How Prexisio empowered a Health Tech Leader with Advanced Customer Insights Using Power BI

Background

A leading health tech software company expanded into consulting services, requiring advanced analytics to optimize revenue and track performance. Prexisio implemented a Power BI solution integrating NetSuite ERP data, enabling dynamic customer segmentation, real-time revenue insights, and interactive dashboards, enhancing decision-making and driving scalable growth.

Challenge

1. Undefined Customer Categories:
   The client lacked a structured framework for identifying key customer behaviors such as churn, returning customers, and cross-sell/upsell opportunities. Manual efforts to classify customers were inconsistent and unscalable.

2. Fragmented Revenue Insights:
   Revenue data from their NetSuite ERP system, precisely the "transaction," "transaction line," "items," and "entity" tables, were siloed. This hindered their ability to understand performance across consulting categories and customer segments.

3. Limited Visualization of Key Metrics:
   Key performance indicators (KPIs) such as Annual Recurring Revenue (ARR), churn rates, customer segments, upsell, and down-sell trends were not readily accessible in a centralized dashboard.

4. Disconnected Analysis Tools:
   Existing workflows relied on static Excel reports, so the client needed an interactive, real-time solution to support decision-making.

Solution

Prexisio worked closely with the client to design and implement a comprehensive solution in Microsoft Power BI. Our approach involved the following steps:

1. Customer Segmentation with Dynamic DAX Calculations

We defined detailed customer segments to understand customer behaviors better:

• Did Not Exist: Customers with no historical transactions.

• New Customers: Customers with revenue recorded for the first time.

• Existing Customers: Customers with consistent revenue.

• Churn: Customers who stopped generating revenue after a period of activity.

• Returning Customers: Customers who returned after a period of inactivity.

• Upsell/Cross-Sell: Customers purchasing higher-value services or additional consulting items.

• Downsell: Customers purchasing lower-value services compared to prior transactions.

We calculated these segments dynamically using advanced DAX formulas, aligning them with the client's business objectives and data structure.

2. Integrated Data Model

We built a robust data model by extracting and transforming data from NetSuite ERP. This included:

• "Entity" data for customer details.

• "Transaction Line" and "Transaction" data for revenue.

• "Items" data to categorize consulting services.

• "Accounting Periods" to calculate ARR and analyze revenue trends.

3. Interactive Dashboards

Prexisio created Power BI dashboards that included:

• Revenue by Consulting Category: Visualized performance for strategy, implementation, and training services.

• ARR Trends: Showed annual revenue growth and retention rates.

• Customer Base Analysis: Displayed the size and composition of customer categories (e.g., new, churn, returning).

• Cross-Sell/Upsell Analysis: Highlighted customers purchasing multiple services or upgrading their spending.

• Downsell Detection: Identified customers with declining revenue to support targeted engagement strategies.

4. User-friendly filtering and Drilldowns

Interactive features allowed stakeholders to:

• Filter revenue and customer data by service type, region, or period.

• Drill down to individual customer transaction histories.

• Compare monthly, quarterly, and annual trends.

Results

1. Enhanced Customer Insights:

   • Churn Identification: Early detection of churn allowed proactive re-engagement strategies, improving customer retention.

   • Upsell and Cross-Sell Opportunities: The client uncovered untapped potential within their customer base, boosting consulting revenue.

2. Improved Revenue Visibility:

   • Real-time dashboards provided actionable insights into consulting revenue, ARR growth, and service-specific performance.

3. Streamlined Decision-Making:

   • The Power BI solution enabled the CaaS Finance Manager to make data-driven decisions, improving the allocation of sales and marketing resources.

4. Scalability:

The integrated data model and interactive dashboards scaled seamlessly with the growing consulting business, ensuring long-term value.