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Optimizing Merchandising Using Big Data Analytics

Applying big data analytics in real-time (or otherwise) is not only necessary (because of the volume, variety, velocity and mix of data) but also crucial to answer questions related to merchandising decisions with more granular data available down to individual levels and to correlate them to market conditions and context.

Merchandising managers, for many years, have been grappling with the following three major challenges (among others), in making product management decisions:

Understanding visitor & purchase behavior in the store (and online)

Silos of product, purchase and customer data that are disconnected, disparate and unrelated with no easy way to analyze them in real-time and run ad-hoc queries to get answers quickly to make agile decisions.

Ability to accurately predict store (local) demand for products, both existing and new, to avoid for example, understocking and overstocking, underpricing or promoting the wrong products.

by Balu Rajagopal

Full Story: http://www.datasciencecentral.com/profiles/blogs/optimizing-merchandising-using-big-data-analytics

Inteneo Systems – Big Data/Business Intelligence Expertise from Big Sky Country http://www.inteneosystems.com 406-531-8119

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