Customer relationship management method and system based on multi-scene and multi-type intervention

Abstract

The invention discloses a customer relationship management method and system based on multi-scene and multi-type intervention. The invention relates to the technical field of SCRM (customer relationship management). Different customer intervention scenes including low-frequency intervention, non-first-order intervention, reward activity intervention and the like are set through a user interface, and the scenes are configured in the system. According to the intervention scene, contents, including a touch mode (WeChat message or telephone call-out), a message copywriting or / and a message attachment and the like, sent to the customer are set, and the contents are configured to the system. According to a BI crowd selection result, customizing a touch object type, and appointing a customer group needing to be intervened; by customizing intervention scenes and sending contents, an enterprise can set different customer intervention scenes and sending contents according to actual requirements, such as low-frequency intervention, non-first-order intervention, reward activity intervention and the like, and flexibly configure a touch mode, a message copywriting, a message attachment and the like, so that the requirements of the enterprise on multi-scene and multi-type intervention are met.

Description

Technical Field

[0001] The present invention relates to the technical field of SCRM (customer relationship management), specifically to customer relationship management with multi-scenario and multi-type interventions, and especially to a customer relationship management method and system based on multi-scenario and multi-type interventions. Background Art

[0002] With the rapid development of internet technology and the widespread adoption of mobile devices, businesses are facing an increasingly complex and volatile market environment, and customer behavior patterns are becoming more diversified and personalized. Against this backdrop, customer relationship management (CRM), a key element of a company's core competitiveness, has become increasingly important. However, traditional customer relationship management systems (SCRM) face a series of pressing challenges in the face of rapidly changing market conditions and customer demands.

[0003] Existing SCRM systems are often limited to single or limited intervention methods, lacking flexible strategies for addressing diverse customer needs across multiple scenarios and types. This makes it difficult for companies to achieve comprehensive and precise management of customer relationships in complex market environments. Traditional SCRM systems lack customer profiling and data analysis capabilities, making them incapable of big data-based BI targeting, thus hindering precision marketing and personalized services. This, to a certain extent, limits companies' ability to improve customer satisfaction and loyalty.

[0004] Existing SCRM systems typically offer only fixed management paths and lack configurability. This makes it difficult for companies to quickly adjust management strategies to adapt to market changes in response to diverse business scenarios and customer needs. Traditional SCRM systems often rely on manual customer management and lack intelligent, automated intervention. This not only increases labor costs but also reduces customer relationship management efficiency.

[0005] In view of this, it is particularly important to build a new type of advanced customer relationship management system. To this end, the present invention proposes a customer relationship management method and system based on multi-scenario and multi-type intervention. Summary of the Invention

[0006] In view of this, the present invention aims to provide a customer relationship management method and system based on multi-scenario and multi-type intervention to solve or alleviate the technical problems existing in the prior art, namely:

[0007] 1) Optimize and upgrade the current SCRM customer management model in multiple scenarios and types;

[0008] 2) Selecting BI groups that are currently unable to accurately manage customers in the SCRM field and support big data;

[0009] 3) In view of the single customer management method in the current SCRM field, the present invention provides strategies and methods for configurable management paths;

[0010] 4) In response to the current manual customer management method in the SCRM field, the present invention provides a configurable timing strategy to intelligently intervene in customers;

[0011] The technical solution of the present invention is achieved as follows:

[0012] First, a customer relationship management approach based on multi-scenario and multi-type interventions:

[0013] (1) Overview:

[0014] The present invention aims to provide a customer relationship management (SCRM) system and method based on multi-scenario and multi-type intervention to achieve precise and efficient management of customers. Specifically, the solution sets different customer intervention scenarios through the user interface, such as low-frequency intervention, intervention for failed first-orders, and intervention for reward activities, and configures the content sent to customers, the target audience, and the push frequency based on these scenarios. At the same time, the system stores and manages the customer's basic information and transaction records to provide data support for subsequent intervention strategies. After the task template is configured, the system parses and generates tasks through the task scheduling center, and uses task scheduling tools such as DolphinScheduler and SchedulerX to execute tasks at specified time points.

