Big Data trends and opportunities in Retail

As retail industry moves from the conventional on-store platform to e-commerce platforms hosted in cloud, companies involved in the retail chain are given immense opportunity to grow their business by leveraging these technical advancements. With huge amount of data being produced from every customer interaction, retailers are now challenged with the task of managing them to ensure compliance and leveraging them to make the best use of it.

Reports suggest that in 2013, retailers will spend nearly $2 billion on business intelligence and $9.4 billion on infrastructure that support big data movements.

Big Data can revolutionize the retail industry that is challenged by relatively slow adoption of technology, say experts. Big data can help retailers gather a variety of information about customers. In addition to the basic demographic information, retailers can also gather information from POS systems, online transactions, call center interaction, mobile/social interaction, supply chain data, loyalty programs and more. Through a deep analysis of this data, retailers can gather insight into various aspects of their business and devise strategies to deliver highly targeted, location-based promotions, in real time.

Retail-Shopping

Apache Hadoop is a revolutionary technology that has redefined the big data space. Hadoop is the open source software framework, used to reliably managing large volumes of structured and unstructured data.

Big data solutions that redefine retail industry

IBM InfoSphere BigInsights

With $1.3 billion from big data-related products and services, IBM is the biggest big data vendor in 2012 by revenues, according to a recent Wikibon report. IBM supports the Hadoop open source data analytics platform. IBM InfoSphere BigInsights brings the power of Hadoop to the enterprises by helping retailers manage and analyze the massive volume, variety and velocity of data that consumers and businesses create every day.

One of its customers, Constant Contact, has improved analysis performance by over 40 times, reduced wait time from hours to seconds, and increased client campaign effectiveness by almost 25 percent using IBM InfoSphere BigInsights, the company claims.

HP Big Data Discovery Experience as a Service

Another vendor leveraging the power of Hadoop in big data applications is HP. With $664 million big data revenues in 2012, HP is the second biggest big data vendor in the world. The company recently rolled out a cloud-based data analytics as a service, delivering an on-demand model that obviates the need for large capital investments.  Services offered through this model include analysis of customer intelligence, supply chain and operations, and sensor data.

Other leading vendors in big data analytics space include Teradata, Oracle, SAP, EMC, Microsoft,, Amazon, Google and VMware.

Teradata’s Aster Data Analytic Platform powers next-generation big data analytic applications with a massively parallel processing (MPP) analytics engine that stores and processes big data analytics together with data.

Oracle’s Big Data Appliance combines an Intel server, Cloudera’s Hadoop distribution and Oracle’s NoSQL database. Oracle Retail Data Model combines the power of Oracle’s Data Warehouse and BI technology to provide retail-specific metrics, which, combined with advanced and predictive analytics, enables retailers to implement a BI solution and immediately improve their bottom line.

SAP is best known for its HANA in-memory database. The solution gives the ability to run big data analytics on 80 terabytes of data, integrate with Hadoop, search text content, harness the power of real-time predictive analytics, and more.

EMC Big Data analytics think tank focuses on analyzing marketing data. EMC’s latest spin-off named Pivotal, also backed by VMware and General Electric, combines Hadoop with EMC’s Greenplum database and HAWQ query tools.

Amazon delivers a number of Big Data products, including the Hadoop-based Elastic MapReduce, DynamoDB big data database, and the Redshift massively parallel data warehouse that all work well with Amazon Web Services.

Microsoft is delivering big data solutions to enterprises with Hortonworks, a Big Data startup, and the HDInsights tool based on Hortonworks Data Platform. Microsoft is also known for its SQL Server database. The software major has grabbed $196 million in big data revenues in 2012.

Google’s BigQuery, a cloud-based Big Data analytics platform, can be used instead of a Hadoop deployment, helping users save money because they only pay for the queries that are processed, rather than pay for the computational costs of running individual Hadoop supporting components. Google has earned $36 million in big data-related revenues last year.

VMware, the big name in virtualization software, is offering VMware vSphere Big Data Extensions, which lets vSphere control Hadoop deployments and make it easier for enterprises to launch Big Data projects. VMware stands just behind Google with $32 million in Big Data-related revenues last year.

Big data revitalizes retail industry

The explosive growth of data can revitalize the retail industry. The huge bundle of data presents new business opportunities for retailers. Retailers can, by analyzing sales data and other data in the right way, can benefit from this opportunity.  A recent report from Mckinsey suggests that retailers using big data to its full potential could increase operating margins by 60 percent.

There is increased investment in technology in the retail space. As the cost of the technology comes down, retailers will be able to see more benefits. Currently 1TB of data costs about $80 a year.

Big data drives the retail industry to leverage multi-channel opportunities in a better way to drive growth. Walgreens said recently those customers who shop both in-store and online spend 3.5 times as much as customers who favor only one channel. Technologies such as Next Best Offer (NBO) are set to create revolution in retail sector. Next-best offer combines predictive data analytics and mobile offers to identify the products or services customers are most likely to be interested in for their next purchase.

Harnessing big data requires a lot of efforts, but it pays off as it helps identify the most profitable customers. Lack of consumer insights is cited as one of the top data-related pain point in retail industry. Harnessing the right data and analyzing it will lead to better customer engagement and more loyal customers and a competitive advantage.

Rajani Baburajan

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