Cross-Channel Query Deduplication in Contact Centers
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Solution Overview
Problem
Contact centers face inefficiencies and increased costs due to customers submitting similar queries across different digital channels, leading to duplicated efforts and inconsistent responses, which can frustrate customers and waste agent time.
Innovation Solution
A computerized method and system that identifies similar queries across multiple channels by using a stream processing application to store query data, filtering queries with common topics, employing Natural Language Understanding to identify identical queries, and determining a primary channel for resolution based on lowest wait time, thereby reducing queue volumes and improving agent efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If customers are allowed to access multiple digital channels freely, then customer service coverage and accessibility are improved, but duplicated query handling and agent workload increase
Solution Approach 1:
The patent merges multiple channel queries into a unified view by implementing cross-channel query identification. When a customer submits a query on one channel and then submits another query on a different channel, the system detects that these are duplicate queries and consolidates them, allowing agents to handle them together rather than separately across different channels.
Solution Approach 2:
The system creates a universal query identification mechanism that works across all digital channels (web, mobile, social media, email). The query identification module universally detects duplicate queries regardless of which channel they originate from, enabling a single agent workflow to serve multiple channels efficiently.
2Reliability
If agents handle each channel query separately, then channel-specific service quality is maintained, but response time increases and customer satisfaction decreases
Solution Approach 1:
The system performs preliminary identification and grouping of duplicate queries before they reach the agent. The query identification module automatically detects duplicate queries across channels and prepares consolidated work items in advance, so when agents receive them, the duplication work has already been eliminated, reducing their handling time.
Solution Approach 2:
The patent introduces an intermediary query identification module and workflow consolidation mechanism between the multiple channels and the agents. This intermediary layer detects duplicate queries, consolidates them into single work items, and presents them to agents in a unified manner, thereby reducing agent workload while maintaining service quality.
3Ease of operation
If duplicate queries are handled across multiple channels, then comprehensive customer support is provided, but operational costs and resource waste increase
Solution Approach 1:
The system extracts and removes duplicate query instances from the workflow. By identifying queries that are duplicates across channels and eliminating redundant handling steps, the system keeps only one instance of each unique query for agent processing, thereby reducing operational waste while preserving customer support accessibility.
Solution Approach 2:
The patent discards duplicate query submissions after the first instance is captured. When the system detects that a customer has already submitted a query on one channel and then submits another query on a different channel about the same issue, it discards the duplicate and recovers the resources that would have been spent handling it separately.
Data Source
AI summary
A computerized-method for improving queries operation in a multichannel contact center is provided herein. The computerized-method includes: (i) operating a stream processing application for each new query of a customer to store query-related data and to identify one or more queries of the customer in a cloud-contact data store. The cloud-contact data store may have one or more interactions-queue types, when one or more queries have been identified: (a) operating a repetition module on the identified one or more queries of the customer to filter out two or more queries having a common query-topic; (b) operating a Natural Language Understanding (NLU) module on the filtered two or more queries having a common topic to identify two or more identical queries. Each query of the identified two or more identical queries have a unique query identification number; and (c) handling the two or more identical.