# Unified Ecommerce Analytics

Unified legacy and modern ecommerce data into a single analytics layer to support pricing and performance decisions.

## Key Takeaways:

- **Visibility:** Improved first-time visibility by linking subscriber characteristics with viewership metrics like hours watched.

- **Operational Velocity:** Delivered reports in minutes, not days, allowing product leadership to independently explore engagement data.

- **System Alignment:** Successfully modeled and joined large-scale viewership data via optimized SQL pipelines.

### Centralized BI Pipeline Unifies Fragmented Data for Executive Intelligence

**Operating with fragmented data across disparate devices and platforms delays critical business reviews and compromises performance visibility.** A centralized analytics layer bridges the gap between raw data and evidence-based decision-making.

### Fragmented Data Constraining Decision-Making

A leading streaming platform struggled to extract actionable insights from highly granular data, making it difficult to analyze customer engagement across different devices. The one-size-fits-all approach to campaigns was underperforming due to a lack of detailed user behavior reporting.

### Cloud-Native Pipeline with Metric Normalization

Supported by our Centers of Excellence, we engineered an interactive dashboard integrated into the senior leadership's regular review process.

- **Technical Components:**  
  - **Ingestion Logic:** Processed large-scale viewership and subscription data into a centralized storage pipeline.  
  - **Transformation Layers:** Utilized **optimized SQL (CTEs)** for cleaning and modeling data to ensure accurate dynamic slicing by device and plan type.  
  - **Daily Updates:** Enabled the marketing team to continuously refine strategies based on daily automated data updates.

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