Building a Real-Time Analytics Platform for a D2C E-Commerce Brand
Client: Direct-to-Consumer E-Commerce Company
The Challenge
The client's analytics relied on nightly CSV exports piped into spreadsheets. Marketing couldn't measure campaign performance until the next day. Inventory decisions were based on gut feel. Customer segmentation was manual and updated quarterly. The business had outgrown its data infrastructure, and the lack of real-time visibility was costing them revenue.
Our Solution
We designed and built a modern data platform over a 16-week engagement. We implemented Kafka for real-time event streaming from their Shopify storefront and fulfillment systems, landed data in Snowflake via a Kafka Connect sink, built a dbt transformation layer with 200+ tested models, and created Looker dashboards for marketing, operations, and executive teams. We also built a customer segmentation pipeline that updates hourly, feeding their email marketing platform with fresh cohorts.
Results
- Real-time visibility into sales, inventory, and marketing performance
- 22% improvement in marketing ROI through faster campaign optimization
- Inventory stockout rate reduced by 35%
- Data team went from 0 to self-sufficient with dbt and Looker
- Pipeline processes 2M+ events daily with 99.9% reliability
Technologies Used
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