Big data analytics are revolutionizing the shopping experience and the way retail organizations engage their customers. With the array of shopping channels available to the modern consumer - including in-store, online, mobile and membership platforms – retail organizations generate and have access to a wealth of underutilized data. By leveraging open source big data technologies, retailers can turn this data into actionable insights on buying behavior and customer 360 view.
The legacy relational database – long the enterprise workhorse for storing and processing data – is being challenged by an explosion of data generated by internet, mobile and cloud applications. Not only is more data being generated, it is being generated by more sources - social, geo, sensor, machine, network (The Internet of Things), to name a few.
Open source big data tools such as Hadoop and NoSQL enable businesses to become more agile and create value from their data by being able to process, store and analyze large volumes of data from disparate sources. Legacy systems were not designed to handle fast-growing volumes of structured, unstructured and semi-structured data in a cost effective manner. With its parallel processing and cost effective scalability, Hadoop provides businesses with greater flexibility on how they can use data.
The journey to becoming an agile business leveraging big data analytics for greater customer insights is filled with many challenges. Ankur Gupta, Sr. Director of Big Data at Sears Holdings Corporation, shares insights into overcoming these challenges at All Payments Expo Europe this May. In addition to sharing lessons learned, Ankur will discuss several key big data analytics use cases that are essential for a successful omnichannel retail strategy.
Smart Network Analytics for In-Store Customer Insights
Hadoop can be used to store, extract and transform data from network devices (IoT) for use by various business users to generate value for the organization. The ability to perform analytics and continuous reporting on this network data in-house is a big cost saver and delivers added business intelligence capabilities, such gaining insight into customer mobile device usage within guest networks.
Fraud Detection for Loyalty Rewards Program
Using big data tools, organizations can develop an intelligent system that learns from customer online behavior to determine if the customer could be a fraudulent user. By applying machine learning techniques on sets of historical data that have already been defined as legitimate or fraudulent, the system “learns” as the user generates new data. Using parameters of fraudulent use, the system determines if the data is legitimate or if the user is tampering with the data to “game the system” to earn points.
Sentiment Analysis using Social Media Data
Using Hadoop, marketers can gain insight to the perception of their products and brands, such as hashtags used, number of mentions, time of day people are mentioning, tone or any other statistic the business user is looking to discover. Furthermore, marketers can gain unparalleled insight into sentiment about the quality and services of their products; whether those sentiments are positive, negative or neutral. Social media analytics allows business users to see the detail of the overall view of what is being discussed about their product or brand, or those of their competitors.
While there are proprietary tools in the market that give businesses similar analytics capabilities, these tools typically carry a hefty price tag and lack the scalability and flexibility of open source tools. Data is growing and changing faster than ever. By leveraging open source platforms, businesses can build analytics solutions that can easily scale with their data, are flexible to meet new business requirements and avoid vendor lock-in to reduce long term costs.
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| Ankur Gupta |
As a Senior Director of Big Data at Sears Holdings Corporation and GM of MetaScale, a subsidiary of Sears, Ankur spearheads a team that has expertise in building, deploying and managing enterprise-scale big data platforms for a variety of customer analytics initiatives. An Engineer from Indian Institute of Technology, Roorkee and MBA from Duke University, Ankur uses his knowledge and skills to manage big data projects for organizations focused on seamlessly connecting digital and physical customer experiences.
Your customers expect a modern shopping experience…are you equipped with the tools and technology needed to provide one? Join Ankur Gupta for his Big Data and Omnichannel Retail Analytics Keynote Address at All Payments Expo Europe. Be sure to register by Friday 17 April to save €200! Just use the code XU2940BLOG.
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