A big data-based communication service pushing method and system

Abstract

The application relates to the technical field of communication services, and discloses a communication service pushing method and system based on big data, which comprises the following steps: obtaining chat data of a chat box to be promoted from a communication database, analyzing and calculating a service promotion index of communication chat in combination with a service priority index, and preliminarily judging the chat box of a customer; the shopping data of the customer on a shopping platform is accurately obtained, and the service priority index is calculated, the importance of the customer is effectively identified, high-value customers can be responded in time, meanwhile, the service priority can be dynamically adjusted, the chat box level is flexibly promoted or maintained according to the historical behavior data of the customer and the service promotion index, the service efficiency is improved, and the waste of resources is avoided, and further, when the system detects that the customer service load is too heavy, the service promotion threshold is intelligently adjusted, unnecessary chat box promotion is reduced, and the working pressure of the customer service personnel is effectively reduced.

Description

Technical Field

[0001] This invention relates to the field of communication service technology, and in particular to a communication service push method and system based on big data. Background Technology

[0002] With the rapid development of internet technology, online trading platforms have become the core carrier of modern commerce, expanding their coverage from daily consumer goods to high-end services, leading to an exponential increase in the number of stores on these platforms. Against this backdrop, customer traffic has surged. Statistics show that leading e-commerce platforms have exceeded 100 million daily active users, with individual stores receiving thousands of inquiries daily, especially during promotional periods when inquiries can increase 3-5 times. In this high-concurrency scenario, customer inquiries are diverse, including standardized questions such as product parameter queries and logistics tracking, as well as complex scenarios involving after-sales disputes and customized needs, posing a significant challenge to the response speed and service quality of customer service systems.

[0003] However, in traditional technologies, customer service personnel deal with a large number of visitors, resulting in significant workload. On the one hand, customer service personnel cannot effectively identify the importance of customers, leading to high-value customers not receiving timely responses, which affects user experience and store conversion rates. On the other hand, they cannot dynamically adjust service priorities based on customers' historical behavior data, resulting in low service efficiency and severely restricting the improvement of communication service quality and efficiency.

[0004] To address the aforementioned technical deficiencies, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to address the problems in traditional technologies where customer service personnel face a large number of visitors and heavy workloads. On the one hand, customer service personnel cannot effectively identify the importance of customers, resulting in high-value customers not receiving timely responses, which affects user experience and store conversion rates. On the other hand, they cannot dynamically adjust service priorities based on customers' historical behavior data, leading to low service efficiency.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a communication service push method based on big data, comprising the following steps: Step 1: Obtain customer service communication information data and, based on customer chat requests, divide the chat information boxes between customer service representatives and customers. Step 2: Obtain customer shopping data on the shopping platform through the communication database, analyze and calculate it to obtain the service priority index of customer communication, and automatically classify the customer's dialogue content into the chat information box between customer service and customer. Step 3: Obtain the chat data of the chat box to be upgraded through the communication database, analyze and calculate the service upgrade index of the communication chat by combining it with the service priority index, and make a preliminary upgrade judgment on the customer's chat box. Step 4: When an upgrade is required, obtain the customer service load data, analyze and calculate it to obtain the customer service communication load index. Step 5: Analyze and calculate the communication load index and the preset communication load threshold to obtain the adjustment coefficient of the service upgrade threshold. Adjust the preset upgrade threshold according to the adjustment coefficient of the service upgrade threshold to upgrade the initial upgrade chat box.

[0007] Furthermore, the chat boxes between customer service representatives and customers are specifically divided into: silent chat boxes, standard chat boxes, and important chat boxes; Silent chat boxes are those where customers send simple inquiries without making further specific requests and do not engage in secondary interactions within a specified time. AI-powered intelligent customer service will automatically process the communication information in silent chat boxes, eliminating the need for human customer service. A standard chat box is a chat box where a customer raises a specific inquiry request, but the urgency and importance of the request are moderate, and the interaction frequency is moderate. After the important chat box communication information is assigned and processed, customer service personnel are arranged to process the communication information in the standard chat box in chronological order. Important chat boxes are those where customers make urgent requests or clearly express a large purchase intention and have a high frequency of interaction. Customer service personnel should be given priority to handle the communication information in important chat boxes immediately.

