In today’s retail landscape, customer loyalty is paramount to brand success. Tech-savvy shoppers have come to expect a convenient and tailor-made shopping experience, challenging retailers to recognize and exploit customer behaviors, patterns, and trends.
The appeal of a personalized shopping experience has dramatically increased the value of customer data. From online searches to in-store purchases, retailers are gaining vital insight into customer demands. To support this rapid influx of information, brands are pursuing newer and more efficient methods of collecting, storing, and leveraging massive amounts of data. Big Data analytics is now being applied to every stage of the retail process to drive competitive advantage – anticipating trends, forecasting demand, optimizing competitive pricing, and identifying and appealing to potential customers.
In the digital age, improving customer loyalty is based on algorithms that scour sales, demographic, and social data and alert retailers to purchasing patterns and upcoming trends. Processing an endless stream of structured and unstructured data in real-time allows retailers to make more informed, data-driven decisions, enhance the relationship between brands and customers, and significantly increase revenue. According to a 2014 Infosys brief, 78% of customers said they would return to retailers who catered to their likes and interests. More notably, 86% reported that they would pay up to 25% more for a tailored shopping experience. It is no surprise then that 82% of retailers agree, Big Data analytics directly impacts customer satisfaction, and an additional 94% describe Big Data as “important” or “extremely important” to their organizations.
Analyzing Big Data has become an essential part of modern retail, so much so that it is no longer optional to retailers looking to expand their businesses. Dominant brands such as Nordstrom, IKEA, Target, and Sephora are investing heavily in Big Data solutions to better understand their customers, maximize sales, and encourage brand loyalty. Other key goals include:
- Improving responsiveness to customers at the point of interaction.
- Integrating recent data with large volumes of historical data to make a targeted recommendation at the point of sale.
- Providing customer service representatives with the knowledge to effectively assist and guide customers to products.
- Raising customer satisfaction and customer retention.
Although retailers have access to a wide range of IT innovations, smaller entities are struggling to overcome the technical and analytical challenges of legacy systems and inefficient data storage – at the risk of losing out to larger entities. Giant retailers likeWalmart spend millions on data-driven merchandising systems, using algorithms to monitor demand, inventory levels, and thousands of transactions and automatically respond to market changes. Consequently, effective Big Data strategies must include scalable storage and a high-performance infrastructure to support troves of customer data and to implement changes in real-time. Investing in transformative technologies such as Big Data Platforms allows retailers to quickly access countless purchases and interactions, generating actionable information in a matter of minutes.
As the retail marketplace continues to evolve, customer loyalty remains a key driver to brand success. Big Data is establishing a new avenue for retailers to optimize operations, improve customer relationships, and maximize sales revenue. Utilizing advanced analytics and storage capabilities will not only influence how customers respond to retail environments, but it will also allow brands to remain relevant in a highly competitive industry.
Originally published on Hewlett Packard Enterprise