Call center system

Abstract

The invention relates to a call center system, which comprises an access module, a routing module, a service processing module, a data management module and a monitoring maintenance module, the modules are communicated through standardized interfaces, and intelligent routing and distribution are carried out by using a distribution algorithm in combination with customer historical data, current requirements and seat states. The system supports client requests of various channels such as telephone, short message, e-mail, social media, webpage chat and the like, and utilizes an intelligent routing algorithm, such as a shortest path algorithm, to optimize request distribution and improve response speed and client satisfaction.

Description

Technical Field

[0001] The invention belongs to the field of communication technology, and in particular relates to a call center system. Background Art

[0002] With the growing demand for corporate services, traditional call centers are facing problems such as poor system scalability, slow response, low resource utilization, and high costs. The existing call center architecture is often difficult to adapt to the rapidly changing market demand and the diversification of customer service models. Therefore, it is particularly important to design an efficient, flexible, and scalable call center architecture solution. Summary of the invention

[0003] (I) Purpose of the invention

[0004] In order to overcome the above shortcomings, the purpose of the present invention is to provide a call center system to solve the above technical problems.

[0005] (II) Technical solution

[0006] To achieve the above objectives, the technical solutions provided by this application are as follows:

[0007] A call center system includes an access module, a routing module, a business processing module, a data management module, and a monitoring and maintenance module. The modules communicate with each other through standardized interfaces. At the same time, the allocation algorithm is used to perform intelligent routing and allocation in combination with customer historical data, current needs, and agent status.

[0008] The access module is the front-end interface of the call center system, responsible for receiving customer requests from various channels and converting these requests into a format recognizable within the system and passing them to subsequent processing modules;

[0009] The routing module distributes the access request to a suitable business processing module or customer representative according to a distribution algorithm;

[0010] The business processing module is the core of the call center system and is responsible for processing customer requests and executing specific business logic;

[0011] The data management module is responsible for collecting, storing, analyzing and reporting all data generated during the call center operation;

[0012] The monitoring and maintenance module is responsible for monitoring the operation status of the call center, including system performance, resource utilization and fault warning.

[0013] Preferably, the smart router has an independent operating system, allowing users to install various applications by themselves to achieve richer network functions. The smart router supports QOS function and can limit bandwidth according to IP and service type to ensure smooth operation of key applications. The smart router supports multi-WAN access, wireless roaming, and wireless AP scanning.

[0014] Preferably, the smart router has a built-in firewall, supports IP address, MAC address, and domain name address filtering, can flexibly control Internet access permissions and time, ensure network security, and supports remote Web management. Users can configure and monitor the router through a browser, which is convenient and fast.

[0015] Preferably, the allocation algorithm is a shortest path algorithm, comprising the following steps:

[0016] Step 1 constructs a network graph, representing the nodes and links in the network in the form of a graph, where the nodes are vertices of the graph, the links are edges of the graph, the nodes are routers or switches, and the links are communication lines;

[0017] Step 2: Define weights. Define a weight for each edge in the graph. The weight can represent the distance, transmission delay, and bandwidth of the link.

[0018] Step 3 applies a shortest path algorithm, including Dijkstra's algorithm and Bellman-Ford, to calculate the shortest path from the source node to all other nodes.

[0019] Preferably, the Dijkstra algorithm is implemented by gradually updating the shortest distance from the source node to other nodes;

[0020] Let dist[i] be the shortest distance from the source node to node i,

[0021] S is the set of nodes for which the shortest path has been found.

[0022] Initially, S only contains the source node, dist[source node] = 0, and the dist values ​​of other nodes are set to infinity;

[0023] Update step: For each node j that is not in S, calculate the distance to j through a node k in the set S, and update dist[j] to the minimum value among all possible paths;

[0024] The formula is: dist[j]=min(dist[j],dist[k]+weight(k,j)), where weight(k,j) is the weight of edge (k,j).