[0008] Furthermore, the calculation process for the customer communication service priority index is as follows: S11. Obtain and analyze the customer's shopping data on the shopping platform. The shopping data includes the customer's cumulative transaction amount, purchase frequency, and product return rate data on the shopping platform. S12. Calculate the customer communication service priority index according to the following formula. : in, This refers to the customer's cumulative transaction amount on the shopping platform. This is the preset standard transaction amount for the shopping platform. The frequency of customer purchases on the shopping platform. This is the preset standard purchase frequency for the shopping platform. The weighting coefficient is the preset transaction amount. The weighting coefficient is the preset purchase frequency. The customer return rate on the shopping platform and the customer communication service priority index are used to reflect the priority level of customers when requesting communication services. S13. Obtain the preset service priority upper limit threshold. Service priority lower threshold Service priority index for communicating with customers When comparing, In this case, the customer's conversation will be automatically placed into the important chat box between the customer service representative and the customer; S14, when In this case, the customer's conversation will be automatically placed into the standard chat box between customer service and customer. S15, when In this case, the customer's conversation will be automatically placed into the silent chat box between customer service and the customer.

[0009] Furthermore, the calculation process for the service enhancement index of communication chat is as follows: S21. Obtain the chat data of the chat box to be upgraded, and analyze and calculate it in combination with the service priority index. The chat box to be upgraded includes a silent chat box and a standard chat box. The chat data includes the number of interactions between the AI ​​intelligent customer service and the customer, the number of customer messages, and the customer's dialogue rounds data. S22. Calculate the service enhancement index for communication chat according to the following formula. : in, The number of interactions between AI-powered intelligent customer service and customers. For the number of customer messages, The preset maximum number of messages for the customer. The preset minimum number of customer messages, For the number of rounds of dialogue with customers, For the preset standard dialogue rounds, The service priority index for chat windows awaiting upgrades reflects the urgency of a customer's chat window needing an upgrade.

[0010] Furthermore, the process of making an initial assessment of the customer's chat box is as follows: S31. Obtain the preset standard upgrade threshold. and important upgrade thresholds Service upgrade index in the chat box to be upgraded Comparative analysis, when If this happens, it is determined that the customer's chat box does not need to be upgraded and should maintain its current level. S32, when If the customer's standard chat box does not need to be upgraded and remains at its current level, the customer's silent chat box will be upgraded to the standard chat box. S33, when If this happens, the customer's silent chat window or standard chat window will be upgraded to an important chat window.

[0011] Furthermore, the calculation process for the customer service communication load index is as follows: S41. Obtain and analyze the customer service load data, including the number of customer service representatives, the number of important chat boxes to be processed, and the average response time of customer service representatives in handling conversations. S42. Calculate the customer service communication load index according to the following formula. : in, The actual number of customer service representatives online. For the total number of customer service staff, The number of important chat boxes to be processed. The average response time for customer service to handle a conversation. This is a preset standard number of important chat boxes to be processed. The maximum response time for customer service conversations is preset, and the customer service communication load index is used to reflect the load of customer service in handling chat conversations.

[0012] Furthermore, the calculation process for the adjustment coefficient of the service upgrade threshold is as follows: S51. Obtain the communication load index and the preset communication load threshold for analysis and calculation; S52. Calculate the adjustment coefficient for the service upgrade threshold according to the following formula. : ,in, The communication load index for customer service. This is the preset communication load threshold.

