Real-World Uses of Big Data for the Retail Industry

Real-World Uses of Big Data for the Retail Industry

 Technology has changed the way retailers and customers interact. Gone are the days when a proprietor could “hang a shingle” and wait for business to come to them — today’s consumers expect to find what they are looking for online. A customer may not ever step foot into a retail establishment and yet remain a loyal and longtime customer. Savvy retailers can use technology to their advantage, and big data analytics is the tool to accomplish that.

Analytics can track everything from point-of-sale information to traffic on social media, and businesses can use this to predict how their customers will behave. Key performance indicators (KPIs) derived from the analyses show a retailer how their practices affect their business. In a recent IBM study, 62 percent of retailers said that they use this information to give them an advantage over their competition.

Retailers can use big data in two general ways to increase their business: enhancement of customer experience and supply management.

Learn Customer Behaviors

Big data analytics can keep track of the data trail that a customer leaves behind. By gathering information from multiple sources, such as online purchases or social media traffic, retailers can tailor their interactions based on consumer behavior. The retail environment is global, and it moves quickly; it behooves retailers to anticipate the needs and preferences of their customers.

Retailers can even track such behavior on an individual basis. Imagine an online retailer that creates customer profiles. Within this goldmine of data are things such as past purchases and click paths (the sequence of links that customers click as they navigate the site). Analyzing this data reveals what drives the customer to the checkout, or not.

Give a Unique Customer Experience

Over half of the people surveyed by Deloitte UK last year reported that they appreciated loyalty programs. There is a caveat: 42 percent of the respondents indicated that they wanted more than points to make them continue to be customers; experience is equally important.

One of the most noteworthy examples of customer loyalty programs is Amazon’s Prime program. Membership rewards include everything from free videos to same-day delivery. Customers are willing to pay the fee for the perks, and Amazon can customize their shopping experience. The upside for Amazon is that Prime members end up spending twice as much as nonmembers.

Attracting a new customer costs at least five times as much as retaining an existing one, and these programs are designed to retain customers. Increasing retention by as little as five percent can return a 25 to 95 percent profit increase.

Improve the In-Store Experience

Retailers can use big data to help improve their in-store sales as well. Using social media or even weather forecasts allows retailers to display the most relevant merchandise. Some stores also use cameras to discover shopper’s habits and can rearrange placement to optimize visibility and sales.

Control Inventory

Retailers can use radio frequency identification tags (RFIDs) to track inventory and shipping. Each tag has a unique serial number embedded within it that an employee can scan when stocking and selling an item. Retailers can now have a daily inventory of products and a summary of what has sold and can tell customers the locations of their shipped packages.

For example, let’s say that a grocery chain uses RFID tracking to control their supply chain. The business can check daily inventory and adjust prices on perishable items that may soon expire, thereby reducing waste and optimizing their inventory.

Stand Out From the Crowd

In today’s fast-paced and technology-driven marketplace, retailers need to understand the market, their competitors, and, of course, their customers. Big data analytics gives businesses the competitive advantage to not only draw in new customers but more importantly, to keep their loyal customers happy and coming back for more.