[0025] Preferably, the allocation algorithm is a minimum cost algorithm, comprising the following steps:

[0026] S1 defines the cost function. According to the actual needs of the network, the cost function of each link or path is defined. The cost may include the weighted sum of multiple factors such as transmission delay, bandwidth consumption, and energy consumption.

[0027] S2 calculates the minimum cost path: uses a method similar to the shortest path algorithm, but replaces the weight with the cost value calculated by the cost function;

[0028] Algorithm formula:

[0029] It varies depending on the specific scenario, but the general form is:

[0030] Cost = Σ(wi*xi);

[0031] Where wi is the weight of the i-th cost factor, xi is the value of the i-th cost factor;

[0032] When selecting a path, it is necessary to calculate the total cost of each path and select the path with the minimum cost.

[0033] Preferably, the allocation algorithm is a minimum congestion algorithm, comprising the following steps:

[0034] A1 monitors network congestion and monitors link utilization, queue length and other parameters in the network in real time to assess the degree of link congestion;

[0035] A2 adjusts the routing strategy. It dynamically adjusts the routing strategy based on the monitored congestion information to avoid directing traffic to links with severe congestion. It uses the traffic prediction model to predict the link load in the future and adjusts the routing strategy based on the prediction results.

[0036] Preferably, the allocation algorithm is an algorithm based on machine learning or artificial intelligence, comprising the following steps:

[0037] B1 data collection, collects real-time status data in the network, including link utilization, transmission delay, and packet loss rate;

[0038] B2 feature extraction, extracting useful features from the collected data for training machine learning models;

[0039] B3 model training, using machine learning or artificial intelligence algorithms to train a model, the artificial intelligence algorithms include neural networks, decision trees and random forests, the model can predict the optimal routing strategy based on the input features;

[0040] B4 online decision-making deploys the trained model to the network, receives network status data in real time, and outputs the optimal routing decision;

[0041] The algorithm formula varies from algorithm to algorithm, but the general form is:

[0042] y=f(x;θ);

[0043] Where x is the input feature vector, y is the output routing decision or prediction value, f is the mapping function of the model, and θ is the parameter of the model.

[0044] Preferably, the customer requests received in the access module include: telephone, text message, email, social media message, web chat.

[0045] Preferably, the monitoring and maintenance module provides maintenance functions for system configuration, backup and recovery, and troubleshooting to ensure the stability and reliability of the system.

[0046] Beneficial effects:

[0047] 1. Multi-channel access and intelligent routing: The system supports customer requests from multiple channels such as phone, SMS, email, social media and web chat, and uses intelligent routing algorithms, such as the shortest path algorithm, to optimize request distribution and improve response speed and customer satisfaction.

[0048] 2. Security and stability: Encryption technology and identity authentication mechanism are used to protect customer information security, and load balancing is implemented to ensure stable operation of the system under high concurrency conditions.

[0049] 3. Efficient business processing: The business processing module responds quickly to customer requests, provides professional answers, and can seamlessly integrate the company's existing business systems to achieve data sharing and business process automation.

[0050] 4. Comprehensive data management: Collect, analyze and report call center operation data, use big data and AI technology for intelligent analysis, provide visual reports, and help enterprises optimize operation strategies.

[0051] 5. Real-time monitoring and maintenance: monitor the system operation status, including performance, resource utilization and fault warning, and provide automated maintenance functions to ensure the stability and reliability of the system. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments. It should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In addition, in the following description, the description of known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.

[0053] Example 1

[0054] The present invention provides a call center system, including an access module, a routing module, a business processing module, a data management module and a monitoring and maintenance module. The modules communicate with each other through a standardized interface.

[0055] The access module is the front-end interface of the call center system, responsible for receiving customer requests from various channels, including phone calls, text messages, emails, social media messages, web chats, and converting these requests into a format recognizable within the system and passing them to subsequent processing modules;

[0056] The features of the access module are: multi-channel support, which can support multiple communication methods to ensure that customers can contact the enterprise through their preferred channels; load balancing, which automatically allocates customer requests to different processing resources to ensure that the system can still run stably under high concurrency; security, which uses encryption technology and identity authentication mechanism to ensure the security of customer information and communication process.

