Method And System For Customer Assistance In A Retail Store

What is this patent about?

’890 is related to the field of monitoring and analyzing consumer behavior, specifically within retail environments. Brick-and-mortar retailers face challenges from online competition, including showrooming, where customers browse in-store but purchase online. They lack the data-driven personalization capabilities of online retailers and struggle to provide relevant, timely information to influence purchasing decisions. Existing methods for understanding consumer behavior, such as POS data, focus groups, and surveys, are limited in scope and often provide only after-the-fact insights.

The underlying idea behind ’890 is to create a system that monitors and analyzes consumer purchasing behavior in real-time within a physical retail store, enabling personalized and targeted digital customer experiences. This is achieved by using a network of information monitoring devices to gather data about customers, including their demographics, sentiment, product interests, and location within the store. This data is then analyzed to provide real-time responses designed to influence purchasing decisions and improve the overall shopping experience.

The claims of ’890 focus on a method that uses information monitoring devices to gather data about a person in a retail store, analyzes this information in real-time, and provides a response based on the analysis. The information gathered includes object identification of products the person is interested in and their sentiment towards those products. The real-time analysis is used to manage inventory. The response can take various forms, such as directing the person to a product location, engaging them with targeted content on displays, alerting a store employee to assist them, providing personalized marketing or advertising, or offering a relevant coupon.

In practice, the system uses cameras, sensors, and Wi-Fi tracking to gather data about customers as they move through the store. Demographic intelligence modules analyze facial features to estimate age, gender, and sentiment. MAC address tracking identifies repeat customers and tracks their movements. Object identification modules recognize products that customers interact with. This information is then used to trigger personalized responses, such as displaying relevant product reviews on nearby screens or sending targeted promotions to the customer's mobile device.

This approach differentiates itself from prior solutions by providing a comprehensive, real-time view of consumer behavior within the store. Unlike traditional methods that rely on after-the-fact data or limited observation techniques, ’890 actively monitors and responds to customer behavior in the moment. By integrating various data sources and analytical modules, the system enables retailers to deliver personalized experiences that rival those of online retailers, ultimately driving sales and improving customer loyalty. The use of real-time inventory management based on customer behavior is also a key differentiator.