IoT Sensor Lead Scoring for Brick-and-Mortar Retail
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Solution Overview
Problem
Retailers and marketers lack the ability to gather and analyze consumer interactions in brick-and-mortar stores, missing opportunities to provide information or market products to consumers who have shown genuine interest, as the interaction data available for online transactions is not applicable to physical stores.
Innovation Solution
Implementing IoT devices and consumer devices with sensors to collect and analyze data on consumer interactions in brick-and-mortar stores, such as proximity, facial expressions, and product handling, to determine a leads score indicating the consumer's interest level, which triggers lead generation when exceeding a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If online transaction data collection methods are used, then consumer interaction information is available for online purchases, but interaction data is unavailable for brick-and-mortar store visits
Solution Approach 1:
The patent introduces IoT devices as intermediary components between consumers and retailers in brick-and-mortar stores. These devices include sensors, cameras, and other detection equipment that capture consumer interactions with products. The intermediary devices translate physical interactions into digital data, enabling the collection of interaction information in physical stores similar to how online transactions are tracked.
Solution Approach 2:
The patent replaces manual or mechanical data collection methods with automated electronic sensing systems. Instead of relying on consumers providing information or retailers manually observing interactions, the system uses electronic sensors, cameras, and IoT devices to automatically detect and record consumer behaviors, product handling, and interactions within the brick-and-mortar environment.
2Loss of information
If sensor data collection is implemented in brick-and-mortar stores, then consumer interaction data becomes available, but data collection complexity increases
Solution Approach 1:
The patent employs multi-functional IoT devices that can perform multiple data collection tasks simultaneously. A single device may capture consumer location, track product interactions, record demographic information, and monitor store traffic patterns all at once. This universality reduces the overall number of devices needed and simplifies the system architecture while still gathering comprehensive interaction data.
Solution Approach 2:
The sensor data collection system is designed to operate autonomously without requiring manual intervention. Sensors automatically detect consumer presence and interactions, devices self-calibrate and self-monitor, and the system continuously collects and processes data without human assistance. This self-service capability reduces operational complexity and maintenance requirements despite the sophisticated technology involved.
3Productivity
If lead generation is triggered by interaction threshold, then marketing resources are focused on interested consumers, but early interest signals may be missed
Solution Approach 1:
The system performs preliminary analysis of consumer interaction data to identify early signs of purchase interest before the consumer reaches the traditional conversion point. By analyzing interaction patterns, dwell time, product handling behaviors, and movement trajectories, the system proactively identifies potential leads in advance, allowing marketers to engage consumers while their interest is still developing rather than waiting for a threshold to be met.
Solution Approach 2:
The system implements continuous feedback loops where consumer interaction data is constantly monitored, analyzed, and used to adjust lead scoring in real-time. As consumers interact with products, the system provides immediate feedback by updating interest level assessments and triggering appropriate marketing responses. This dynamic feedback mechanism ensures that early interest signals are captured and acted upon promptly while maintaining resource efficiency.
Data Source
AI summary
Techniques for generating leads for consumers using IoT devices at brick-and-mortar stores are provided. A retailer can determine a consumer's level of interest in a product and provide information or other benefits to the consumer. In some embodiments, sensor data from at least one of one or more consumer devices or IoT devices are received, the sensor data being indicative of interaction of a consumer with a product. One or more interactions of the consumer with the product are determined based on the received sensor data. An interaction database is searched for an interaction mapped to specific sensor data requirements matching the received sensor data. A leads score is calculated based on the one or more interactions, the leads score indicating an interest level of the consumer in the product. When the leads score exceeds a threshold, a lead is generated for the consumer.