[0057] The routing module distributes the incoming request to the appropriate business processing module or customer representative according to a distribution algorithm, wherein the distribution algorithm is based on the customer's history, the type of service request, the customer service representative's skills or the current workload.

[0058] The routing module is characterized by: intelligent allocation, using AI or machine learning algorithms to optimize routing strategies to improve customer satisfaction and customer service efficiency; flexibility, supporting custom routing rules that can be adjusted according to business needs; real-time monitoring, monitoring routing status and efficiency, and making timely adjustments to respond to emergencies.

[0059] The business processing module is the core of the call center system and is responsible for processing customer requests and executing specific business logic, including querying orders, answering questions, and handling complaints;

[0060] The business processing module is characterized by: efficient processing, rapid response to customer requests, and provision of accurate and professional answers or solutions; integration, the ability to seamlessly integrate the company's existing business systems and databases to achieve data sharing and business process automation; scalability, supporting rapid deployment of new businesses and optimization and adjustment of existing business processes.

[0061] The data management module is responsible for collecting, storing, analyzing and reporting all data generated during the call center operation process, including customer information, interaction records, service quality indicators, etc. It provides enterprises with the ability to gain in-depth understanding of customer needs, evaluate service quality and optimize operation strategies.

[0062] The characteristics of the data management module are: comprehensiveness, covering all aspects of the call center to ensure the integrity and accuracy of the data; intelligent analysis, using big data and AI technology to conduct in-depth mining and analysis of massive data to discover potential problems and opportunities; visual reports, providing intuitive data reports and charts to help decision makers quickly understand the operating status.

[0063] The monitoring and maintenance module is responsible for monitoring the operation status of the call center, including system performance, resource utilization and fault warning. It also provides maintenance functions such as system configuration, backup and recovery, and troubleshooting to ensure the stability and reliability of the system.

[0064] The features of the monitoring and maintenance module are: real-time monitoring, 24-hour uninterrupted monitoring of the system operation status, timely detection and resolution of problems; early warning mechanism, setting thresholds, automatic alarm when system performance or resource utilization exceeds preset values; automated maintenance, supporting automatic backup, recovery and simple troubleshooting, reducing the burden on operation and maintenance personnel.

[0065] At the same time, it combines customer historical data, current needs and agent status, and uses allocation algorithms for intelligent routing and allocation.

[0066] Advanced AI algorithms are introduced to combine customer historical data, current needs and agent status to achieve intelligent routing and distribution of incoming calls. This strategy can automatically select the best agent or automatic voice assistant for processing, reducing waiting time and improving processing efficiency.

[0067] Smart routing, as the name implies, refers to a router system with intelligent management capabilities. This type of router usually has the following features:

[0068] Independent operating system: Smart routers have independent operating systems, allowing users to install various applications on their own to achieve richer network functions.

[0069] Multi-function support: Support QoS (Quality of Service) function, which can limit bandwidth according to IP and service type to ensure the smooth operation of key applications. At the same time, it supports multiple WAN access, wireless roaming, wireless AP scanning and other functions to improve the flexibility and availability of the network.

[0070] Security management: Built-in firewall, supports IP address, MAC address, domain name address filtering, can flexibly control Internet access permissions and time, and ensure network security.

[0071] Remote Management: Supports remote Web management. Users can configure and monitor the router through a browser, which is convenient and fast.

[0072] Intelligent features: It can automatically adjust routing strategies according to network environment and user needs to optimize network performance. For example, in terms of load balancing, intelligent routers can automatically select the best path to transmit data and reduce network congestion.

[0073] The allocation algorithm is a shortest path algorithm, comprising the following steps:

[0074] Step 1 constructs a network graph, representing the nodes and links in the network in the form of a graph, where the nodes are vertices of the graph, the links are edges of the graph, the nodes are routers or switches, and the links are communication lines;

[0075] Step 2: Define weights. Define a weight for each edge in the graph. The weight can represent the distance, transmission delay, and bandwidth of the link.

