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Salesforce’s Data Cloud Revolution: Unlocking Business Potential

Salesforce’s Data Cloud is the fastest-growing internally developed product in the company’s history—that is, it was developed internally, not through acquisitions. The goal may be referred to as the “Holy Grail of CRM,” meaning that the data issue that has plagued CRM since its inception has finally been resolved.

According to a Salesforce study, the typical business has 928 systems, which means that a large company probably has thousands of systems, and a small company probably has hundreds. When you have multiple systems, resolving identity becomes difficult.

Different applications within each vertical, additional objects in the data model, and regulations to navigate are some of the additional challenges that come with industry. Data Cloud appears to be a positive step towards resolving these data harmonization issues.

What part will generative AI play in use cases for industry? What projects is Salesforce currently working on, and why is industry such a big deal to them?

Chief Product Officer at Salesforce David Schmaier led the charge on much of what is now known as the Data Cloud. In addition, he founded Vlocity, which is now Salesforce Industries after Salesforce purchased Vlocity. He discussed his two passions, Salesforce Industries and Data Cloud, in an interview. This is what we discovered.

How it Works

A customer data platform is called Data Cloud (CDP). Through identity resolution, these allow organisations to combine information from various sources into a single profile for that person.

For instance, data harmonisation takes into account the fact that you may be referred to by both your birth name and a nickname in different systems while creating a single, cohesive profile. This allows the brand to provide you with the best possible experience, tailored to your individual needs and past interactions.

Data Cloud is pre-wired to Salesforce objects (such as the Product and Order objects) at the time of purchase. The foundation is in place for you, even though you still need to work on mapping the systems and putting policies in place to enhance or preserve the data quality.

Contrast this effort with the previous method of setting up a CDP (or doing it yourself). It takes a fraction of the effort that it used to, making it incredibly easier.

Industries Challenges

Salesforce realised this important point—that industries operate differently from others—when it acquired Vlocity and made additional significant investments in creating Salesforce Industries solutions. Twelve Salesforce Industries “Clouds,” including the Financial Services Cloud, Communications Cloud, Nonprofit Cloud, and others, have been sparked by this.

Salesforce is prepared to provide these twelve industries with Data Cloud capabilities, which are essentially a technological layer, by providing industry-specific data models and processes.

In the case of industries, there are other difficulties that arise, such as:

Extra Objects: When mapping data points for data harmonisation, some Industry Clouds take into account more than 200 additional objects in their data model.

Regulations: For instance, patient experience is only one aspect of health care; patient data confidentiality is also protected by regulations. Health Cloud includes unique items that facilitate HIPAA compliance in the United States and other regulations in other countries, such as France and Japan.

Various uses in the respective categories: For instance, the judicial system, tax and revenue, and citizens’ services are all part of the public sector. Each goes in a different direction with data harmonization.

The distinctive edge of Salesforce

Data Cloud is impressive in and of itself. Even though many businesses would view it as costly, if you were to turn the tables and purchase your own data warehouse, construct a star schema, and pay for continuous compute storage, the total cost would likely be five to ten times higher than what Salesforce charges for Data Cloud. Furthermore, data harmonisation functions optimally when your CRM data is highlighted.

Data models tailored for specific industries: Effective data harmonization depends on your CRM data, as was previously mentioned. Accuracy, completeness, consistency, and timeliness are the most important aspects of data quality, and they all depend on getting data into your CRM and using it. Good Data + Good AI → Results. Bad Data + Good AI → Garbage.

Customized creation of prompts for specific industries: Since prompts are questions in natural language, prompt engineering is the art of crafting prompts to elicit the best possible response (i.e. a user typing as they would in conversation). Users can use the information from these Industry Clouds to enhance the outputs they receive by responding to an industry-specific prompt.

What's Next?

The development of Data Cloud for Industries will proceed through the standard pilot, beta, and general availability phases. The patient experience on Data Cloud for Health Care will be the first; many more will be revealed soon.

Salesforce has a distinct advantage in the industry due to their industry-specific data models, even though there are still other challenges. Since data enables AI to produce better results, this results in more efficient prompt engineering.

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