Marketing data processing method based on dynamic rule adaptation

Abstract

The invention discloses a marketing data processing method based on dynamic rule adaptation, and the method comprises the steps: obtaining an adaptive dynamic rule through a matching factor according to collected marketing plan data, and the matching factor at least comprises any one of time, region and product; according to the dynamic rule, combining with the marketing plan data to obtain a marketing cost pool; and according to the marketing cost pool, adjusting the marketing plan data, and according to the adjusted and executed marketing plan data, obtaining an execution cost pool to determine the performance of the execution personnel. Through dynamic rule adaptation, multi-dimensional matching factor and cost pool full life cycle management, the core problems of low efficiency, poor flexibility and slow response speed in traditional marketing cost calculation are solved, and an intelligent and extensible solution is provided for enterprise marketing management.

Description

Technical Field

[0001] The present invention belongs to the technical field of marketing data processing, and in particular relates to a marketing data processing method based on dynamic rule adaptation. Background Art

[0002] In the process of developing and maintaining a company's sales business market, how to evaluate and motivate sales personnel based on sales indicators is a core issue in improving the enthusiasm of the sales team and the competitiveness of the company.

[0003] Currently, most companies still rely on offline manual processes or Excel spreadsheets to calculate sales performance. This method is not only time-consuming and labor-intensive, but also prone to data errors due to human intervention. It also fails to integrate with existing enterprise systems (such as ERP and CRM), resulting in data silos and duplicate entries. Manual processing cannot meet the automated calculation requirements of complex sales policies (such as gradient incentives and conditional formulas), leading to long performance realization cycles and undermining sales staff's work enthusiasm.

[0004] A few companies have attempted to implement sales performance management through customized software development, but such systems are expensive to develop and require long policy adjustments (for example, programmers must hardcode logic). Existing customized systems lack the ability to dynamically adapt rules and respond quickly to market changes or policy adjustments, causing sales strategies to lag behind actual needs. The separation of expense pools from performance evaluations makes it difficult for companies to adjust strategies based on real-time data, reducing the effectiveness of sales team incentives.

[0005] Therefore, there is an urgent need to develop a marketing data processing method for adjusting marketing plan data and determining the performance of executives based on the processing of marketing data. Summary of the Invention

[0006] The present invention provides a marketing data processing method based on dynamic rule adaptation to solve the problems of low manual calculation efficiency and slow response speed to rule changes, and is used to adjust marketing plan data and determine the performance of executives.

[0007] The technical solution adopted in the present invention is:

[0008] A marketing data processing method based on dynamic rule adaptation, comprising:

[0009] According to the collected marketing plan data, adaptive dynamic rules are obtained through matching factors, wherein the matching factors include at least any one of time, region, and product;

[0010] According to dynamic rules, combined with the marketing plan data, a marketing expense pool is obtained;

[0011] The marketing plan data is adjusted according to the marketing expense pool, and an execution expense pool is obtained based on the adjusted executed marketing plan data to determine the performance of the execution personnel.

[0012] The marketing data processing method based on dynamic rule adaptation described in the present invention also includes the following additional technical features:

[0013] The dynamic rules are specifically:

[0014] Collect rule definition files corresponding to different time periods, different regions, and different products;

[0015] According to the rule definition file, through a visual interface, in response to the user's rule formula input, the dynamic rule corresponding to the matching factor is obtained; or,

[0016] According to the rule definition file, a corresponding rule formula is obtained through a semantic parsing tool to obtain the dynamic rule corresponding to the matching factor.

[0017] The adapted dynamic rules are as follows:

[0018] According to the multiple types of matching factors, dynamic rules are matched, wherein the multiple types of matching factors are set with priorities one by one;

[0019] If the dynamic rule obtained by matching is not unique and the corresponding matching factor types are inconsistent, the dynamic rule obtained by filtering the matching factor with a higher priority;

[0020] If the dynamic rule is not unique after screening, an adapted dynamic rule is obtained by weighting a plurality of the dynamic rules.

