Catalog and Retail
The retail industry is extremely competitive, and as such, retail companies are constantly innovating and implementing new technology in an attempt to gain a competitive advantage. Retailers have come to rely on Big Data, and in particular, predictive analytics software and cost-effective cloud storage. According to a recent study published by IBM and Accenture, predictive analytics lead to a 73% increase in sales for retailers as compared to competitors who have not implemented predictive analytics into their data infrastructure.
Catalog and Retail User Stories
“Build a 360-degree view of your customer”. If you are in marketing or sales you’ve heard this line countless times. It makes sense, the more you know about a customer the better chance you have of successfully marketing to them. But what is the most effective way to build a 360-degree view of your customer? Many companies are using Hadoop analytics to determine customer sentiment in an attempt to refine and improve customer interaction in the store and through marketing channels. Big Data analytics can correlate structured data, such as, online browsing behavior, in-store shopping trends, product preferences, with unstructured data streams such as social media traffic, which helps retailers understand customer sentiment. This knowledge is invaluable, as it allows companies to develop efficient inventory, pricing, and marketing strategies.
Marketers can use Big Data analytics to create custom offers based off of various data sources and browsing history. Customized promotions can be effective in numerous ways. For instance, marketers can create custom promotions for localized marketing efforts, deliver offers to a consumers smartphone, or increase online sales by using real-time offers through online advertising or social media.