Over the past few years, retailers have changed the way they do business and continue to evolve as customers find new ways of shopping.
With the growing popularity of online shopping and mobile commerce, customers are using more channels than ever before to search for products, compare prices, make purchases and provide feedback about the products they are interested in or have bought.
Social media has become one of the key channels for these kind of activities, and it is now being used to help consumers find product recommendations, voice complaints, search for product offers and engage in ongoing discussions with their favorite brands.
As you can imagine, massive amounts of data are collected and stored as a result of all of these online interactions.
In IT, the term big data refers to the massive amounts of data collected over time that are difficult to analyze using conventional tools. The data collected by a company can come from different sources and can vary in nature. All this data requires innovative forms of information processing to help organizations gain enhanced insight and make better business decisions.
Retailers in general have access to a huge amount of information about their customers, but they don’t know how to get value out of it because it is usually sitting in its most raw form in a semi-structured or unstructured format. Sometimes they don’t even know whether it is all worth keeping because they don’t have the expertise to extract valuable information from that data.
On a smarter planet, the need to analyze large volumes of data, find patterns and drive insights becomes very critical if a company wants to increase its efficiency and remain competitive. For these purposes we’ll need systems that are optimized to deal with vast amounts of data and complex analytic processing.
The concept of big data is well applied in today’s increasingly data-driven world, and big data has become a critical top-line business issue that retailers must tackle in order to remain competitive.
Following are some simple situations that can be explored using a big data strategy to add business value to a company:
Increase the precision of specific customer segments by analyzing their transactions and shopping behavior patterns across retail channels.
Gain knowledge and enrich the understanding of customers by integrating data from online transactions and data from social media channels.
Optimize the customer’s interactions by knowing one’s location and delivering relevant real-time offers based on that location.
Predict customer shopping behavior and offer relevant, enticing products to influence customers.
Big data solutions are ideal for analyzing data from a wide variety of sources, and retailers can use these solutions in many different scenarios, such as comparing the volume of website traffic for a given advertised product to the number of sales of that product.
Effectively analyzing a large volume of customer data opens new opportunities for retailers to gain a deeper and more complete understanding of each customer.
IBM’s big data platform offers a unique opportunity to extract insight from an immense volume of data at a fast velocity.
As part of the IBM Smarter Computing strategy, IBM offers a complete portfolio to help clients design, develop and execute big data strategy to enhance and complement existing systems and processes. Namely some of the solutions are:
InfoSphere Streams – which enable continuous analysis of massive volumes of streaming data with sub-millisecond response times to take actions in near real time
InfoSphere BigInsights – an enterprise-ready Apache Hadoop-based solution for managing and analyzing massive volumes of structured and unstructured data
InfoSphere Data Explorer – software for discovery and navigation that provides near real-time access and fusion of big data with rich and varied data from enterprise applications for greater insight
IBM PureData System for Analytics – simplifies and optimizes performance of data services for analytic applications, enabling very complex algorithms to run in minutes
IBM InfoSphere Warehouse – provides a comprehensive data warehouse platform that delivers access to structured and unstructured information in near real time
IBM Smart Analytics System – provides a comprehensive portfolio of data management, hardware, software and service capabilities that modularly delivers a wide assortment of business-changing analytics
InfoSphere Master Data Management – creates trusted views of your master data for improving your applications and business processes
InfoSphere Information Server – understand, cleanse, transform and deliver trusted information to critical business initiatives, integrating big data into the rest of IT systems
The strategies involved in big data aren’t just for big businesses. Smaller companies can also benefit. Big data does not necessarily mean really big, but simply data that cannot be managed or analyzed by other traditional technologies.
The retail industry is just one of the endless number of fields that can use big data to increase efficiency and improve results.
Please leave us feedback in the comments on how you are handling your customers’ information to improve your business operations.
Renato Stoffalette Joao is a Software Engineer at Linux Technology Center (LTC), IBM Brazil. His work in LTC consists of interactions with various open source Linux communities and development of extensions for Eclipse environment using the Java language. You can find him on Twitter: @renatosjoao.
To effectively compete in today’s changing world, it is essential that companies leverage innovative technology to differentiate from competitors. Learn how you can do that and more in the Smarter Computing Analyst Paper from Hurwitz and Associates.