Multi-task-based configurable Lego activity configuration device

Abstract

The invention discloses a configurable Lego activity configuration device based on multiple tasks, which adopts a modularized and Lego type activity configuration mode, so that the development cycle of a system is greatly shortened, and tenants can online new marketing activities without waiting for long-time system development and testing. The tenants can flexibly adjust task rules, reward schemes and assessment indexes directly on a visual front-end interface by dragging, configuring and combining various preset activity components according to own operation requirements, so as to quickly respond to market changes and strategy adjustment. For example, when the order quantity of a certain operation area is increased sharply, the tenant can configure the reward activity matched with the tenant in real time; or customized tasks are launched on specific holidays and festivals, more drivers are attracted to participate, and the operation efficiency is improved. According to the mode, the dependence on professional development resources is reduced, and the agility and the self-service capability of the business are remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the field of online car-hailing, and specifically relates to a Lego-like activity configuration device based on multi-task configurability. Background Art

[0002] In the current online ride-hailing industry, with intensifying market competition and evolving business models, tenants' demands for marketing campaigns are becoming increasingly diverse and personalized. Traditional marketing campaign systems often utilize fixed, pre-set functional modules, resulting in a rigid system design. Expanding new functionality requires close collaboration across multiple processes, including product development, R&D, and testing, resulting in long development cycles and high labor costs. Furthermore, a single campaign format not only fails to meet tenants' precise marketing needs across different regions, time periods, and driver groups, but also fails to motivate drivers to participate consistently.

[0003] Existing marketing campaign systems typically employ a fixed design. Initially developed to meet basic business needs, they pre-set a set of static functional modules and logical structures. However, with intensified market competition and the continuous development of the ride-hailing business, tenants' demands for marketing campaigns have become more flexible and personalized. Traditional systems often face high labor costs and time investment when expanding new features, requiring close collaboration among multiple departments, including product development, R&D, and testing. This not only prolongs feature launch cycles but also reduces the ability to quickly respond to the market. Furthermore, because the original system design failed to fully consider future scalability and diverse needs, new marketing strategies often require significant customization, increasing the difficulty of maintenance and upgrades. Ultimately, this fails to meet tenants' precise marketing needs across different regions, time periods, or driver groups. Furthermore, single-model campaigns not only lack sufficient appeal to inspire long-term driver participation, but also make it difficult for marketing campaigns to effectively differentiate themselves, further impacting the overall platform's operational efficiency.

[0004] In view of this, the present invention is proposed. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a Lego-based activity configuration device that is configurable based on multiple tasks, thereby solving the problems raised in the above-mentioned background technology.

[0006] In order to solve the above technical problems, the basic concept of the technical solution adopted by the present invention is:

[0007] A multi-task configurable Lego-style activity configuration device includes: a task component creation module: used to create various types of task components, each task component has specific rules and configuration methods, and includes participation conditions, assessment conditions, and reward conditions; task components can exist as independent subtasks, or as part of a combo parent task and be combined with other subtasks;

[0008] Task combination module: used to combine multiple task components according to preset rules to generate a combo parent task consisting of multiple tasks. Each task component can exist independently as a subtask or be combined with other subtasks. Both the parent task and the subtask contain participation conditions, assessment conditions, and reward conditions. Task type definition module: divides the parent task into check-in tasks, level-breaking tasks, and task package tasks according to the gameplay. Each task type has specific rules and configuration methods.

[0009] Activity Component Library: This library stores a variety of draggable and assembled activity component libraries, covering modules such as activity assessment indicators, participation conditions, and reward conditions. Each module contains a single "Lego-like" component, and there are logical and hierarchical relationships between components.

[0010] Front-end display and operation module: Provides a standard Combo task creation page. Users can select marketing activity components with corresponding characteristics for different marketing scenarios as relevant indicator data for the parent task on the front-end web page, and then select subtasks to assemble and combine to form a complete activity.

