From POC to Scale: Growing Data Cloud Value in 12 Months

Getting started with Data Cloud usually begins small. Most teams start with a proof of concept (POC) to test a single use case. That's useful, but the real benefits come when you take what works and scale it across the business. A 12-month roadmap helps you move from "experiment" to "business value."

Months 0–3: Prove Something Clear

A POC should focus on one specific problem, such as:

• Combining customer data from a few key systems
• Running a targeted campaign with unified profiles
• Testing identity resolution on a limited dataset

Keep it simple. The aim is to show value, not boil the ocean.

Months 4–6: Add More Connections

Once you've proven the concept, expand carefully. This stage often includes:

• Adding more data sources like CRM, commerce, or service data
• Activating insights across more than one channel
• Tracking clear metrics, such as engagement lift or cost savings

Stakeholders start seeing how the POC can grow.

Months 7–9: Build Trust

Scaling only works if people trust the data. In this stage, focus on:

• Governance rules for who can use which data
• Privacy and compliance guardrails
• Data quality checks to make sure results are reliable

This is where Data Cloud shifts from being "a marketing tool" to a company-wide asset.

Months 10–12: Widen the Impact

With governance in place, you can expand further:

• Use Data Cloud across sales, service, and marketing teams
• Apply advanced segmentation and predictions
• Build dashboards that tie results to business outcomes like pipeline or retention

By the one-year mark, the question isn't "Can this work?" but "Where else should we use it?"

The Result

Moving from POC to scale within 12 months takes discipline, but the reward is a platform that's trusted and adopted across the business. It's no longer just a proof of concept — it's a proof of value.