Multi-dimensional rating model construction method based on entropy weight method and normal distribution fitting

Abstract

The invention provides a multi-dimensional rating model construction method based on an entropy weight method and normal distribution fitting, and the method comprises the steps: obtaining, storing, managing and cleaning multi-dimensional data, constructing a multi-dimensional marketing capability rating system which comprises six first-level indexes, and the first-level indexes correspond to a plurality of second-level indexes; calculating a mean value and a standard deviation according to the scores of all the secondary indexes, and drawing a normal distribution curve to obtain a secondary index score of the to-be-evaluated person; performing standardization processing on the score of the second-level index, and calculating the weight of the second-level index by adopting an entropy weight method; according to the second-level index score and the corresponding weight of the to-be-assessed person, performing weighted calculation to obtain a first-level index score, and performing calculation to obtain a comprehensive ability score of the to-be-assessed person; and according to the comprehensive ability score, obtaining a marketing ability rating, and completing the construction of a multi-dimensional rating model. According to the method, multi-dimensional comprehensive evaluation of the marketing ability of the sales personnel can be realized, the objectivity and scientificity of evaluation are ensured, and full-dimensional dynamic tracking analysis can be realized.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method for constructing a multidimensional rating model based on an entropy weight method and normal distribution fitting. Background Art

[0002] The existing methods for evaluating the marketing capabilities of sales personnel mainly rely on single indicators such as sales volume, which obviously has great limitations. The manual scoring and rating methods are highly subjective and lack a systematic analysis of sales personnel indicators. In addition, the evaluation weights lack scientific basis, and the evaluation results lack dynamic tracking and analysis.

[0003] Therefore, there is an urgent need for a model that can achieve a multi-dimensional comprehensive evaluation of sales personnel's marketing capabilities, ensure the scientific nature of indicator weights, reduce subjective influences, and conduct full-dimensional dynamic tracking and analysis. Summary of the invention

[0004] Based on this, it is necessary to provide a method for constructing a multidimensional rating model based on the entropy weight method and normal distribution fitting to address the above technical problems.

[0005] A method for constructing a multidimensional rating model based on an entropy weight method and normal distribution fitting comprises the following steps: obtaining multidimensional data, and storing, managing and cleaning the multidimensional data; constructing a multidimensional marketing capability rating system according to the multidimensional data, including six primary indicators of customer acquisition capability, conversion capability, execution capability, results capability, service capability and collaboration capability, wherein the primary indicators correspond to a plurality of secondary indicators; according to the scores of all secondary indicators, the corresponding mean and standard deviation are calculated to draw a normal distribution curve, and the secondary indicator scores of the persons to be evaluated are obtained based on the normal distribution curve; the secondary indicator scores are standardized, and the weights of the secondary indicators are calculated by the entropy weight method; according to the secondary indicator scores and corresponding weights of the persons to be evaluated, the primary indicator scores are obtained by weighted calculation, and the comprehensive capability scores of the persons to be evaluated are obtained according to all the primary indicator scores; according to the comprehensive capability scores, a marketing capability rating is obtained, and the construction of a multidimensional rating model is completed.

[0006] In one embodiment, the secondary indicators corresponding to the customer acquisition power include the completeness of the property brochure, the number of national registrations, the number of regional retentions, the rate of owners registering as brokers, and the number of conversions of expanded brokers; the secondary indicators corresponding to the conversion power include the customer acquisition retention rate, the number of customer retention conversions to visits, the visit transaction conversion rate, the customer acquisition flow conversion deviation rate, the customer intention deviation, the repeat visit rate, and the online customer acquisition file creation timeliness rate; the secondary indicators corresponding to the execution power include the visit code scanning rate, the customer file verification rate, the customer file completeness, the customer file secondary follow-up rate, the same-day visit rate, the internal member sub-item average, the visiting customer portrait generation rate, and the customer portrait update rate; the secondary indicators corresponding to the achievement power include the subscription completion rate, the online subscription completion rate, the overall subscription completion rate, the self-visit subscription completion rate, the old-to-new subscription contribution rate, the employee recommendation subscription contribution rate, the total subscription amount, and the self-acquired customer subscription proportion; the secondary indicators corresponding to the service power include the customer praise rate, the customer evaluation invitation rate, and the customer negative review rate; the secondary indicators corresponding to the collaboration power include the leadership score and the colleague score.