[0011] Data storage and transmission module: stores and transmits generated activities in standard JSON format, facilitating structured display and analysis, and ensuring the integrity and accuracy of activity data;

[0012] Server-side matching module: Based on pre-designed component combination data, activity matching operations are performed for different computing scenarios, such as "orders", "duration", "post-commission flow", etc., to achieve accurate matching of drivers, orders, and activities.

[0013] Optionally, create multiple types of task components, each with specific rules and configuration methods. The steps are as follows:

[0014] Create various types of task components, each with specific rules and configurations based on different marketing needs;

[0015] Set specific parameters for each task component. For order tasks, you can set the number of completed orders to meet the target, for online time tasks, you can set the cumulative time target, and for turnover tasks, you can set the minimum turnover amount. At the same time, you can also customize the calculation method, time limit, and repeat claim rules for rewards after task completion.

[0016] Each task component can exist as an independent subtask, and drivers can complete these tasks independently without relying on other tasks. Task components can not only exist independently, but can also be combined according to preset rules to form a Combo parent task. The Combo parent task consists of multiple subtasks and sets logical relationships based on operational needs. The logical relationships use "and" relationships, "or" relationships, and threshold relationships.

[0017] After the task components are combined, the system will perform logical verification on the task rules to avoid conflicts or unreasonable configurations. In addition, users can adjust the task configuration through a visual interface.

[0018] Optionally, when configuring a check-in task, drivers can complete the task by simply checking in daily, without any additional steps. Assessment criteria are consecutive check-in days or cumulative check-in days. Rewards are awarded based on check-in frequency, with the ability to set fixed or tiered rewards.

[0019] Optionally, define rules when configuring a level-by-level mission: Drivers must complete the mission in a progressively higher-level hierarchy, progressing to the next level after completing each one. Each level has increasingly challenging assessment criteria. Assessment criteria include completing a certain number of orders, accumulating online time, and achieving turnover targets. Reward criteria: Each level completed earns a corresponding reward, with the option to set individual rewards or a grand prize.

[0020] Optionally, task packages define rules: Drivers must complete a set of tasks within a time limit. Each task can stand alone or be combined, and the relationships between tasks within a task package can be set as "AND" or "OR." Assessment criteria: A task package contains multiple subtasks, and drivers must complete some or all of them. Reward criteria: Task packages can have fixed or tiered rewards.

[0021] Optionally, store a variety of draggable activity element components, covering modules such as activity assessment indicators, participation conditions, and reward conditions. Each module contains a single "Lego-like" component. The logical and hierarchical relationships between components are as follows:

[0022] Create an activity element component library to store a variety of activity element components that can be dragged and assembled. The component library is classified according to modules such as assessment indicators, participation conditions, and reward conditions. Each module contains multiple "Lego-like" components. Then, according to the needs of the marketing activities, the components are divided into the following categories and the corresponding attributes and parameters are set: Assessment indicator components: order completion volume, online time, and turnover amount. Participation condition components: driver level, new and old users, and service areas. Reward condition components: reward type (cash, points, coupons), reward amount, and distribution method;

[0023] To ensure that components remain reasonable when assembled, it is necessary to define mutual exclusion relationships, combination mutual exclusion relationships, upper and lower association relationships, and threshold association relationships.

[0024] Optionally, a visual interface is provided in the front-end display and operation module, supporting users to select and assemble activity element components by dragging and dropping. The assembled task components are stored in JSON format. Users can select the required assessment indicators, participation conditions, and reward condition components, drag the components to the task configuration area, and freely combine them to form a complete task.

[0025] Based on pre-designed component combination data, activity matching operations are performed for different computing scenarios, such as "orders," "duration," and "post-commission turnover." The steps to achieve accurate matching between drivers, orders, and activities are as follows:

[0026] Create a component combination database to store pre-designed task component combination data and classify and store it according to different computing scenarios (such as number of orders, online time, and turnover amount);

[0027] Define supported computing scenarios and set corresponding matching logic, including but not limited to: order scenarios, duration scenarios, and post-commission flow scenarios;

[0028] Task data is stored in a unified JSON format for subsequent matching and parsing. Driver behavior data (number of orders, online time, turnover amount, etc.) is monitored in real time. When a driver's behavior data meets the calculation scenario of a task, the system automatically matches the corresponding task.

