Intelligent matrix customer obtaining management system based on AI reinforcement learning

The intelligent matrix customer acquisition management system, which utilizes AI-enhanced learning and multi-agent collaboration and deep Q-networks, solves the problem that existing systems cannot optimize customer acquisition strategies in complex market environments. It enables autonomous learning of customer acquisition strategies and multi-channel collaboration, thereby improving customer acquisition efficiency and customer conversion rates.

CN121660723AInactive Publication Date: 2026-03-13NINGBO JIAYUAN TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202511851402.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-10
Publication Date
2026-03-13
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Existing customer acquisition management systems are ill-suited to the complex and ever-changing market environment and lack multi-channel collaboration mechanisms, resulting in wasted customer acquisition resources and a decline in customer experience. Furthermore, existing systems cannot effectively optimize customer acquisition strategies.

Method used

An AI-based intelligent matrix customer acquisition management system is adopted. It achieves autonomous optimization of customer acquisition strategies through reinforcement learning algorithms, coordinates multiple channels through a multi-agent collaborative mechanism, and combines deep Q-networks and Markov decision processes to achieve autonomous learning and optimization of customer acquisition strategies.

Benefits of technology

It enables autonomous learning and adaptive adjustment of customer acquisition strategies, improving customer acquisition efficiency and conversion rates, breaking the problem of isolated information across multiple channels, and enhancing resource utilization efficiency and customer experience.

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Abstract

The invention discloses an intelligent matrix customer obtaining management system based on AI reinforcement learning, and relates to the technical field of machine learning, and the system comprises a data collection module which is used for collecting multi-source customer behavior data and constructing customer feature vectors, a state coding module which is used for coding the customer feature vectors, the system comprises a client feature vector encoding module for encoding a client feature vector into a state representation in a Markov decision state space, a deep Q network decision module for outputting a Q value of a client obtaining action based on a current state and selecting a client obtaining strategy, a multi-agent collaboration module for coordinating a plurality of channel agents to execute the client obtaining action, and a reward calculation module for calculating the client feature vector. According to the method, autonomous optimization of the customer obtaining strategy is realized through reinforcement learning, the customer conversion rate and the customer obtaining efficiency are improved, the customer obtaining cost is reduced, and intelligent and adaptive customer obtaining management is realized.
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