[0007] In one embodiment, the method of calculating the corresponding mean and standard deviation based on the scores of all secondary indicators to draw a normal distribution curve, and obtaining the secondary indicator score of the person to be evaluated based on the normal distribution curve, includes: obtaining the scores of all secondary indicators, normalizing them, and calculating the mean and standard deviation of all secondary indicators respectively, and calculating the secondary indicator score of the person to be evaluated based on the mean and standard deviation, and the formula is:

[0008]

[0009] In the formula, μ is the population mean, and σ is the population standard deviation; a normal distribution curve is drawn according to the mean and standard deviation, and the secondary indicator score of the person to be evaluated is obtained according to the normal distribution curve.

[0010] In one embodiment, the standardization of the secondary indicator scores and the use of the entropy weight method to calculate the weights of the secondary indicators include: standardizing the secondary indicator scores using a standardization method; constructing a data matrix based on the person to be evaluated and the standardized secondary indicator scores, which is:

[0011]

[0012] In the formula, j represents the person to be evaluated, and j represents the secondary indicator; the data matrix is ​​normalized, and the formula is:

[0013]

[0014] Calculate the entropy value of each secondary indicator, the formula is:

[0015]

[0016] Among them, H j is the entropy value, is the normalized ratio, Where n is the number of secondary indicators; the weight of the corresponding secondary indicator is calculated according to the entropy value of the secondary indicator, and the formula is:

[0017]

[0018] In the formula, w j is the weight.

[0019] In one embodiment, the weighted calculation is performed according to the secondary indicator scores and corresponding weights of the person to be evaluated to obtain the primary indicator scores, and the comprehensive ability score of the person to be evaluated is calculated according to all the primary indicator scores, including: the weighted calculation is performed according to the secondary indicator scores and corresponding weights of the person to be evaluated to obtain the corresponding primary indicator scores, and the formula is:

[0020]

[0021] In the formula, Score is the first-level indicator score, w j is the weight of the j-th secondary indicator, Z j is the jth secondary index value after standardization, m is the number of secondary indexes, where Z j The calculation formula is:

[0022]

[0023] Among them, Z is the standardized value, X is the original value, is the mean value of the indicator, is the standard deviation of the indicator; the comprehensive ability score of the person to be evaluated is calculated based on the scores of all the first-level indicators.

[0024] In one embodiment, the marketing capability rating is obtained according to the comprehensive capability score, including: according to the first-level indicator score, the first-level indicator of the person to be evaluated is graded by the median method to obtain the first-level indicator grade, and the first-level indicator grade includes excellent, good, medium and needs to be improved; according to the comprehensive capability score, the marketing capability grade of the person to be evaluated is graded by the median method, and the marketing capability grade includes excellent, good, medium and needs to be improved.

[0025] Compared with the prior art, the advantages and beneficial effects of the present invention are as follows: by acquiring multidimensional data and performing storage, management and cleaning, the automation and real-time updating of data collection can be realized, and a multidimensional marketing capability rating system can be constructed, including six primary indicators of customer acquisition, conversion, execution, results, service and collaboration. The primary indicators correspond to multiple secondary indicators. According to the scores of all secondary indicators, the corresponding means and standard deviations are calculated to draw a normal distribution curve, and the secondary indicator scores of the persons to be evaluated are obtained based on the normal distribution curve. The secondary indicator scores are standardized, and the entropy weight method is used to calculate the weights of the secondary indicators according to the information entropy value to ensure the objectivity and scientificity of the evaluation results. According to the secondary indicator scores and corresponding weights of the persons to be evaluated, the primary indicator scores are weightedly calculated, and the comprehensive ability evaluation of the persons to be evaluated is calculated according to all the primary indicator scores. According to the comprehensive ability score, the marketing ability rating is obtained, and the construction of the multidimensional rating model is completed, which can realize the multidimensional comprehensive evaluation of the marketing ability of sales personnel, avoid the subjectivity of manual rating, ensure the objectivity and scientificity of the evaluation results, and realize the full-dimensional dynamic tracking and analysis of sales personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A flowchart of a method for constructing a multidimensional rating model based on entropy weight method and normal distribution fitting in one embodiment;

[0027] Figure 2 This is an example diagram of a normal distribution fitting score in one embodiment. DETAILED DESCRIPTION

[0028] Before describing the specific embodiments of the present invention, the overall concept of the present invention is described as follows:

[0029] The present invention is mainly developed based on the model building process. The current method for evaluating the marketing ability of sales personnel relies on manual rating, which lacks scientificity and is difficult to achieve dynamic tracking and analysis.

