Communication Process Flow Paths for Automated Action Variations
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Solution Overview
Problem
Generating a large quantity of paths for communication process flow variations is time-consuming and inefficient due to the manual generation of action variation combinations, leading to unreliable and inefficient results.
Innovation Solution
Utilizing artificial intelligence (AI) and machine learning (ML) models to automatically generate paths for each possible combination of action variations in communication process flows, dynamically allocate traffic based on performance metrics, and update models to improve path efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual generation of action variation combinations is used, then communication process flow paths can be generated, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system performs self-service by automatically generating communication process flow paths using AI/ML models without requiring manual intervention. The models autonomously create multiple action variation combinations and generate corresponding paths, eliminating the need for human operators to manually construct each path variation.
Solution Approach 2:
The patent replaces the manual mechanical process of path generation with an automated intelligent system. AI/ML models substitute the manual operational mechanism, using algorithms to generate paths based on performance metrics and automation events, thereby dramatically improving efficiency and reducing time consumption.
2Reliability
If multiple action variations are implemented, then communication effectiveness can be improved, but the complexity of managing multiple paths increases
Solution Approach 1:
The system changes parameters dynamically by adjusting which action variations are applied to which users based on performance metrics and automation events. Instead of manually managing complex path configurations, the system automatically modifies action parameters (such as sending different numbers of emails, varying email content, or adjusting timing) based on real-time performance data, thereby improving reliability without increasing management complexity.
3Productivity
If automated AI/ML models are used to generate paths, then path generation efficiency improves, but the complexity of the system increases
Solution Approach 1:
The patent introduces an intermediary layer of AI/ML models that mediate between the input data (performance metrics, automation events) and the output (generated communication paths). This intermediary automatically processes information and generates paths without requiring complex manual configuration, thereby improving generation speed while managing system complexity through automated intelligence rather than manual processes.
Data Source
AI summary
A computing device of a data processing system may receive an indication from a user to create a communication process flow that includes a set of actions that control electronic communications between an entity and a set of users. The computing device may further receive one or more user inputs that indicate at least two first action variations of a first action of the set of actions and at least two second action variations of a second action of the set of actions. The system may then generate the communication process flow to include a set of paths for a set of combinations of the at least two first action variations and the at least two second action variations based on receiving the one or more user inputs. The system may then execute the communication process flow that includes the set of paths for the set of users.