Organizational Analytics Case Study for Non-Profit Engagement

Customer Background

A network of small and mid-sized non-profit organizations operating nationwide needed a unified and consistent way to measure financial health, giving trends, attendance patterns, and donor engagement. Each organization used different management and accounting systems, resulting in fragmented reporting and limited cross-organization insight.

Objective

The objective was to build a scalable cloud-based business intelligence platform capable of integrating diverse non-profit data sources-including QuickBooks, SQL Server, and non-profit management systems-into a standardized enterprise data model. The platform would enable leaders to monitor trends, benchmark performance across organizations, and drive improved donor engagement and attendance consistency.

Approach

• Data Integration - Connected QuickBooks, membership databases, and legacy non-profit systems using secure API integrations and Azure Data Factory pipelines.
• Standardized Data Model - Unified attendance, giving, donor segmentation, and retention metrics into a cross-organizational schema.
• KPI Framework - Defined consistent measures for weekly attendance, giving growth, donor tiering, digital giving ratios, and year-over-year comparisons.
• Interactive Dashboards - Built Power BI dashboards supporting forecasting, cohort analysis, and multi-organization benchmarking.
• Multi-Phase Expansion - Two-year iterative delivery including new datasets, automation improvements, and additional KPI categories.

Outcomes

• Single source of truth for giving, attendance, and engagement data across multiple non-profits.
• Enhanced donor insight with tier segmentation and multi-year contribution trends.
• Improved decision-making through standardized KPIs and real-time visibility.
• Operational efficiency by eliminating manual QuickBooks and attendance reporting.
• Scalable onboarding allowing new non-profits to join the platform with minimal setup.

Related Services:

• Business Data Intelligence - Cross-organizational KPI standardization and reporting modernization.
• Data Engineering Services - API integrations, Azure pipelines, and scalable semantic modeling.