Research Hub > Smart Retail Technologies Deliver Insights in Real Time
3 min

Smart Retail Technologies Deliver Insights in Real Time

The real value of analytics and the Internet of Things comes when retailers can leverage data while a customer is in the store.


Many reports suggest overall sales for the 2016 holiday shopping season were slightly higher than the previous year’s figures, but several large retailers lagged behind. Most of the damage came at the hands of online channels, primarily Amazon.

Among those slammed were some of retail’s most progressive companies, which were quick to use mobile marketing, implement in-store Wi-Fi and work to track in-store behaviors in order to be more responsive. The problem: Despite capturing large amounts of customer data, they haven’t reached the point where they can do much with it that’s constructive. I’m not talking about acting on information after the fact, which most retailers can do. The real value comes when a store can do something with information in real time and in-context. That’s when it becomes a smart store.

Retailers have a major opportunity to build trust with consumers so that customers feel like they’re getting something of value and they keep coming back.

Encouraging Impulse Buying

The ability to apply real-time analytics to data created by Internet of Things (IoT) systems and other sources is a cornerstone of smart store initiatives. One area in which smart stores can deliver significant results is impulse purchasing, which represents a significant source of brick-and-mortar revenues. In a 2016 survey conducted by Princeton Survey Research Associates, 84 percent of U.S. shoppers said they buy on impulse, and 79 percent said they make the majority of such purchases in stores.

With a robust infrastructure and relevant, timely data available at the point of purchase, stores can capitalize on the value consumers place on a quality in-store experience. First, they can better compete with online channels on price. Shoppers increasingly conduct retail “showrooming,” in which they browse in-store inventory and then use a mobile device to compare pricing for a desired product. A retailer can use real-time analytics to change its strategy and regain the business it may be losing to showrooming.

To make this work, retailers have to be able to track the way customers move around the store and where they stop, as well as who they are and why they’re there. With a mechanism to push offers and information to a customer’s smartphone or other mobile device in real time, such as a branded mobile app or a loyalty program app, a retailer can provide customers with an incentive to buy on the spot. For example, a bookstore that can determine how long customers dwell in a specific genre section can deliver a mobile coupon that encourages buyers to make a purchase then and there, or through the retailer’s branded website rather than through a competing site such as Amazon.

Real-time analytics also can improve sales in other ways. For example, an office supply store that offers in-store pickup for items ordered through its website may entice customers to make an impulse purchase when they arrive for their purchase.

If a customer has downloaded the store’s mobile app or enrolled in a loyalty program, he or she will receive information at the door with directions about where to pick up the purchase. Supported by rapid back-end calculations based on personal data, this message also can deliver an offer to save 20 percent on a related item such as printer ink.

Orchestrating Retail Solutions

But many stores aren’t taking advantage of these opportunities. I often seen retailers make two major mistakes: 1) They’re too caught up in technology and don’t think enough about what they want to achieve, and 2) They’re concerned that they don’t have the skills to install and configure the different layers that comprise an IoT solution.

My team makes no technology decisions until we understand a retailer’s business and its objectives. We use that knowledge to orchestrate the most effective end-to-end solution.

IoT platforms depend on IT orchestration to bring together key components, including infrastructure, front-end tools and analytics. These enable retailers to learn customer preferences, purchase histories and traffic patterns — and gives them the agility to act on this information.

While these projects will probably require some infrastructure investment — on beacons, for example — it’s not likely to be overly expensive. If I’m a retailer, I’m not particularly concerned about hardware investments, but whether they help me to quickly and intelligently execute on the data I collect.

Taking Steps Toward Retail Innovation

For retailers that want to use smart store tools, inactivity is the enemy. It’s better to just get started — perhaps by deploying simple location-based services. Start with some beacons to identify shoppers. Offer them access to high-speed Wi-Fi and ask them to log in, explaining that knowing them better will allow you to serve them better.

As your store gains customers’ trust, it will gain more access permissions, deliver better offers and gather more data that can be measured. Gaining this trust and delivering targeted offers keeps customers coming back, because they value the relationship.
For many retailers, a growing number of smart store components are available as cloud solutions, which cost less than running everything in an on-premises data center. Further, retailers that run IoT and analytics in the cloud gain the flexibility to change business models as needed.

The bottom line: Start with something simple, and treat data respectfully to build a long-lasting trust relationship with customers. When infrastructure supports innovation, retailers can streamline the experience for customers, better interact with them and leave the competition behind.

To learn more about how CDW’s solutions and services can help retail operations employ data analytics and other advanced services, visit