Using Beacons, Facial Recognition and Digital Displays for 1:1 Marketing
Whether in restaurants or banking, marketers face the challenge of creating an integrated, relevant and personalized experience across multiple channels. They must target a diverse set of customers with different needs based on demographics such as region, language, gender, economic strata, age and other factors. Emerging technologies, such as BLE/Beacons, facial recognition and digital displays can dovetail with research data to create personalized, relevant, real-time experiences that lead to enhanced targeting and conversion.
BLE-Beacons: Who, What, Where
BLE-Beacons use low-energy Bluetooth connections to trigger an action on a smartphone or tablet and will allow marketers to target a specific user for a personalized, one-to-one experience. In-store retail and offline payments are in the first wave of beacon applications, and the possibilities are nearly endless as marketers can communicate directly with and collect data from customers based on their geographic proximity. The applications and approaches, however, differ across industries. For example, utilizing mobile BLE capabilities, a marketer might see XYZ person is walking by the store. In the retail arena, that proximity provides an opportunity for focused one-on-one engagement—e.g. "She loves shoes, send her a coupon." However, in retail banking, that same incentive doesn't quite work—taking out a loan does not mean she loves loans. However, marketers can use existing data to see that individual has an educational saving plan, hasn't contributed recently and send a reminder to set aside funds.
Facial recognition gives marketers the ability to capture the characteristics of customers (age, race, gender) with a camera that does an algorithmic analysis of their faces to drive relevant messaging to the consumer. Banks can use facial recognition integrated with digital signage to profile and more accurately target their customers. For example, when XYZ individual walks into a bank branch, facial analysis tells the bank that a white woman, age 40 to 50, during this visit, has been watching ads on digital screens about university tuition and savings plans. This information allows the bank associate to better focus the conversation and digital advertising to that customer's needs and interests. Similarly, in markets where privacy is less of a concern (Asia) high-net-worth banks use a camera facing the front door to identify patrons and greet them by name for a transparent, one-to-one digital interaction.