Retail CRM System Using Mobile Device Proximity Detection
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Solution Overview
Problem
CRM systems are underutilized in retail settings, primarily limited to data collection and transaction processing, failing to leverage their full potential in enhancing customer relationships and sales processes.
Innovation Solution
A novel method and system that detects customer mobile devices entering a physical space, creates opportunity records for products, and triggers CRM actions such as messaging and coupon transmission based on customer interactions and purchases, enabling more comprehensive CRM functionality in retail environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CRM systems are integrated with point of sale systems for data collection and transaction processing, then customer data management capability is improved, but system complexity increases
Solution Approach 1:
The patent combines multiple previously separate functions into a unified CRM system: mobile device detection, product proximity sensing, opportunity record creation, and point of sale integration are merged into a single system architecture. This consolidation improves data management reliability while managing complexity through integrated design rather than separate interconnected systems.
Solution Approach 2:
The CRM system is designed to perform multiple functions: it detects mobile devices, tracks product interactions, creates opportunity records, processes transactions, and sends communications. This multi-functional approach improves overall system capability while reducing the need for multiple separate systems, thereby managing complexity.
2Adaptability or versatility
If CRM systems track customer interactions and create opportunity records in real-time, then customer engagement quality is improved, but data processing requirements increase
Solution Approach 1:
The system creates opportunity records in advance when customers interact with products, before the actual purchase decision is made. This preliminary action allows the system to prepare and organize data structures ahead of time, improving engagement quality while managing data processing loads by spreading work over time rather than concentrating it at the point of sale.
Solution Approach 2:
The system automatically detects mobile devices, tracks product interactions, and creates opportunity records without requiring manual data entry or intervention. This self-service approach improves engagement quality through continuous tracking while reducing the processing burden on human operators, though automated data processing requirements increase.
3Productivity
If the system detects mobile device proximity to products and creates opportunity records, then sales opportunity identification is improved, but measurement precision requirements increase
Solution Approach 1:
The system uses mobile devices as intermediaries between the customer and the product. Rather than directly measuring customer proximity to products, the system detects the customer's mobile device, which serves as a proxy for customer location and interaction. This intermediary approach improves sales opportunity identification while reducing the precision requirements for direct customer-product measurement.
Data Source
AI summary
Embodiments of the invention provide a method, system and computer program product for retail deployed CRM. A CRM method for retail environments includes sensing entry of a mobile device into a physical space and identifying a customer record for a customer in a CRM system associated with the detected mobile device. The method also includes thereafter detecting a proximity of the mobile device to a product stored in the physical space and creating an opportunity record in the CRM system in connection with the customer for the product. Finally, the method includes responding to sensing egress of the mobile device from the physical space, by marking the opportunity record as closed-won if the product has been purchased by the customer.