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The numerous ways Walmart uses analytics

@WalmartLabs is Walmart’s digital technology arm that uses predictive analytics to create and capture value

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@WalmartLabs is the digital technology division of Walmart.  It was created in 2011 through the acquisition of Kosmix, a website that let users search the web by topic.  The same year, the team acquired OneRiot, a network of mobile apps that analyses social media signals.  In 2013, @WalmartLabs acquired Inkiru, a predictive intelligence platform that uses big data and analytics to inform business decisions.  Today, @WalmartLabs is using OpenStack to support its eCommerce and data analytics platform. @WalmartLabs is also focused on acquiring Pinterest-like product recommendation marketplaces such as Luvocra which it acquired last year.

Through these numerous acquisitions and developments at @WalmartLabs, Walmart is able to drive value creation and capture by using big data in several different ways.  For example, @WalmartLabs uses social media analytics to guide its inventory decisions.  Normally, social buzz precedes retail buzz and @WalmartLabs uses social media as a real-time feedback source about new products or new upgrades people love or hate.  @WalmartLabs successfully predicted an increased consumer interest in cake-pop makers by relying on chats on Facebook and Twitter.  This data was sent to Walmart’s buying team that used it to make their purchasing decisions.  The buying team also relies on their social-media analytics dashboard to make decisions on what products to stock, whether they should be stocked online or in stores, and which stores.  For example, buyers can see the number of tweets about some specific flip-flops and which colors were the most liked depending on location.

@WalmartLabs also uses big data to improve the online customer shopping experience based on their purchasing and browsing history, trends on Twitter, and other external events such as the weather or the results of an NFL match.    By carefully choosing these independent variables, the team is able to ensure that the recommended products are relevant to their customers.  Another approach is to reproduce “recommended by a friend” projections by creating a subspace of customers based on their past purchases.  The team is then able to create recommendations to users by relying on what similar users in the subspace acquired.

Walmart is also quick to follow the mobile trend.  They have developed numerous iOS and Android apps that focus on customer experience and also created their own tools like Thorax that allow them to build large-scale applications.  By combining its big data research and mobile efforts, Walmart is currently working on improving in-store customer experience where a customer’s in store trajectory is guided by data such as what products they mentioned on social media.


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