Agenda-Driven Chatbot for User Journey Personalization
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Solution Overview
Problem
Current chatbot systems lack comprehensive and seamless conversational support for user journeys, particularly in handling temporary or long-term suspensions, and fail to effectively personalize user experiences across multiple touchpoints.
Innovation Solution
A system employing agenda-driven conversational support using chatbots that dynamically update user interactions based on user behavior, previous conversations, and personal data, allowing for goal-oriented conversations across various touchpoints, and enabling suspension and resumption of conversations with reminders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If chatbot systems provide comprehensive conversational support across multiple touchpoints, then user journey personalization improves, but system complexity increases
Solution Approach 1:
The system segments the user journey into distinct stages (awareness, consideration, decision, retention) and deploys specialized chatbots for each stage. Each chatbot is configured with specific agendas and capabilities appropriate to its stage, rather than using a single monolithic chatbot system. This segmentation allows personalized support across multiple touchpoints while managing complexity through modular design.
Solution Approach 2:
The patent implements a universal chatbot framework that can operate across multiple platforms and touchpoints (website, mobile app, social media, offline locations) with consistent personalization capabilities. The system uses unified user profiles, shared agenda structures, and cross-platform conversation history to provide adaptable support universally across different channels without requiring separate systems for each touchpoint.
2Loss of information
If chatbot systems monitor user behavior and update agendas dynamically, then conversation relevance improves, but information processing requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-defining agenda structures, conversation templates, and decision trees before user interactions occur. Chatbots are pre-configured with potential user needs, common questions, and appropriate responses for different journey stages. This preliminary preparation reduces real-time processing requirements while maintaining high conversation relevance through dynamic agenda updates based on actual user behavior.
Solution Approach 2:
The system implements continuous feedback loops where user responses and behavior patterns are monitored and fed back to dynamically update conversation agendas and personalization parameters. This feedback mechanism allows the chatbot to adapt to user needs in real-time, maintaining high relevance without requiring complete reprocessing of all user data. The feedback-driven agenda updates optimize information processing by focusing only on relevant user signals.
3Ease of operation
If chatbot systems support user journey suspensions and resumptions, then user convenience improves, but conversation management complexity increases
Solution Approach 1:
The system implements self-service capabilities where the chatbot automatically detects user suspensions (inactivity, explicit cancellation) and autonomously manages conversation state preservation and resumption. When users return, the chatbot automatically retrieves saved conversation context, updates agendas based on elapsed time, and continues seamlessly without requiring manual intervention from support agents. This automation improves user convenience while managing complexity through rule-based suspension handling.
Solution Approach 2:
The patent ensures continuity of useful action by maintaining persistent conversation states and agenda structures even during user suspensions. The system continuously updates user profiles, preserves conversation history, and keeps agendas synchronized with current user journey stages. When users resume, the chatbot immediately restores the appropriate conversation context and continues providing relevant support, eliminating gaps in service and maintaining continuous value delivery despite interruptions.
Data Source
AI summary
Interacting with a user of an electronic device includes presenting information to the user on a screen of the electronic device, a first chatbot that corresponds to the information presented to the user engaging in a conversation with the user based on an agenda that is related to the information presented to the user, the first chatbot recommending an action to the user based at least in part on the conversation and on the agenda, and updating the agenda and presenting new information on the electronic device in response to an action performed by the user. The agenda may be customized for the user based on available information about the user. Information about the user may include information about user behavior, previous actions performed by the user, previous user conversations with chatbots, and/or user personal data. The first chatbot may answer questions by the user about the information.