[KDD 2020] Price Investment using Prescriptive Analytics and Optimization in Retail - CrossMinds.ai
[KDD 2020] Price Investment using Prescriptive Analytics and Optimization in Retail
Aug 13, 202017 views
Linsey Pang
As the world’s largest retailer, Walmart’s core mission is to save,people money so they can live better. We call the strategy we use to,accomplish this goal our,Every Day Low Price,strategy. By keeping,operational expenses as low as possible, we can continually apply,a downward pressure on our prices, in turn increasing the amount,of traffic, and ultimately, sales within our stores. In this paper, we,apply Machine Learning (ML) algorithms and Operations Research,techniques for forecasting and optimization to build a new price,recommendation system, which improves our ability to generate,price recommendations accurately and automatically. Comprised of,a demand forecasting step, two optimizations, and causal inference,analysis, our system was evaluated in the form of forecast backtests,and live pricing experiments, both of which suggested that our,approach was more effective than the current rule-based pricing,system.
SIGKDD_2020
Applied Research
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