• Dynamic Talks: Tampa "Building an algorithmic price management system using ML"

    Come join us at the first event of our free technical meetup series, "Dynamic Talks", in Tampa! If you are interested in artificial intelligence, then you will enjoy this event, which will have technical talks, free food and drinks, and networking opportunities. The meetup will take place at the Datex Business Center in Clearwater, and will feature one technical talk. This talk will be given by Ilya Katsov, Head of Practice, Industrial AI at Grid Dynamics, and will be about price optimization methods for a number of use cases, how to apply these methods in practice, and how algorithmic price management components were fitted into pricing strategies. Note: There are 3 buildings, and the building where our event is held is in the very back with the largest blue roof that sits on the pond. The front door has a keypad, and the code will be emailed to attendees. After you enter, take the elevators to the 3rd floor -- there should be signage that directs you to the correct room. Agenda [6:00PM - 6:30PM]: Guests arrive, pizza and drinks are served [6:30PM - 7:30PM]: First talk will be presented by Ilya Katsov on "Building an algorithmic price management system using ML", followed by a Q&A [7:30PM - 9:00PM]: Book signing by Ilya and time to network Talk details: Ilya Katsov's talk details: Title: "Building an algorithmic price management system using ML" Abstract: Leading retailers and marketplaces like Amazon and Groupon implemented very sophisticated, and highly automated price management solutions over the recent years. These solutions are able to dynamically change prices every several minutes, intelligently personalize discounts, and respond to competitor moves in order to optimize profits and inventory. It creates pressure on other retailers and manufacturers, and challenges traditional price management techniques, making it increasingly more complex to stay competitive and profitable. In this talk, we will discuss how predictive modeling and reinforcement learning can be used to build advanced price management systems that unlock the potential of dynamic and personalized pricing. We will present price optimization methods for a number of use cases including introductory pricing, promotion calendars, replenishable and seasonal products, targeted offers, and flash sales. We will also review case studies that demonstrate how these methods were applied in practice and how algorithmic price management components were fitted into pricing strategies.

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