[0021] According to dynamic rules, combined with the marketing plan data, a marketing expense pool is obtained, specifically:

[0022] According to the dynamic rules, the marketing plan data is called, and the marketing expense share is obtained according to the dimension combination;

[0023] The marketing expense pool is obtained according to multiple marketing expense shares under a single dimension.

[0024] The dimensions are specifically:

[0025] The dimension includes at least any one of the expense collection dimension, the expense object dimension and the expense item dimension.

[0026] Adjust the marketing plan data, specifically:

[0027] If any of the dynamic rules changes, a marketing expense pool is obtained based on the changed dynamic rules and the unexecuted marketing plan data;

[0028] When the marketing expense pool decreases, the marketing plan data is adjusted according to the marketing expense pool.

[0029] Adjust the marketing plan data according to the marketing expense pool, specifically:

[0030] According to the marketing expense pool, the unexecuted marketing plan data is adjusted to obtain a marketing expense pool. When the adjusted marketing expense pool is greater than or equal to the marketing expense pool before the dynamic rule change, the adjustment iteration is stopped and the marketing plan data is determined for execution.

[0031] When the number of adjustments to the marketing plan data is greater than or equal to a preset threshold, the adjustment iteration is stopped, and the marketing plan data is selected for execution according to the corresponding marketing expense pool.

[0032] Determine executive performance, specifically:

[0033] According to the marketing plan data executed by the executives, the marketing expenses are obtained one by one;

[0034] According to the marketing expenses, combined with the marketing expense pool corresponding to the marketing plan data, the performance ratio of the executive personnel is obtained.

[0035] The present invention also provides a storage medium,

[0036] The storage medium stores a computer program, which, when executed, implements the steps of the marketing data processing method based on dynamic rule adaptation.

[0037] The present invention further provides an electronic device, comprising:

[0038] One or more central processing units,

[0039] one or more memories having a computer program stored therein,

[0040] The central processing unit is used to execute the computer program to implement the marketing data processing method based on dynamic rule adaptation.

[0041] Due to the adoption of the above technical solution, the beneficial effects achieved by the present invention are as follows:

[0042] 1. In the present invention, dynamic rules are automatically adapted through matching factors (time, region, product), replacing traditional manual calculations or Excel operations. The automated calculation process greatly reduces manual intervention and shortens the calculation cycle, and automatically binds business data through adapted dynamic rules to avoid human calculation errors. The matching factor can support combined matching of multiple dimensions (time, region, product), and ensures that dynamic rules are highly consistent with business scenarios through multi-dimensional attribute matching. Moreover, when the rules of some regions change, it is only necessary to adjust the rules of the region to support rapid adjustments under market changes and improve the response speed of the strategy.

[0043] Adjust unexecuted marketing plan data based on the marketing expense pool and generate an executed expense pool through iterative optimization. The expense pool calculation results can be used to optimize resource allocation, improve resource utilization efficiency, and obtain a more optimal marketing plan.

[0044] By using the executed marketing plan data, we can generate an execution fee pool and generate performance results. Performance evaluation is based on actual execution data, avoiding deviations from planned data and improving incentive accuracy. This can also motivate sales personnel to adjust strategies, such as strengthening execution of unmet targets.

[0045] The present invention solves the core problems of low efficiency, poor flexibility and slow response speed in traditional marketing expense calculation through dynamic rule adaptation, multi-dimensional matching factors and full life cycle management of expense pools, providing an intelligent and scalable solution for enterprise marketing management. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0047] Figure 1 The figure is a flowchart of the marketing data processing method based on dynamic rule adaptation in one embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to more clearly illustrate the overall concept of the present invention, a detailed description is given below in an exemplary manner in conjunction with the accompanying drawings.

