Data Cloud Insights from Salesforce Connections

Prolocity’s Data Cloud Lead, Ryan Hernalsteen, recently attended Connections in Chicago with Nonprofit Practice Lead, Jeremy Donelan, and Marketing Cloud Lead, Maria Kelley. They presented two highly attended sessions: one showcasing compelling real-life stories that highlighted the transformative potential of Data Cloud, and another on the advantages of unified profiles versus golden records. Throughout the event, the team both educated others and gained valuable insights.

Here’s what Ryan said after returning from the Windy City.


 

Data Cloud is Central to Everything

Representing Prolocity at Salesforce Connections this year was truly an honor. My last visit, a few years ago, found me as a newcomer to the Salesforce ecosystem, navigating the fundamentals in an in-house role. Since then, my network within the Salesforce ecosystem has grown exponentially, and it was great to spend time with so many people that I’d previously only seen on the other side of a Google Meet.

My biggest takeaway from the two-day event was that having a strong Data Cloud strategy is more important than ever.

Connections was full of exciting announcements about AI and Personalization.  Salesforce announced two new exciting AI features, Einstein Copilot for Marketing and Merchants, both of which are powered by Data Cloud.  There was a huge emphasis placed on Marketing Cloud Growth, built on Data Cloud, with several demos and round-table sessions focused on how to get started on the tool.  

Salesforce also announced “Einstein Personalization”, which is the beginning of moving Marketing Cloud Personalization (formerly known as Interaction Studio) features to the Data Cloud platform.

If you haven’t noticed, Data Cloud is at the center of everything Salesforce is doing right now.

Salesforce is Listening: The Rise of Data Cloud Connectors

Having implemented Data Cloud for various clients, from globally recognized retail brands to nonprofit organizations to large pharmaceutical companies, I’ve experienced firsthand the challenges posed by the lack of native connectors to non-Salesforce systems.

The good news? Salesforce is addressing this pain point. At Connections, Salesforce announced over 200 new native connectors. 

Prioritize Data Strategy Over Implementation

With 200+ new connectors, and extremely powerful Data Cloud functionality available with a few mouse clicks, it’s very easy to bring in large amounts of data from all over your organization.  However, by doing so, you introduce some potential risks to your Salesforce implementation.  It’s important to take a very focused “use case first” approach to your implementation to help mitigate these risks.

  1. Long Implementation Timeline - Data Cloud is the shiny new sports car, and all of the marketing material talks about unifying data from all of your data sources.  It’s really tempting to try to bring in data from every single system, and implement all of the Data Cloud features, you end up spending a lot of unnecessary time and energy building to an architecture, instead of building to valuable use cases.
  2. Data Quality - Salesforce’s AI features are only as good as the data powering them.  If you introduce a large volume of irrelevant data, how good do you think your Einstein Copilot will be?  Even worse, imagine the results if you introduce bad data.
  3. Credit Consumption Billing Model - With this model, you only pay for the features and volume of data that you use.  This gives organizations the ability to start with a very small, focused implementation and scale their usage up as they see opportunities for additional value.  On the other hand, this model can be confusing, and if you aren’t careful, it’s very possible to implement a solution that consumes more credits than expected. There is no indicator in Data Cloud of how many credits you’ve consumed, so it’s important that you have a strong understanding of the model, or partner with someone who does.

Getting Started with Data Cloud

The first step to getting started with Data Cloud is to build a strong Data Strategy.  This involves understanding all of your data, where it lives, and what questions it can answer.  In addition, you need to define and prioritize your organization’s use cases to understand what use cases are most valuable to you.  These two artifacts (your catalog of source data and prioritized use cases) serve as the first two building blocks for a strong Data Strategy.

At Prolocity, we've guided numerous clients through these initial steps and beyond in their Data Cloud implementations. We’re here to help you define your Data Strategy and kickstart your Data Cloud journey. Contact us to get started!

About The Author: Ryan Hernalsteen
Salesforce Consultant

With a wealth of experience in the Salesforce ecosystem, Ryan seamlessly transitioned from a client to a consultant over the years. Specializing in Marketing Cloud and Data Cloud, he continues to sharpen his focus on these domains at Prolocity. Beyond his technical prowess, Ryan's passion lies in empowering individuals to navigate and solve complex problems.

Data Cloud & Strategy Questions? We’re here to help.

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