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Machine Learning Usecase 04-Retail: Promotional Price Prediction

Machine learning algorithms can quickly analyze enormous, retail-scale data sets. They can automate highly accurate, granular forecasting for both stores and online channels without an outsize time investment from a planning team working in spreadsheets.
Machine Learning Usecase 04-Retail: Promotional Price Prediction
Image from: https://fmemodules.wordpress.com/2015/04/09/top-5-popular-sales-promotions-types-in-2015/

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.

Probyto AI allow organizations to build and manage such usecases and track the benefits of AI adoption in their businesses. Currently, FREE 60 minutes AI Consultation is being provided to the registered users in the Probyto AI Demo platform. If you haven't registered yet, register now to Probyto AI Demo.

#Probyto #AIinRetail #DataProblem? #Machinelearning

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