[0049] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0050] like Figure 1 As shown, a marketing data processing method based on dynamic rule adaptation includes:

[0051] S100: Obtaining adaptive dynamic rules based on the collected marketing plan data through matching factors, wherein the matching factors include at least any one of time, region, and product.

[0052] The core purpose of this step is to solve the problems of low efficiency in complex policy matching and long rule adjustment cycle in the calculation of corporate marketing expenses through a dynamic rule adaptation mechanism.

[0053] It should be noted that the marketing plan data collected in this step can be the expected data of the formulated marketing plan, which is imported into this method for processing and used to determine the expected effect of the marketing plan through the marketing expense pool.

[0054] Of course, it can also be actual data generated during the execution of the marketing plan, which can be directly imported through the enterprise ERP system or other management systems to calculate the execution cost pool and evaluate the execution effect of the marketing plan.

[0055] The collected marketing plan data can include sales targets, marketing activity plans, channel rebate agreements, etc., and must include at least one matching factor (time, region, product). Of course, other matching factors, such as customer type, can also be supported through user-defined extensions to adapt to diverse sales policies, which is not limited by the present invention.

[0056] It should be noted that this step uses a combination of all types of matching factors, such as time, region, and product, to perform dynamic rule matching, retrieving candidate rules from a pre-stored dynamic rule library to improve rule matching accuracy. Furthermore, automated rule matching replaces manual operations, reducing time costs. If the rules for a specific location or product change, only the rules for the corresponding matching factors need to be adjusted to adapt the method, thus shortening the response time after the rule adjustment.

[0057] The adapted dynamic rules are passed to the subsequent cost calculation module to execute formula parsing data and calculate the marketing cost pool to avoid human calculation errors.

[0058] This step addresses the inefficiency, rigidity, and multi-dimensional matching challenges of existing marketing expense calculation technologies through a dynamic rule adaptation mechanism and multi-dimensional matching factor priority management. Based on the multi-dimensional attributes (time, region, and product) of marketing plan data, applicable expense calculation rules are dynamically adapted, replacing traditional manual matching or simple rule-based systems.

[0059] S200: According to dynamic rules and in combination with the marketing plan data, a marketing expense pool is obtained.

[0060] The core purpose of this step is to generate a marketing expense pool by combining dynamic rules with marketing plan data, and to achieve automated collection and classification management of expense data.

[0061] Based on the dynamic rules matched in the previous steps, analyze the variables and calculation logic within the rules. Bind the rules to the marketing plan data to generate a calculation formula. Calculate the cost share for each dimension combination using the dynamic rules and store it as structured data.

[0062] It should be noted that this step calculates the marketing expenses separately according to the combination of multiple dimensions, and then combines the marketing expenses to obtain the marketing expense pool, which is the total marketing expenses.

[0063] The marketing expense pool can be used to evaluate marketing plans overall and verify whether the generated expense pool is within the preset budget. If it exceeds the budget, an early warning mechanism (such as a "expense pool overrun") is triggered to facilitate adjustments to the marketing plan. Furthermore, the marketing expense pool can also be used to evaluate the effectiveness of marketing plans and select from multiple marketing plans.

[0064] Calculating marketing expenses for each dimension combination can be used to assess the impact of multi-dimensional plans on marketing results, allowing for targeted adjustments to marketing plans and improving their efficiency. For example, adjustments can be made to the dimension plan with the lowest marketing expenses to maximize the effectiveness of these adjustments. This step improves the ability to aggregate multi-dimensional expenses, reduces data fragmentation, and enables categorized data management.

[0065] This step addresses the low efficiency, fragmented data, and inflexibility of existing marketing expense calculation technologies through dynamic rule parsing and multi-dimensional expense aggregation. By categorizing expense shares by multiple dimensions, a structured marketing expense pool is formed, adapting to complex business scenarios and providing a data foundation for subsequent adjustments and performance calculations.

[0066] S300: According to the marketing expense pool, the marketing plan data is adjusted, and according to the adjusted marketing plan data that is executed, an execution expense pool is obtained to determine the performance of the execution personnel.

