On Thursday, May 22, 2025, our CTO, Angelica Buffa, had the opportunity to present a workshop at the Datablazer Mastery Onsite event in New York City. She shared her proven approach to scoping and launching successful Data Cloud pilots.
Her key message?
Start with a business problem, and not the platform.
When it comes to Salesforce Data Cloud, it can be tough for companies to figure out where to start. The platform offers powerful tools for real-time data unification and customer personalization. But it’s easy to get lost without a clear use case.
Let’s walk through some of Angelica’s advice for pinning down the right use case for your Data Cloud implementation.
Start with the customer journey
Before evaluating your data sources or thinking about objects and connectors, take a step back and look at your customer experience.
It’s helpful to think through the full lifecycle, starting by considering how your customers discover your brand in the first place. You want to understand what encourages them to engage with you, what helps or prevents them from converting, whether they’re actually using what they’ve bought, and whether they continue to come back for more.
By identifying pain points along the journey, you can do a better job of prioritizing where unified data and real-time insights could have the most impact. For example:
- If marketing is struggling to target the right audience, you could explore real-time audience segmentation.
- If sales lacks context during outreach, you could use Data Cloud to surface cross-channel engagement history.
- If retention is an issue, you could automate personalized outreach after key product milestones.
This kind of thinking will have you making proper use of Data Cloud to solve real problems.
Get a clear understand of the data landscape
Many companies face the challenge of having their data scattered across multiple systems that don’t provide a complete picture of the customer.
Your data is likely coming from a mix of CRM systems, marketing automation tools, e-commerce or transactional systems, customer support platforms, and unstructured sources like email or chat logs. It’s key to identify which sources hold the most valuable and actionable customer data. Then, Data Cloud can help you bring that information together, so you can actually use it in Salesforce for automation, AI, or better insights.
Keep in mind, this only works if your scope is realistic and well planned.
Be sure to scope a strong MVP
If you’ve identified a promising use case, the next step is to define a focused MVP (Minimum Viable Product).
Here’s how Angelica recommends doing that:
1. Start with relevant data sources
You don’t need to connect everything right away. Instead, you can start with a few key systems that hold the data most relevant to your chosen use case. CRM and marketing platforms are often good starting points. Having at least two sources is important so that Data Cloud’s unification engine can actually match records across systems.
2. Choose key data objects
It’s important to select objects that will help you solve your initial problem. These objects typically fall into the categories of customer profile data (e.g. Contacts, Accounts) and transactional or behavioral data (e.g. Orders, Cases, Campaign activity).
Remember, it’s better to resist the urge to bring in everything at once. You’ll move faster and get clearer results.
3. Be strategic about fields
Successful identity resolution depends on choosing the right fields for unification.
Rather than trying to unify based on generic attributes like state, industry, or job title, Angelica encourages looking for unique email addresses, mobile phone numbers, customer IDs, and URLs.
You’ll also want to make sure your fields are well populated, consistent, and clean. Tools like Cuneiform can help you assess this before you go too far.
Avoid common mistakes
When scoping your MVP, it’s crucial to avoid common mistakes like trying to ingest too many systems or objects at once. It’s better to avoid using low-quality or incomplete identity fields. It’s best not to pull data from legacy systems that are being phased out, and stay away from building use cases that don’t connect to a clear business goal.
Remember, the goal is to show value quickly and build a foundation you can scale over time.
Use this quick readiness checklist:
If you’re still not sure your organization is ready for Data Cloud, you might consider the following quick and important questions:
- Do you have customer data living in multiple systems?
- Are you able to identify the same customer across those systems using shared identifiers?
- Would real-time insights or personalization improve your marketing, sales, or service outcomes?
If you answered yes to all three, you're likely ready to begin exploring a Data Cloud use case.
Summary
It’s not necessary to have a perfect data strategy to get started with Salesforce Data Cloud, but it’s wise to plan a smart, focused approach. By mapping your customer journey, identifying a clear problem to solve, and scoping your MVP carefully, you’ll be in a much better position to prove value quickly and build momentum for future phases.
At Modelit, we provide a free Data Cloud POC, which can help you get a quick start on your data journey. Reach out to us if you’re ready to chat with our certified experts and take the next step today.