[0029] The successfully matched task information is stored in the matching record database for subsequent operational analysis and execution of the reward and punishment mechanism.

[0030] After adopting the above technical solution, the present invention has the following beneficial effects compared with the prior art. Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described below at the same time:

[0031] The present invention significantly shortens the development cycle of the system by adopting a modular, Lego-style activity configuration method. Tenants can launch new marketing activities without waiting for a long time for system development and testing. Tenants can directly drag, configure and combine various preset activity components on the visual front-end interface to flexibly adjust task rules, reward plans and assessment indicators according to their own operational needs, thereby quickly responding to market changes and strategy adjustments. For example, when the order volume in a certain operating area surges, tenants can instantly configure reward activities to match it; or launch customized tasks on specific holidays to attract more drivers to participate and improve operational efficiency. This approach not only reduces dependence on professional development resources, but also significantly improves the agility and self-service capabilities of the business, allowing operational strategies to be implemented more quickly and accurately, ultimately promoting the improvement of overall operational efficiency.

[0032] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The drawings described below are only some embodiments. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0034] In the picture:

[0035] Figure 1 Configure the overall process diagram for Lego-based activities;

[0036] Figure 2 Schematic diagram of assembling an activity template by dragging and dropping activity element components.

[0037] It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but rather to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0038] The present invention will now be described in further detail with reference to the accompanying drawings.

[0039] See also Figure 1-2 As shown, in this embodiment, a multi-task configurable Lego-based activity configuration device is provided, including

[0040] Task component creation module: used to create various types of task components, each task component has specific rules and configuration methods, and includes participation conditions, assessment conditions and reward conditions; task components can exist as independent subtasks, or be combined with other subtasks as part of a Combo parent task; in the task component creation module, task types include but are not limited to sign-in tasks, level-breaking tasks, task package tasks, etc. Each task type has specific rules and configuration methods. For example, a sign-in task requires the driver to sign in within the specified time, a level-breaking task requires the driver to complete a series of preset tasks, and a task package task packages multiple subtasks into a task package for the driver to complete.

[0041] Task combination module: used to combine multiple task components according to preset rules to generate a Combo parent task consisting of multiple tasks. Each task component can exist independently as a subtask or be combined with other subtasks. Both the parent task and the subtask include participation conditions, assessment conditions and reward conditions; in the task combination module, the assessment conditions of the parent task include but are not limited to the driver's number of completed orders, vehicle dispatch time, turnover after commission deduction and other indicators, and the assessment conditions of multiple subtasks can be set with "and" or "or" logical relationships.

[0042] Task type definition module: divides parent tasks into check-in tasks, level-breaking tasks, and task package tasks according to gameplay. Each task type has specific rules and configuration methods;

[0043] Activity element component library: stores a variety of activity element components that can be dragged and assembled, covering modules such as activity assessment indicators, participation conditions, and reward conditions. Each module contains a single "Lego-like" component, and there are logical and hierarchical relationships between components. In the activity element component library, the activity element components also include configuration items such as the activity reward type, reward amount, and reward distribution method, and the reward rules can be flexibly set, such as giving different levels of rewards based on the number or quality of tasks completed by the driver.

[0044] Front-end display and operation module: provides a standard Combo task creation page. Users can select marketing activity element components with corresponding characteristics for different marketing scenarios as relevant indicator data of the parent task on the front-end web page, and select sub-tasks to assemble and combine to form a complete activity; the front-end display and operation module provides a visual interface for users to perform operations such as dragging, selecting, and configuring, and preview the combination effects and logical relationships of the activities in real time to ensure the accuracy and rationality of the activity configuration.

