DiscoveryData & Salesforce Hierarchy: Resolving FinTech MRR Reporting Gaps
High-volume data enrichment corrupted account hierarchies for a $50M+ FinTech SaaS provider.
We engineered custom Salesforce revenue objects and DiscoveryData validation rules. They map MRR/ARR automatically to a multi-tiered broker-dealer hierarchy, which eliminated manual deduplication for the finance team.
Executive Summary
Context
A $50M+ Enterprise FinTech SaaS provider manages this data. Broker-dealers and financial advisors are the focus.
What We Built
A custom Salesforce data architecture automates revenue object creation. It runs DiscoveryData deduplication logic and maintains a multi-tiered account hierarchy.
Tech Stack
- Salesforce (SFDC), DiscoveryData, Custom MRR/ARR Objects, Validation Rule Logic.
Not a fit when the CRM only tracks simple, one-to-one sales cycles or when third-party data enrichment is not a primary lead source.
The Challenge
High-volume data enrichment from DiscoveryData flooded the CRM with thousands of orphan records. These ignored the established broker-dealer hierarchy. Sales reps lost hours manually deduplicating leads. The finance team had to export CRM data into external spreadsheets just to calculate monthly recurring revenue. The system relied on the native Opportunity object to track both one-time fees and recurring licenses. That left no programmatic way to isolate ARR for multi-year contracts. Any new CSV import threatened to overwrite custom fields that reps had manually corrected. That created a cycle of data decay. Executive reporting became unreliable as a result.
Our Approach
We chose a structural overhaul of the Salesforce data model. A simple data cleanse would not have been enough. We decided to treat DiscoveryData as a staging source rather than a direct-to-account feed. We implemented custom validation rules to enforce data integrity during the import process. To solve the reporting gap, we built custom objects for MRR and ARR. We linked them directly to the Account hierarchy. That allowed automated roll-up summaries. Revenue from individual advisor offices (child accounts) now attributes correctly to the primary broker-dealer (parent account), without manual intervention.
Impact
Automated Revenue Attribution
Manual MRR/ARR calculations went away. Automated roll-up summaries across complex account hierarchies replaced them, giving real-time visibility into total contract value at the parent account level.
100% Field-Mapping Accuracy on Imports
Strict validation logic for DiscoveryData imports cut record bloat. It stopped duplicate accounts from forming and gave 100% field-mapping accuracy for new leads.
Operational Reporting Speed
The monthly revenue reporting cycle got shorter for the finance team. Spreadsheet-based calculations gave way to native Salesforce revenue objects.
We engineered a parent-child-grandchild account structure. It reflects the reality of the broker-dealer landscape. That architecture ties marketing attribution and sales activity to the right enterprise entity, while it keeps individual advisor records intact.
We developed a custom import utility. It also built a validation rule set, specifically for DiscoveryData CSVs. Both include fuzzy match logic on account names and strict enforcement of unique identifiers, stopping duplicate creation before it hits the production environment.
A data flow architecture mapping DiscoveryData imports into a Salesforce CRM configured for enterprise FinTech. It establishes a staging validation gate for record reconciliation to resolve deduplication failures against complex broker-dealer hierarchies. Custom MRR/ARR objects enable automated revenue roll-up from child advisor offices to national parent entities.
FAQ
Native Revenue Cloud was too heavy for where the client's team stood operationally. We opted for a lightweight custom-object approach instead. It gave the reporting granularity needed, without the high licensing cost and implementation complexity of a full CPQ deployment.
