Walmart pioneered the use of Big Data to improve operational efficiency in the retail industry well before the term Big Data even existed. The company understood that by harnessing the power of data, it could streamline its complex supply chain to take advantage of economies of scale, thus limiting excess inventory and reducing associated costs. It passed on some of these Big Data-enabled savings to customers in the form of low prices that (in some cases significantly) undercut the retailer's competition.
That was in the 1990s and early 2000s. Since then, retailers have continued to make innovative use of data to provide value-add services that both benefit customers and improve the bottom-line. Among these innovative retailers is Amazon, which in the mid-2000s began using what it knew about its customers' buying patterns and behavior to recommend similar and related items to customers at the point of check-out.
Today, data-driven supply chain optimization and recommendation engines are table stakes for major retailers.
In 2013, forward-thinking retailers continue to blaze an innovative path in Big Data. Based on conversations with members of the Wikibon community and a number of retailers, Wikibon has identified the following Big Data applications as among the more innovative and/or promising currently in use:
- Dynamic price optimization. Retailers are using Big Data-backed techniques to dynamically price goods and services, both online and in stores. In its most sophisticated form, dynamic price optimization applications take into consider myriad data streams - including competitor pricing, supply chain and inventory data, market data and consumer behavior data - to adjust prices in real time to maximize sales, increase profit margin or meet other strategic goals.
- Video-enabled store layout and product placement analysis. A small number of retailers have begun analyzing video data - not metadata associated with video, but the content of video itself - to improve store layout, product placement and promotional displays with the goal of driving higher conversion rates. These retailers are using video to understand, for example, which in-store promotional displays may be drawing large numbers of customer eyeballs but not resulting in significant sales.
- Staffing analysis and decision support. Retailers, particularly national and multinational retailers with diverse and geographically dispersed workforces, have long struggled with optimizing in-store staffing. Many factors impact staffing requirements, including weather forecasts, promotional campaigns, time of year/month/week/day. Today, retailers are analyzing data associated with these and other factors to ensure stores are optimally staffed.
Retailers are using a variety of technologies and techniques to support these and other Big Data applications. They include Hadoop, massively parallel analytic databases, enterprise data warehouses and data visualization tools, among many others.
Action Item: Large retailers that have yet to begin using Big Data to streamline operations, improve the customer experience, analyze marketing campaigns or otherwise increase sales and maximize profitability must put in place plans to do so immediately. As noted, the retail industry is among the early adopters and innovative users of Big Data, meaning those retailers that have not begun harnessing data to their advantage are farther behind laggards in other industries. Retail CIOs should waste no time in bringing together IT and business stakeholders to lay out a Big Data vision for the enterprise and practical plans to implement them.
Footnotes: For a list of Wikibon clients, click here.
