Web Form Inquiry Contact Plan Automation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current web form response systems are inadequate in maximizing the potential of user inquiries, as they lack effective automated guidance for responding to user requests, leading to suboptimal contact success rates.
Innovation Solution
A system and method that involve providing a web form to users to collect contact data, retrieving additional user data, associating users with a preferred contact plan, and contacting them via various methods and schedules, utilizing a contact server to deliver information to agents, and an apparatus with modules for data collection, analysis, and contact plan generation to optimize contact attempts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated guidance is implemented to respond to web form inquiries, then contact success rates improve, but system complexity increases
Solution Approach 1:
The system is divided into distinct functional modules: a data collection module that gathers contact attempt records, a data analysis module that processes the records to identify patterns, a contact plan generation module that creates optimized contact plans, and a plan selection module that chooses appropriate plans for specific users. This segmentation allows each module to specialize in one aspect of the complex task, improving overall reliability while managing system complexity through modular design.
Solution Approach 2:
The system performs preliminary data collection and analysis to create contact plans before actual contact attempts are made. By pre-analyzing contact attempt records and generating optimized contact plans in advance, the system prepares guidance strategies beforehand, which improves contact success rates when the plans are executed without adding operational complexity during the actual contact process.
2Productivity
If multiple contact methods and schedules are utilized, then contact effectiveness improves, but operational complexity increases
Solution Approach 1:
The system automatically collects contact attempt records, analyzes the data to identify patterns and correlations, generates optimized contact plans, and selects appropriate plans for execution. This self-service automation eliminates the need for manual configuration of multiple contact methods and schedules, improving contact effectiveness while reducing operational complexity by removing human intervention from the process.
Solution Approach 2:
The system continuously collects feedback from contact attempt records, including information about successful and unsuccessful contact attempts. This feedback is analyzed to refine and optimize contact plans, allowing the system to learn from past outcomes and improve future contact effectiveness. The feedback loop enables automatic adjustment of contact strategies without increasing operational complexity.
3Reliability
If user data is collected and analyzed to optimize contact attempts, then contact success rates improve, but data processing requirements increase
Solution Approach 1:
The system extracts only the most relevant features and patterns from contact attempt records that are necessary for optimizing contact success. Rather than processing all raw data, the data analysis module identifies and extracts key correlations between contact outcomes and various factors such as contact time, method, and user characteristics. This selective extraction reduces data processing requirements while maintaining high contact success rates.
Data Source
AI summary
An apparatus, system, and method are disclosed for generating contact plans and responding to web form inquires using the contact plans.