[0013] Furthermore, the process of upgrading the chat box is as follows: S61, when If this occurs, it indicates that the customer service team is overloaded with chat messages. In this case, the preset standard threshold should be raised. Adjusted to The preset important escalation threshold will be set. Adjusted to Increase the standard upgrade threshold and the important upgrade threshold, and upgrade according to the adjusted standard upgrade threshold. and the adjusted important upgrade threshold During the initial upgrade assessment process, the chat boxes of customers who are being upgraded are re-compared and assessed to reduce the number of chat boxes being upgraded and lower the workload of customer service. S62, when If the customer service load is moderate or light, then the original preset standard upgrade threshold should be maintained. and important upgrade thresholds This remains unchanged, ensuring that high-priority customer requests are handled promptly.

[0014] The present invention also provides a communication service push system based on big data, including a communication partitioning unit, a priority service unit, a preliminary upgrade unit, a communication load unit, a threshold adjustment unit, and an upgrade adjustment unit; The communication segmentation unit is used to acquire customer service communication information data and, in conjunction with customer chat requests, divide the chat information boxes between customer service and customers into silent chat boxes, standard chat boxes, and important chat boxes. The priority service unit is used to obtain customers' shopping data on the shopping platform through the communication database, analyze and calculate it to obtain the service priority index of customer communication, and automatically classify the customer's dialogue content into the chat information box between customer service and customer. The preliminary upgrade unit is used to obtain the chat data of the chat box to be upgraded through the communication database, analyze and calculate the service upgrade index of the communication chat by combining the service priority index, and make a preliminary upgrade judgment on the customer's chat box. The communication load unit is used to obtain customer service load data, perform analysis and calculation when an upgrade is required, obtain the customer service communication load index, and compare it with the preset communication load threshold to obtain the upgrade threshold coefficient. The threshold adjustment unit is used to obtain the communication load index and the preset communication load threshold for analysis and calculation, and to obtain the adjustment coefficient of the service upgrade threshold. The upgrade adjustment unit is used to adjust the preset upgrade threshold according to the adjustment coefficient of the service upgrade threshold, and to upgrade the initial upgrade chat box.

[0015] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: This big data-based communication service push method and system accurately acquires customers' shopping data on shopping platforms and calculates a service priority index, effectively identifying customer importance and ensuring that high-value customers receive timely responses, thereby significantly improving user experience and store conversion rates. Simultaneously, the system can dynamically adjust service priorities, flexibly upgrading or maintaining chat box levels based on customers' historical behavior data and service upgrade index, improving service efficiency and avoiding resource waste. Furthermore, when the system detects excessive customer service load, it intelligently adjusts the service upgrade threshold, reducing unnecessary chat box upgrades and effectively alleviating the workload of customer service personnel. When the customer service load is moderate or light, the original threshold remains unchanged, ensuring that high-priority customer requests are handled promptly. These combined measures not only optimize customer service resource allocation but also significantly improve the quality and efficiency of communication services. Attached Figure Description

[0016] Figure 1 A schematic diagram of the method flow of the present invention is shown; Figure 2 A schematic diagram of the system flow of the present invention is shown. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] like Figure 1 As shown, a communication service push method based on big data firstly obtains customer service communication information data, and then divides the chat information boxes between customer service and customers based on customer chat requests. The chat boxes between customer service and customers are specifically divided into: silent chat boxes, standard chat boxes, and important chat boxes; Silent chat boxes are those where customers send simple inquiries (such as "Are you there?") without making any further specific requests, and do not engage in secondary interaction within a specified time (such as 5 minutes). In these cases, AI-powered intelligent customer service will automatically process the communication information in the silent chat boxes, eliminating the need for human customer service personnel. The standard chat box is a chat box where customers raise specific inquiries (such as product specifications or logistics information), but the urgency and importance of the inquiries are moderate, and the interaction frequency is moderate. After the important chat box communication information is assigned and processed, customer service personnel will process the communication information in the standard chat box in chronological order. Important chat boxes are those where customers raise urgent requests (such as after-sales complaints or order anomalies) or clearly express a large purchase intention and have a high frequency of interaction. Customer service personnel should be given priority to handle the communication information in important chat boxes immediately.

