ML Applications In Retail

Optimizing AOV & Inventory Management

Originally Aired: September 29th, 2020

Is machine learning (ML) part of your retail business strategy? If it isn't, it should be. Machine learning is a critical component​ when optimizing average order value (AOV), ​​improving inventory management, ​​reducing ​waste, and more accurately detecting fraud.

However, you need to be deliberate in your ML implementation. When ML is done poorly, it’s worse than doing nothing at all.

Join our webinar with Chief Architect, Phil Horwitz, and Senior Vice President of Delivery, Joe Rose, ​where they will share real world examples of ML and how technologies like the AWS ML stack can be implemented to achieve specific goals ​within the customer journey. Walk away with an understanding of where to apply ML, where to use real people and what makes the ​largest impact.

Our experts will cover the top five do’s and don’ts in each of the areas below when implementing ML into your overall digital transformation strategy:

  • Product recommendations and market basket analysis
  • Demand planning and inventory logistics
  • Buyer segmentation (loyalty programs, membership)
  • Fraud detection and prevention​

If you can't attend live, register anyway and we'll send you the recording.

Originally Aired: September 29th, 2020

Joe Rose
Speaker: Joe Rose
Senior Vice President of Delivery
Joe joined JBS in 2012 as a developer and was elevated to SR Vice President of Delivery. With over 11 years experience in project delivery in Retail, Ecommerce and Multimedia web applications, Joe’s focus is on making projects delivered on-time, on-budget and with technical excellence. Joe holds Bachelors and Masters degrees in Computer Science from Georgia Southern University.
Philip Horwitz
Speaker: Philip Horwitz
Chief Architect
Phil joined JBS in 2009 as a software architect. Over time, Phil has founded JBS’s Open Source Practice and its Architecture Group; he is now JBS’s Chief Architect. An industry veteran with over 20 years of experience, Phil has designed and developed systems in a variety of areas – defense, healthcare, retail, scientific, finance, and insurance industries to name just a few. He holds both a BS in Computer Science and a BS in Mathematics from the University of Pennsylvania and lives in Philadelphia, PA.