[0030] Therefore, the present invention proposes a multidimensional rating model construction method based on the entropy weight method and normal distribution fitting. By acquiring multidimensional data and performing storage, governance and cleaning, the data collection can be automated and updated in real time, and a multidimensional marketing capability rating system can be constructed, including six first-level indicators of customer acquisition, conversion, execution, results, service and collaboration. The first-level indicators correspond to multiple second-level indicators. According to the scores of all second-level indicators, the corresponding means and standard deviations are calculated to draw a normal distribution curve, and the second-level indicator scores of the persons to be evaluated are obtained based on the normal distribution curve. The second-level indicator scores are standardized, and the weights of the second-level indicators are calculated using the entropy weight method to ensure the objectivity and scientificity of the evaluation results. According to the second-level indicator scores and corresponding weights of the persons to be evaluated, the first-level indicator scores are weightedly calculated, and the comprehensive ability evaluation of the persons to be evaluated is calculated according to all the first-level indicator scores. According to the comprehensive ability score, the marketing ability rating is obtained, and the construction of the multidimensional rating model is completed. The multi-dimensional comprehensive evaluation of the marketing ability of sales personnel can be realized, the subjectivity of manual rating can be avoided, the objectivity and scientificity of the evaluation results can be ensured, and the full-dimensional dynamic tracking and analysis of sales personnel can be realized.

[0031] After introducing the overall concept of the present invention, in order to make the purpose, technical solution and advantages of the present invention more clear, the present invention is further described in detail by specific implementation methods in combination with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0032] In one embodiment, Figure 1 As shown, a method for constructing a multidimensional rating model based on entropy weight method and normal distribution fitting is provided, including the following steps:

[0033] Step S110, acquiring multidimensional data, and storing, managing and cleaning the multidimensional data.

[0034] Specifically, multidimensional data is obtained through data sources such as the company's internal CRM (Customer Relationship Management) system, customer online data, sales manager APP, market research, etc., and the multidimensional data is stored, managed and cleaned through the data warehouse.

[0035] Step S120, constructing a multi-dimensional marketing capability rating system based on the multi-dimensional data, including six first-level indicators: customer acquisition capability, conversion capability, execution capability, results capability, service capability and collaboration capability. The first-level indicators correspond to multiple second-level indicators.

[0036] Specifically, after data collection and processing, relevant indicators are selected according to the availability, effectiveness and impact of the indicators on sales capabilities to construct a multi-dimensional marketing capability rating system. The first-level indicators include customer acquisition, conversion, execution, results, service and collaboration. This can fully reflect the marketing capabilities of sales personnel from aspects such as customer satisfaction, market share, sales execution, and team collaboration, achieve multi-dimensional comprehensive evaluation, and more accurately measure the overall capabilities of sales personnel, avoiding the one-sidedness caused by a single indicator. There are multiple second-level indicators corresponding to the first-level indicators, and the second-level indicators can be personalized according to the focus of project marketing to better adapt to marketing projects.

[0037] Among them, the secondary indicators corresponding to customer acquisition power include the completeness of brochures, the number of national registrations, the number of regional retentions, the rate of owners registering as brokers and the conversion volume of expanded brokers; the secondary indicators corresponding to conversion power include customer retention rate, the number of customer retention converted to visits, the visit transaction conversion rate, the customer flow conversion deviation rate, the customer intention deviation, the repeat visit rate, and the online customer acquisition file creation timeliness rate; the secondary indicators corresponding to execution power include the visit code scanning rate, the customer file verification rate, the customer file completeness, the customer file secondary follow-up rate, the same-day visit rate, the internal member sub-item average, the visiting customer portrait generation rate and the customer portrait update rate; the secondary indicators corresponding to results power include the subscription completion rate, the online subscription completion rate, the overall subscription completion rate, the self-visit subscription completion rate, the old-to-new subscription contribution rate, the employee recommendation subscription contribution rate, the total subscription amount and the self-acquired customer subscription proportion; the secondary indicators corresponding to service power include the customer praise rate, the customer evaluation invitation rate and the customer negative review rate; the secondary indicators corresponding to collaboration power include leadership scores and colleague scores, etc.

