Near Real-Time Retail Pricing: Predicting the Effects of Price and Discounts (June 24, 2016 – 2:30PM)
Predictive modelling techniques that use either supervised and unsupervised learning along with new advances in big data and machine learning have much application including the delivery of near real-time retail pricing. The use of these techniques to deliver a customized price to consumers in the retail setting has many challenges such as the need for rapid prediction and information delivery. This session will present a working model that delivers near real-time prices to customers in a simulated retail environment thru the use of predictive modelling.
In this session, you will:
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Predictive modelling techniques that use either supervised and unsupervised learning along with new advances in big data and machine learning have much application including the delivery of near real-time retail pricing. The use of these techniques to deliver a customized price to consumers in the retail setting has many challenges such as the need for rapid prediction and information delivery. This session will present a working model that delivers near real-time prices to customers in a simulated retail environment thru the use of predictive modelling.
In this session, you will:
- Understand the application of structured data (i.e. historical retail purchases) with un-structure data (i.e. customer location within the store) to deliver a customised price action (i.e. a coupon).
- Survey different predictive modelling techniques that can deliver near real-time prices in the retail environment
- Consider different models that use triggers such as a customer walking into the store, a customer standing in front of a display, and more, to deliver a near real-time pricing experience.
- Evaluate a working model that deliver near real-time prices to customers in a retail environment.
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