The volume, variety, and velocity of data being produced in all areas of the retail industry are growing exponentially, creating both challenges and opportunities for those diligently analyzing this data to gain a competitive advantage. Although retailers have been using data analytics to generate business intelligence for years, the extreme composition of today’s data necessitates new approaches ...and tools. This is because the retail industry has entered the big data era, having access to more information that can be used to create amazing shopping experiences and forge tighter connections between customers, brands, and retailers.
A trail of data follows products as they are manufactured, shipped, stocked, advertised, purchased, consumed, and talked about by consumers – all of which can help forward-thinking retailers increase sales and operations performance. This requires an end-to-end retail analytics solution capable of analyzing large datasets populated by retail systems and sensors, enterprise resource planning (ERP), inventory control, social media, and other sources.
How does one start a big data project? In an attempt to demystify retail data analytics, this paper chronicles a real-world implementation that is producing tangible benefits, such as allowing retailers to:
• Increase sales per visit with a deeper understanding of customers’ purchase patterns.
• Learn about new sales opportunities by identifying unexpected trends from social media.
• Improve inventory management with greater visibility into the product pipeline.