[0015] (2) Technical solution:

[0016] To achieve the above technical objectives, upon receiving an activation instruction from a user or system administrator to trigger the start of a customer relationship management solution on the user interface of the SCRM system, the present invention selects to execute the following operation steps.

[0017] 2.1 Step S1, task template configuration:

[0018] Set different customer intervention scenarios through the user interface, including low-frequency intervention, intervention for failed first orders, and intervention for incentive activities, and configure these scenarios into the system.

[0019] Based on the intervention scenario, set the content sent to customers, including the contact method (WeChat message or outbound phone call), message copy, and / or attachments, and configure this content into the system. Based on the BI audience selection results, customize the contact target type and specify the customer groups requiring intervention.

[0020] Set the frequency of push notifications and configure these frequencies into the system.

[0021] 2.1.1 Step S100: Setting and configuring customer intervention scenarios:

[0022] Different customer intervention scenarios can be set through the user interface, including low-frequency intervention, intervention for failed first-orders, and intervention for incentive campaigns. Based on the intervention scenarios, companies need to set the specific content sent to customers, including the contact method (WeChat message or outbound phone call, etc.), message copy, and message attachments. These contents should also be configured in the system to ensure that when the intervention scenario is triggered, the system can send the message to the customer according to the preset content.

[0023] 2.1.2 Step S101: Customize the target type and specify the customer group:

[0024] Utilize BI crowd selection technology to classify customers based on their portraits and behavioral characteristics, and assign different labels; based on the results of BI crowd selection, customize the types of targets to be reached, including customer groups with specific age groups, consumption habits, or interest preferences.

[0025] 2.1.3 Step S102: Set and configure the frequency of push messages:

[0026] Based on the intervention scenario and customer group's needs, set the frequency of push notifications, including single, daily, weekly, or monthly. Configure these frequencies into the system to ensure that the system can send messages to customers at the preset frequency, avoiding over- or under-intervention.

[0027] 2.2 Step S2, data storage and update:

[0028] Store and manage customer data, including basic customer information and transaction records.

[0029] 2.2.1 Step S200, storing basic customer information:

[0030] Collect and organize basic customer information, including name, gender, age, contact information, and address, and store this information in the customer data management module of the SCRM system.

[0031] 2.2.2 Step S201, Transaction Record Management:

[0032] Record every customer transaction, including transaction time, transaction items, transaction amount, and payment method. Transaction records are also stored in the customer data management module.

[0033] 2.2.3 Step S202: Real-time data update:

[0034] Establish a middle platform for storing and updating customer data in real time; through data streaming technology, capture and update customers' latest transaction information and behavioral characteristics in real time to ensure the timeliness and accuracy of customer data.

[0035] 2.3 Step S3, task analysis and generation:

[0036] After the task template is configured, the task is parsed through the task scheduling center, and specific intervention tasks are generated based on the set intervention scenario, sending content, reach objects, and push frequency information; the generated tasks are stored in the persistence layer for subsequent execution and query.

[0037] 2.3.1 Step S300: Task Scheduling Center Intervention:

[0038] After the task template is configured, the task scheduling center begins to intervene and analyze the task template based on the set intervention scenario, delivery content, reachable objects, push frequency and other information;

[0039] The parsing process converts the abstract configuration in the task template into executable task instructions.

[0040] 2.3.2 Step S301: Generate specific intervention tasks:

[0041] Based on the analysis results, the task scheduling center generates specific intervention tasks, including the specific sending time, sending content, contact method and contact object.

[0042] 2.3.3 Step S302: Tasks are stored in the persistence layer:

[0043] The generated specific intervention tasks are stored in the persistence layer (database or file system) for subsequent execution and query.

[0044] 2.4 Step S4, task scheduling and execution:

[0045] Through the DolphinScheduler task scheduling tool and SchedulerX task scheduling tool, tasks are parsed and executed at the specified time point according to the set push frequency; before the task reaches the time, the task is disassembled and stored in the persistence layer, and then the task time wheel is facilitated to traverse the task execution at that time point.