[0045] Data storage and transmission module: stores and transmits generated activities in standard JSON format, facilitating structured display and analysis, and ensuring the integrity and accuracy of activity data;

[0046] The server-side matching module uses pre-designed component data to perform activity matching for different computing scenarios, such as "order," "duration," and "post-commission turnover," achieving accurate matching between drivers, orders, and activities. This server-side matching module automatically identifies and matches activity rules and task requirements for different computing scenarios, enabling real-time monitoring of driver behavior data and automatic distribution of activity rewards, improving operational efficiency and driver engagement.

[0047] In this embodiment, the steps for creating multiple types of task components, each with specific rules and configuration methods, are as follows:

[0048] Create various types of task components, each with specific rules and configurations based on different marketing needs. For example, a task component can involve core assessment indicators such as order quantity, online time, and turnover amount. Each task component sets participation conditions (such as driver level, applicable area, etc.), assessment conditions (such as specific requirements for task completion), and reward conditions (such as reward amount and distribution method);

[0049] Set specific parameters for each task component. For order tasks, you can set the number of completed orders to meet the target, for online time tasks, you can set the cumulative time target, and for turnover tasks, you can set the minimum turnover amount. At the same time, you can also customize the calculation method, time limit, and repeat claim rules for rewards after task completion.

[0050] Each task component can exist as an independent subtask, and drivers can complete these tasks independently without relying on other tasks. Task components can not only exist independently, but can also be combined according to preset rules to form a Combo parent task. The Combo parent task is composed of multiple subtasks, and the logical relationship is set according to operational needs. The logical relationship adopts "and" relationship, "or" relationship, and threshold relationship. For example, a task of "rewarding 10 yuan for completing 5 orders per day" can be run independently and rewarded without being constrained by other tasks; among them, "and" relationship: the driver needs to complete all subtasks to receive the reward. "Or" relationship: the driver only needs to complete one of the subtasks to receive the reward. Threshold relationship: the task reward is issued in a tiered manner according to the number or quality of completed subtasks.

[0051] After task components are combined, the system will perform a logical check on the task rules to avoid conflicts or unreasonable configurations. In addition, users can adjust task configurations through a visual interface. For example, tasks within the same time period should not be mutually exclusive (e.g., "high turnover tasks" and "low turnover tasks" cannot be effective at the same time), and reward rules should not contain duplicate calculations.

[0052] Logical verification includes mutual exclusion check and logical consistency check:

[0053] Mutual exclusion check: The same driver cannot participate in conflicting tasks (such as "high-flow tasks" and "low-flow tasks") at the same time.

[0054] Logical consistency check: whether the reward rules of the combined task match the assessment conditions to avoid reward calculation conflicts.

[0055] In this embodiment, when configuring a sign-in task, drivers can complete the task by signing in every day without any additional steps. The assessment conditions are the number of consecutive sign-in days or the cumulative number of sign-in days (for example, a reward of 50 yuan is given for signing in for 7 consecutive days). The reward conditions are based on the frequency of sign-in, and can be set as fixed rewards or tiered rewards (for example, 5 yuan on the first day, 50 yuan on the seventh day).

[0056] In this embodiment, the rules for configuring the level-breaking tasks are defined: drivers must complete the tasks in a hierarchical and progressive manner, and can only enter the next level after completing each level. The assessment requirements for each level increase step by step. Assessment conditions include completing a certain number of orders, cumulative online time, and achieving a turnover target (e.g., Level 1: completing 5 orders, Level 2: completing 10 orders). Reward conditions: Each completed level can receive a corresponding reward, and individual rewards or a final grand prize can be set (e.g., a total reward of 200 yuan for successfully completing a level).

[0057] In this embodiment, the task package task configuration definition rules are as follows: the driver needs to complete a set of tasks within a limited time. Each task can exist independently or be completed in combination. The task relationship within the task package can be set as "and" or "or". Assessment conditions: The task package contains multiple subtasks (such as "5 orders + 6 hours online + 500 yuan in turnover"), and the driver needs to complete some or all of them. Reward conditions: The task package can be set with fixed rewards or graded rewards (such as 20 yuan for completing 2 items and 50 yuan for completing 3 items).

