Customer Tracking Module for Service Business Identity Resolution
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Solution Overview
Problem
Service businesses face challenges in gaining a comprehensive understanding of their customers and operations, particularly in identifying customer information, especially for large-scale operations with numerous customers and properties, leading to potential unhappiness and unprofitability.
Innovation Solution
A system and method utilizing a customer tracking module that processes data from property databases to determine identifying information for customers, including unknown and known customers, by analyzing interactions with devices and drawing relationship mappings based on behavioral patterns and geolocation data, facilitating tasks such as converting unknown customers to registered ones and offering promotions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a service business manually tracks customer information, then it can maintain accurate customer records, but it becomes difficult to gain comprehensive understanding of all customers especially in large-scale operations
Solution Approach 1:
The patent replaces manual mechanical tracking methods with automated electronic data processing systems. The customer tracking module automatically collects, processes, and analyzes customer interaction data from multiple devices and properties, eliminating the need for manual record-keeping while comprehensively tracking all customers in large-scale operations.
Solution Approach 2:
The patent introduces a customer tracking module as an intermediary system between various business operations and customer information management. This module serves as a central hub that aggregates data from different devices, properties, and interaction points, enabling comprehensive customer understanding without direct manual intervention at each point of contact.
2Quantity of substance
If a service business expands to large-scale operations with multiple properties, then it can serve more customers, but it becomes difficult to determine identifying information for all customers
Solution Approach 1:
The customer tracking module is designed as a universal system that can handle customer identification across multiple properties and devices. It performs multiple functions including data collection, customer identification, relationship mapping, and behavioral analysis, enabling the business to maintain comprehensive customer information across expanded operations without proportionally increasing complexity.
3Device complexity
If a service business uses traditional customer management methods, then it can maintain simple operations, but it cannot effectively understand customer relationships and behaviors
Solution Approach 1:
The patent segments customer information management into distinct functional components: data collection from interactions, customer identification, relationship mapping, and behavioral pattern analysis. This segmentation allows the system to handle complex analytical tasks while maintaining manageable operational complexity through modular processing steps.
Solution Approach 2:
The patent adds a new dimension of analysis by creating relationship mappings between customers and analyzing behavioral patterns over time. This transforms traditional single-dimension customer records into multi-dimensional customer profiles that include relationships with other customers, behavioral trends, and interaction patterns across different properties and devices.
Data Source
AI summary
Systems and methods for determining identifying information associated with a customer of a service business are disclosed. Data indicative of assets associated with a service business may be received from at least one database. Data indicative of a plurality of interactions with at least one device of the service business may be determined based on the data indicative of assets associated with the service business. An identity associated with at least one customer of the service business may be determined based on the data indicative of the plurality of interactions with the at least one device of the service business. The identity may indicate, for example, a identify of an unknown customer of the service business. As another example, the identify may indicate a relationship between two known customers of the service business.