[0046] The intervention strategy execution module executes the corresponding intervention strategy based on the customized intervention scenario and the content sent, including sending WeChat messages or making outbound calls.

[0047] 2.4.1 Step S400, task scheduling tool preparation:

[0048] Before the task reaches its deadline, DolphinScheduler and SchedulerX are used to parse and disassemble the tasks stored in the persistence layer. The parsing process converts the task instructions into specific execution actions, including sending WeChat messages and making outbound calls.

[0049] 2.4.2 Step S401, task time wheel traversal and execution:

[0050] The convenient task time wheel triggers the execution of tasks when traversing to the tasks at the specified time point; the intervention strategy execution module executes the corresponding intervention strategy according to the customized intervention scenario and sent content;

[0051] The execution process includes calling the corresponding sending interface (WeChat message interface or telephone outbound call interface) to send the message to the designated customer.

[0052] 2.4.3 Step S402, execution result feedback:

[0053] After the task is completed, the execution results will be fed back to the task scheduling center or related business systems.

[0054] The execution result includes the final status of the task (success, failure) and customer feedback (whether the message has been read, whether it has been replied, etc.).

[0055] (3) Mechanisms for resolving technical issues:

[0056] 3.1 The mechanism and principle of multi-scenario and multi-type optimization and upgrading based on the singleness of current SCRM customer management:

[0057] This invention uses a custom intervention scenario module to allow companies to set different customer intervention scenarios based on actual needs, such as low-frequency intervention, intervention for failed first-orders, and intervention for incentive activities. At the same time, the content customization module allows for flexible customization of the content sent to customers, including contact methods, message text, and message attachments.

[0058] By using these two modules in conjunction, enterprises can develop personalized intervention strategies for different customer scenarios and needs, thereby breaking the singleness of traditional SCRM customer management and achieving multi-scenario and multi-type optimization, upgrading and transformation.

[0059] 3.2 The mechanism and principle of selecting BI groups supported by big data in the current SCRM field, which cannot accurately manage customers:

[0060] This invention uses BI crowd selection technology to classify customer profiles through big data and assign different labels to achieve accurate customer classification and screening. The reach target module can customize the reach target type based on the BI crowd selection results and specify the customer groups that need intervention.

[0061] Big data-based customer profiling technology can deeply explore customer behaviors and characteristics, providing strong support for precision management. BI crowd selection technology can further refine customer groups, ensuring that intervention strategies can accurately reach target customers.

[0062] 3.3 In view of the single customer management method in the current SCRM field, the present invention provides a mechanism and principle of configurable management strategy and method:

[0063] This invention provides configurable management approaches, including custom intervention scenarios, content sent, reach targets, push frequency, and other aspects. Enterprises can flexibly configure these management approaches according to actual needs to form personalized management strategies.

[0064] By providing a configurable management approach, the present invention gives enterprises more autonomy and flexibility, enabling them to formulate management strategies that better meet their own needs based on actual conditions, thereby solving the problem of a single way of managing customers.

[0065] 3.4 In response to the current manual customer management method in the SCRM field, the present invention provides a mechanism and principle for intelligent customer intervention using configurable timing strategies:

[0066] This invention implements a configurable timing strategy by intervening in the strategy execution module and combining it with task scheduling tools such as DolphinScheduler and SchedulerX. Enterprises can set the frequency of push messages as needed and parse and execute tasks at specified times.

[0067] Through intelligent task scheduling and execution tools, this invention can automatically execute intervention strategies, avoiding the tedious and inefficient manual management of customers. Furthermore, configurable timing strategies allow companies to more flexibly adjust the execution time and frequency of intervention strategies, improving customer satisfaction and loyalty.