[0076] Step 3 applies a shortest path algorithm, including Dijkstra's algorithm and Bellman-Ford, to calculate the shortest path from the source node to all other nodes.

[0077] The Dijkstra algorithm is implemented by gradually updating the shortest distance from the source node to other nodes;

[0078] Let dist[i] be the shortest distance from the source node to node i,

[0079] S is the set of nodes for which the shortest path has been found.

[0080] Initially, S only contains the source node, dist[source node] = 0, and the dist values ​​of other nodes are set to infinity;

[0081] Update step: For each node j that is not in S, calculate the distance to j through a node k in the set S, and update dist[j] to the minimum value among all possible paths;

[0082] The formula is: dist[j]=min(dist[j],dist[k]+weight(k,j)), where weight(k,j) is the weight of edge (k,j).

[0083] Example 2

[0084] The difference between this embodiment and other embodiments is that the allocation algorithm is a minimum cost algorithm, which includes the following steps:

[0085] S1 defines the cost function. According to the actual needs of the network, the cost function of each link or path is defined. The cost may include the weighted sum of multiple factors such as transmission delay, bandwidth consumption, and energy consumption.

[0086] S2 calculates the minimum cost path: uses a method similar to the shortest path algorithm, but replaces the weight with the cost value calculated by the cost function;

[0087] Algorithm formula:

[0088] It varies depending on the specific scenario, but the general form is:

[0089] Cost = Σ(wi*xi);

[0090] Where wi is the weight of the i-th cost factor, xi is the value of the i-th cost factor;

[0091] When selecting a path, it is necessary to calculate the total cost of each path and select the path with the minimum cost.

[0092] Example 3

[0093] This embodiment is different from other embodiments in that the allocation algorithm is a minimum congestion algorithm, which includes the following steps:

[0094] A1 monitors network congestion and monitors link utilization, queue length and other parameters in the network in real time to assess the degree of link congestion;

[0095] A2 adjusts the routing strategy. It dynamically adjusts the routing strategy based on the monitored congestion information to avoid directing traffic to links with severe congestion. It uses the traffic prediction model to predict the link load in the future and adjusts the routing strategy based on the prediction results.

[0096] Example 4

[0097] 10. This embodiment is different from other embodiments in that the allocation algorithm is an algorithm based on machine learning or artificial intelligence, including the following steps:

[0098] B1 data collection, collects real-time status data in the network, including link utilization, transmission delay, and packet loss rate;

[0099] B2 feature extraction, extracting useful features from the collected data for training machine learning models;

[0100] B3 model training, using machine learning or artificial intelligence algorithms to train a model, the artificial intelligence algorithms include neural networks, decision trees and random forests, the model can predict the optimal routing strategy based on the input features;

[0101] B4 online decision-making deploys the trained model to the network, receives network status data in real time, and outputs the optimal routing decision;

[0102] The algorithm formula varies from algorithm to algorithm, but the general form is:

[0103] y=f(x;θ);

[0104] Where x is the input feature vector, y is the output routing decision or prediction value, f is the mapping function of the model, and θ is the parameter of the model.

[0105] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0106] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A call center system, characterized in that: It includes access module, routing module, business processing module, data management module and monitoring and maintenance module. Each module communicates through standardized interfaces. At the same time, it combines customer historical data, current needs and seat status, and uses allocation algorithms for intelligent routing and allocation. The access module is the front-end interface of the call center system, responsible for receiving customer requests from various channels and converting these requests into a format recognizable within the system and passing them to subsequent processing modules; The routing module distributes the access request to a suitable business processing module or customer representative according to a distribution algorithm; The business processing module is the core of the call center system and is responsible for processing customer requests and executing specific business logic; The data management module is responsible for collecting, storing, analyzing and reporting all data generated during the call center operation; The monitoring and maintenance module is responsible for monitoring the operation status of the call center, including system performance, resource utilization and fault warning.

