Business Concepts


The combined forces of technological innovation, changing consumer preferences and a prolonged period of slow economic growth are driving rapid changes in the retail industry. For retailers, Apache Hadoop can be a powerful tool for responding to that change.

In many countries, “new normal” post-recession consumer spending growth rates are lower than before the crisis. At the same time, technology has empowered consumers to be smarter, more social shoppers. Online ratings, reviews, and price comparisons influence their shopping and when it comes time to buy, they can purchase on a mobile device, online or in a store. The new shopping hours are 24×7.

In this climate, retailers need data-driven ways to segment customers, interact with them, and manage supply chains to match products with consumer demand.

Hadoop improves customer segmentation. Retailers mine a rich trail of consumer data from sources previously unavailable at a large scale: online reviews, blogs, and social network messages. The new data sources in Hadoop deliver retailers unprecedented insights into consumer behavior and preferences. Hadoop data also improves customer interactions with confident next-product- to-buy (NPTB) recommendations. It can also recognize customers across multiple channels and touch points to produce in-store or online personalized recommendations, along with real-time coupons to whet their shoppers’ appetites.


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Finally, retailers use Hadoop for better forecasting, purchasing and supply chain optimization. They can optimize distribution routes and inventory levels to appeal to the local and rapidly changing tastes of individual consumers.

Build a Modern Retail Data Architecture with Enterprise Hadoop

Ingest all the data, store it at scale and analyze it with the tools you already use (Source: Hortonworks)

To realize the value of your investment in big data, use the blueprint for Enterprise Hadoop to integrate with your EDW and related data systems. Building a modern data architecture enables your organization to store and analyze the data most important to your business at massive scale, extract critical business insights from all types of data from any source, and ultimately improve your competitive position in the market and maximize customer loyalty and revenues.


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