The sensors know you want one.[/caption] Big Data: Now available in Aisle 5. Mondelēz International, manufacturer of diet-killing snacks such as Oreos, Wheat-Thins, and Ritz crackers, plans to build a sensor-studded grocery shelf that analyzes approaching faces and bodies—the better to build databases of potential customers. On the hardware side of things, the “smart shelf” will rely on Microsoft Kinect—a motion-sensing device originally built as an Xbox video-game controller—as an integral component. “When people walk by, it’s a missed opportunity. We must know how the consumer behaves in the store,” Mondelēz CIO Mark Dajani is quoted as telling The Wall Street Journal. Mondelēz isn’t the first company to plunge deeply into retail data: multiple startups are using analytics to either improve the shopping process or improve the flow of information between retailers and consumers. St. Louis-based Food Essentials, for example, compiles information about food products into a single database, which various clients—including the U.S. Food and Drug Administration—use as part of their own analysis into customer habits. Aisle411, another St. Louis startup, creates recommendation and mapping tools for shoppers. In theory, customers could take things one step further by connecting a database of their shopping behavior with, say, an analytics tool run by a primary caregiver, which would give their physicians insight into their eating and lifestyle habits. Consumer data also plays a large role in predictive analytics; retailers such as Target can look at shopping patterns to predict who may be pregnant, for example, and make sure they receive baby-related offers. But customers also react badly to invasions of privacy, and Mondelēz—or any other company tiptoeing into the shopping analytics field—must remain aware of how quickly public sentiment can turn against a program viewed as too intrusive. Shelf-based sensors that collect customer data in aggregate is one thing; sensors that determine an individual’s identity and make extremely specific recommendations might be viewed as a miracle by some, but will probably attract negative attention (and possibly lawsuits) from those leery of being analyzed in public. As that great retail entrepreneur Walter White once said: “Tread lightly.” Image: Curioso/Shutterstock.com The “Smart Shelf” That Collects Customer Data
[caption id="attachment_13192" align="aligncenter" width="500"] The sensors know you want one.[/caption] Big Data: Now available in Aisle 5. Mondelēz International, manufacturer of diet-killing snacks such as Oreos, Wheat-Thins, and Ritz crackers, plans to build a sensor-studded grocery shelf that analyzes approaching faces and bodies—the better to build databases of potential customers. On the hardware side of things, the “smart shelf” will rely on Microsoft Kinect—a motion-sensing device originally built as an Xbox video-game controller—as an integral component. “When people walk by, it’s a missed opportunity. We must know how the consumer behaves in the store,” Mondelēz CIO Mark Dajani is quoted as telling The Wall Street Journal. Mondelēz isn’t the first company to plunge deeply into retail data: multiple startups are using analytics to either improve the shopping process or improve the flow of information between retailers and consumers. St. Louis-based Food Essentials, for example, compiles information about food products into a single database, which various clients—including the U.S. Food and Drug Administration—use as part of their own analysis into customer habits. Aisle411, another St. Louis startup, creates recommendation and mapping tools for shoppers. In theory, customers could take things one step further by connecting a database of their shopping behavior with, say, an analytics tool run by a primary caregiver, which would give their physicians insight into their eating and lifestyle habits. Consumer data also plays a large role in predictive analytics; retailers such as Target can look at shopping patterns to predict who may be pregnant, for example, and make sure they receive baby-related offers. But customers also react badly to invasions of privacy, and Mondelēz—or any other company tiptoeing into the shopping analytics field—must remain aware of how quickly public sentiment can turn against a program viewed as too intrusive. Shelf-based sensors that collect customer data in aggregate is one thing; sensors that determine an individual’s identity and make extremely specific recommendations might be viewed as a miracle by some, but will probably attract negative attention (and possibly lawsuits) from those leery of being analyzed in public. As that great retail entrepreneur Walter White once said: “Tread lightly.” Image: Curioso/Shutterstock.com
The sensors know you want one.[/caption] Big Data: Now available in Aisle 5. Mondelēz International, manufacturer of diet-killing snacks such as Oreos, Wheat-Thins, and Ritz crackers, plans to build a sensor-studded grocery shelf that analyzes approaching faces and bodies—the better to build databases of potential customers. On the hardware side of things, the “smart shelf” will rely on Microsoft Kinect—a motion-sensing device originally built as an Xbox video-game controller—as an integral component. “When people walk by, it’s a missed opportunity. We must know how the consumer behaves in the store,” Mondelēz CIO Mark Dajani is quoted as telling The Wall Street Journal. Mondelēz isn’t the first company to plunge deeply into retail data: multiple startups are using analytics to either improve the shopping process or improve the flow of information between retailers and consumers. St. Louis-based Food Essentials, for example, compiles information about food products into a single database, which various clients—including the U.S. Food and Drug Administration—use as part of their own analysis into customer habits. Aisle411, another St. Louis startup, creates recommendation and mapping tools for shoppers. In theory, customers could take things one step further by connecting a database of their shopping behavior with, say, an analytics tool run by a primary caregiver, which would give their physicians insight into their eating and lifestyle habits. Consumer data also plays a large role in predictive analytics; retailers such as Target can look at shopping patterns to predict who may be pregnant, for example, and make sure they receive baby-related offers. But customers also react badly to invasions of privacy, and Mondelēz—or any other company tiptoeing into the shopping analytics field—must remain aware of how quickly public sentiment can turn against a program viewed as too intrusive. Shelf-based sensors that collect customer data in aggregate is one thing; sensors that determine an individual’s identity and make extremely specific recommendations might be viewed as a miracle by some, but will probably attract negative attention (and possibly lawsuits) from those leery of being analyzed in public. As that great retail entrepreneur Walter White once said: “Tread lightly.” Image: Curioso/Shutterstock.com 