Data Migration and Modernization
for a leading e-commerce
platform for health & wellness
50,000+
healthcare and wellness
products
12+ million
active customers across
the globe
180+ countries
supported with fulfilled
orders
Business Case
The client offering health and nutrition products globally realized that its legacy DB2 system could no longer support growing business demands. Data was scattered across several systems leading to following challenges in:
EPR
No unified view of products, SKUs, customers, or sales channels, limiting strategic insights
Marketing
Inability to measure campaign effectiveness and allocate spend efficiently, leading to poor conversions.
Pricing systems
Lack of real-time updates created a rigid, outdated pricing structure.
Inventory management
Frequent stockouts and ageing inventory due to missing expiry tracking.
15% reduction in
marketing spend
Via segmentation and high-propensity targeting with Marketlo™
20% improvement
in inventory
turnover
Predictive analytics reduced ageing and stockouts
50% fasterreporting andinsights generation
Snowflake + Power BI enabled near real-time data access
Our Solution
We adopted a phased, consultative approach to modernize the client’s data landscape:
Centralized Data Warehouse
Built a unified warehouse with integrated facts (orders, shipping) and dimensions (product, customer, region, channel) aligned to SKU and product hierarchies.
SQL to Snowflake Migration
Transitioned legacy SQL systems to Snowflake for scalable, cloud-native architecture.
Forecasting & Inventory Optimization
Deployed predictive models to reduce stockouts, manage SKU expiry, and drive efficient pricing strategies.
BI Modernization
Upgraded from Sisense to Power BI after evaluating performance and usability against Tableau.
Data Unification
Integrated siloed sources—ERP (Mozart), pricing systems, marketing data (Adobe, Google, Yahoo, Amplitude, Creteo), and Revionics—into a single source of truth.
Customer Intelligence with Marketlo™
Used Inferenz’s proprietary platform to segment and predict customer behavior (e.g., 80% aged 60+), enabling 0–100 centile-based targeting and optimized catalogue delivery.