Project Overview
The client was facing growing technical debt in Salesforce due to inconsistent data hygiene, manual processes, and limited governance, leading to reduced data reliability and operational inefficiencies. Closeloop modernized the Salesforce data ecosystem by implementing automated cleansing, validation, and monitoring workflows integrated with Cloudingo. The solution improved data accuracy by 90%, reduced duplicate records by 80%, cut manual data maintenance effort by 70%, and established a scalable framework for long-term data integrity.
Business Challenges
- High volume of incomplete, inconsistent, and duplicate data across Salesforce objects
- Manual data cleanup consuming significant time for Sales and Support teams
- Inaccurate and mismatched KPIs leading to unreliable leadership reporting
- Disconnected GTM systems operating in silos with inconsistent data structures
- Legacy Apex code and workflows creating technical debt and operational risk
Solution
- Automated identification and merging of duplicate records using Cloudingo
- Standardized data formats, corrected record relationships, and removed invalid entries
- Implemented approval-based deletion workflows to ensure audit readiness
- Repaired sync logic and validated all incoming data from connected platforms
- Refactored legacy Apex, Flows, and Workflows to reduce technical debt
- Eliminated redundant logic and replaced outdated automations with best-practice solutions
Approach
- Audited existing Salesforce data, workflows, and hygiene practices to identify duplication, inconsistencies, and technical debt.
- Defined data quality rules, validation logic, and governance gaps aligned with business-critical Salesforce objects.
- Implemented Cloudingo-driven automation for deduplication, normalization, and ongoing data cleanup.
- Established standardized processes and controls to prevent future data degradation.
- Enabled continuous monitoring, reporting, and fine-tuning to sustain high data quality at scale.
Technology Stack
