A global B2B mobile marketing and advertising platform, connecting enterprise advertisers with app publishers at scale, had grown rapidly and was reaching the limits of its initial Salesforce setup. Campaign revenue data was expanding faster than the system could handle, and Finance relied on Salesforce not to automate workflows, but to gain visibility into performance and revenue attribution.
A custom object holding nearly six million records had grown to consume almost half of CRM storage. Month-end reconciliation required hours of manual exports, and the growing volume introduced both cost and performance risk. While Snowflake remained the system of record, Salesforce had become a secondary repository for reporting, carrying millions of non-operational records.
The moment called for a rethink: Finance needed full visibility into revenue without storing it in Salesforce. The organization required a solution that would reduce storage costs, preserve existing workflows, and create a foundation for scalable, future-ready reporting. And that solution involved utilizing Salesforce Data 360.
When Visibility Becomes a Costly Burden
At the center of the strain was a custom Campaign Revenue object inside Salesforce. It contained nearly six million records and consumed approximately 45 percent of total CRM storage.
Yet Salesforce was not the system of record for revenue; Snowflake already was. Revenue data was being replicated into CRM primarily for visibility. Finance relied on Salesforce reports and dashboards, and month-end reconciliation required exporting full datasets. Salesforce was not transforming or governing this data; it was simply storing it.
As record counts increased, storage costs escalated and performance risk grew. Manual exports into Google Sheets became standard practice for full reconciliation, constrained by Salesforce row limits. Meaningful revenue analysis required contextual joins to Campaign, Account, Opportunity, and User objects, reinforcing the belief that revenue needed to reside inside Salesforce to remain usable.
What began as a practical reporting workaround had evolved into a structurally expensive pattern. Salesforce had become a secondary warehouse, carrying millions of non-operational records to support a visibility requirement. The issue was not access to revenue data. It was where that data was being held, and at what cost.
Preserving Finance Workflows Without Compromise
The objective was not to replace Salesforce or redesign Finance workflows. But rather, it was to correct the data placement model without introducing operational friction.
Finance needed uninterrupted visibility into campaign revenue inside Salesforce. Dashboards, summaries, and reporting workflows were deeply embedded in month-end processes and could not be destabilized. At the same time, the team required full dataset access for reconciliation and financial analysis, without relying on manual exports or workaround spreadsheets.
Leadership also needed cost discipline. Nearly half of CRM storage was being consumed by non-operational revenue records. That growth trajectory was neither necessary nor sustainable.
Finally, the architecture needed to remain future-ready. As the company’s data strategy evolved, it would require flexibility for bidirectional data movement between Salesforce and Snowflake. Success was defined by a simple but demanding constraint: preserve the Salesforce experience Finance relied on while removing the structural storage burden beneath it.
The Default Approach That Couldn’t Scale
Initially, the path forward seemed clear. Campaign Revenue data would remain in Salesforce. Finance relied on Salesforce reports, and the existing structure needed to stay in place to avoid retraining users or disrupting established workflows.
From an operational standpoint, preserving the current model felt like the safest approach. However, maintaining this structure would continue driving significant storage consumption without delivering additional business value. The organization would retain familiarity, but the underlying storage challenge would remain unresolved.
Discovering the True Source of Truth
During discovery, the team identified the root of the Finance department’s reporting challenges. Millions of revenue records were stored in Salesforce primarily for visibility, not operational use. This created inefficiencies, high storage costs, and growing performance risk.
The investigation also revealed practical constraints that would shape the solution. Salesforce row-based reporting had a 50,000-row limit, which restricted access to full datasets. Future needs included the ability to synchronize changes from Finance back to the system of record. With these realities clarified, the team shifted the priority. The focus was no longer just reducing storage. The goal became creating a scalable, efficient architecture that preserved Finance’s reporting workflows.
Modernizing Reporting with Data 360
The team designed a modernized, cost-efficient finance reporting pipeline built on Data 360. Revenue data was accessed using Data 360 Zero Copy from Snowflake. This approach eliminated duplication, avoided consuming Salesforce storage, and provided efficient visibility for Finance.
Supporting CRM objects, including Customer Campaign, Account, Opportunity, and User, were ingested into Data 360. Relationships were established using Data Model Objects to provide meaningful revenue context.
Salesforce reports were built on Data 360 data for visualization, delivering the totals, aggregates, and summaries Finance required on a daily, weekly, and month-end basis.
To enable full dataset access, an automated download process was implemented. A Screen Flow triggered by the Finance team performed an HTTP callout to Snowflake. Snowflake processed the query and returned a CSV file directly to a Slack channel. This bypassed Salesforce’s 50,000-record export limitation and provided Finance with the complete dataset required for reconciliation.
The solution was delivered in close collaboration with the client’s data team and their Snowflake partner. The architecture was designed to be low credit, with attention to long-term Data 360 cost considerations. For example, user attributes such as Owner Name were generated in Snowflake rather than in Data 360 to reduce credit usage.
Faster, Cleaner, Cost-Efficient Finance Reporting
Before the solution, Finance spent significant time navigating a cumbersome system, manually exporting revenue data each month while Salesforce storage approached capacity.
After implementing the new architecture, 45 percent of Salesforce storage was reclaimed, allowing the Campaign Revenue object to be removed entirely. Finance workflows remained unchanged, but the effort required for monthly exports was dramatically reduced. Tasks that had previously taken hours now complete in minutes, freeing the team to focus on analysis rather than manual processes.
The architecture also supports future enhancements, including reverse syncing of edited campaign data back to Snowflake. This ensures Finance can continue using Salesforce for visibility while relying on Snowflake. The system transformed from a high-maintenance, storage-heavy setup to one that is efficient, scalable, and ready for evolving business needs.
The Right Data in the Right Place at the Right Cost
This project shows how organizations can modernize revenue reporting without overloading Salesforce. By moving revenue data to Data 360, Finance no longer relies on storing millions of records in the CRM, yet reporting remains fully accessible within Salesforce.
Zero-Copy ingestion and careful credit management made the solution efficient and sustainable. Working closely with the client’s data team also accelerated delivery and strengthened trust in the new architecture.
The result is a system that delivers the right data, in the right place, at the right cost. Finance teams can focus on insights rather than manual processes, and the architecture is positioned to support future enhancements, including reverse syncing to Snowflake.
For companies facing similar friction in revenue operations or reporting, this story demonstrates a clear principle: aligning architecture with the source of truth enables efficiency, reliability, and confidence in the data. If your team is navigating similar challenges, there is an opportunity to rethink how your data is structured and accessed to reduce costs, improve efficiency, and future-proof your systems. Let’s chat.