[0038] Step S130, according to the scores of all secondary indicators, the corresponding mean and standard deviation are calculated to draw a normal distribution curve, and the secondary indicator score of the person to be evaluated is obtained based on the normal distribution curve.

[0039] Specifically, after constructing the multi-dimensional marketing capability rating system, the mean and standard deviation of each secondary indicator are calculated based on the scores of multiple secondary indicators, a normal distribution curve is drawn based on the mean and standard deviation, and the secondary indicator scores of the persons to be evaluated are obtained based on the normal distribution curve, so as to scientifically score the persons to be evaluated based on the secondary indicators and ensure the objectivity and fairness of the evaluation results.

[0040] Among them, step S130 includes: obtaining the scores of all secondary indicators, performing normalization processing, and calculating the mean and standard deviation of all secondary indicators respectively, and calculating the secondary indicator score of the person to be evaluated according to the mean and standard deviation, the formula is:

[0041]

[0042] In the formula, μ is the population mean, and σ is the population standard deviation; a normal distribution curve is drawn according to the mean and standard deviation, and the secondary indicator score of the person to be evaluated is obtained according to the normal distribution curve.

[0043] Specifically, the scores of all secondary indicators are obtained, and the scores of each indicator of all persons to be evaluated are normalized to eliminate the dimensional influence between different indicators, the mean and standard deviation of each indicator are calculated, and normal distribution fitting is performed.

[0044] Taking the autonomous customer acquisition power of the person to be evaluated in the customer acquisition power as an example, the normal distribution fitting score example is as follows: Figure 2 As shown, assuming that the monthly average of a secondary indicator is 40 and the standard deviation is 10, the performance of the person to be evaluated is evaluated. Taking Zhang San and Li Si as examples, Zhang San's autonomous customer acquisition volume in one month is 30. According to the normal distribution formula, the corresponding secondary indicator score is 15.9 points; Li Si's autonomous customer acquisition volume is 50, and the corresponding secondary indicator score is 84.1 points, thereby achieving scientific scoring of the secondary indicators, which can more accurately reflect the marketing capabilities of each salesperson and ensure the objectivity and fairness of the evaluation results.

[0045] Step S140, normalize the secondary indicator scores and calculate the weights of the secondary indicators using the entropy weight method.

[0046] Specifically, the Z-score standardization or Min-Max standardization method is used to convert the secondary indicator scores of different dimensions and ranges into a unified standard format. The Z-score standardization method converts the indicator value of the person to be evaluated into a Z score by calculating the mean and standard deviation of each secondary indicator, thereby achieving fair comparison between indicators, while the Min-Max standardization method scales the indicator value to the [0,1] interval to eliminate the dimension effect. Through standardization, the comparability and consistency of all indicators in the subsequent ability score calculation are ensured, providing a solid foundation for comprehensive ability assessment.

[0047] The entropy weight method is used to calculate the weights of the selected secondary indicators, rather than relying on the personal experience or subjective judgment of the scorer. The entropy weight method can objectively and scientifically calculate the contribution of each indicator in the comprehensive evaluation based on the information entropy of each indicator, thereby ensuring the objectivity and accuracy of the evaluation results.

[0048] Wherein, step S140 includes: using a standardization method to standardize the secondary indicator scores; constructing a data matrix according to the person to be evaluated and the secondary indicator scores after the standardization, which is:

[0049]

[0050] In the formula, i represents the person to be evaluated, and j represents the secondary indicator; the data matrix is ​​normalized, and the formula is:

[0051]

[0052] Calculate the entropy value of each secondary indicator, the formula is:

[0053]

[0054] Among them, H j is the entropy value, is the normalized ratio, Among them, n is the number of secondary indicators; the weight of the corresponding secondary indicator is calculated according to the entropy value of the secondary indicator, and the formula is:

[0055]

[0056] In the formula, w j is the weight.

