Global Health & Wellness Company – Building a Global Analytics Platform for Sales, Customer, Network, and Supply Chain Intelligence

Introduction

A global health and wellness company operating in a multi-level marketing model needed a modern analytics foundation to understand its sales performance, partner network, customer behavior, and supply chain demand across dozens of international markets. With data coming from multiple e-commerce stores, legacy systems, and internal operational platforms, the organization sought a unified data warehouse that could support leadership, field teams, supply chain planners, and marketing.

‍

The Problem (Gut-Based Decisions)

Before the engagement, data was fragmented and inconsistent across many systems:

• 10+ global Shopify stores generated high-volume order, customer, and subscription data.
• Legacy systems held historical sales, customer, and operational information.
• A central integration layer produced its own event-level data.
• Marketing platforms collected campaign, engagement, and attribution details.
• A standalone commissioning system tracked partner and downline performance.

Because these systems were disconnected:

• Sales performance was difficult to view holistically across markets.
• Field leadership lacked visibility into downline activity and network health.
• Customer segmentation was shallow and inconsistent.
• Supply chain teams had limited insight into true demand or SKU-level movement.
• Reporting differed across regions due to inconsistent logic and manual work.

Critical decisions — from partner promotions to inventory planning — were made with incomplete information.

‍

‍

The Solution (How Data Changes the Game)

We delivered an enterprise-grade analytics ecosystem built for global scale and cross-functional insight.

1. Snowflake Enterprise Data Warehouse

• Unified all data sources into a clean, scalable warehouse.
• Created a global data model representing customers, partners, orders, commissions, and inventory.
• Enabled consistent KPIs regardless of geography.

2. Modern Data Ingestion Using Fivetran

Automated ELT pipelines were used to ingest data from:

• All Shopify stores across multiple currencies and regions
• Legacy systems (finance, customer, product, commissions)
• The integration platform producing operational event data
• Marketing and campaign systems
• The commissioning system tracking partner network performance

Fivetran ensured reliability, low maintenance, and continuous data flow.

3. Power BI Reporting Layer

Built dashboards to support every major function:

• Sales & Revenue Analytics
  
  • Market-level trends
  • Subscription growth and retention
  • SKU-level performance
• Partner Network & MLM Structure
  
  • Downline activity
  • Network health metrics
  • Title progression and performance
• Customer Analytics
  
  • Segmentation
  • Cohorts
  • Lifetime value
  • Retention and churn indicators
• Supply Chain & Demand Planning
  
  • Demand trends
  • Inventory levels
  • SKU movement and forecasting inputs
• Executive Dashboards
  
  • Cross-market KPIs
  • Financial and operational performance indicators

4. Enterprise Reporting & Governance

• Established standard metric definitions across markets.
• Reduced manual reporting and spreadsheet dependency.
• Ensured secure, role-based access for global teams.

‍

Real-World Example (Specific Client Outcomes)

After the implementation, the organization achieved:

• A single source of truth for all e-commerce, partner, and operational data.
• Deep visibility into partner network activity and global downline performance.
• Consistent sales tracking across all international Shopify stores.
• Improved customer segmentation supporting marketing and retention programs.
• Reliable demand signals for supply chain and inventory planning.
• Strong cross-department alignment thanks to shared KPIs and dashboards.
• Significant reduction in manual reporting effort across regions.

The platform quickly became the backbone of the company’s decision-making ecosystem.

‍

Conclusion

By integrating e-commerce, marketing, operations, commissions, and legacy system data into Snowflake — automated through Fivetran and visualized in Power BI — the organization transformed how it understood its global business. Leaders, partners, and operational teams gained real-time visibility into sales, network health, demand, and customer behavior. What once required fragmented spreadsheets and manual reporting became a unified, scalable intelligence platform supporting growth across dozens of international markets.