Overview
Industry
Software Development
Region
Uxbridge, Middlesex
Company Size
5,001-10,000 employees
Featured Solution
Salesforce Data Quality Analysis Framework
About Client
A global provider of smart insurance software, delivering a powerful platform. Founded in 1982, the company serves over 600 customers across 30+ countries. Its solutions use AI and automation to support property and casualty, workers’ compensation, and life insurance operations.
A CRM Built for Scale, Held Back by Data Gaps
Salesforce sits at the center of their operations, managing accounts, contacts, leads, opportunities, campaigns, activities, cases, and contracts across multiple teams. Over time, data completeness gaps began accumulating across these standard objects. Reports existed, but no single mechanism evaluated the overall data health. Teams pulled from multiple reports to piece together a picture of missing data. With no standardized baseline and no automated evaluation in place, maintaining consistent data quality across the organization became increasingly difficult.
The Business Cost of Unstructured Data
Incomplete data does not stay contained to the teams managing it. It surfaces in the forecasts leadership relies on, in the pipeline reviews that shape resource decisions, and in the customer records teams depend on during critical interactions.
How These Challenges Impacted Their Business:
Increased Manual Workload Across Teams
Without automated evaluation, teams had to investigate gaps manually to identify incomplete or missing records, adding avoidable operational overhead.
Forecasts Built on Incomplete Opportunity Data
Incomplete Opportunity data meant pipeline reports reflected what reps had entered, not what was real. Leadership was making resource and revenue decisions based on unvalidated numbers, increasing the margin for error in every forecast cycle.
Zero Owner Accountability
Without field-level visibility tied to individual records, owners had no way to identify gaps in what they managed, let alone act on them.
From Manual Audits to Automated Governance: How We Rebuilt Data Quality Into Salesforce
The goal was to make data quality something Salesforce managed automatically. Our Salesforce experts built a reusable Salesforce Data Quality Analysis Framework was implemented across all standard objects, bringing automated scoring, centralized visibility, and owner-level accountability into a single framework.
What We Delivered:
- Customizable Scoring Logic:
Data Quality Score logic is built using native Salesforce formulas, giving teams full control to define required fields, assign field weightage, and configure object-specific quality rules.
- Automated Record Evaluation:
Critical fields are defined for each object. Formula-based logic evaluates every record automatically against those completeness criteria, removing manual investigation from the process entirely.
- Data Quality Dashboards:
Prebuilt dashboards aggregate individual record scores into an organization-wide view of CRM data health, updated in real time. Leadership and operations teams can see overall data quality score trends, completeness by object, owner-level performance, and records missing critical information.
Building a High-Trust CRM Data Layer on Salesforce
Before the framework, data completeness was inconsistent, quality checks were manual, and accountability was unclear. With the Salesforce Data Quality Analysis Framework in place, data quality becomes systematic. Scoring is automated, record owners have clear visibility into gaps, and leadership gets a real-time, unified view of CRM health. And because the framework is built on native Salesforce formulas, it adapts as business requirements evolve without needing to be rebuilt.
Highlights
40%
Improvement in Data Completeness
30%
Reduction in Duplicate Records
20%
Improvement in Ownership Accountability
100%
Automated Record Scoring
Conclusion
For a business operating across 30+ countries, the integrity of CRM data determines how accurately revenue is forecasted, how confidently customers are managed, and how reliably Salesforce serves as the foundation for business decisions. That reliability is now built into the system, and it scales as the business does.
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