Real-Time Opt-In Conversation Bots with Intent Detection
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Solution Overview
Problem
Existing systems lack an efficient and automated method to determine whether to present opt-in offers for supplemental communications with users in real-time during interactions, often leading to inefficiencies and missed opportunities for engagement.
Innovation Solution
An automated bot system dynamically processes real-time messages to identify user intents and offers opt-in opportunities, facilitating a second communication channel for confirmation, and uses machine learning to refine its decisions based on user feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated bots process messages in real-time to identify opt-in opportunities, then user engagement is enhanced, but system complexity increases
Solution Approach 1:
The system is divided into distinct functional modules: a message processing module that analyzes ongoing messages, an intent identification module that determines user intent, and an opt-in offer module that presents opportunities. This segmentation allows each component to specialize in specific tasks, improving overall efficiency while managing complexity through modular design.
Solution Approach 2:
An integration bot acts as an intermediary between the automated bot system and the user's contact information system. The integration bot facilitates the second communications session by transmitting opt-in confirmation requests and receiving confirmations, mediating the complex interaction between systems while maintaining real-time processing capabilities.
2Productivity
If the system presents opt-in offers during ongoing communications sessions, then supplemental communication opportunities increase, but risk of user annoyance increases
Solution Approach 1:
The system continuously monitors the communications session in real-time to detect user responses to opt-in offers. By processing ongoing messages and analyzing user intent dynamically, the system can detect signs of user disinterest or annoyance and adjust its behavior accordingly, such as withdrawing the offer or switching to a different communication strategy.
Solution Approach 2:
The opt-in offer presentation is dynamic rather than static. The system generates instructions to present offers based on real-time analysis of the conversation context, user intent, and engagement signals. This dynamic approach allows the offer timing, content, and delivery method to adapt to the evolving conversation state, reducing the risk of user annoyance.
3Measurement precision
If real-time message processing is implemented to detect user intent, then accuracy of opt-in identification improves, but computational resources increase
Solution Approach 1:
The system applies partial processing by focusing computational resources on key aspects of message analysis rather than processing every element of every message in full detail. The bot identifies and prioritizes specific intent indicators and contextual signals that are most predictive of opt-in opportunities, achieving high accuracy while reducing overall computational burden.
Data Source
AI summary
Disclosed embodiments provide a framework for implementing automated bots configured to automatically and in real-time process messages exchanged with a user to determine whether to present an opt-in offer for supplemental communications. An agent bot processes ongoing messages exchanged in real-time during a first communications session as these messages are exchanged to determine whether to present an opt-in authorization request for supplemental communications. If the user approves the request, contact information associated with the user is used to facilitate a second communications session through which the user is prompted to provide an opt-in confirmation. The opt-in confirmation and the approval of the opt-in authorization request is provided to allow for transmission of the supplemental communications to the user.