Data Cloud is the fastest growing organically built product in Salesforce’s history (i.e. Salesforce built it themselves, not via acquisitions). The objective could be described as the “Holy Grail of CRM”, which means that the data problem that’s existed since the infancy of CRM is now solvable.
A Salesforce study revealed that the average company has 928 systems – meaning that a big company has thousands, and a small company likely has hundreds. As soon as you have more than one system, identity resolution becomes a challenge.
When it comes to industries, additional challenges present themselves – with additional objects in the data model, regulations to navigate, and different applications within each vertical. Data Cloud is looking like a step in the right direction for these data harmonization challenges.
How will generative AI play a role in industry use cases? What are Salesforce already working on, and why do they care so much about industries?
David Schmaier, Chief Product Officer at Salesforce, spearheaded much of what we know to be Data Cloud. He’s also the founder of Vlocity (now Salesforce Industries, after Vlocity was acquired by Salesforce). During an interview, he shared insight into his two passions: Salesforce Industries and Data Cloud. Here’s what we found out…
How it Works
Data Cloud is a Customer Data Platform (CDP). These enable organizations to consolidate data points from multiple sources into a unified profile for that individual – known as identity resolution.
For example, whether you’re known by your birth name in one system and a nickname in another, data harmonization respects that while building up a unified profile – so that the brand can give you the best experience, personalized to your history and current needs.
When purchased, Data Cloud comes pre-wired to Salesforce objects (e.g. the Product object, Order object, etc.). While you still need to work to map the systems and put measures in place to improve/maintain the data quality, the groundwork is done for you.
Compare this effort to how setting up a CDP used to be (or, doing it yourself). It’s immensely easier – a fraction of what effort used to be required.
Industries Challenges
When acquiring Vlocity and further investing heavily in developing Salesforce Industries solutions, Salesforce recognized the key point: Industries work differently from others. This has spurred on 12 Salesforce Industries ‘Clouds’ ranging from Financial Services Cloud, Communications Cloud, Nonprofit Cloud, and others.
By delivering industry-specific data models and processes to these dozen industries, Salesforce are ready to deliver Data Cloud capabilities – which is essentially a technology layer – to these industries.
When it comes to industries, additional challenges present themselves, which include:
- Additional objects: Some Industry Clouds have 200+ additional objects in their data model to consider when mapping data points for data harmonization.
- Regulations: For example, in health care, it’s not just about the patient experience – there are regulations to protect the confidentiality of patient data. Health Cloud comes with special objects that support HIPAA compliance in America and other regulations in, for example, France and Japan.
- Different applications within the verticals: For example, in the government/public sector, there are citizens’ services, tax and revenue, judicial, and others. Each takes data harmonization down another tangent.
Salesforce’s Unique Advantage
Data Cloud, in itself, is impressive. While many organizations would consider it expensive, if you were to flip the argument on its head by buying your own data warehouse, building what’s called a star schema, and paying for ongoing compute storage, you’d be looking to spend five to ten times more than what Salesforce are charging for Data Cloud. Plus, data harmonization works best when your CRM data is front and center.
- Industry-specific data models: As mentioned above, your CRM data is key to effective data harmonization. Getting data into your CRM and being able to utilize it is key to all dimensions of data quality – especially accuracy, completeness, consistency, and timeliness. Good Data + Good AI → Results. Bad Data + Good AI → Garbage.
- Industry-specific prompt engineering: Prompt engineering is the art of writing prompts to get the most optimal answer, as prompts are natural language queries (i.e. a user typing as they would in conversation). With an industry-specific prompt, users can take the knowledge from these Industry Clouds to improve the outputs they receive.
What’s Next?
Data Cloud for Industries is being worked on and will be released via the typical pilot, beta, general availability sequence. The first will be Data Cloud for Health Care (the patient experience), with many more to be announced.
When it comes to industries – while additional challenges present themselves – Salesforce is at a unique advantage with their industry-specific data models. This leads to more effective prompt engineering because, after all, data empowers the AI to drive better outcomes.