How to Automate Pricing with Machine Learning : Challenges and Learnings Jennifer Est / Salon, Data

Author: Salon, Data
Published: [Erscheinungsort nicht ermittelbar] : Data Science Salon, 2019.
Boston, MA : Safari
Edition: 1st edition.
Physical Description: 1 online resource (1 video file, approximately 22 min.)
Additional Creators: Safari, an O'Reilly Media Company

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Summary: Presented by Jennifer Esteche, Machine Learning Research Engineer at Tryolabs Determining prices for retail products manually is an extremely time-consuming process and leads to neither cost-effective nor consistent pricing. In this talk, we will introduce you to the tremendous potential of machine learning for automated pricing. We will share our learnings from building a machine learning system able to determine prices based on product metadata and images, implemented by a large online consignment marketplace. As a result, the company prices more than half of the products in their catalog automatically. You will learn what kind of data is valuable for an automated pricing system, what machine learning models can be used, some major challenges in building an intelligent pricing system and how to overcome them. Further, we will explore opportunities on how retailers can use machine learning for optimizing their prices for revenue.
Note: Online resource; Title from title screen (viewed September 10, 2019).

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