| | December 20159CIOReviewBig data impacts every point along the value chain so the analytic potential is endlessin the future. Also, because big data technologies are presently fairly robust, we are seeing downward pricing pressure on many retailers notably through cross-retailer price comparisons. This is evident most notably between Amazon and Walmart.com, in many cases eroding margins as they are competing on price.E-Commerce (B2C, B2B, Mobile Commerce) Although ecommerce has been around for a while, the offering methods have changed and continue to evolve as well as the mastery and adoption of ancillary technology tools. For example, B2C and B2B systems have traditionally been on premise offerings. Over the past 4-5 years, the explosion of Social Media offerings and Mobility capabilities present enriched capabilities to engage shoppers, manage content strategy and overall digital presence to drive loyalty programs, social advertising, crowdsourcing, social selling, partner advocacy and expand revenue opportunities. Conversion techniques must be approached thoughtfully analyzing and understanding patterns matching and demographics of shoppers, quickly shifting merchandising strategies that are tailored to individual shoppers. An important consideration we need to understand is that big data/information, mobile, social media are all derivatives and possible because of the huge compute capacity of the Cloud. Core Operations (Store operations, merchandising, Infrastructure) Big data impacts every point along the value chain so the analytic potential is endless. Marketing is enriched by micro-segmentation, sentiment monitoring, and enhancement of the multichannel consumer experience. In Merchandizing assortment, pricing, and product placement can be optimized in near real-time. Within Operations, labor inputs optimization can now be enhanced, creating more accurate predictions of staffing needs based on optimized labor inputs, automated time and attendance tracking, and improved labor scheduling all aggregated in near real time. Additionally, within supply chain, we obtain better inventory management through analytics that mine multiple datasets. Transport analytics improve fuel efficiency, vehicle maintenance, and driver behavior. Customer and transaction data informs retailer negotiations with suppliers to obtain concessions on products. Transforming In-Store Experience: Role of Big Data and AnalyticsRetailers engaged in Big Data analytics capitalize on the tremendous volume, variety, and veracity of data by mapping the right metrics to business decision processes. Using data in near real time, they can personalize marketing campaigns, optimize assortment, products differentiation, shopper journey, predictive modeling and drive customer conversions. In addition, Retailers can drive improved merchandising decisions and identify in-store and online inefficiencies in distribution and operations. Overall, through the disruptive nature of the Cloud and a new generation of advanced and big data analytics commercially available, retailers not only gain efficiency points, but also have the potential to leapfrog competitors by delivering new and unexpected benefits to customers. Just picture the potential in this market and consider: Resale is only going to grow. So let's do it better. "
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