Web Visitor Tracking System with Persistent Customer Profiles
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Solution Overview
Problem
Existing call center systems lack a comprehensive and real-time understanding of Web visitors' behavior and preferences, leading to inefficient proactive contact methods that fail to convert potential customers due to incomplete data profiles and lack of channel-independent information access.
Innovation Solution
A unique Web-monitoring system with persistent data storage and retrieval methods that tracks and records visitor behavior across multiple channels, providing agents with rich, real-time information for intelligent customer targeting and service, using scripts to monitor navigation, search, and shopping cart interactions, and enabling messaging through various channels like email, SMS, and phone calls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If Web monitoring systems aggregate information rather than store it on an individual basis, then data storage efficiency is improved, but the completeness and personalization of customer profiles deteriorates
Solution Approach 1:
The system segments customer data into individual profiles, storing each customer's behavior, preferences, and interaction history separately rather than aggregating all data together. This segmentation enables personalized marketing while maintaining storage efficiency through structured organization of discrete customer records.
Solution Approach 2:
The system adds a new dimension of data organization by creating individual customer profiles that track behavior across multiple channels and time periods. This dimensional approach transforms flat aggregated data into multi-dimensional customer views, enabling richer personalization without proportionally increasing storage requirements.
2Loss of information
If Web monitoring systems provide real-time information about individual visitors, then the personalization and effectiveness of proactive contact is improved, but the complexity of the system increases
Solution Approach 1:
The system performs preliminary actions by pre-collecting and organizing customer data into structured profiles before proactive contact is needed. Behavior tracking, preference capture, and channel information are gathered and organized in advance, so when proactive contact occurs, personalized information is immediately available without complex real-time processing.
Solution Approach 2:
The system introduces intermediary components including customer profiles as data structures, behavior tracking modules, and integration interfaces that mediate between raw data collection and proactive contact delivery. These intermediaries simplify the overall system architecture by creating clear layers of data processing and management.
3Productivity
If call centers use limited customer information for proactive contact, then the simplicity of the contact process is maintained, but the success rate of transaction closing deteriorates
Solution Approach 1:
The system implements feedback loops where customer behavior data, preference information, and channel interactions are continuously collected and fed back into updated customer profiles. This feedback mechanism ensures that proactive contact campaigns are based on the most current and comprehensive customer information available, improving targeting accuracy and transaction closing rates.
Solution Approach 2:
The system changes key parameters of customer understanding by tracking multiple behavior dimensions including navigation patterns, search history, shopping cart activities, and channel preferences. By capturing and utilizing these varied parameters, the system transforms limited contact information into rich customer profiles that enable highly effective personalized marketing.
4Adaptability or versatility
If information about Web visitors is not maintained after contact, then the simplicity of the contact process is preserved, but the ability to provide consistent service across channels deteriorates
Solution Approach 1:
The system creates universal customer profiles that serve multiple functions across different contact channels. The same profile structure and data elements are used whether the customer interacts via Web, phone, email, or other channels, ensuring consistent service delivery. This multi-functional approach eliminates information silos and enables seamless cross-channel customer experiences.
Data Source
AI summary
A system for interacting with a person browsing a web site has an Internet-connected server and a connected data repository, and software executing on the server from a non-transitory physical medium. The software provides an identity function identifying the person, a selection function checking the data repository for stored information regarding the identified person, including any tracking rules associated with the identified person, and one or more tracking functions monitoring and recording behavior of the person browsing the web site. The one or more tracking functions follow the tracking rules, if any, associated with the identified person in monitoring and recording behavior of the browsing person.