[0019] Then, the customer's shopping data on the shopping platform is obtained through the communication database, analyzed and calculated to obtain the service priority index of customer communication, and the customer's dialogue content is automatically divided into the chat information box between customer service and customer. The calculation process for the customer communication service priority index is as follows: S11. Obtain and analyze the customer's shopping data on the shopping platform. The shopping data includes the customer's cumulative transaction amount, purchase frequency, and product return rate data on the shopping platform. S12. Calculate the customer communication service priority index according to the following formula. : in, This refers to the customer's cumulative transaction amount on the shopping platform. This is the preset standard transaction amount for the shopping platform. The frequency of customer purchases on the shopping platform. This is the preset standard purchase frequency for the shopping platform. The weighting coefficient is the preset transaction amount. The weighting coefficient is the preset purchase frequency. The customer's return rate on the shopping platform is used to measure the customer's communication service priority index. The higher the service priority index, the higher the customer's communication service priority, and the lower the service priority index, the lower the customer's communication service priority. S13. Obtain the preset service priority upper limit threshold. Service priority lower threshold Service priority index for communicating with customers When comparing, In this case, the customer's conversation will be automatically placed into the important chat box between the customer service representative and the customer; S14, when In this case, the customer's conversation will be automatically placed into the standard chat box between customer service and customer. S15, when In this case, the customer's conversation will be automatically placed into the silent chat box between customer service and the customer.

[0020] Then, the chat data of the chat box to be upgraded is obtained through the communication database, and the service priority index is analyzed and calculated to obtain the service upgrade index of the communication chat, and a preliminary upgrade judgment is made for the customer's chat box. The calculation process for the service enhancement index of communication chat is as follows: S21. Obtain the chat data of the chat box to be upgraded, and analyze and calculate it in combination with the service priority index. The chat box to be upgraded includes a silent chat box and a standard chat box. The chat data includes the number of interactions between the AI ​​intelligent customer service and the customer, the number of customer messages, and the customer's dialogue rounds data. S22. Calculate the service enhancement index for communication chat according to the following formula. : in, The number of interactions between AI-powered intelligent customer service and customers. For the number of customer messages, The preset maximum number of messages for the customer. The preset minimum number of customer messages, For the number of rounds of dialogue with customers, For the preset standard dialogue rounds, The service priority index for chat windows awaiting upgrades reflects the urgency of upgrading a customer's chat window. A higher service priority index indicates a higher urgency of upgrading, while a lower service priority index indicates a lower urgency of upgrading.

[0021] The process of making an initial assessment of the customer's chat box is as follows: S31. Obtain the preset standard upgrade threshold. and important upgrade thresholds Service upgrade index in the chat box to be upgraded Comparative analysis, when If this happens, it is determined that the customer's chat box does not need to be upgraded and should maintain its current level. S32, when If the customer's standard chat box does not need to be upgraded and remains at its current level, the customer's silent chat box will be upgraded to the standard chat box. S33, when If this happens, the customer's silent chat window or standard chat window will be upgraded to an important chat window.

[0022] Subsequently, when a situation arises requiring an upgrade, the customer service load data is obtained, analyzed, and calculated to derive the customer service communication load index. The calculation process for the customer service communication load index is as follows: S41. Obtain and analyze the customer service load data, including the number of customer service representatives, the number of important chat boxes to be processed, and the average response time of customer service representatives in handling conversations. S42. Calculate the customer service communication load index according to the following formula. : in, The actual number of customer service representatives online. For the total number of customer service staff, The number of important chat boxes to be processed. The average response time for customer service to handle a conversation. This is a preset standard number of important chat boxes to be processed. The communication load index is used to reflect the workload of customer service representatives in handling chat conversations, which is the preset maximum response time for customer service representatives to process chat conversations. The higher the value of the communication load index, the heavier the workload of customer service representatives in handling chat conversations, and the lower the value of the communication load index, the lighter the workload of customer service representatives in handling chat conversations.

