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 ended the manual deduplication reps had been doing.
Executive Summary
Context
A $50M+ Enterprise FinTech SaaS provider manages data for a network of broker-dealers and financial advisors.
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 that ignored the established broker-dealer hierarchy, and sales reps lost hours deduplicating them by hand. The finance team had to export CRM data into external spreadsheets just to calculate monthly recurring revenue. That's because the native Opportunity object tracked one-time fees and recurring licenses together, leaving no programmatic way to isolate ARR for multi-year contracts. Any new CSV import also threatened to overwrite custom fields that reps had corrected by hand, which set up a cycle of data decay that made executive reporting unreliable.
Our Approach
A simple data cleanse would not have been enough, so we chose a structural overhaul of the Salesforce data model. We began by treating DiscoveryData as a staging source rather than a direct-to-account feed, with custom validation rules enforcing data integrity during import. To close the reporting gap, we built custom objects for MRR and ARR and linked them directly to the Account hierarchy, which enabled automated roll-up summaries. Revenue from individual advisor offices, the child accounts, now attributes correctly to the primary broker-dealer parent account without manual intervention.
This engagement is part of our customization + optimization work for finance & insurance organisations.
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.
Duplicate Accounts Stopped at Import
Strict validation logic for DiscoveryData imports cut record bloat. It stopped duplicate accounts from forming and held new leads to the mapped fields.
Operational Reporting Speed
The monthly revenue reporting cycle got shorter for the finance team, as 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 and a validation rule set for DiscoveryData CSVs. Both include fuzzy match logic on account names and strict enforcement of unique identifiers, which stops duplicate creation before it reaches the production environment.
DiscoveryData enrichment flooded the CRM with orphan records that ignored the broker-dealer hierarchy. The Opportunity object also mixed one-time fees with recurring licenses, so finance exported data to spreadsheets. Now DiscoveryData lands in a staging source with custom validation rules, not directly on accounts. Custom MRR and ARR objects linked to the Account hierarchy roll revenue from child advisor offices up to the parent broker-dealer account.
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.
