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Retail Analytics in Physical Stores: A Path to Omni-Channel Success

The right retail data can determine whether a consumer makes a purchase or chooses to visit a retailer again. Consumers expect a shopping experience that is personal, informative and convenient. Although a brick-and-mortar store certainly can fulfill the latter two needs based on general knowledge of its consumer base, it’s hard for a retailer to offer a personalized customer experience without having the retail analytics technology to glean information about a specific shopper.

E-commerce retailers have a much easier time gathering individual shopper data. Web technology makes it possible for online retailers to not only track what a consumer purchased and when, but it also can track where the user is shopping from in terms of both physical location and device used. Additionally, web technology tracks how the shopper reached the site, what other items the consumer looked at on the site and how long the consumer spent shopping on the site. When this information is associated with an IP address or a shopper’s store account, the retail website can send the consumer targeted emails and website ads, customized deals and suggested products. This serves a dual purpose: the consumers will have an easier shopping experience because they are presented with the products they are likely searching for, and the retailer can generate more sales from related-item purchases and repeat business.

It is much harder to reach this retail analytics nirvana in a brick-and-mortar store. At best, most stores are able to track consumer sales behavior through loyalty programs, which can link purchases to specific individuals. Otherwise, the stores can track item sales to see which products are the most popular. However, this does not track an individual shopper’s physical path to purchase, including what else he or she looked at before arriving at the register. As a result, brick-and-mortar retailers are limited in the number of ways they can offer a customized, convenient shopping experience to every customer without retail analytics technology.  

Retailers Slow to Upgrade Analytics Technology

There are multiple technology innovations available to help retailers learn more about their in-store shoppers, but so far only the biggest corporations have the financial means to test and implement the latest options. According to the 28th Annual Retail Technology Study: Wake Up Call for Digital Transformation by Retail Info Systems and Gartner, only 16 percent of surveyed senior-level retail executives reported that their stores have up-to-date shopper-tracking capabilities. Another 33 percent plan to upgrade their shopper-tracking capabilities within the next two years, and 42 percent have no plans to update their technology. Similarly, only 10 percent have up-to-date location-based sensing for marketing or communication in place, 49 percent plan to upgrade their technology within the next two years and 40 percent have no current plans to invest in such technology.

By comparison, most of the participants said they are spending their technology budgets on customer relationship management and personalization management, mobile devices for associates and in-store pickup and return options.

Despite this slow progression toward the latest retail analytics and reporting technology, all of the respondents to Jabil and Dimensional Research’s 2018 The Future of Retail Technology study agree that technology innovation is essential to meet the expectations of today’s shoppers. Such investments will help stores improve shopping efficiency and deliver a more customized experience. In fact, without the right retail technology at hand, ultimate personalization won’t be possible in physical stores. Download Jabil's Future of Retail Technology Report.

retail analytics technology - imperative for success

Compiling Retail Analytics with Beacons

One retail analytics technology that is gaining in popularity is in-store beacons, which have multiple uses. For example, these beacons can track traffic flow throughout the store to determine what areas of the store are busiest. This information could guide retailers to adjust their planograms to move promotional items to high-traffic areas or to just create more space in these areas to accommodate the number of shoppers. The data could also be used to track traffic at certain times of the day and week to help the retailer plan personnel for staffing registers and restocking items at a given time.

If connected to a smartphone app, beacons could be used to track individual shoppers and even send them customized messaging and promotions. For example, when a beacon connects with a shopper’s smartphone, it can send the consumer a welcome message, remind him or her to pick up some favorite or commonly purchased items or send the user some targeted coupons or deals. At the same time, the beacon could track the consumer’s physical path to purchase and learn more about his or her specific shopping behaviors. This technology is already in use by numerous retailers including Target, CVS, Nordstrom and Walmart.

Amazon Go stores are another example of some of this technology in action, though for a slightly different use. At these cashier-less stores, customers enter by scanning a barcode found in the Amazon Go app on their smartphones, shop for the items they need and then exit without needing to stop to pay. Hundreds of cameras throughout the stores track the shoppers’ movements, including what they pick up, put back on the shelf or end up taking with them. Each product also has a large, camera-friendly code that the cameras can read to know exactly what item has been taken, the Chicago Tribune reports. Computers then combine this information with data from the shelf’s weight sensor to confirm that a product has been removed. As shoppers exit the store, they are automatically charged for their purchases, and they even receive notifications telling them how quick their shopping trips were.

This combination of computer vision, deep-learning algorithms and sensor fusion creates a quick, convenient shopping experience for consumers, who are increasingly time-poor. In addition, this technology creates a shopping environment more akin to e-commerce in terms of potential analytics, as this system can track where in the store a specific consumer went, what items he or she picked up, and what items he or she ultimately purchased.

Investing in the Future of Retail Analytics

In line with retail innovations and trends like this, nearly half of the participants in the recent Jabil survey are investing in, or at least have plans to invest in, some type of retail analytics and reporting technology. Specifically:

  • 55 percent are investing in data visualization
  • 49 percent are focusing on location-based mobile targeting
  • 49 percent have plans to expand their big data efforts
  • 48 percent will invest in in-store sensors
  • 41 percent are looking to implement machine learning and artificial intelligence.

When new data analytics and reporting technologies are combined, they could potentially collect thousands of data points about a single shopper in a given visit. Retailers will need the best data visualization software to analyze these data points and highlight the meaningful insights. Actionable data can help inform supply and demand decisions, reduce costs, create more revenue, influence quality improvements, accelerate process efficiencies and create better shopping experiences that meet consumer preferences.

improving retail analytics

Location-based mobile targeting could help bring more consumers into stores and also guide them around the stores to find promotional items. More than 70 percent of retail marketers already have some sort of location-based advertising strategy in place to drive foot traffic, according to research by Blis, WBR Insights and Future Stores. Half of surveyed retailers noted that consumers who already are near a given store are more receptive to receiving mobile promotions in real time. About two-thirds of surveyed retailers also offer local product or inventory search and interactive maps to help shoppers who are in the store or are nearby.

Big data efforts also can help drive purchases. For example, if a shopper with a store’s app typically buys a specific item every shopping trip, the app could use the store’s big data to recognize this and remind the consumer to pick up that item, thus driving continued purchases. In addition, if these insights are shared with a consumer packaged goods company, the retailer and food or beverage manufacturer could partner on cross-promotions to send shoppers targeted coupons to encourage them to try new brands or to pick up complementary items, such as hot fudge to top ice cream.

Machine learning and artificial intelligence can help store staff fill in customer service gaps to offer a better, more convenient store experience. For example, automated kiosks coupled with smart lighting systems could help guide shoppers to specific items they are searching for. Data gathered by these kiosks can shed light on which items are popular and which items might be hard to find. Other robots can help stock shelves, face products and do other mundane tasks that might get skipped or postponed while the staff focuses on other customer service efforts. Plus, shoppers likely will welcome this added technology in the stores. Consumers today are very tech savvy and are accustomed to dealing with interactive technology. As a result, they want an interactive retail experience that embraces technology.

To say that retail analytics and reporting technology will be critical to the future of retail would be an understatement. Analytics is fundamental for a retailer to drive business, whether the goal is to sell more items, increase profits, offer better customer service experiences or all of the above. Retail data analytics and reporting can help store managers track and accommodate traffic flows, optimize product placement, encourage consumers to try new products or different brands and offer a seamless store experience that is closer to an e-commerce environment. Retailers need to invest in data analytics and reporting technology today so that they can gather actionable insights and deliver the store experiences desired by the consumers of tomorrow.