A 51 cent deposit is a signal. We helped Valley National Bank act on it

Valley National Bank already owned two strong systems, Financial Services Cloud and Snowflake, but they had never been integrated in a way to seamlessly feed leads through a logic and rules framework, and the gap was more than technical. Pulling any signal out of Snowflake meant writing code or custom queries against the warehouse directly, and bankers were never Snowflake users. So even real analytical work, churn risk scoring, retention modeling, sat unusable: the insight existed, but there was no foundation in place to scale from a data scientist's query to a banker's day.

A $0.51 micro-deposit likely signaling a new fintech relationship, or a $100,000 inflow representing a same-day wealth conversation, both sat in the warehouse doing nothing.

Reactive, by default:

• Data trapped in Snowflake. Insight like churn risk scores and retention models existed but had no way to reach a banker.
• Financial Services Cloud and Snowflake, never integrated to feed leads through a logic and rules framework.
• No foundation in place to scale from a data scientist's query to a banker's day.

Rather than replicating Valley's data into Salesforce, the conventional and costly fix, Zennify built Salesforce Data 360 as a zero-copy bridge. It reads directly from Snowflake, scores every signal in real time, and routes a scored task straight into the banker's existing Financial Services Cloud workflow. Bankers don't have to learn a new tool. The scored lead and the next best action show up inside the system they already live in.

The mechanism behind it: 

• Signal: Raw account activity streams out of Snowflake, the kind that used to sit unused, like a $0.51 micro-deposit or a $100,000 inflow.
• Decision: Data 360 scores that signal in real time and decides what it means and how urgently it should be acted on.
• Action: A scored task routes straight into the banker's existing Financial Services Cloud workflow, no new tool required.

The entire CRM team now controls which signals matter and which leads bankers see. The logic can evolve without a data request ticket. A banker's day changes shape entirely the most pressing leads are already surfaced in front of them, in the platform they already use.

What this means: 

• Signals become scored tasks. Every trigger is scored and routed straight into the banker's day.
• The CRM team owns the logic. It can evolve without a data request ticket to a Snowflake engineer.
• A zero-copy foundation. Built to carry new signals and use cases without duplicating data again.

Ten distinct use cases now run in production off a single, real-time foundation, from micro-deposit signals to wealth-conversation triggers. The team went from kickoff to go-live in five months, delivering on time. And because the architecture reads Snowflake data in place rather than copying it into Salesforce, Valley cut data movement costs by 96% compared to a traditional replication approach, all while keeping a single source of truth in Snowflake.