Real-time retail involves monitoring needs as they change and adapting as necessary no matter which channels customers use for shopping. Not surprisingly, data is a tremendously important part of real-time retail since brands often use platforms that collect and analyze trends, then use the generated information to help drive decision-making.
Retailers have relied on data centers for a while, but the emergence of retail-time retail has deepened that dependence in several ways.
Edge computing is a familiar concept to people in the cloud computing sector. It processes data at the edge of a network instead of sending it back to a central data center.
Analysts believe that as edge computing becomes ever more popular in the retail industry and otherwise, the size and location of data centers will change. They suggest that the massive data centers commonly seen today will not disappear, but they will become less frequent as smaller, more localized data centers come into favor.
It's also possible retailers could use micro-data centers bolted onto existing telecommunications structures, such as telephone poles. In that scenario, those data centers could become especially prominent near areas where people congregate to shop, such as malls.
Virtual reality (VR) and augmented reality (AR) are both technologies that have recently become mainstream. When used in the retail sector, they help people experience products in interactive, immersive ways.
For example, Sephora has an AR-equipped mirror that lets people sample shades of cosmetics. Similarly, Macy's will offer a VR solution in dozens of stores to encourage people to buy furniture and provide a broader merchandise assortment. A trial phase reportedly reduced the rate of returns to less than two percent, suggesting VR content helps people feel confident about their purchases.
Data centers are crucial for allowing retailers to embrace VR and AR technologies. But, those facilities must be sufficiently equipped to speedily process and securely store the information generated by these technologies, especially because they deliver various content depending on ever-changing factors such as a person's position in space or the options they select.
In the case of Sephora's mirror, the technology tracks the location of a person's face as it moves. Then, the system applies the specific makeup shades they choose.
When retailers abide by best practices for inventory management, they conduct regular stock audits to ensure the counts taken by hand match the expected numbers a computer shows. Some use the ABC Method of categorizing products in a system depending on how well they sell, then ensuring that the best-selling items have the tightest inventory controls.
Plus, retailers may begin tracking customers once they walk into stores or visit a brand's website. A 2017 survey found a third of consumers were comfortable with the practice, an increased amount compared to an older study. Then, retailers can identify which products capture shoppers' attention the most and proactively incorporate such data into inventory management plans.
Research also shows the time between when a person initially tweets about an interesting product and initiates a dedicated Internet search for it is about four hours.
However, various things affect the desire to shop in stores or online. For example, traffic spikes could occur during the holiday season, just before students start college classes and in regions forecasted to experience unusual weather, whether a hurricane or a long-awaited break in cold weather. Or, people might notice a bracelet worn by an actress during the Academy Awards and decide they must buy it online.
All these fluctuations mean the retail-related traffic flowing into data centers is not constant. So, those facilities must seamlessly accommodate for changes in demand and handle them without experiencing outages. When that happens, real-time technologies improve the retail industry by anticipating customers' needs and offering more personalization, thanks to well-equipped data centers.
The real-time aspects that are gaining prominence in the retail sector also extend to payments. According to a recent survey, more than three-quarters of retailers polled believe real-time payments would improve their operations, and approximately the same percentage think the method will replace using credit or debit cards to pay for products and services.
For example, in the Netherlands, people can pay for things by scanning QR codes. And, mobile wallets are more common examples of how individuals can buy the items they want without having the respective cards in hand.
However, the same research mentioned earlier in this section found 61 percent of retailers felt they were at a greater risk of a data breach at the time of the survey than a year previously. That means whether retailers use this real-time technology to facilitate people who want to buy merchandise or are depending on it to refund earlier transactions, the parties involved must trust in the security of their data.
If customers feel unsafe about trying real-time methods of payment, they'll likely stick with what's more familiar to them. However, if retailers can demonstrate that they store transactional data safely and have partnered with data centers that have that same strong commitment to security, it should be easier to encourage adoption.
Also, it may not be very long before people start seeing real-time payments after redeeming loyalty points earned by shopping. Statistics show the average household subscribes to 29 loyalty programs, but over half of the people enrolled in them do not actively participate. The lack of waiting for rewards could make them more excited, but data security must be of paramount importance.
The trends described above highlight why retailers increasingly need the services that data centers offer.
Conversely, the retail industry could prove a significant profit generator for data centers, making it crucial for those facilities to remain innovative and up-to-date.
Kayla Matthews writes about data centers and big data for several industry publications, including The Data Center Journal, Data Center Frontier and insideBIGDATA. To read more posts from Kayla, you can follower her personal tech blog at ProductivityBytes.com.