[0057] Specifically, a standardized method is used to standardize the scores of the secondary indicators. A data matrix is ​​constructed according to the persons to be evaluated and the standardized scores of the secondary indicators. The data matrix is ​​normalized, the entropy value of each secondary indicator is calculated, and the weight of the corresponding secondary indicator is calculated based on the entropy value. This can ensure the objectivity and scientificity of the weight of each indicator, making the evaluation result more accurate and reliable.

[0058] Step S150, according to the secondary indicator scores and corresponding weights of the person to be evaluated, the primary indicator scores are weighted and the comprehensive ability score of the person to be evaluated is calculated based on all the primary indicator scores.

[0059] Specifically, based on all the secondary indicator scores and corresponding weights of the person to be evaluated, a weighted calculation is performed to obtain the first-level indicator scores corresponding to the secondary indicators, and all the first-level indicator scores of the person to be evaluated are calculated. Finally, the comprehensive ability score of the person to be evaluated is calculated based on all the first-level indicator scores, thereby realizing a multi-dimensional evaluation of the ability of the person to be evaluated and ensuring the reliability of the comprehensive ability score.

[0060] Wherein, step S150 includes: according to the secondary indicator score and the corresponding weight of the person to be evaluated, weighted calculation is performed to obtain the corresponding primary indicator score, and the formula is:

[0061]

[0062] In the formula, Score is the first-level indicator score, w j is the weight of the j-th secondary indicator, Z j is the jth secondary index value after standardization, m is the number of secondary indexes, where Z jThe calculation formula is:

[0063]

[0064] Among them, Z is the standardized secondary index value, X is the original secondary index value, is the mean value of the indicator, is the standard deviation of the indicator; the comprehensive ability score of the person to be evaluated is calculated based on the scores of all the first-level indicators.

[0065] Specifically, after obtaining the scores and corresponding weights of all indicators of each salesperson, the weighted method of formula (6) is used to calculate the scores of six first-level indicators, including customer acquisition score, conversion score, execution score, results score, service score and collaboration score. In order to facilitate the analysis of the ability shortcomings of each salesperson, the scores of the six first-level indicators are converted into a 100-point system to facilitate the hierarchical evaluation of the multi-dimensional ability of each salesperson; at the same time, based on the same weighted calculation method, the comprehensive ability score of the person to be evaluated is calculated according to the scores of all the first-level indicators, so that the comprehensive ability of the person to be evaluated can be evaluated according to the comprehensive ability score.

[0066] Step S160, obtaining a marketing capability rating based on the comprehensive capability score, and completing the construction of a multi-dimensional rating model.

[0067] Specifically, according to the comprehensive ability score of the person to be evaluated, the marketing ability rating of the person to be evaluated is obtained, thereby obtaining a multidimensional rating model. The comprehensive ability evaluation of the person to be evaluated is realized through the multidimensional rating model, which can realize static evaluation while having the ability of dynamic tracking and analysis. By continuously collecting and analyzing the multi-dimensional data of sales personnel, the changes in their marketing ability can be detected in real time, so as to find problems in time and make corresponding adjustments.

[0068] In addition, the evaluation results can be presented in the form of intuitive dynamic charts, using radar charts and time bar charts, allowing managers to quickly understand the overall performance of the team and the relative ability distribution of each salesperson.

[0069] Through the scientific and comprehensive evaluation results and intuitive visualization provided by the present invention, managers can more quickly and accurately understand the overall performance of the sales team and the relative capabilities of each salesperson. This helps managers make more scientific decisions, such as customer resource allocation, personnel deployment, and training needs identification, thereby improving the team's overall marketing capabilities and performance.

[0070] Among them, step S160 includes: according to the first-level indicator score, the first-level indicator of the person to be evaluated is graded by the median method to obtain the first-level indicator level, and the first-level indicator level includes excellent, good, medium and needs to be improved; according to the comprehensive ability score, the marketing ability level of the person to be evaluated is graded by the median method, and the marketing ability level includes excellent, good, medium and needs to be improved.

