of trust and security.

Advanced analytics

Salesforce offers a specific analytics visualization and insights tool called Tableau CRM (formerly Einstein Analytics), but AI-based advanced analytics capabilities have been built into Salesforce. These business-focused advanced analytics are highlighted through various reports and dashboards like Einstein Lead Scoring, sales summaries and marketing campaigns.

CRM + AI + Data + Trust

Salesforce’s focus on Einstein as “CRM + AI + Data + Trust” provides powerful tools within the Salesforce ecosystem. These tools are only enhanced by starting with Data Cloud as the tool to aggregate, unify and activate data. Expect to see this continue to improve over time even further. The rate of change in the AI space has been incredible, and Salesforce continues to lead the way through their investments and approach.

If you’re going to be at Dreamforce 2024, Gustavo Netto and I will be presenting on September 17 at 1 PM in Moscone North, LL, Campground, Theater 1 on “Fueling Generative AI with Precision.” Please stop by and say hello. IBM has over 100 years of experience in responsibly organizing the world’s data, and I’d love to hear about the challenges and successes you see with Data Cloud and AI.

Join IBM at Dreamforce 2024
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