[0067] The core purpose of this step is to achieve accurate calculation and real-time optimization of executor performance by dynamically adjusting marketing plan data and generating an execution cost pool.

[0068] Based on the calculated results of a multi-dimensional marketing expense pool, select marketing plans for certain dimensions and adjust them. You can adjust the marketing plans corresponding to the dimensions with the lowest marketing expenses to address shortcomings. Similarly, you can adjust the marketing plans corresponding to the dimensions with the highest marketing expenses to increase adjustment sensitivity.

[0069] Automatically revise unexecuted marketing plan data based on changes in the marketing expense pool (such as budget overruns or policy adjustments) to ensure reasonable expense allocation.

[0070] Combine adjusted marketing plan data (e.g., revised budget allocations) with actual execution data (e.g., achieved sales targets). Generate an execution fee pool based on dynamic rule parsing formulas. Comparing the execution fee pool with the marketing fee pool allows for plan adjustments and evaluation of execution effectiveness. Recalculate the execution fee pool based on the adjusted marketing plan data, providing a data foundation for performance evaluation. By linking the execution fee pool with actual execution data, the performance contribution of execution personnel can be quantified, improving the fairness and transparency of incentives.

[0071] This step solves the problems of low efficiency, slow response and lack of fairness in performance evaluation of existing technologies by dynamically adjusting marketing plan data and executing cost pool generation.

[0072] As a preferred embodiment of the present invention, the dynamic rules are specifically:

[0073] Collect rule definition files corresponding to different time periods, different regions, and different products;

[0074] According to the rule definition file, through a visual interface, in response to the user's rule formula input, the dynamic rule corresponding to the matching factor is obtained; or,

[0075] According to the rule definition file, a corresponding rule formula is obtained through a semantic parsing tool to obtain the dynamic rule corresponding to the matching factor.

[0076] The core purpose of this implementation is to bind the rule formula entered by the user with the matching factors (time, region, product) through a flexible rule definition method (visual interface or semantic parsing tool) to generate adaptive dynamic rules, thereby solving the problem of rigid rule definition and reliance on hard-coded logic in the existing technology.

[0077] First, collect the rule definition files. It is understandable that different regions, different times, and different products may have different rule definition files. Therefore, it is necessary to synchronize the rule configuration files for different times, regions, and products.

[0078] The collected rule definition file is parsed, that is, the rule formula in the rule definition file is integrated into the method to form dynamic rules for matching. This can be done through the following embodiments, which are not limited by the present invention.

[0079] Example 1: Define dynamic rules through a visual interface. The user selects a matching factor in the visual interface and enters a rule formula. The system automatically binds the variables in the formula to the business data source.

[0080] It should be noted that in this embodiment, it is necessary to check the formula syntax (such as bracket matching and variable validity) and verify the consistency of the matching factor with the rule definition file.

[0081] Example 2: Generate dynamic rules through semantic parsing tools. Based on the collected rule definition file, the semantic parsing tool converts the description into a rule formula and automatically binds the matching factors according to the tags in the rule definition file.

[0082] The generated dynamic rules are associated with matching factors (time, region, product) and stored for dynamic rule adaptation.

[0083] Of course, the methods of the above two embodiments can also be used simultaneously to compare the obtained rule formulas. When the rule formulas obtained in embodiment one and embodiment two are inconsistent, the user is reminded through the visual interface in embodiment one to confirm the input of the rule formula.

[0084] The visual interface and semantic parsing tools will shorten rule definition time and reduce development costs (e.g., by reducing the frequency of programmer involvement). When the market changes, business personnel can adjust rules directly through the interface without waiting for the development team, improving response time.

[0085] This implementation, through a visual interface and semantic parsing tools, addresses the rigidity of existing rule definitions and their reliance on hard-coded logic, enabling flexible dynamic rule generation and multi-dimensional matching factor adaptation. This allows non-technical personnel (such as business personnel) to define complex rules without programming, lowering the barrier to entry for rule definition.

