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...