[0023] Finally, the communication load index and the preset communication load threshold are obtained and analyzed to obtain the adjustment coefficient of the service upgrade threshold. Based on the adjustment coefficient of the service upgrade threshold, the preset upgrade threshold (including the preset standard upgrade threshold and the important upgrade threshold) is adjusted to upgrade the initial upgrade chat box. The calculation process for the adjustment coefficient of the service upgrade threshold is as follows: S51. Obtain the communication load index and the preset communication load threshold for analysis and calculation; S52. Calculate the adjustment coefficient for the service upgrade threshold according to the following formula. : ,in, The communication load index for customer service. This is the preset communication load threshold.

[0024] The process of adjusting the level-up chat box is as follows: S61, when If this occurs, it indicates that the customer service team is overloaded with chat messages. In this case, the preset standard threshold should be raised. Adjusted to The preset important escalation threshold will be set. Adjusted to Increase the standard upgrade threshold and the important upgrade threshold, and upgrade according to the adjusted standard upgrade threshold. and the adjusted important upgrade threshold During the initial upgrade assessment process, the chat boxes of customers who are being upgraded are re-compared and assessed to reduce the number of chat boxes being upgraded and lower the workload of customer service. S62, when If the customer service load is moderate or light, then the original preset standard upgrade threshold should be maintained. and important upgrade thresholds This remains unchanged, ensuring that high-priority customer requests are handled promptly.

[0025] This invention accurately acquires customer shopping data on shopping platforms and calculates a service priority index, effectively identifying customer importance and ensuring that high-value customers receive timely responses, thereby significantly improving user experience and store conversion rates. Simultaneously, the system can dynamically adjust service priorities, flexibly upgrading or maintaining chat window levels based on customer historical behavior data and the service upgrade index, improving service efficiency and avoiding resource waste. Furthermore, when the system detects excessive customer service load, it intelligently adjusts the service upgrade threshold, reducing unnecessary chat window upgrades and effectively alleviating the workload of customer service personnel. When the customer service load is moderate or light, the original threshold remains unchanged, ensuring that high-priority customer requests are handled promptly. These combined measures not only optimize customer service resource allocation but also significantly improve the quality and efficiency of communication services.

[0026] Example 2: like Figure 2 As shown, a communication service push system based on big data is applied to a communication service push method based on big data, including a communication partitioning unit, a priority service unit, a preliminary upgrade unit, a communication load unit, a threshold adjustment unit, and an upgrade adjustment unit; The communication segmentation unit is used to acquire customer service communication information data and, in conjunction with customer chat requests, divide the chat information boxes between customer service and customers into silent chat boxes, standard chat boxes, and important chat boxes. The priority service unit is used to obtain customers' shopping data on the shopping platform through the communication database, analyze and calculate it to obtain the service priority index of customer communication, and automatically classify the customer's dialogue content into the chat information box between customer service and customer. The preliminary upgrade unit is used to obtain the chat data of the chat box to be upgraded through the communication database, analyze and calculate the service upgrade index of the communication chat by combining the service priority index, and make a preliminary upgrade judgment on the customer's chat box. The communication load unit is used to obtain customer service load data, perform analysis and calculation when an upgrade is required, obtain the customer service communication load index, and compare it with the preset communication load threshold to obtain the upgrade threshold coefficient. The threshold adjustment unit is used to obtain the communication load index and the preset communication load threshold for analysis and calculation, and to obtain the adjustment coefficient of the service upgrade threshold. The upgrade adjustment unit is used to adjust the preset upgrade threshold according to the adjustment coefficient of the service upgrade threshold, and to upgrade the initial upgrade chat box.