[0071] Specifically, the evaluation adopts the median division method. For example, the three quantiles of 25%, 50% and 75% are used to grade the customer acquisition ability of each salesperson. Through this method, the customer acquisition ability of salespeople can be divided into four levels: A represents excellent, B represents good, C is medium, and D is for improvement. The above evaluation system can not only intuitively reflect the ability level of salespeople, but also help managers quickly identify the ability shortcomings of the team, facilitate the formulation of subsequent training and development plans, and thus improve overall sales performance.

[0072] In addition, according to the affiliation of each project with the regional company, the sales staff's index scores can be summed up in sequence and the average value can be calculated. For example, in the Shandong regional company, there are 620 sales staff, and their independent customer acquisition index score is the average of all sales staff's independent customer acquisition index scores, which represents the index score of the Shandong regional company. Subsequently, the weight system established by the entropy weight method and the quantile method are used to ABCD grade the marketing capabilities of the six dimensions of each region. Finally, these rating results are visualized for in-depth analysis and decision support.

[0073] In the above steps, the entropy weight method is combined with the normal distribution to systematically rate the capabilities of the personnel to be evaluated. By collecting multi-dimensional sales data, including sales, customer satisfaction, and market share, automation and real-time updates in data collection and analysis are achieved, eliminating the reliance on manual scoring, reducing evaluation costs and improving efficiency. The entropy weight method is applied to ensure the objectivity and scientificity of the evaluation results, prevent the influence of a single indicator, and standardize the performance of the personnel to be evaluated through normal distribution modeling, which is convenient for horizontal comparison. In addition, a comprehensive evaluation is provided by integrating multiple sales indicators to help companies identify and cultivate sales talents, and enhance managers' decision-making support capabilities through intuitive visualization.

[0074] In this embodiment, by acquiring multidimensional data and performing storage, governance and cleaning, it is possible to realize automation and real-time updating of data collection, and build a multidimensional marketing capability rating system, including six first-level indicators of customer acquisition, conversion, execution, results, service and collaboration. The first-level indicators correspond to multiple second-level indicators. According to the scores of all second-level indicators, the corresponding means and standard deviations are calculated to draw a normal distribution curve, and the second-level indicator scores of the persons to be evaluated are obtained based on the normal distribution curve. The second-level indicator scores are standardized, and the entropy weight method is used to calculate the weights of the second-level indicators to ensure the objectivity and scientificity of the evaluation results. According to the second-level indicator scores and corresponding weights of the persons to be evaluated, the first-level indicator scores are weightedly calculated, and the comprehensive capability evaluation of the persons to be evaluated is calculated based on all the first-level indicator scores. According to the comprehensive capability score, the marketing capability rating is obtained, and the construction of the multidimensional rating model is completed. It is possible to realize a multi-dimensional comprehensive evaluation of the marketing capability of sales personnel, avoid the subjectivity of manual rating, ensure the objectivity and scientificity of the evaluation results, and realize full-dimensional dynamic tracking and analysis of sales personnel.

[0075] Obviously, those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a computer storage medium (ROM / RAM, magnetic disk, optical disk) and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than that here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Therefore, the present invention is not limited to any specific combination of hardware and software.

[0076] The above contents are further detailed descriptions of the present invention in combination with specific implementation methods, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the scope of protection of the present invention.

Claims

1. A method for constructing a multidimensional rating model based on entropy weight method and normal distribution fitting, characterized in that: The following steps are involved: Acquire multidimensional data, and store, manage and clean the multidimensional data; A multi-dimensional marketing capability rating system is constructed based on the multi-dimensional data, including six primary indicators: customer acquisition capability, conversion capability, execution capability, results capability, service capability, and collaboration capability. The primary indicators correspond to multiple secondary indicators. According to the scores of all secondary indicators, the corresponding mean and standard deviation are calculated to draw a normal distribution curve, and the secondary indicator score of the person to be evaluated is obtained based on the normal distribution curve; The scores of the secondary indicators are standardized, and the weights of the secondary indicators are calculated using the entropy weight method; According to the secondary indicator scores and corresponding weights of the person to be evaluated, the primary indicator scores are calculated by weighted calculation, and the comprehensive ability score of the person to be evaluated is calculated based on all the primary indicator scores; Based on the comprehensive capability score, a marketing capability rating is obtained, completing the construction of a multidimensional rating model.

