In retail deciding on promotional prices for an SKU can be challenging. It depends on several factors, including but not limited to Class, Subclass, Style of an SKU, Seasonal product, Previous cost history, profits. Few Countries have a regulation for the retail stores to choose promotions only for a certain number of days in a whole year. Choosing the right promotions for the product at the right time, so profits are not affected and provide maximum customer satisfaction, is tedious and involves a lot of calculations. These calculations are not simple and would consume huge IO, CPU time, and memory with my experience with a large retail company and always misses SLA.
Is this a data problem? Can machine learning help solve this problem and help buyers to optimize their departments effectively? Please share your thoughts and how you would approach this problem? What data will be required if this is a machine learning problem? What are the challenges in the machine learning approach? Please update your comments.
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