[0068] Secondly, a customer relationship management system based on multi-scenario and multi-type intervention:

[0069] like Figures 2-3 As shown, the system is used to implement the customer relationship management method and system based on multi-scenario and multi-type intervention described above, which includes:

[0070] A custom intervention scenario module for setting different customer intervention scenarios based on enterprise needs: including low-frequency intervention, intervention for failed first-orders, and intervention for incentive activities;

[0071] A customizable module for setting the content sent to customers: including contact method (WeChat message and outbound call), message copy, message attachments, and / or push frequency;

[0072] The reach object module of the custom reach object class: specify according to BI population and specify customers according to circle;

[0073] Push frequency setting module for setting the frequency of push messages: including single, daily, weekly and / or monthly;

[0074] The content type setting module is used to set the type of content to be sent, including sending WeChat messages and / or outbound calls;

[0075] Customer data management module for storing and managing customer data: including basic customer information and / or transaction records;

[0076] An intervention strategy execution module is used to execute corresponding intervention strategies based on customized intervention scenarios and sent content.

[0077] Compared with the prior art, the present invention has the following beneficial effects:

[0078] 1. Meeting the enterprise's needs for multi-scenario and multi-type intervention: By customizing intervention scenarios and delivery content, enterprises can set different customer intervention scenarios and delivery content according to actual needs, such as low-frequency intervention, intervention for failed first-orders, intervention for reward activities, etc., and flexibly configure contact methods, message copy, message attachments, etc., to meet the enterprise's needs for multi-scenario and multi-type intervention.

[0079] Second, it improves customer precision management: By leveraging BI crowd selection technology powered by big data, this invention can deeply explore customer behaviors and characteristics, enabling precise customer classification and screening. This enables companies to more accurately reach target customers and improve the precision of customer relationship management.

[0080] 3. Improve intervention effectiveness and customer satisfaction: By flexibly setting push frequency and content types, companies can develop personalized intervention strategies based on customers' actual needs and preferences. This helps improve intervention effectiveness and enhance customer satisfaction and loyalty.

[0081] Fourth, providing data support and decision-making basis for enterprises: The present invention also provides a customer data management module for storing and managing customer data, including basic customer information and transaction records. This data provides strong data support and decision-making basis for enterprises, helping them better understand customer needs and market trends and formulate more scientific and reasonable marketing strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0083] Figure 1 Schematic diagram of the method flow of the present invention;

[0084] Figure 2 Schematic diagram of the system architecture of the present invention;

[0085] Figure 3 Schematic diagram of the system execution flow of the present invention. DETAILED DESCRIPTION

[0086] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. The following description sets forth many specific details to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art can make similar improvements without violating the scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0087] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0088] Explanation of relevant terms:

[0089] (1) Low-frequency intervention: refers to intervention measures that are carried out on customers less frequently to maintain or improve customer relationships.

[0090] (2) Intervention for customers who have not completed their first purchase: Special intervention is carried out for customers who have not completed their first purchase to promote their conversion.

[0091] (3) Reward activity intervention: By providing rewards or preferential activities to motivate customers to purchase or participate, thereby enhancing customer stickiness.

[0092] (4) BI crowd selection: Use big data technology to classify customer portraits and label them with different labels to accurately select target customer groups.

[0093] (5) Object type: During the intervention process, the type or category of the client being intervened is specified.

[0094] (6) Customer groups: Customer groups with similar characteristics or needs are the main targets of intervention strategies.

[0095] (7) Frequency of push messages: The frequency of sending messages to customers during the intervention process, such as daily, weekly, etc.

[0096] (8) Basic customer information: including the customer’s name, contact information, address and other basic information, used to identify and manage customers.

[0097] (9) Transaction records: records customers’ purchasing behavior, including purchased items, amount, time, etc., for analyzing customer needs and purchasing habits.

[0098] (10) Specific intervention tasks: Specific intervention actions targeted at specific customer groups are generated based on preset intervention scenarios and strategies.

[0099] (11) DolphinScheduler task scheduling tool: A tool for task parsing, scheduling, and execution, ensuring that intervention tasks are executed accurately at the specified time.

[0100] (12) SchedulerX task scheduling tool: Another task scheduling tool similar to DolphinScheduler, which provides task parsing, scheduling and execution functions and supports complex task scheduling strategies.