2. The method for constructing a multidimensional rating model based on entropy weight method and normal distribution fitting according to claim 1 is characterized in that: The secondary indicators corresponding to the customer acquisition power include the completeness of the property brochure, the number of national registrations, the number of regional retentions, the rate of owners registering as brokers, and the number of conversions of expanded brokers; The secondary indicators corresponding to the conversion power include customer acquisition retention rate, customer acquisition retention conversion volume, visit transaction conversion rate, customer acquisition flow conversion deviation rate, customer intention deviation, revisit rate, and online customer acquisition file creation timeliness rate; The secondary indicators corresponding to the execution capability include visitor code scanning rate, customer file verification rate, customer file completeness, customer file secondary follow-up rate, visitor check rate on the same day, internal member sub-item average, visitor profile generation rate and customer profile update rate; The secondary indicators corresponding to the achievement power include subscription completion rate, online subscription completion rate, overall subscription completion rate, self-visit subscription completion rate, old-to-new subscription contribution rate, employee recommendation subscription contribution rate, total subscription amount and self-acquired customer subscription proportion; The secondary indicators corresponding to the service capability include customer favorable review rate, customer review invitation rate and customer unfavorable review rate; The secondary indicators corresponding to the collaboration include leadership scores and colleague scores.

3. The method for constructing a multidimensional rating model based on entropy weight method and normal distribution fitting according to claim 1, characterized in that: According to the scores of all secondary indicators, the corresponding mean and standard deviation are calculated to draw a normal distribution curve, and the secondary indicator score of the person to be evaluated is obtained based on the normal distribution curve, including: Obtain the scores of all secondary indicators, perform normalization, and calculate the mean and standard deviation of all secondary indicators respectively. Calculate the secondary indicator score of the person to be evaluated based on the mean and standard deviation. The formula is: In the formula, μ is the population mean, σ is the population standard deviation; A normal distribution curve is drawn according to the mean and standard deviation, and the secondary indicator score of the person to be evaluated is obtained according to the normal distribution curve.

4. The method for constructing a multidimensional rating model based on entropy weight method and normal distribution fitting according to claim 3 is characterized in that: The step of normalizing the scores of the secondary indicators and calculating the weights of the secondary indicators using the entropy weight method includes: The secondary indicator scores are standardized using a standardized method; The data matrix is ​​constructed based on the persons to be evaluated and the standardized secondary indicator scores: In the formula, i represents the person to be evaluated, and j represents the secondary indicator; The data matrix is ​​normalized, and the formula is: Calculate the entropy value of each secondary indicator, the formula is: Among them, H j is the entropy value, is the normalized ratio, Among them, n is the number of secondary indicators; The weight of the corresponding secondary indicator is calculated according to the entropy value of the secondary indicator, and the formula is: In the formula, w j is the weight.

5. The method for constructing a multidimensional rating model based on entropy weight method and normal distribution fitting according to claim 4 is characterized in that: The first-level indicator score is obtained by weighted calculation based on the second-level indicator score and the corresponding weight of the person to be evaluated, and the comprehensive ability score of the person to be evaluated is calculated based on all the first-level indicator scores, including: According to the secondary indicator scores and corresponding weights of the persons to be evaluated, the corresponding primary indicator scores are obtained by weighted calculation. The formula is: In the formula, Score is the first-level indicator score, w j is the weight of the j-th secondary indicator, Z j is the jth secondary index value after standardization, m is the number of secondary indexes, where Z j The calculation formula is: Among them, Z is the standardized value, X is the original value, is the mean value of the indicator, is the standard deviation of the indicator; The comprehensive ability score of the person to be evaluated is calculated based on the scores of all first-level indicators.

6. The method for constructing a multidimensional rating model based on entropy weight method and normal distribution fitting according to claim 1, characterized in that: The marketing capability rating is obtained based on the comprehensive capability score, including: According to the first-level indicator scores, the first-level indicators of the personnel to be evaluated are graded using the median division method to obtain first-level indicator grades, which include excellent, good, medium and need to be improved; According to the comprehensive ability score, the median division method is used to grade the person to be evaluated, and the marketing ability level of the person to be evaluated is obtained. The marketing ability levels include excellent, good, medium and needs improvement.

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