Precalculated Caller-Agent Pairs for Contact Routing
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Solution Overview
Problem
Conventional contact center routing systems rely on random matching processes, which do not consider the relative capabilities of agents and individual characteristics of callers, leading to suboptimal caller-agent pairings and inefficient resource allocation.
Innovation Solution
Implement a pattern matching algorithm to precalculate caller-agent pairs based on agent and caller data, storing scores in a look-up table for efficient retrieval during routing decisions, allowing for performance-based and affinity-driven matching to optimize interactions such as sales, cost, and customer satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If round-robin contact routing is used to connect callers to agents, then the routing process is simple and easy to implement, but the matching between callers and agents is essentially random and does not consider relative capabilities or individual characteristics
Solution Approach 1:
The system pre-calculates and stores caller-agent pairing scores in a lookup table before actual routing occurs. This preliminary computation of matching scores based on agent and caller characteristics allows for accurate, capability-based routing while maintaining simple operation during actual call handling.
2Reliability
If pattern matching algorithm is used to precalculate caller-agent pairs, then the likelihood of optimal interactions is enhanced, but the computational complexity increases
Solution Approach 1:
Complex pattern matching computations are performed in advance during system initialization or offline processing, with results stored in a lookup table. This separates the complex computational task from the real-time routing operation, maintaining high reliability while reducing operational complexity.
Solution Approach 2:
The system creates a simplified representation of the complex matching logic in the form of pre-computed lookup tables. Instead of executing complex algorithms during each routing decision, the system uses pre-generated match scores that replicate the optimal pairing decisions without the computational overhead.
3Measurement precision
If real-time pattern matching is performed for each routing decision, then optimal caller-agent pairing is achieved, but the execution time for routing engines increases
Solution Approach 1:
Matching scores are pre-computed and stored in a lookup table before routing decisions are needed. During actual routing, the system simply queries the pre-computed table rather than performing real-time pattern matching, achieving accurate matching while significantly reducing execution time.
Solution Approach 2:
The system uses a simplified lookup table structure that copies the essential matching information from complex real-time computations. This allows rapid retrieval of matching scores without re-executing the computationally intensive pattern matching algorithms during each routing decision.
Data Source
AI summary
Systems and methods are disclosed for preprocessing caller-agent pairs in a contact routing center, along with an intelligent routing system. A method includes determining at least one agent data for each agent of a set of agents, determining at least one caller data for each caller of a set of callers, and determining a score for each possible caller-agent pair of the set of agents and the set of callers using the agent data and the caller data in a pattern matching algorithm. The scores for each possible caller-agent pair may then be stored, e.g., in a look-up table, for retrieval, where matching a caller of the set of callers to an agent of the set of agents is based on the previously determined or calculated scores. For example, the caller-agent pair having the best score of all potential caller-agent pairs may be connected.