[0086] As a preferred embodiment of this implementation, the adaptive dynamic rules are as follows:

[0087] According to the multiple types of matching factors, dynamic rules are matched, wherein the multiple types of matching factors are set with priorities one by one;

[0088] If the dynamic rule obtained by matching is not unique and the corresponding matching factor types are inconsistent, the dynamic rule obtained by filtering the matching factor with a higher priority;

[0089] If the dynamic rule is not unique after screening, an adapted dynamic rule is obtained by weighting a plurality of the dynamic rules.

[0090] The core purpose of this embodiment is to ensure accurate adaptation of dynamic rules through priority setting and conflict resolution mechanism of multiple types of matching factors, and to solve the problem of rule selection deviation caused by multi-dimensional rule matching conflicts in the existing technology.

[0091] Users define the priority of matching factors (e.g., region > product > time) through a visual interface or configuration file. Priority weights can be expressed as numerical values ​​(e.g., region = 3, product = 2, time = 1) or hierarchical levels (e.g., region is the highest priority).

[0092] Based on the input marketing plan data, all matching rules are retrieved from the rule base. If the matching rule is unique, it is output as the adapted dynamic rule.

[0093] If the matching rule is not unique, it is filtered based on the priority of the matching factor type. For example, Rule 1 is obtained by matching the region factor, and Rule 2 is obtained by matching the product factor. Because the region factor has a higher priority, the rule corresponding to the higher-priority matching factor is selected, that is, Rule 1 is output as the adaptive dynamic rule.

[0094] If conflicts still exist after filtering (e.g., both Rule 1 and Rule 2 are based on regional factor matching), this may occur when two conflicting rule files exist for the same region. In this case, a weighted average is used to calculate the final rule. The weighting method can be customized, such as setting the authority of the rule file for the industry.

[0095] Priority screening and weighted calculation mechanisms shorten conflict resolution time, reduce development costs, and ensure that rules are highly aligned with business scenarios. Weighted calculations support complex scenarios and enable compromise when multiple rules partially match.

[0096] The final adapted dynamic rules are passed to the subsequent cost calculation module for formula parsing.

[0097] This step addresses the existing problem of rule selection bias caused by multi-dimensional rule matching conflicts by prioritizing multiple matching factors and implementing a dynamic rule conflict resolution mechanism. Priorities are set to resolve rule conflicts. When multiple rules match, the final matching rule is generated through priority screening and weighted calculation, eliminating manual intervention. This supports rule adaptation in complex scenarios and improves the flexibility and accuracy of enterprise sales strategies.

[0098] As a preferred embodiment of the present invention, according to dynamic rules, combined with the marketing plan data, a marketing expense pool is obtained, specifically:

[0099] According to the dynamic rules, the marketing plan data is called, and the marketing expense share is obtained according to the dimension combination;

[0100] The marketing expense pool is obtained according to multiple marketing expense shares under a single dimension.

[0101] The core purpose of this implementation is to achieve automated collection and classification management of the marketing expense pool through the combination of dynamic rules and marketing plan data, and to solve the problems of low expense calculation efficiency, data dispersion and poor flexibility in the existing technology.

[0102] Based on the matched dynamic rules, the variables and operation logic in the rules are analyzed. The rules are bound to the marketing plan data and the calculation formula after data filling is generated.

[0103] Specifically, the dimensions are:

[0104] The dimension includes at least any one of the expense collection dimension, the expense object dimension and the expense item dimension.

[0105] The core purpose of this embodiment is to achieve flexible construction and refined management of the marketing expense pool by defining a multi-dimensional expense classification system (expense collection dimension, expense object dimension, expense item dimension), and to solve the problem of single expense classification and inability to adapt to complex business scenarios in existing technologies.