[0058] In this embodiment, a variety of draggable and assembled activity element components are stored, covering modules such as activity assessment indicators, participation conditions, and reward conditions. Each module contains a single "Lego-like" component. The logical and hierarchical relationships between components are as follows:

[0059] Create an activity element component library to store a variety of activity element components that can be dragged and assembled. The component library is classified according to modules such as assessment indicators, participation conditions, and reward conditions. Each module contains multiple "Lego-like" components. Then, according to the needs of the marketing activities, the components are divided into the following categories and the corresponding attributes and parameters are set: Assessment indicator components: order completion volume, online time, and turnover amount. Participation condition components: driver level, new and old users, and service areas. Reward condition components: reward type (cash, points, coupons), reward amount, and distribution method;

[0060] To ensure that components remain reasonable when assembled, it is necessary to define mutual exclusion relationships, combination mutual exclusion relationships, upper and lower association relationships, and threshold association relationships;

[0061] Mutually exclusive relationships: Conflicting components cannot be used at the same time (e.g., "high turnover rewards" and "low turnover rewards" cannot be configured at the same time). Combination mutually exclusive relationships: Specific task combinations cannot coexist (e.g., "single order rewards" and "cumulative order rewards" cannot exist at the same time). Contextual relationships: Some tasks depend on other tasks (e.g., "level-breaking tasks" must depend on "basic tasks"). Threshold relationships: The completion criteria of some tasks are limited by other tasks (e.g., "turnover rewards" can only be unlocked after "completing 10 orders").

[0062] In this embodiment, a visual interface is provided in the front-end display and operation module, which supports users to select and assemble activity element components by dragging and dropping. The assembled task components are stored in JSON format. The required assessment indicators, participation conditions and reward condition components are selected, and the components are dragged to the task configuration area to freely combine them to form a complete task.

[0063] Based on pre-designed component combination data, activity matching operations are performed for different computing scenarios, such as "orders," "duration," and "post-commission turnover." The steps to achieve accurate matching between drivers, orders, and activities are as follows:

[0064] Create a component combination database to store pre-designed task component combination data and classify and store it according to different computing scenarios (such as number of orders, online time, and turnover amount);

[0065] Define supported computing scenarios and set corresponding matching logic, including but not limited to: order scenarios, duration scenarios, and post-commission flow scenarios;

[0066] Order scenario: Task matching is based on the number of orders completed by the driver (e.g. “Complete 10 orders and get a 50 yuan reward”).

[0067] Duration scenario: Matching is based on the driver's online time (e.g. "Get a reward if you are online for 6 hours").

[0068] Post-commission turnover scenario: Matching is based on the driver's turnover amount after deducting the commission (such as "unlock additional rewards when the post-commission turnover reaches 500 yuan").

[0069] Task data is stored in a unified JSON format for subsequent matching and parsing, and the driver's behavior data (number of orders, online time, turnover amount, etc.) is monitored in real time. When the driver's behavior data meets the calculation scenario of a task, the system automatically matches the corresponding task. For example:

[0070] When a driver completes 10 orders in total, the system matches the task to the order scenario and triggers the reward distribution process.

[0071] When a driver is online for 6 hours, the system matches the task with the required duration and calculates whether the driver meets the reward conditions.

[0072] When the driver's turnover after commission reaches 500 yuan, the system will match the tasks of the turnover scenario and calculate the corresponding rewards.

[0073] The successfully matched task information is stored in the matching record database for subsequent operational analysis and execution of the reward and punishment mechanism.

[0074] The task enters the activity execution module to calculate and distribute rewards to ensure a closed-loop task.

[0075] Drivers can view task progress and matching results in real time on the front-end page to increase activity participation.