[0027] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value.

[0028] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for pushing communication services based on big data, characterized in that, Includes the following steps: Step 1: Obtain customer service communication information data and, based on customer chat requests, divide the chat information boxes between customer service representatives and customers. Step 2: Obtain customer shopping data on the shopping platform through the communication database, analyze and calculate it to obtain the service priority index of customer communication, and automatically classify the customer's dialogue content into the chat information box between customer service and customer. Step 3: Obtain the chat data of the chat box to be upgraded through the communication database, analyze and calculate the service upgrade index of the communication chat by combining it with the service priority index, and make a preliminary upgrade judgment on the customer's chat box. Step 4: When an upgrade is required, obtain the customer service load data, analyze and calculate it to obtain the customer service communication load index. Step 5: Analyze and calculate the communication load index and the preset communication load threshold to obtain the adjustment coefficient of the service upgrade threshold. Adjust the preset upgrade threshold according to the adjustment coefficient of the service upgrade threshold to upgrade the initial upgrade chat box.

2. The communication service push method based on big data according to claim 1, characterized in that, The chat boxes between customer service and customers are specifically divided into: silent chat boxes, standard chat boxes, and important chat boxes; Silent chat boxes are those where customers send simple inquiries without making further specific requests and do not engage in secondary interactions within a specified time. AI-powered intelligent customer service will automatically process the communication information in silent chat boxes, eliminating the need for human customer service. A standard chat box is a chat box where a customer raises a specific inquiry request, but the urgency and importance of the request are moderate, and the interaction frequency is moderate. After the important chat box communication information is assigned and processed, customer service personnel are arranged to process the communication information in the standard chat box in chronological order. Important chat boxes are those where customers make urgent requests or clearly express a large purchase intention and have a high frequency of interaction. Customer service personnel should be given priority to handle the communication information in important chat boxes immediately.

3. The communication service push method based on big data according to claim 1, characterized in that, The calculation process for the customer communication service priority index is as follows: S11. Obtain and analyze the customer's shopping data on the shopping platform. The shopping data includes the customer's cumulative transaction amount, purchase frequency, and product return rate data on the shopping platform. S12. Calculate the customer communication service priority index according to the following formula. : in, This refers to the customer's cumulative transaction amount on the shopping platform. This is the preset standard transaction amount for the shopping platform. The frequency of customer purchases on the shopping platform. This is the preset standard purchase frequency for the shopping platform. The weighting coefficient is the preset transaction amount. The weighting coefficient is the preset purchase frequency. The customer return rate on the shopping platform and the customer communication service priority index are used to reflect the priority level of customers when requesting communication services. S13. Obtain the preset service priority upper limit threshold. Service priority lower threshold Service priority index for communicating with customers When comparing, In this case, the customer's conversation will be automatically placed into the important chat box between the customer service representative and the customer; S14, when In this case, the customer's conversation will be automatically placed into the standard chat box between customer service and customer. S15, when In this case, the customer's conversation will be automatically placed into the silent chat box between customer service and the customer.

4. The communication service push method based on big data according to claim 1, characterized in that, The calculation process for the service enhancement index of communication chat is as follows: S21. Obtain the chat data of the chat box to be upgraded, and analyze and calculate it in combination with the service priority index. The chat box to be upgraded includes a silent chat box and a standard chat box. The chat data includes the number of interactions between the AI ​​intelligent customer service and the customer, the number of customer messages, and the customer's dialogue rounds data. S22. Calculate the service enhancement index for communication chat according to the following formula. : in, The number of interactions between AI-powered intelligent customer service and customers. For the number of customer messages, The preset maximum number of messages for the customer. The preset minimum number of customer messages, For the number of rounds of dialogue with customers, For the preset standard dialogue rounds, The service priority index for chat windows awaiting upgrades reflects the urgency of a customer's chat window needing an upgrade.

