Big data in retail images retail december-2012


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Big Data approach and strategy for retail. A practical and pragmatic view towards Big Data in retail.

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Big data in retail images retail december-2012

  1. 1. technologyBig Can Reap Big Returns in Retail Big questions, big data, biganswers, big returns – this wouldhave been a short and sweet story forbig data in retail and that too witha happy ending. For a generation ofretailers who have grown up on MISreports evolving into dashboards andtrend analytics recently, it will be asteady and gradual journey towards In today’s digital world, no other industry has the Data potential to witness an exponential rate of growth of data than retail. More and more retailers are warming up to draw blueprints on ways to identify, capture and harness mountains of raw data into manageable business cases and actionable insights with tangible business benefits By Shijo Sunny Thomascomprehending and realizing the influenced even before interacting manage, process and analyze can bebig-data business case. The current with the retail channels, and purchase classified as big data. Each item on areports and dashboards would have opinions are shared way beyond the retail invoice, customer service call,been created out of transactional data, point-of-purchase. In such a case, it email, social media activity and eachwith the data sourced from within the becomes imperative for retailers to tweet present an opportunity for databoundaries of the retail organization. capture customer feedback from data to be generated in retail.These sources would range from sources outside their realm of physical Consider these opportunities inpoint-of-sale and customer database influence. the light of an increasing consumerto supply chain transactions. So, the first question that many population with increasingly complex As retail channels evolve, the retailers ask would be, how big is big demographics and a growing affinitycustomer interactions transcend data? The answer is simple: any data towards digital channels and devices.into areas outside the boundaries volume and data type that is beyond The proliferation in product lines,of a retailer’s control. Shoppers are the current capabilities of a retailer to stores, social-media platforms and98 . images retail . december 2012
  2. 2. technologydigital devices represent a potential variety of data can be as structured as from store-video feeds. These canpermutation to generate data of the point-of-sale data and as unstructured provide information around how longhighest magnitude. In reality, this is as store-video feeds. The volume of do shoppers spend in a particular aislejust the beginning of things to come. data amassed by retailers can easily or their interactions with products.We have only accounted for scenarios be a few terabytes a day depending The implications of big-data insightswhere humans generate data. How on the variety. Velocity is the speed at range from customer analytics andabout a future where devices interact which data is captured from its source merchandising decisions to storewith other devices and generate and turned into meaningful insights. performance, assortment managementvolumes of data? This will create a It is evident that technology decisions and loss prevention. These are areasdata heap that will make finding a depend highly on the variety, volume where it is necessary for retailers toneedle in a haystack look easy. and velocity of data. rapidly take decisions based on a The case for big data can very often Fortunately for today’s retailer, quick understanding of the customerget overwhelming and intimidating inexpensive hardware and innovations profile, brand interactions, sentimentsfor many retailers. Often, the and basket size. The decisions can bebusiness value of harnessing big data in the form of accelerating productis wrapped along with additional shipments from various locations,layers of technology such as cloud, mark-down decisions or initiatingmobility and analytics. Since vendor replenishments ina lot of these aspects are in evaluation stage in many In an industry with razor-markets, there are chances of a thin margins, defining andbig data idea being put on the executing your big-databack burner. This often tangles strategy has the potential tothe business value and the ROI bolster the retail margins bymodel becomes complicated. a significant extent. GranularTherefore, it is important to customer insights leading tounderstand how retailers can form highly personalized messagesa pragmatic strategy and approach to the shoppers will lead to antowards big data within the retail increase in the basket size and asorganization. well as in the number of shopper Defining and implementing a big- visits to retailer strategy involves decisions across Another area where retailers standmultiple technology layers to decide in processing capabilities coupled with to gain from big data is customeron the execution model. The journey the scalability of cloud computing service where service requests can befor a retail organization should can be ingredients to an attractive fulfilled in the shortest possible timecommence with first evaluating big-data value proposition. This way, and in the most precise manner. Bigif the organization is a big-data the retailer can concentrate more on data implementation eventually payscandidate. The evaluation process the operational and business-oriented for itself when the ROI is measuredconsists of forming a business case aspects of big data. This involves against reduced cost of operations,and associated business scenarios. In integrating to various sources of big efficient assortments and reducedmost cases the scenarios are in the data and translating the data into a stock-outs.area of offering highly customized manageable and analysable form. So, hopefully within a few years,promotional offers, analysis of These are used to define analysis if a customer tweets about howpromotional effectiveness in real models where substantial inputs are a rain spoiled her day, she wouldtime or analysis of store space required from the business users to immediately receive a discount offereffectiveness by analysing the shopper define the various actionable items for an umbrella. To her surprise, thepath. Breaking up the business that can be created out of the data. color of the offered umbrella wouldcase into scenarios helps retailers Now we are entering the realm of big match with the dress she bought twoidentify current technology and skill data analytics which is ultimately the weeks earlier from the store!limitations, investments and the wow factor in big-data management.associated returns. Retailers can benefit from big data Identification of various candidate to such an extent that each customerdata sources that will serve as can be classified as a separate ABOUT THE AUTHORinputs to the business scenario is segment. Shopper behavior can be Shijo Sunny Thomas is theessential to get a firm grip on the data tracked across all channels and the Industry Lead–Retail & CPG at Fujitsu Consulting India. He hascharacteristics. These characteristics information can be correlated with worked extensively in advisoryare popularly classified into areas the current assortment characteristics. and operational roles withof variety, volume and velocity. For Retailers can also tailor the store and medium to large cross-channeleach candidate business scenario, the shelf space through insights gathered retailers december 2012 . images retail . 99