2. A call center system according to claim 1, characterized in that: The smart router has an independent operating system, allowing users to install various applications by themselves to achieve richer network functions. The smart router supports QOS function, which can limit bandwidth according to IP and service type to ensure the smooth operation of key applications. The smart router supports multi-WAN access, wireless roaming, and wireless AP scanning.

3. A call center system according to claim 1 or 2, characterized in that: The smart router has a built-in firewall and supports filtering of IP addresses, MAC addresses, and domain name addresses. It can flexibly control Internet access permissions and time to ensure network security. It also supports remote Web management, and users can configure and monitor the router through a browser, which is convenient and fast.

4. A call center system according to claim 1, characterized in that: The allocation algorithm is a shortest path algorithm, comprising the following steps: Step 1 constructs a network graph, representing the nodes and links in the network in the form of a graph, where the nodes are vertices of the graph, the links are edges of the graph, the nodes are routers or switches, and the links are communication lines; Step 2: Define weights. Define a weight for each edge in the graph. The weight can represent the distance, transmission delay, and bandwidth of the link. Step 3 applies a shortest path algorithm, including Dijkstra's algorithm and Bellman-Ford, to calculate the shortest path from the source node to all other nodes.

5. A call center system according to claim 4, characterized in that: The Dijkstra algorithm is implemented by gradually updating the shortest distance from the source node to other nodes; Let dist[i] be the shortest distance from the source node to node i, S is the set of nodes for which the shortest path has been found. Initially, S only contains the source node, dist[source node] = 0, and the dist values ​​of other nodes are set to infinity; Update step: For each node j that is not in S, calculate the distance to j through a node k in the set S, and update dist[j] to the minimum value among all possible paths; The formula is: dist[j]=min(dist[j],dist[k]+weight(k,j)), where weight(k,j) is the weight of edge (k,j).

6. A call center system according to claim 1, characterized in that: The allocation algorithm is a minimum cost algorithm, which includes the following steps: S1 defines the cost function. According to the actual needs of the network, the cost function of each link or path is defined. The cost may include the weighted sum of multiple factors such as transmission delay, bandwidth consumption, and energy consumption. S2 calculates the minimum cost path: uses a method similar to the shortest path algorithm, but replaces the weight with the cost value calculated by the cost function; Algorithm formula: It varies depending on the specific scenario, but the general form is: Cost = Σ(wi*xi); Where wi is the weight of the i-th cost factor, xi is the value of the i-th cost factor; When selecting a path, it is necessary to calculate the total cost of each path and select the path with the minimum cost.

7. A call center system according to claim 1, characterized in that: The allocation algorithm is a minimum congestion algorithm, comprising the following steps: A1 monitors network congestion and monitors link utilization, queue length and other parameters in the network in real time to assess the degree of link congestion; A2 adjusts the routing strategy. It dynamically adjusts the routing strategy based on the monitored congestion information to avoid directing traffic to links with severe congestion. It uses the traffic prediction model to predict the link load in the future and adjusts the routing strategy based on the prediction results.

8. A call center system according to claim 1, characterized in that: The allocation algorithm is an algorithm based on machine learning or artificial intelligence, comprising the following steps: B1 data collection, collects real-time status data in the network, including link utilization, transmission delay, and packet loss rate; B2 feature extraction, extracting useful features from the collected data for training machine learning models; B3 model training, using machine learning or artificial intelligence algorithms to train a model, the artificial intelligence algorithms include neural networks, decision trees and random forests, the model can predict the optimal routing strategy based on the input features; B4 online decision-making deploys the trained model to the network, receives network status data in real time, and outputs the optimal routing decision; The algorithm formula varies from algorithm to algorithm, but the general form is: y=f(x;θ); Where x is the input feature vector, y is the output routing decision or prediction value, f is the mapping function of the model, and θ is the parameter of the model.

9. A call center system according to claim 1, characterized in that: The customer requests received in the access module include: phone calls, text messages, emails, social media messages, and web chats.

10. A call center system according to claim 1, characterized in that: The monitoring and maintenance module provides maintenance functions for system configuration, backup and recovery, and troubleshooting to ensure the stability and reliability of the system.