[0076] like Figure 1 As the name suggests, combo means combination. Combo multi-task (hereinafter referred to as parent task) is to combine multiple task components according to a rule to generate a new task composed of multiple tasks; as shown in the process, the user can select the task skin he wants in the jigsaw puzzle processing device, and then select the task component he wants to find from the component processing device. Through the task processing device, this series of components and skins are generated into individual task components (hereinafter referred to as subtasks). The user can select one or more subtasks to associate and combine them into a complete combo parent task. Thus, a standard combo task is generated. Each complete combo task is a standard JSON format data, which is conducive to storage, structured display and parsing; the JSON format is as follows:

[0077]

[0078]

[0079] like Figure 2 The following shows a standard combo task creation page. On the front-end web page, users can select marketing campaign components with specific characteristics for different marketing scenarios as relevant indicator data for the parent task. They can also select subtasks, assemble them into a combined task with the parent task, and submit it to the server. It's like building blocks with Lego. Each small unit (whether a component or a subtask) can be combined into a complete whole according to your preferences.

[0080] This activity includes modules such as assessment indicators, participation conditions, and reward conditions. Each module contains individual "Lego-like" components. These components are combined to form a complete activity. Basic activity data is stored and transmitted as a JSON-formatted text file. This basic data unit is called an activity Lego component.

[0081] The server performs activity matching operations based on pre-designed component combination data, targeting different calculation scenarios such as "orders", "duration", "post-commission flow", and according to activity data requirements, thereby accurately achieving driver-order-activity matching operations.

[0082] Of course, the template plug-ins contain information such as the logical relationship and hierarchical relationship of each activity element. The mutual exclusion relationship between templates, the combination mutual exclusion relationship, the upper and lower association relationship, the threshold association relationship, etc. The rich Lego-like components ensure the diversity of gameplay and once again ensure the accuracy of the matching operation of driver-order-activity. Figure 2 The three reward rule activity elements "number of completed orders", "time of vehicle dispatch" and "turnover after commission" have an "and" relationship, which means that all three rules must be met; at the same time, they all belong to the parent activity element "reward rules".

[0083]

[0084]

[0085]

[0086] The present invention is not limited to the above-described embodiments. Any structural changes made under the guidance of the present invention, which have the same or similar technical solutions as the present invention, should be understood to fall within the scope of protection of the present invention. The technologies, shapes, and structural parts not described in detail in the present invention are all well-known technologies.

Claims

1. A multi-task configurable Lego-like activity configuration device, characterized in that: include: Task component creation module: used to create various types of task components. Each task component has specific rules and configuration methods, and includes participation conditions, assessment conditions, and reward conditions. Task components can exist as independent subtasks or be combined with other subtasks as part of a combo parent task. Task combination module: used to combine multiple task components according to preset rules to generate a Combo parent task consisting of multiple tasks. Each task component can exist independently as a subtask or be combined with other subtasks. Both the parent task and the subtask contain participation conditions, assessment conditions, and reward conditions. Task type definition module: divides parent tasks into check-in tasks, level-breaking tasks, and task package tasks according to gameplay. Each task type has specific rules and configuration methods; Activity Component Library: This library stores a variety of activity component libraries that can be dragged and assembled, covering modules such as activity assessment indicators, participation conditions, and reward conditions. Each module contains a single "Lego-like" component, and there are logical and hierarchical relationships between components. Front-end display and operation module: Provides a standard Combo task creation page. Users can select marketing activity components with corresponding characteristics for different marketing scenarios as relevant indicator data for the parent task on the front-end web page, and then select subtasks to assemble and combine to form a complete activity. Data storage and transmission module: stores and transmits generated activities in standard JSON format, facilitating structured display and analysis, and ensuring the integrity and accuracy of activity data; Server-side matching module: Based on pre-designed component combination data, it performs activity matching operations for different computing scenarios, such as "orders", "duration", and "post-commission turnover", to achieve accurate matching of drivers, orders, and activities.