[0106] The expense collection dimension is used to categorize expense sources, such as time (quarterly, monthly), region (East China, North China), and product (Class A, Class B). The expense object dimension is used to distinguish expense uses, such as regional funds, special funds, and marketing funds. The expense item dimension is used to refine expense types, such as travel expenses, commercial rebates, and advertising expenses.

[0107] The above dimensions are arbitrarily combined to obtain a dimension combination. It should be noted that the dimension combination can refer to a combination of the three dimensions of the expense collection dimension, the expense object dimension, and the expense item dimension, or a combination of any two of these dimensions, or a dimension combination formed by a single dimension. The present invention is not limited to this.

[0108] Based on each expense dimension, rule-based calculations are performed to generate an expense share, which is then stored as structured data. By combining the expense shares of all sub-dimensions combined within a single dimension, a marketing expense pool is generated. This prevents duplicate calculations of expense shares, which can lead to miscalculations and inflated costs.

[0109] This implementation addresses the low efficiency, fragmented data, and inflexibility of existing marketing expense calculation technologies through dynamic rule parsing and multi-dimensional expense aggregation. Dynamic rule-based analysis of business data (such as sales figures and achievement rates) automatically generates expense shares, eliminating the inefficiencies and errors of manual calculations and automating expense aggregation. Expense shares are categorized by expense aggregation dimension to form a structured marketing expense pool, providing a data foundation for subsequent adjustments and performance calculations.

[0110] As a preferred embodiment of the present invention, the marketing plan data is adjusted as follows:

[0111] If any of the dynamic rules changes, a marketing expense pool is obtained based on the changed dynamic rules and the unexecuted marketing plan data;

[0112] When the marketing expense pool decreases, the marketing plan data is adjusted according to the marketing expense pool.

[0113] The core purpose of this step is to trigger automatic adjustment of marketing plan data through dynamic rule changes, ensure the rationality of the marketing expense pool and the flexibility of resource allocation under rule changes, and solve the problem of the inability to respond quickly after rule changes in the existing technology and the imbalance of the expense pool leading to resource waste or overspending.

[0114] When a rule definition file changes, it is parsed, dynamic rules are generated, and the rule base is updated. The system monitors rule base changes in real time and immediately triggers the adjustment process upon detecting a rule update. This automated adjustment process reduces manual intervention, shortens the adjustment cycle after rule changes, and improves the company's responsiveness to market changes.

[0115] At this time, the changed dynamic rules are applied to the unexecuted marketing plan data and aggregated to form a new marketing expense pool.

[0116] If the total amount of the marketing expense pool after the rule change is less than the expense pool before the change (for example, due to a reduction in the rule coefficient, the expense pool will be reduced), the marketing plan data will be adjusted. If the expense pool does not decrease after the rule change, no adjustment is required and the expense pool under the new rule will be directly implemented.

[0117] When dynamic rules (such as tiered incentive policies and gradient coefficients) are adjusted, unexecuted marketing plan data is automatically corrected to avoid imbalances in the expense pool caused by rule changes. When the adjusted marketing expense pool is reduced (such as due to budget overruns), the marketing plan data is adjusted (such as reducing the budget for low-priority areas) to ensure that the expense pool is reasonably allocated within the budget.

[0118] This embodiment solves the problems of delayed response and imbalanced fee pool after rule changes in the prior art through a dynamic rule change triggering mechanism.

[0119] As a preferred embodiment of this implementation, the marketing plan data is adjusted according to the marketing expense pool, specifically:

[0120] According to the marketing expense pool, the unexecuted marketing plan data is adjusted to obtain a marketing expense pool. When the adjusted marketing expense pool is greater than or equal to the marketing expense pool before the dynamic rule change, the adjustment iteration is stopped and the marketing plan data is determined for execution.

[0121] When the number of adjustments to the marketing plan data is greater than or equal to a preset threshold, the adjustment iteration is stopped, and the marketing plan data is selected for execution according to the corresponding marketing expense pool.

