Retail Analytics Consolidation Case Study | Lina Lula

Unifying Fragmented Multi-Channel Data for Executive Clarity

Client Type: Retail / E-commerce

Platforms: Shopify, Amazon, Custom POS

Services: Data Warehousing, BI Automation

The Challenge

A high-growth retail brand was struggling with significant data silos. Sales and customer data lived in separate ecosystems across Shopify, Amazon, and physical POS systems. This fragmentation led to conflicting performance reports, manual data entry errors, and a total lack of executive visibility into cross-platform customer behavior.

The Solution

Lina Lula implemented a three-stage analytics overhaul to centralize intelligence:

Centralized Data Warehouse: Built a robust BigQuery infrastructure to pull and clean data from all sources via automated pipelines.
Unified Identity Mapping: Used deterministic matching logic to merge customer records across platforms, enabling true Lifetime Value (LTV) tracking.
Automated Executive Dashboards: Developed Looker Studio dashboards that updated hourly, tracking inventory levels vs. sales velocity in real-time.

The Outcome

The project transformed the brand’s reporting culture from reactive to proactive. By eliminating manual spreadsheets, the team gained a “single source of truth.”

15 Hours saved per week in manual reporting

Executive leadership now makes inventory and marketing allocation decisions based on live, unified data rather than weeks-old snapshots.