2. The multi-task configurable Lego-like activity configuration device according to claim 1, characterized in that: The steps to create various types of task components, each with specific rules and configuration methods, are as follows: Create various types of task components, each with specific rules and configurations based on different marketing needs; Set specific parameters for each task component. For order tasks, you can set the number of completed orders to meet the target, for online time tasks, you can set the cumulative time target, and for turnover tasks, you can set the minimum turnover amount. At the same time, you can also customize the calculation method, time limit, and repeat claim rules for rewards after task completion. Each task component can exist as an independent subtask, and drivers can complete these tasks independently without relying on other tasks. Task components can not only exist independently, but can also be combined according to preset rules to form a combo parent task. A combo parent task consists of multiple subtasks, and the logical relationships are set according to operational needs. The logical relationships use "and" relationships, "or" relationships, and threshold relationships. After the task components are combined, the system will perform logical verification on the task rules to avoid conflicts or unreasonable configurations. In addition, users can adjust the task configuration through a visual interface.

3. The multi-task configurable Lego-like activity configuration device according to claim 1, characterized in that: When configuring a sign-in task, drivers can complete the task by signing in every day without any additional operations. The assessment conditions are the number of consecutive sign-in days or the cumulative number of sign-in days. The reward conditions are rewards based on the frequency of sign-ins. Fixed rewards or tiered rewards can be set.

4. The multi-task configurable Lego-like activity configuration device according to claim 1, characterized in that: Rules are defined when configuring the task: drivers need to complete the task in a hierarchical manner, and can only enter the next level after completing each level. The assessment conditions for each level increase step by step. Assessment conditions include: completing a certain number of orders, accumulating online time, achieving turnover targets, etc. Reward conditions: each completed level can receive a corresponding reward, and individual rewards or a final grand prize can be set.

5. The multi-task configurable Lego-like activity configuration device according to claim 1, characterized in that: Task package task configuration definition rules: Drivers need to complete a set of tasks within a limited time. Each task can exist independently or be completed in combination. The task relationship within the task package can be set as "and" or "or". Assessment conditions: The task package contains multiple subtasks, and the driver must complete some or all of them. Reward conditions: The task package can set fixed rewards or tiered rewards.

6. The multi-task configurable Lego-like activity configuration device according to claim 1, characterized in that: Stores a variety of activity element components that can be dragged and assembled, covering modules such as activity assessment indicators, participation conditions, and reward conditions. Each module contains a single "Lego-like" component. The logical and hierarchical relationships between components are as follows: Create an activity component library to store various drag-and-drop activity component libraries. Categorize the library by modules such as assessment indicators, participation conditions, and reward conditions. Each module contains multiple "Lego-like" components. Then, based on the needs of the marketing campaign, divide the components into the following categories and set corresponding attributes and parameters: Assessment indicator components: order completion volume, online time, and turnover amount; Participation condition components: driver level, new and existing users, and service area; Reward condition components: reward type, reward amount, and distribution method. To ensure that components remain reasonable when assembled, it is necessary to define mutual exclusion relationships, combination mutual exclusion relationships, upper and lower association relationships, and threshold association relationships.

7. The multi-task configurable Lego-like activity configuration device according to claim 1, characterized in that: In the front-end display and operation module, a visual interface is provided to support users to select and assemble activity element components by dragging and dropping. The assembled task components are stored in JSON format. Users can select the required assessment indicators, participation conditions and reward condition components, drag the components to the task configuration area, and freely combine them to form a complete task.

8. Based on pre-designed component combination data, activity matching operations are performed for different calculation scenarios, such as "orders," "duration," and "post-commission turnover." The steps to achieve accurate matching between drivers, orders, and activities are as follows: Create a component combination database to store pre-designed task component combination data and classify and store them according to different computing scenarios; Define supported computing scenarios and set corresponding matching logic, including but not limited to: order scenarios, duration scenarios, and post-commission flow scenarios; Task data is stored in a unified JSON format for subsequent matching and parsing, and driver behavior data is monitored in real time. When the driver's behavior data meets the calculation scenario of a task, the system automatically matches the corresponding task. The successfully matched task information is stored in the matching record database for subsequent operational analysis and execution of the reward and punishment mechanism.

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