THE ML MISSION
Immediate answers at the
scale of retail.
Scale of retail means insights exist across the enterprise. Example: Customer Churn risk exists...
In a product lines
In product genres
In stores, sites, apps, marketplaes
Across our retail brand
OUR IP
YOUR ARCHITECTURE
OpenML, deployed as part of your OpenCLOUD, has crossed the chasm between data science project to product.
We provide full training and dedicated collaboration time for your data science team
to not merely unlock our data science, but empower your ongoing efforts.
See: Get OPEN
PREBUILT ML FEATURES
Features feed Machine Learning. Through our data contextualization we've created an abundant, ever-expanding collection - all engineered for continuous, adaptive learning.
ADDITIONAL FEATURES
Your customers are more complex than simply transaction and engagement.
Open supports enhanced feature engineering including:
- Email Engagement
- Media Serving
(1st party Ad tracking)
- Appended Data
- Loyalty Program
DEPLOYMENT INCLUDES
- Predictive Models
(purchase propensity)
(churn risk)
- Neural Network
(Predicting Line level purchase)
(30/60/90 day future look)
(Custom date ranges)
- Statistical Models
(SKU/UPC next most likely product)
(Seasonal influenced SKU/UPC)
More...