[0122] The core purpose of this embodiment is to ensure the rationality of the marketing expense pool and the flexibility of resource allocation by dynamically adjusting the marketing plan data and setting the iteration termination conditions, so as to solve the problems in the existing technology of being unable to respond quickly after rule changes and the imbalance of the expense pool leading to resource waste or overspending.

[0123] In this embodiment, iterative adjustment of the unexecuted marketing plan data is performed, and the unexecuted marketing plan data is gradually corrected to obtain an adjusted cost pool.

[0124] Example 1: If the total amount of the marketing expense pool after adjustment is ≥ the expense pool before the dynamic rule change (for example, the expense is reduced due to a reduction in the rule coefficient and then supplemented by adjustment), the iteration is terminated.

[0125] Example 2: If the number of adjustments is greater than or equal to a preset threshold (eg, 3 times), the iteration is terminated, and the marketing plan data corresponding to the currently adjusted cost pool is selected for execution.

[0126] This embodiment addresses the existing issues of delayed response and imbalanced expense pools after rule changes by presetting termination conditions. By setting an iteration termination condition (either when the expense pool reaches a target or when the number of adjustments is capped), it prevents wasteful resource use or excessive adjustments, ensuring that the marketing expense pool is properly allocated within the budget. By limiting the number of adjustments using termination conditions, the adjustment cycle after rule changes is shortened, improving the company's responsiveness to market changes.

[0127] As a preferred embodiment of the present invention, the performance of the executive is determined as follows:

[0128] According to the marketing plan data executed by the executives, the marketing expenses are obtained one by one;

[0129] According to the marketing expenses, combined with the marketing expense pool corresponding to the marketing plan data, the performance ratio of the executive personnel is obtained.

[0130] The core purpose of this implementation is to achieve accurate calculation of performance ratio by quantifying the relationship between the marketing expenses of executives and the marketing expense pool, thereby improving the objectivity and incentive effect of performance evaluation and solving the problem in existing technologies that performance evaluation is highly subjective and cannot quantify individual contributions.

[0131] Bind the executor's marketing plan data with their actual execution records, analyze the formula based on dynamic rules, and calculate the actual marketing expenses incurred by the executor.

[0132] By comparing the marketing expenses of the executive with the corresponding marketing expense pool, the completion ratio of the executive can be obtained, and thus the performance ratio can be obtained. Of course, other factors (such as achievement rate and customer satisfaction) can also be considered to adjust the ratio, and the present invention does not limit this.

[0133] The expense ratio formula objectively reflects the actual contribution of executives to the expense pool. High performers receive a higher ratio for efficient budget utilization, while low performers are warned or face strategic adjustments due to low expense ratios, thereby reducing the risk of resource waste. By linking the expense pool with performance, companies can improve the overall efficiency of marketing resource utilization, replace manual statistics with automated calculations, and shorten the performance evaluation cycle.

[0134] Furthermore, by comparing marketing expenses with the marketing expense pool corresponding to the marketing plan data, rather than the execution expense pool, it is possible to evaluate the effectiveness of the execution personnel in executing the plan. This implementation solves the existing problems of subjectivity in performance evaluation and difficulty in quantifying contributions by combining the expense ratio formula with dynamic rules.

[0135] The present invention also provides a storage medium,

[0136] The storage medium stores a computer program, which, when executed, implements the steps of any one of the marketing data processing methods based on dynamic rule adaptation.

[0137] Therefore, this storage medium can achieve any effect of the marketing data processing method based on dynamic rule adaptation, which will not be elaborated here.

[0138] The present invention also provides an electronic device, comprising:

[0139] One or more central processing units,

[0140] one or more memories having a computer program stored therein,

[0141] The central processing unit is used to execute the computer program to implement any one of the marketing data processing methods based on dynamic rule adaptation.

[0142] Therefore, this electronic device can achieve any effect of the marketing data processing method based on dynamic rule adaptation, which will not be elaborated here.