5. The communication service push method based on big data according to claim 1, characterized in that, The process of making an initial assessment of the customer's chat box is as follows: S31. Obtain the preset standard upgrade threshold. and important upgrade thresholds Service upgrade index in the chat box to be upgraded Comparative analysis, when If this happens, it is determined that the customer's chat box does not need to be upgraded and should maintain its current level. S32, when If the customer's standard chat box does not need to be upgraded and remains at its current level, the customer's silent chat box will be upgraded to the standard chat box. S33, when If this happens, the customer's silent chat window or standard chat window will be upgraded to an important chat window.

6. The communication service push method based on big data according to claim 1, characterized in that, The calculation process for the customer service communication load index is as follows: S41. Obtain and analyze the customer service load data, including the number of customer service representatives, the number of important chat boxes to be processed, and the average response time of customer service representatives in handling conversations. S42. Calculate the customer service communication load index according to the following formula. : in, The actual number of customer service representatives online. For the total number of customer service staff, The number of important chat boxes to be processed. The average response time for customer service to handle a conversation. This is a preset standard number of important chat boxes to be processed. The maximum response time for customer service conversations is preset, and the customer service communication load index is used to reflect the load of customer service in handling chat conversations.

7. The communication service push method based on big data according to claim 1, characterized in that, The calculation process for the adjustment coefficient of the service upgrade threshold is as follows: S51. Obtain the communication load index and the preset communication load threshold for analysis and calculation; S52. Calculate the adjustment coefficient for the service upgrade threshold according to the following formula. : ,in, The communication load index for customer service. This is the preset communication load threshold.

8. The method for pushing communication services based on big data according to claim 1, characterized in that, The process of adjusting the level-up chat box is as follows: S61, when If this occurs, it indicates that the customer service team is overloaded with chat messages. In this case, the preset standard threshold should be raised. Adjusted to The preset important escalation threshold will be set. Adjusted to Increase the standard upgrade threshold and the important upgrade threshold, and upgrade according to the adjusted standard upgrade threshold. and the adjusted important upgrade threshold During the initial upgrade assessment process, the chat boxes of customers who are being upgraded are re-compared and assessed to reduce the number of chat boxes being upgraded and lower the workload of customer service. S62, when If the customer service load is moderate or light, then the original preset standard upgrade threshold should be maintained. and important upgrade thresholds This remains unchanged, ensuring that high-priority customer requests are handled promptly.

9. A big data-based communication service push system, applied to the big data-based communication service push method described in any one of claims 1-8, characterized in that, It includes a communication partitioning unit, a priority service unit, a preliminary upgrade unit, a communication load unit, a threshold adjustment unit, and an upgrade adjustment unit; The communication segmentation unit is used to acquire customer service communication information data and, in conjunction with customer chat requests, divide the chat information boxes between customer service and customers into silent chat boxes, standard chat boxes, and important chat boxes. The priority service unit is used to obtain customers' shopping data on the shopping platform through the communication database, analyze and calculate it to obtain the service priority index of customer communication, and automatically classify the customer's dialogue content into the chat information box between customer service and customer. The preliminary upgrade unit is used to obtain the chat data of the chat box to be upgraded through the communication database, analyze and calculate the service upgrade index of the communication chat by combining the service priority index, and make a preliminary upgrade judgment on the customer's chat box. The communication load unit is used to obtain customer service load data, perform analysis and calculation when an upgrade is required, obtain the customer service communication load index, and compare it with the preset communication load threshold to obtain the upgrade threshold coefficient. The threshold adjustment unit is used to obtain the communication load index and the preset communication load threshold for analysis and calculation, and to obtain the adjustment coefficient of the service upgrade threshold. The upgrade adjustment unit is used to adjust the preset upgrade threshold according to the adjustment coefficient of the service upgrade threshold, and to upgrade the initial upgrade chat box.

Images