Cross-Channel Intent Modeling for Consistent User Engagement
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Solution Overview
Problem
Existing communication channels within organizations often fail to coordinate messaging consistently across different channels, leading to frustration for customers who must repeat information when switching channels, such as from chat to phone.
Innovation Solution
A system that captures and organizes interaction data across multiple channels, using a trained intent model to predict user intent, ensuring consistent messaging and interaction across all channels based on user history and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple independent communication channels are used to engage customers, then the organization can provide diverse communication options, but the messaging becomes inconsistent across channels
Solution Approach 1:
The patent merges multiple independent communication channels into a unified system by implementing a central data warehouse that consolidates customer interaction data from all channels (phone, email, chat, social media). This centralization enables consistent messaging across diverse channels while preserving channel-specific communication styles, resolving the contradiction between channel diversity and messaging consistency.
Solution Approach 2:
The patent creates a universal platform that serves multiple communication functions across different channels. The system uses a single customer view and unified data warehouse that can be accessed by all communication channels, enabling each channel to maintain its unique characteristics while adhering to consistent organizational messaging guidelines.
2Ease of operation
If communication channels operate independently without coordination, then each channel can be managed separately, but customers must repeat information when switching channels
Solution Approach 1:
The patent implements preliminary action by capturing and storing customer interaction data in a centralized data warehouse as interactions occur across any channel. This pre-consolidation of data ensures that when customers switch channels, their information is already available in the unified system, eliminating the need to repeat information and reducing time loss.
Solution Approach 2:
The patent introduces a central data warehouse and unified customer view as intermediaries between independent communication channels. This intermediary layer enables seamless information sharing across channels while allowing each channel to operate with relative independence, resolving the contradiction between management simplicity and information continuity.
3Device complexity
If channels cannot coordinate or change messaging based on customer feedback, then channel operations remain simple, but customer satisfaction decreases due to inconsistent experiences
Solution Approach 1:
The patent implements comprehensive feedback mechanisms that capture customer interactions, sentiments, and outcomes across all communication channels. This feedback is consolidated in the unified data warehouse and used to continuously improve messaging consistency and customer experience. The system enables real-time and historical analysis of customer feedback to refine communication strategies across channels.
Solution Approach 2:
The patent creates a dynamic system where messaging and communication strategies can adapt based on real-time customer feedback and interaction history. The unified customer view and centralized data warehouse enable flexible adjustment of messaging across channels while maintaining coordination, allowing the organization to respond dynamically to customer needs without excessive complexity.
Data Source
AI summary
Disclosed are various embodiments facilitating a holistic engagement with a user across multiple communication channels of an organization or an enterprise based at least in part on a determined user intent. As users interact with various services associated with the organization through one or more communication channels, interaction data can be captured and stored. In various examples, the interaction data that is stored by the various services can be obtained and organized according to a predefined schema. The organized interaction data can be applied to a trained intent model that outputs a user intent based at least in part on observations of other users with similar histories. The predicted intent can be provided to the different services such that subsequent interactions between the user and the organization can be based at least in part on the intent in a consistent manner, regardless of the communication channel associated with the interaction.