[0143] Anything not described in the present invention can be achieved by adopting or drawing on existing technologies.

[0144] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0145] The foregoing is merely an embodiment of the present invention and is not intended to limit the present invention. It will be apparent to those skilled in the art that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A marketing data processing method based on dynamic rule adaptation, characterized in that: include: According to the collected marketing plan data, adaptive dynamic rules are obtained through matching factors, wherein the matching factors include at least any one of time, region, and product; According to dynamic rules, combined with the marketing plan data, a marketing expense pool is obtained; The marketing plan data is adjusted according to the marketing expense pool, and an execution expense pool is obtained based on the adjusted executed marketing plan data to determine the performance of the execution personnel.

2. The marketing data processing method based on dynamic rule adaptation according to claim 1, characterized in that: The dynamic rules are specifically: Collect rule definition files corresponding to different time periods, different regions, and different products; According to the rule definition file, through a visual interface, in response to the user's rule formula input, the dynamic rule corresponding to the matching factor is obtained; or, According to the rule definition file, a corresponding rule formula is obtained through a semantic parsing tool to obtain the dynamic rule corresponding to the matching factor.

3. The marketing data processing method based on dynamic rule adaptation according to claim 2, characterized in that: The adapted dynamic rules are as follows: According to the multiple types of matching factors, dynamic rules are matched, wherein the multiple types of matching factors are set with priorities one by one; If the dynamic rule obtained by matching is not unique and the corresponding matching factor types are inconsistent, the dynamic rule obtained by filtering the matching factor with a higher priority; If the dynamic rule is not unique after screening, an adapted dynamic rule is obtained by weighting a plurality of the dynamic rules.

4. The marketing data processing method based on dynamic rule adaptation according to claim 1, characterized in that: According to dynamic rules, combined with the marketing plan data, a marketing expense pool is obtained, specifically: According to the dynamic rules, the marketing plan data is called, and the marketing expense share is obtained according to the dimension combination; The marketing expense pool is obtained according to multiple marketing expense shares under a single dimension.

5. The marketing data processing method based on dynamic rule adaptation according to claim 4, characterized in that: The dimensions are specifically: The dimension includes at least any one of the expense collection dimension, the expense object dimension and the expense item dimension.

6. The marketing data processing method based on dynamic rule adaptation according to claim 1, characterized in that: Adjust the marketing plan data, specifically: If any of the dynamic rules changes, a marketing expense pool is obtained based on the changed dynamic rules and the unexecuted marketing plan data; When the marketing expense pool decreases, the marketing plan data is adjusted according to the marketing expense pool.

7. The marketing data processing method based on dynamic rule adaptation according to claim 6, characterized in that: Adjust the marketing plan data according to the marketing expense pool, specifically: According to the marketing expense pool, the unexecuted marketing plan data is adjusted to obtain a marketing expense pool. When the adjusted marketing expense pool is greater than or equal to the marketing expense pool before the dynamic rule change, the adjustment iteration is stopped and the marketing plan data is determined for execution. When the number of adjustments to the marketing plan data is greater than or equal to a preset threshold, the adjustment iteration is stopped, and the marketing plan data is selected for execution according to the corresponding marketing expense pool.

8. The marketing data processing method based on dynamic rule adaptation according to claim 1, characterized in that: Determine executive performance, specifically: According to the marketing plan data executed by the executives, the marketing expenses are obtained one by one; According to the marketing expenses, combined with the marketing expense pool corresponding to the marketing plan data, the performance ratio of the executive personnel is obtained.

9. A storage medium, characterized in that: The storage medium stores a computer program, which, when executed, implements the steps of the marketing data processing method based on dynamic rule adaptation as described in any one of claims 1 to 8.

10. An electronic device, characterized in that: include: One or more central processing units, one or more memories having a computer program stored therein, The central processing unit is used to execute the computer program to implement the marketing data processing method based on dynamic rule adaptation as described in any one of claims 1 to 8.

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