A leading Canadian fintech company, known for disrupting traditional wealth management with its digital-first, consumer-focused approach, had outgrown its initial Salesforce deployment. With a rapidly expanding client base and surging transaction volume, the company’s growth outpaced the architecture originally put in place to support it.
Salesforce Sales Cloud played a central role in their go-to-market operations, supporting acquisition, customer visibility, and growth. But the platform was being stretched beyond its intended purpose: absorbing high-volume financial data, not for workflow automation, but for visibility.
As usage scaled and demands increased, Salesforce performance degraded under the weight of non-operational data. Page load times slowed. Row lock errors emerged. Data became inconsistent and, critically, user trust eventually started to erode.
The moment called for a shift: from nightly syncs and heavy storage to lightweight visibility. And it had to happen without waiting for the company’s long-term data warehouse strategy to catch up.
The Problem: Where Things Started to Break Down
Salesforce had become overloaded, not just with users, but with data it was never architected to handle.
The company’s GTM team relied on Salesforce Sales Cloud to track customer relationships and growth metrics. But over time, millions of high-frequency financial transactions (especially auto-closed records tied to promotional campaigns) were written into Salesforce as core data objects. Over time, this resulted in storage overages of nearly 180%, significant cost exposure, and performance degradation across the platform.
A nightly reverse ETL pipeline (powered by a third-party platform) pushed large datasets into Salesforce, intended to keep customer records current. But the sync strategy had several architectural flaws:
- Heavy write operations led to row lock errors and data contention
- Sync failures occurred silently, creating inconsistent or partial data visibility
- Performance issues emerged at both the UI and reporting layers
- Most critically, the data being loaded was informational, not operational, but still incurred platform costs and complexity
Salesforce was being used as a reporting layer for financial data, but that data already had a system of record elsewhere. And while visibility was a legitimate need, the method of delivery was eroding the system’s reliability, bloating cost, and putting platform stability at risk.
Even more concerning was that confidence in Salesforce as a trustworthy platform was weakening. Teams began second-guessing reports, waiting on slow-loading pages, and questioning whether the data they were seeing was up to date.
What the Business Needed: Visibility Was the Goal, Not Data Volume
As teams tried to keep up with the growing volume of financial transactions, it became clear that Salesforce was being asked to do too much. What the business needed wasn’t more data inside Salesforce. It needed better access to the right data, at the right time, without compromising system performance or scalability.
Sales and growth teams weren’t asking for persistent storage of every financial transaction. They needed visibility into key customer financial signals (i.e. deposit activity, transfer history, and promotional triggers) that would allow them to prioritize outreach, personalize messaging, and make revenue-driving decisions in context.
From a systems architecture perspective, success meant:
- Eliminating the need for Salesforce to act as a financial data warehouse
- Reducing storage usage and unnecessary writes to core objects
- Minimizing platform risk caused by nightly batch syncs
- Preserving Salesforce’s role as a customer engagement system, not a backend data store
The challenge wasn’t just technical; it was architectural. Salesforce needed to remain fast, reliable, and usable by frontline teams. That meant rethinking how data was delivered, not just where it lived. Shifting the focus to visibility rather than volume opened the door to a solution that was simpler, safer, and more effective for the teams who relied on it.
Learnings Along the Way: What Changed the Direction of Solutioning
The original solution design was solid on paper:
- Build a dedicated Snowflake environment for the Salesforce team
- Use Salesforce Data 360 (formerly Data Cloud) as the long-term access layer
- Avoid direct object writes by unifying data from multiple systems
But in execution, the plan hit friction.
The client’s broader migration from Redshift to Snowflake was still underway, and data engineering resources were tied up with foundational infrastructure work. Productionizing a Data 360 architecture would take months. Meanwhile, Salesforce performance continued to degrade, and user trust was eroding faster than it could be rebuilt.
That’s when the insight clicked: The goal wasn’t unification or replication. It was visibility.
Persisting transactional data in Salesforce wasn’t just unnecessary; it was actively introducing risk. The reverse ETL model, optimized for marketing data enrichment, wasn’t fit for high-volume, high-frequency financial activity.
Worse, the nightly batch loads obscured failure points. Sync errors weren’t always caught in real time, so users couldn’t tell if the data they were seeing was complete, current or trustworthy.
What changed the trajectory of the project was a shift in mindset: Instead of thinking about data movement, think about data access. That shift unlocked a simpler, safer, faster way forward.
The Solution: A Better Way Forward
To meet the business need without compromising platform health, Lane Four implemented a lean, on-demand data access model, eliminating the need to persist large financial datasets in Salesforce entirely.
Key Architectural Decisions:
- Zero-copy integration between Snowflake and Salesforce
- Instead of syncing millions of records, Lane Four enabled live data access directly from Snowflake, the system of record.
- This preserved source integrity and eliminated storage bloat in Salesforce.
- Custom Lightning Web Component (LWC) on the Account object
- Lane Four built a modular, performant LWC that surfaces financial transfer data in real time, rendered natively inside the Salesforce UI.
- Users could access contextual data within the flow of work without triggering syncs or additional storage.
- No reliance on nightly batch processing
- Abandoning the brittle reverse ETL model, the solution delivered on-demand visibility with no risk of row locks, sync failures, or deployment lag.
This architecture gave Salesforce users exactly what they needed:
- Customer insights
- System reliability
- Zero performance compromise
And it did so without requiring additional platform licenses, middleware, or database duplication. The solution was both strategically aligned, technically lean, and purpose-built to respect Salesforce’s strengths as a CRM, while offloading what its core platform was never meant to handle.
The Impact: What Changed for the Business
The shift to a UI-level data access model delivered immediate and measurable results without the need for long implementation cycles or costly replatforming. The key outcomes included:
- Storage overages eliminated: By removing millions of transactional records from core objects, Salesforce storage was stabilized, avoiding significant overage fees and the operational complexity of archive strategies.
- Row lock errors and batch failures removed: With reverse ETL eliminated, the platform no longer experienced contention from high-volume writes. System reliability returned.
- Salesforce performance preserved at scale: UI responsiveness and reporting improved. Teams no longer experienced delays or questioned data integrity.
- User trust restored: Sales and growth users regained confidence in the system. For the first time, they could view relevant financial activity without waiting for overnight syncs or questioning stale records.
- Future-proofed architecture: The solution delivered value independently of upstream Snowflake delays. And when Data 360 becomes viable, the access layer can evolve without rearchitecting the Salesforce side.
This was a strategic resolution to a technical bottleneck, executed in a way that aligned with both current constraints and future platform goals.
Stability, Confidence, and a Platform the Team Could Trust Again
When Salesforce performance starts to degrade, it’s rarely sudden, and never obvious at first. It happens gradually, almost invisibly, through a series of well-intentioned decisions: a sync job here, a visibility enhancement there, and the quiet assumption that more data must mean better insight.
But for data-rich businesses, especially in fintech and high-volume B2C environments, visibility doesn’t require persistence.
This case proves a critical point for every technical and operational leader: The most scalable Salesforce orgs aren’t the ones with the most data. They’re the ones with the most intentional architecture.
Rather than force-fitting Salesforce into the role of a financial data warehouse, Lane Four helped the business reframe the problem, shifting from data persistence to data access. By designing for visibility instead of volume, we restored platform performance and user trust. Modern data platforms like Data 360 are purpose-built to serve as access and insight layers, not storage layers, enabling scalable visibility without compromising CRM stability.
Looking to stabilize your platform or rethink your architecture before it becomes a bottleneck? Let’s chat.