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Big Data in Retail Sector – An Evolution that Turned to a Revolution

June 24, 2021
Uploaded through Retail - Category: Data Science E-Books » Retail - Tags: ##retail  #big_data_in_retail  #good_marketing  #marketing_campaigning  0 133 0
It was a prominent belief among people that good marketing is an art, but of late, a scientific element has been introduced to marketing campaigns by the big data. Marketers are relying on data to test, devise, and inform strategies than ever before. No doubt, there is no match for the creative minds in best marketing campaigns, but data and analytics can definitely provide the marketers with tools to upgrade performance. With the advent of universal digital technology, retailers make well-informed decisions utilizing online data in order to discover, associate, and buy products anytime from anywhere. Information acts as a game changer for retailers and is collected from different sources as shown in Fig. 1. Retail data analytics enables companies to stay well-informed of the latest shopping trends by implementing customer diagnostics to expose, understand, and act on meaningful data insights. The retailers are accepting the data-first strategy to have a deep insight of customers buying patterns, mapping them to products, and forming strategies to increase the sale in order to register increased profits. Retailers utilize the structured and unstructured information available about their consumer’s behavior to utmost potential. Future of retail is totally dependent on big data analytics as it is capable of separating the wheat from the chaff. Retail is adopting data- centric technology for boosting sales. Retailers have achieved 73% increase in sales. Retailers are mining customers analytics to increase profits, increase growth and to be in competition, whether it is in-store or online. Data analytics is not a new concept in the retail sector. The retail market has always been interested in finding and analyzing new buying trends in customer’s behavior. This allows retailers to associate products like shampoo and conditioner, toothpaste and toothbrushes, as the data patterns show that the people who buy shampoo will invariably also buy a conditioner. Placing related products together influences the buying behavior of the customer.