[0101] Example 1: Figure 1 As shown, this embodiment discloses an application example of a customer relationship management method based on multi-scenario and multi-type intervention in an online ride-hailing platform. This SCRM solution aims to optimize and upgrade the customer relationship management of the online ride-hailing platform in multiple scenarios and types, and realize precise management, configurable management methods, and intelligent customer intervention. The specific process is as follows:

[0102] In this embodiment, regarding the task template configuration:

[0103] Specifically, step S100: Set and configure customer intervention scenarios: On the ride-hailing platform, set scenarios such as low-frequency intervention (e.g., sending coupons to users who haven't used the platform for a long time), intervention for missed orders (e.g., sending first-order discounts to new users), and reward activity intervention (e.g., sending points rewards to frequent users). Depending on the intervention scenario, set the content to be sent, such as WeChat messages (containing coupon links or activity details) or outbound calls (customer service staff informing customers of discount information).

[0104] Specifically, step S101: Customize the target type and specify the customer group: Utilize big data technology to analyze the user profiles and behavioral characteristics of the ride-hailing platform, classify and label them, such as "low-frequency users," "new users," "high-frequency users," etc. Based on the BI population selection results, customize the target type, such as "low-frequency user group," "new user group," etc., and specify the customer group that requires intervention.

[0105] Specifically, step S102: Set and configure the push message frequency: Based on the intervention scenario and customer group needs, set the push message frequency, such as sending coupons once a month to low-frequency users, and sending first-order discounts to new users immediately after registration. Configure these frequencies in the SCRM system to ensure that the system can send messages to customers according to the preset frequency.

[0106] In this embodiment, regarding S2: Data storage and update:

[0107] Specifically, step S200: storing basic customer information: collecting and organizing basic information of users of the online ride-hailing platform, including name, gender, age, contact information, address, etc. This information is stored in the customer data management module of the SCRM system for subsequent use.

[0108] Specifically, step S201: transaction record management: record each transaction information of the user, including order number, transaction time, transaction amount, payment method, etc. The transaction record is also stored in the customer data management module for subsequent analysis and decision-making.

[0109] Specifically, step S202: Real-time data update: Establish a data center for storing and updating customer data in real time. Using data streaming technology, capture and update users' latest transaction information and behavioral characteristics in real time to ensure the timeliness and accuracy of customer data.

[0110] In this embodiment, regarding S3: task parsing and generation:

[0111] Specifically, step S300: Task Scheduling Center Intervention: After the task template is configured, the task scheduling center begins intervening and parses the task template based on the configured intervention scenario, content, reach, and push frequency. The parsing process converts the abstract configuration in the task template into executable task instructions.

[0112] Specifically, step S301: Generate a specific intervention task: Based on the analysis results, the task scheduling center generates a specific intervention task, including the specific sending time, sending content, contact method, and contact target. For example, "Send a coupon WeChat message to low-frequency user groups on XX month XX day."

[0113] Specifically, step S302: storing the task in the persistence layer: the generated specific intervention task is stored in the persistence layer (such as a database or a file system) for subsequent execution and query.

[0114] In this embodiment, regarding S4: task scheduling and execution:

[0115] Specifically, step S400: Task scheduling tool preparation: Before the task reaches its deadline, DolphinScheduler and SchedulerX are used to parse and decompose the tasks stored in the persistence layer. The parsing process converts the task instructions into specific execution actions, such as calling the WeChat message interface to send a message or making an outbound call.

[0116] Specifically, step S401: Task Timeline Traversal and Execution: The task timeline facilitates traversal and triggers the execution of tasks at designated time points. The intervention strategy execution module executes the corresponding intervention strategy based on the customized intervention scenario and content. For example, calling the WeChat message interface to send a coupon link to a designated low-frequency user.

[0117] Specifically, step S402: execution result feedback: after the task is completed, the execution result is fed back to the task scheduling center or related business system.

[0118] Example 2: Based on Example 1, this example further provides its Python execution program as follows:

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[0124] All of the above embodiments merely represent implementation methods of the present invention in practical applications. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the scope of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the appended claims.

