This experiment demonstrates how to build a price elasticity model with combos and external factors.
Price elasticity is the foundation of price optimization. This experiment uses the transaction data of a burger restaurant to show how to get price elasticity when users need to deal with combos and add external information including weather and holiday into the pricing model. It is the third demo experiment in the [Cortana Analytics Webinar for Retail Pricing]. **Input**: Daily price and demand of burger. Combo information. External features. **Output**: The burger's price elasticity. See the output port of 'Train Model'. The feature weight of 'Log_Price' is the price elasticity. **Related Resources**: Check the video of the [Cortana Analytics Webinar for Retail Pricing] which is hosted also by Xueshan to learn the concept of price elasticity and the three steps to do price optimization. Created by a Microsoft Employee. : https://info.microsoft.com/CO-Azure-WBNR-FY16-13Oct15-CortanaAnalyticsRetailPricing-Register.html?ls=Website%20target=