Web Visitor Behavior Scoring for Sales Prospect Qualification
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Solution Overview
Problem
E-commerce websites face challenges in effectively qualifying sales prospects based on visitor behavior analysis, as existing methods lack comprehensive and efficient tools to track and analyze visitor interactions before and after conversion events.
Innovation Solution
A system utilizing program code executed on a server to monitor time spent on web pages, calculate a numeric web behavior qualification score by multiplying page weights with visit durations, and store data in log files for prospect qualification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive visitor behavior tracking is implemented to improve prospect qualification accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The tracking system is segmented into multiple independent components: page view tracking, form submission tracking, time spent calculation, and score generation. Each component handles a specific aspect of visitor behavior analysis, making the overall system more manageable and less complex while maintaining comprehensive tracking capabilities
Solution Approach 2:
A server acts as an intermediary between the website and the analysis system. The server collects raw visitor data, processes it through standardized procedures, and generates qualification scores. This intermediary layer simplifies the architecture by centralizing complex processing logic and providing a clean interface for data collection and score delivery
2Loss of information
If detailed visitor behavior data is collected before and after conversion events, then information completeness is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary tracking of visitor behavior from the moment they arrive at the website, continuously collecting data on pages viewed, time spent, and navigation patterns. This preliminary action ensures that when a conversion event occurs, all necessary pre-conversion data is already captured and ready for immediate analysis, eliminating delays in data collection
Solution Approach 2:
The tracking system operates continuously throughout the visitor's session, maintaining uninterrupted data collection both before and after conversion events. This continuous tracking ensures complete information capture without requiring separate data collection phases, thereby reducing overall processing time while maintaining data completeness
3Productivity
If manual analysis of visitor behavior is used to maintain simplicity, then device complexity is reduced, but productivity decreases
Solution Approach 1:
The system is designed to automatically calculate qualification scores by self-service processing of visitor behavior data. The server autonomously collects tracking information, applies weighting factors to different behaviors, computes scores, and delivers results without requiring manual intervention. This automation dramatically improves productivity while keeping the interface simple for users
Solution Approach 2:
The system uses parameter changes in the form of weighting factors assigned to different visitor behaviors (e.g., time spent on pages, form submissions, navigation patterns). By automatically adjusting and applying these parameters to visitor data, the system efficiently generates qualification scores without manual analysis, improving productivity while maintaining manageable complexity through standardized parameter sets
Data Source
AI summary
A web data analysis system, computer software product, and method of operation thereof, that uses Internet based data sources, and which operates in an automated manner to collect weighted visitor behavior statistics, and consolidate collected data into a single qualification score to accompany and supplement the entry of web site visitor information for printing, distribution or entry into a sales, prospect or contact management system.


