
Predictive Analytics for eCommerce
ClientShopMax Inc.ServiceAI / Data Analytics
PlatformWeb PlatformTechnologyPython • BigQuery • TensorFlow
Predictive Analytics Platform for eCommerce
The Challenge:
- No demand forecasting led to 40% overstock on seasonal items.
- Manual inventory reviews took 2+ days per category.
- Customer segmentation was too broad, lowering conversion rates.
- No attribution model to measure marketing channel ROI.
Solution:
- Built ML demand prediction models trained on 3 years of sales data.
- Automated inventory alerts triggered by real-time stock thresholds.
- Implemented behavioral clustering to power personalized campaigns.
- Developed a multi-touch attribution dashboard for marketing teams.
Features:
- Discovery: Data audit, KPI alignment & stakeholder workshops.
- Design: Intuitive analytics dashboards with drill-down views.
- Development: TensorFlow models served via BigQuery ML.
- Testing: Backtesting models on 24-month historical data.
Results:
- 35% increase in revenue from AI-driven product recommendations.
- 40% reduction in overstock through accurate demand forecasting.
- 3× improvement in email campaign conversion via segmentation.
- Real-time analytics dashboard processing 5M events per day.