[0125] For those skilled in the art, it can be further appreciated that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0126] At the same time, those skilled in the art will understand that all or part of the processes in all the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

Claims

1. A customer relationship management method based on multi-scenario and multi-type intervention, characterized by: When receiving the activation instruction of the customer relationship management solution triggered by the user or system administrator on the SCRM system user interface, the following operation process is executed: S1: Set up different customer intervention scenarios through the user interface, including low-frequency intervention, intervention for failed first-orders, and intervention for incentive activities, and configure these scenarios into the system; S2, stores and manages customer data, including basic customer information and transaction records; S3: After the task template is configured, the task scheduling center analyzes the task and generates a specific intervention task based on the intervention scenario, content, target audience, and push frequency information. S4, the intervention strategy execution module executes the corresponding intervention strategy according to the customized intervention scenario and the content sent, including sending WeChat messages or making outbound calls.

2. The customer relationship management method according to claim 1, wherein: In S1, the content to be sent to the customer is set according to the intervention scenario, including the contact method, message copy and / or message attachments, and these contents are configured in the system; Based on the BI population selection results, customize the target type and specify the customer groups that need intervention; Set the frequency of push notifications and configure these frequencies into the system.

3. The customer relationship management method according to claim 2, wherein: The execution process of S1 includes: S100: Set different customer intervention scenarios through the user interface, including low-frequency intervention, intervention for failed first-orders, and intervention for incentive programs. Based on the configured intervention scenarios, set the specific content sent to customers, including contact methods, message copy, and message attachments. S101 uses BI crowd selection technology to categorize customers based on their profiles and behavioral characteristics, and assigns them different labels. Based on the results of BI crowd selection, you can customize the types of customers you can reach, including customer groups based on specific age groups, consumption habits, or interest preferences. S102, according to the intervention scenario and the needs of the customer group, set the frequency of push messages, including single, daily, weekly or monthly.

4. The customer relationship management method according to claim 1, wherein: The execution process of S2 includes: S200, collect and organize the customer's basic information, including name, gender, age, contact information and address, and store it in the customer data management module of the SCRM system; S201, record each customer's transaction information, including transaction time, transaction goods, transaction amount and payment method; S202, establish a middle platform for storing and updating customer data in real time; through data streaming technology, capture and update customers' latest transaction information and behavioral characteristics in real time.

5. The customer relationship management method according to claim 1, wherein: The execution process of S3 includes: S300: After the task template is configured, the task scheduling center begins to intervene and analyzes the task template based on the configured intervention scenario, delivery content, reachable objects, and push frequency. S301: Based on the analysis results, the task scheduling center generates a specific intervention task, including the specific sending time, sending content, contact method, and contact target; S302: The generated specific intervention task is stored in the persistence layer.

6. The customer relationship management method according to claim 5, characterized in that: In the S300 , the parsing process converts the abstract configuration in the task template into executable task instructions.

7. The customer relationship management method according to claim 1, wherein: In the S4, the DolphinScheduler task scheduling tool and the SchedulerX task scheduling tool are used to parse and execute tasks at specified time points according to the set push frequency; before the task reaches the time, the task is disassembled and stored in the persistence layer.

8. The customer relationship management method according to claim 7, characterized in that: The execution process of S4 includes: S400: Before the task reaches its scheduled time, DolphinScheduler and SchedulerX are used to parse and decompose the tasks stored in the persistence layer. The parsing process converts the task instructions into specific execution actions, such as sending WeChat messages and making outbound calls. S401, the task time wheel is convenient. When traversing to the task at the specified time point, the task execution is triggered; the intervention strategy execution module executes the corresponding intervention strategy according to the customized intervention scenario and the sent content; S402: After the task is completed, the execution result is fed back to the task scheduling center or related business system.

9. A system for implementing the customer relationship management method according to any one of claims 1 to 8, characterized in that: The system comprises: A custom intervention scenario module for setting different customer intervention scenarios based on enterprise needs; Send content customization module for setting the content sent to customers; The reach object module of the custom reach object class; A push frequency setting module for setting the frequency of push messages; A sending content type setting module is used to set the type of sending content.

10. The system according to claim 9, characterized in that: The system further includes a customer data management module for storing and managing customer data, and an intervention strategy execution module for implementing customized intervention scenarios and sending content.

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