Customer Data Integration Grid for E-Commerce
Client Partner: TrendStyles Retail · Build Timeline: 4 Months
Project Tech Stack
Allocated Engineering Pod
- Data Engineerx2
- Analytics Leadx1
"We now target campaigns based on live, consolidated client profiles."
Sarah Jenkins
Director of Marketing
1. Context & Business Goal
The Core Challenge: TrendStyles marketing campaigns had low returns because metrics were split across disjointed platforms.
The Agreed Objective: Consolidate customer store logs, email metrics, and ad logs into a central warehouse.
2. Technical Research & Discovery
Mapped sales metrics formats to structure custom database views. Prior to writing any code, our team compiled reference data frameworks and mapped API endpoints to identify speed limits.
3. System Architecture Design
Layout Scheme: Executive summary dashboards showing customer lifetime values and purchase patterns.
Database Infrastructure Setup: Google BigQuery database fed by Python ETL scripts, transforming records via dbt.
4. Production Implementation Lifecycle
Data Sync Configurations
Established Airbyte connections to fetch ad and email analytics logs.
dbt Modeling Phase
Programmed dbt query layers to assemble complete customer records.
5. Validated Business Outcomes
- ✓Created unified profiles for over 4.2 million active customer emails.
- ✓Increased return rates of marketing emails by 28%.